Association of PTPN22 C1858T polymorphism with vitiligo susceptibility.
Genetic polymorphisms are variations in DNA found in 1% or more of the population which may alter the structure and function of protein through a single nucleotide base substitution in a gene’s coding region. It may alter the gene expression either by affecting mRNA stability when occurring in a gene’s 3′-untranslated region or by changing transcription factor binding when occurring in the 5′-promoter region. A polymorphism does not have any effect on the protein product when it occurs within DNA regions that are not involved in gene transcription or translation but serves as the basis for genetic linkage analysis [1].
\nThe information on genetic polymorphisms facilitates to explain pathologic mechanisms and help in identifying individuals at risk. It also helps us to find novel targets for drug treatment. The protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene is an important predisposing gene for human autoimmune diseases. The alterations in PTPN22 render a person susceptible and lead to the development of several autoimmune diseases. Many single nucleotide polymorphisms (SNPs) have been identified in PTPN22, but only one non-synonymous SNP has been intensively studied in relation to autoimmune diseases. This SNP C1858T (rs2476601) in exon 14 of the PTPN22 gene has been associated with a number of autoimmune diseases and considered as a risk factor due to significant production of autoantibodies [2, 3].
\nThe PTPN22 C1858T variant has been studied in autoimmune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus, juvenile idiopathic arthritis (JIA), inflammatory bowel disease (IBD) including Crohn’s disease (CD) and ulcerative colitis (UC), antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis, vitiligo, systemic sclerosis (SSc), Graves’ disease (GD), myasthenia gravis (MG), Addison’s disease, psoriasis, psoriatic arthritis (PsA), Behcet’s disease (BD), endometriosis, autoimmune thyroid disease (AITD), giant cell arteritis (GCA), alopecia areata (AA), and Sjögren’s syndrome. The association of PTPN22 C1858T genetic polymorphism is very significant and noteworthy in some autoimmune diseases, while in other it is less significant [3]. However, available literature on PTPN22 C1858T polymorphism and autoimmune diseases shows inconsistencies and ethnic variations exist.
\nPTPN22 gene is located on chromosomes 1p13.3–p13.1 and encodes a lymphoid-specific tyrosine phosphatase (Lyp). Lyp is an intracellular protein tyrosine phosphatase, bound to the SH3 domain of the C-terminal Src kinase (Csk) through a proline-rich motif. It is believed to suppress kinases mediating T-cell activation [4]. Lyp plays an important role in B-cell signaling, besides functioning as a negative regulator of T cells. It works in signaling cascade at various levels and targets several signaling intermediates involved in T-cell receptor signaling [5, 6]. After HLA, PTPN22 gene is the second-most important predisposing gene for human autoimmune diseases.
\nThe minor allele 1858T in the PTPN22 locus has a strong and consistent genetic association with autoimmune diseases. In PTPN22 C1858T (rs2476601), cytosine changes to thymidine at nucleotide 1858, resulting in an amino acid change from arginine to tryptophan at codon 620 (R620W), located in the polyproline-binding motif P1 [7, 8]. Yet there is no consensus whether C1858T polymorphism is a gain- or loss-of-function variant. The C1858T has been reported as a susceptibility locus associated with several autoimmune diseases. It was first reported in type 1 diabetes mellitus (T1DM) [7].
\nPTPN22 C1858T polymorphism has been suggested to increase Lyp protein activity which in turn inhibits T-cell signaling and results in a failure to delete autoreactive T cells during thymic selection. The association of this polymorphism is restricted to disorders that have a strong autoantibody component as it results in immune responses against autoantigens [8].
\nWith the advent of new genotyping and molecular biology techniques, a huge amount of data are available for analysis. A large number of genes associated with diseases have been identified by the GWAS, candidate gene, and epidemiological studies. Therefore, the focus should be on the way genetic associations are reported. Even in the overlapping meta-analyses on the same topic, the limitations such as inclusion and exclusion criteria and number of included studies result in consistency of association results of genes, although the meta-analysis has been considered as a powerful approach to identify true-positive association of genes with disease.
\nThe PTPN22 C1858T variant has been studied in several autoimmune or autoimmunity-related diseases in different ethnic populations worldwide.
\nAutoimmune diseases are pathological conditions identified by abnormal autoimmune responses and characterized by autoantibodies and T-cell responses to self-molecules by immune system reactivity. Human autoimmune diseases occur frequently (affecting in aggregate more than 5% of the population worldwide) and impose a significant burden of morbidity and mortality on the human population [9].
\nThe etiology of autoimmune diseases involves both genetic and environmental factors. Familial clustering is known in autoimmune diseases with higher rate of concordance in monozygotic twins as compared to dizygotic twins [10, 11, 12]. Most autoimmune diseases are multigenic, with multiple susceptibility genes working in concert to produce the disease; however, a few autoimmune diseases are caused by mutations in a single gene. Even in such cases other genes modify the severity of disease. On the other hand, some individuals with these mutations do not manifest the disease.
\nThe genetic polymorphisms also occur in normal population and are compatible with a normal immune function. However, when these polymorphisms occur with other susceptibility genes, they develop autoimmunity [13, 14]. The extent of risk is not same for all such genes, and some of the genes confer a much higher level of risk than others [9].
\nThe results of various association studies of PTPN22 C1858T variant with some of the autoimmune diseases are summarized in Tables 1–18.
\nPopulation | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Mexican | \n187/223 | \nCT | \nSusceptible | \n[20] | \n
Indian (Tamils) | \n264/264 | \nCT | \nSusceptible | \n[25] | \n
Indian (Gujarati) | \n126/140 | \nC1858T | \nNo association | \n[32] | \n
English | \n165/304 | \nC1858T | \nSusceptible | \n[29] | \n
Romanian | \n– | \nT-allele | \nSusceptible | \n[30] | \n
European\n*\n\n Asian | \n2094/3613 | \nT-allele T-allele | \nSusceptible No association | \n[28] | \n
Turkish | \n107/112 | \nC1858T | \nNo association | \n[27] | \n
European\n*\n\n Asian | \n1800/3269 | \nT-allele T-allele | \nSusceptible No association | \n[26] | \n
Jordanian | \n55/85 | \nC1858T | \nNo association | \n[33] | \n
Egyptian | \n100/120 | \nC1858T | \nNo association | \n[34] | \n
Caucasian\n#\n\n European | \n1514/2813 | \nC1858T | \nSusceptible | \n[31] | \n
Association of PTPN22 C1858T polymorphism with vitiligo susceptibility.
Meta-analysis.
Genome-wide association study.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Mexican | \n64/225 | \nT-allele | \nSusceptible | \n[41] | \n
Belgian-German | \n435/628 | \nC1858T | \nSusceptible | \n[39] | \n
English | \n196/507 | \nC1858T | \nSusceptible | \n[38] | \n
Mixed\n*\n\n | \n1129/1702 | \nT and CT | \nSusceptible | \n[43] | \n
Mixed\n*\n\n | \n365/173 | \nC1858T | \nSusceptible | \n[42] | \n
Egyptian | \n103/100 | \nCT, TT | \nSusceptible | \n[40] | \n
Iranian | \n69/69 | \nT-allele | \nNo association | \n[44] | \n
Association of PYPN22 C1858T polymorphism with alopecia susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Saudi | \n106/200 | \nT-allele, CT | \nSusceptible | \n[53] | \n
German | \n375 + 418/376 + 561 | \nC1858T | \nNo association | \n[57] | \n
English | \n647/566 | \nC1858T | \nNo association | \n[58] | \n
Caucasian | \n1146 | \nC1858T | \nNo association | \n[59] | \n
Mixed\n*\n\n | \n3334/5753 | \nT-allele | \nNo association | \n[56] | \n
Mixed\n*\n\n | \n1448/1385 | \nC1858T | \nNo association | \n[55] | \n
Cretan (Greek) | \n173/348 | \nT-allele | \nNo association | \n[60] | \n
Association of PTPN22 C1858T polymorphism with psoriasis susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Toronto (admixed) | \n207/199 | \nT-allele | \nSusceptible | \n[61] | \n
Swedish | \n291/725 | \nT-allele | \nSusceptible | \n[62] | \n
Mixed\n#\n\n | \n1177/2155 | \nC1858T | \nSusceptible | \n[63] | \n
UK | \n455/595 | \nC1858T | \nNo association | \n[65] | \n
Newfoundland | \n238/149 | \nT-allele | \nNo association | \n[61] | \n
German | \n375/376 | \nT-allele | \nNo association | \n[66] | \n
Association of PTPN22 C1858T polymorphism with psoriatic arthritis susceptibility.
Genome-wide association study.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
American (European ancestry) | \n647/751 | \nC1858T | \nSusceptible | \n[67] | \n
Australian | \n324/568 | \nC1858T | \nSusceptible | \n[70] | \n
Australian | \n413/690 1608/9284 | \nC1858T | \nSusceptible in females | \n[71] | \n
Greek | \n128/221 | \nC1858T | \nSusceptible | \n[73] | \n
Egyptian | \n60/40 | \nT-allele | \nSusceptible | \n[75] | \n
UK | \n661/595 | \nC1858T | \nSusceptible | \n[65] | \n
Czechs | \n130/400 | \nT-allele | \nSusceptible | \n[72] | \n
European | \n809/3535 | \nC1858T | \nSusceptible | \n[69] | \n
Norwegian | \n320/555 | \nC1858T | \nSusceptible | \n[74] | \n
Mixed\n*\n\n | \n4552/10,161 | \nC1858T | \nSusceptible | \n[77] | \n
Mixed\n*\n\n | \n4238/6012 | \nC1858T | \nSusceptible | \n[76] | \n
Finish | \n230 | \nT-allele | \nNo association | \n[78] | \n
Hungarian | \n150/200 | \nT-allele | \nNo association | \n[79] | \n
Association of PTPN22 C1858T polymorphism with juvenile idiopathic arthritis susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Spanish | \n826/1036 | \nT-allele | \nSusceptible | \n[96] | \n
Italian | \n396/477 | \nT-allele | \nSusceptible | \n[92] | \n
Turkish | \n323/426 | \nC1858T | \nSusceptible | \n[97] | \n
Colombian | \n298/308 | \nT-allele | \nSusceptible | \n[86] | \n
Colombian | \n413/434 | \nT-allele | \nSusceptible | \n[87] | \n
Egyptian | \n150/150 | \nT-allele | \nSusceptible | \n[89] | \n
Egyptian | \n394/398 | \nC1858T | \nSusceptible | \n[90] | \n
Egyptian | \n112/122 | \nT-allele | \nSusceptible | \n[88] | \n
Egyptian | \n100/114 | \nC1858T | \nNo association | \n[100] | \n
Algerian | \n110/197 | \nC1858T | \nSusceptible | \n[85] | \n
Mexican | \n315/315 | \nC1858T | \nSusceptible | \n[95] | \n
Mexican | \n364/387 | \nC1858T | \nSusceptible | \n[94] | \n
Mexican | \n309/347 | \nT-allele | \nSusceptible | \n[93] | \n
UK | \n886/595 | \nC1858T | \nSusceptible | \n[65] | \n
Iranian | \n120/120 | \nC1858T | \nSusceptible | \n[91] | \n
Iranian | \n120/120 | \nT-allele | \nSusceptible | \n[84] | \n
Iranian | \n405/467 | \nC1858T | \nNo association | \n[101] | \n
Chinese Han | \n358/564 | \nC1858T | \nNo association | \n[99] | \n
Chinese-Yunnan | \n192/288 | \nC1858T | \nNo association | \n[98] | \n
Caucasian\n*\n\n Asian\n*\n\n | \n27,205/27,677 | \nC1858T C1858T | \nSusceptible No association | \n[103] | \n
European\n*\n\n Asian and African | \n29 studies | \nC1858T C1858T | \nSusceptible No association | \n[104] | \n
Mixed\n*\n\n | \n11,727/12,640 | \nT-allele | \nSusceptible | \n[105] | \n
Mixed\n*\n\n | \n3209/3692 | \nC1858T | \nSusceptible | \n[106] | \n
Mixed\n*\n\n | \n20,344/21,828 | \nC1858T | \nSusceptible | \n[76] | \n
Mixed\n*\n\n | \n13 studies | \nT-allele | \nSusceptible | \n[107] | \n
Mixed\n*\n\n | \n17,961/18,611 | \nC1858T | \nSusceptible | \n[102] | \n
Mixed\n*\n\n | \n34 studies | \nC1858T | \nSusceptible | \n[108] | \n
Mixed\n*\n\n | \n36 studies | \nT-allele | \nSusceptible | \n[2] | \n
Association of PTPN22 C1858T polymorphism with RA susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Spanish | \n338/1036 | \nT-allele | \nSusceptible | \n[96] | \n
Swedish | \n571/1042 | \nC1858T | \nSusceptible | \n[120] | \n
American | \n525/1961 | \nC1858T | \nSusceptible | \n[116] | \n
Crete | \n328/427 | \nC1858T | \nSusceptible | \n[119] | \n
Colombian | \n94/434 | \nT-allele | \nSusceptible | \n[87] | \n
Colombian | \n143/308 | \nT-allele | \nSusceptible | \n[86] | \n
Polish | \n135/201 | \nCT, T-allele | \nSusceptible | \n[122] | \n
Polish | \n150/300 | \nC1858T | \nSusceptible | \n[121] | \n
Mixed\n*\n\n | \n6 studies | \nT-allele | \nsusceptible | \n[107] | \n
Mixed\n*\n\n | \n772/1092 | \nC1858T | \nSusceptible | \n[126] | \n
Mixed\n*\n\n | \n9120/11724 | \nC1858T | \nSusceptible | \n[128] | \n
Mixed\n*\n\n | \n11 studies | \nCT, TT | \nSusceptible | \n[125] | \n
Mixed\n*\n\n | \n14 studies | \nT-allele | \nSusceptible | \n[2] | \n
Mixed\n*\n\n | \n3868/7458 | \nT-allele, TT | \nSusceptible | \n[127] | \n
European-Americans | \n3936/3491 | \nC1858T | \nSusceptible | \n[118] | \n
Hispanics | \n1492/807 | \nC1858T | \nNo association | \n[118] | \n
African-Americans | \n1527/1811 | \nC1858T | \nNo association | \n[118] | \n
Asians | \n1265/1260 | \nC1858T | \nNo association | \n[118] | \n
Egyptian | \n170/241 | \nC1858T | \nSusceptible | \n[124] | \n
Egyptian | \n40/20 | \nCT | \nSusceptible | \n[123] | \n
Egyptian | \n60/60 | \nC1858T | \nNo association | \n[133] | \n
European-American | \n1680/1467 | \nT-allele | \nSusceptible | \n[117] | \n
Mexican | \n500/355 | \nT-allele | \nSusceptible | \n[134] | \n
Mexican mestizos | \n150/150 | \nC1858T | \nNo association | \n[130] | \n
Turkish | \n158/155 | \nC1858T | \nNo association | \n[131] | \n
Turkish | \n137/160 | \nC1858T | \nNo association | \n[132] | \n
Chinese Han | \n713/672 | \nC1858T | \nNo association | \n[99] | \n
Chinese | \n40/20 | \nC1858T | \nNo association | \n[129] | \n
Association of PTPN22 C1858T polymorphism with SLE susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Egyptian | \n60/60 | \nC1858T | \nSusceptible | \n[133] | \n
German | \n140/100 | \nT-allele | \nSusceptible | \n[138] | \n
Mixed\n*\n\n | \n3764/3328 | \nC1858T | \nSusceptible | \n[139] | \n
Japanese | \n456/221 | \nT-allele | \nNo association | \n[143] | \n
Japanese | \n334/179 | \nC1858T | \nNo association | \n[144] | \n
Korean | \n212/225 | \nT-allele | \nNo association | \n[145] | \n
Polish | \n149/200 | \nC1858T | \nNo association | \n[147] | \n
Jordanian Arab | \n204/2016 | \nC1858T | \nNo association | \n[146] | \n
Association of PTPN22 C1858T polymorphism with AITD susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Latin-American | \n83/336 | \nC1858T | \nSusceptible | \n[148] | \n
Polish | \n166/154 | \nC1858T | \nSusceptible | \n[149] | \n
Polish | \n290/310 | \nT-allele | \nSusceptible | \n[150] | \n
Polish | \n735/1216 | \nC1858T | \nNo association | \n[154] | \n
English | \n768/768 | \nC1858T | \nSusceptible | \n[140] | \n
English | \n549/429 | \nC1858T | \nSusceptible | \n[151] | \n
English | \n901/833 | \nC1858T | \nSusceptible | \n[152] | \n
Mixed\n*\n\n | \n3 studies | \nT-allele | \nSusceptible | \n[2] | \n
Mixed\n*\n\n | \n3764/3328 | \nC1858T | \nSusceptible | \n[139] | \n
Indian Kashmiri | \n135/150 | \nC1858T | \nNo association | \n[155] | \n
Chinese Han\n#\n\n | \n5904/5866 | \nC1858T | \nNo association | \n[153] | \n
Association of PTPN22 C1858T polymorphism with Graves’ disease susceptibility.
Meta-analysis.
Genome-wide association study.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReference | \n
---|---|---|---|---|
Tunisian | \n164/100 | \nC1858T | \nSusceptible | \n[163] | \n
Moroccan | \n195/311 | \nC1858T | \nNo association | \n[167] | \n
Spanish | \n1903CD, 1677UC/3111 | \nC1858T | \nProtective to CD | \n[165] | \n
New Zealanders | \n315/4081 | \nC1858T | \nNo association with CD | \n[168] | \n
Czech | \n345/501 | \nC1858T | \nNo association | \n[169] | \n
Canadian | \n455/190 | \nC1858T | \nNo association with CD | \n[170] | \n
Canadian | \n249/207 | \nT-allele | \nNo association with CD | \n[171] | \n
British | \n514/374 | \nC1858T | \nNo association | \n[172] | \n
Spanish | \n1113/812 | \nC1858T | \nNo association | \n[173] | \n
German | \n146 | \nC1858T | \nNo association with CD | \n[174] | \n
Mixed\n*\n\n | \n8182/13356 | \nC1858T | \nSusceptible to CD | \n[164] | \n
Meta-analysis | \n\n | C1858T | \nProtective to CD | \n[2] | \n
Italian | \n649/256 | \nC1858T | \nNo association | \n[175] | \n
Association of PTPN22 C1858T polymorphism with IBD (CD + UC) susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Saudi | \n372/372 | \nT-allele | \nSusceptible | \n[184] | \n
German | \n220/239 | \nC1858T | \nSusceptible | \n[185] | \n
Egyptian | \n150/165 | \nT-allele | \nSusceptible | \n[186] | \n
Egyptian | \n120/120 | \nT-allele | \nSusceptible | \n[187] | \n
Kuwaiti Arabs | \n253/2014 | \nT-allele | \nSusceptible | \n[188] | \n
Chinese | \n202/240 | \nC1858T | \nSusceptible | \n[189] | \n
Chinese | \n364/719 | \nC1858T | \nNo association | \n[178] | \n
Brazilian | \n612/792 | \nC1858T | \nSusceptible | \n[190] | \n
Brazilian | \n205/308 | \nC1858T | \nSusceptible | \n[191] | \n
Polish | \n215/236 | \nC1858T | \nSusceptible | \n[192] | \n
Polish | \n147/327 | \nC1858T | \nSusceptible | \n[193] | \n
Russian | \n27/62 families | \nC1858T | \nSusceptible | \n[194] | \n
Croatian | \n102/193 | \nT-allele | \nSusceptible | \n[195] | \n
Caucasian | \n140/100 | \nT-allele | \nSusceptible | \n[138] | \n
Caucasian | \n8677 | \nC1858T | \nSusceptible | \n[196] | \n
Caucasian | \n113 | \nC1858T | \nSusceptible | \n[197] | \n
Czechs | \n372/400 | \nT-allele | \nSusceptible | \n[72] | \n
Iranian (Azeri) | \n160/271 | \nT-allele | \nSusceptible | \n[72] | \n
Iranian | \n99/100 | \nC1858T | \nSusceptible | \n[84] | \n
Iranian | \n144/197 | \nC1858T | \nNo association | \n[181] | \n
Estonian | \n170/230 | \nT-allele | \nSusceptible | \n[198] | \n
Italian | \n271/89 | \nC1858T | \nSusceptible | \n[199] | \n
Spanish | \n316/554 | \nT-allele | \nSusceptible | \n[200] | \n
Colorado | \n753/662 | \nCT, TT | \nSusceptible | \n[201] | \n
Colombian | \n110/308 | \nT-allele | \nSusceptible | \n[86] | \n
Colombian | \n197 families | \nC1858T | \nSusceptible | \n[202] | \n
International children | \n257 | \nC1858T | \nAssociated with proinsulin levels | \n[203] | \n
Mixed\n*\n\n | \n6 studies | \nC1858T | \nSusceptible | \n[107] | \n
Mixed\n*\n\n | \n19,495/25,341 | \nC1858T | \nSusceptible | \n[204] | \n
Mixed\n*\n\n | \n22,485/35,292 | \nC1858T | \nSusceptible in Caucasian | \n[205] | \n
Mixed\n*\n\n | \n11 studies | \nT-allele | \nSusceptible in European | \n[206] | \n
Mixed\n*\n\n | \n16,240/17,997 | \nC1858T | \nSusceptible | \n[207] | \n
Mixed\n*\n\n | \n8869/20,829 | \nC1858T | \nSusceptible | \n[208] | \n
Mixed\n*\n\n | \n10 studies | \nC1858T | \nSusceptible | \n[209] | \n
Indian | \n145/210 | \nT-allele | \nSusceptible | \n[210] | \n
Indian | \n129/109 | \nC1858T | \nNo association | \n[180] | \n
Greek | \n130/135 | \nC1858T | \nNo association | \n[179] | \n
Association of PTPN22 C1858T polymorphism with T1DM susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
French | \n659/504 | \nT-allele | \nSusceptible | \n[216] | \n
French | \n121/103 | \nC1858T | \nNo association | \n[218] | \n
Mixed White, Black, Hispanic | \n1120/716 | \nC1858T | \nSusceptible | \n[217] | \n
Caucasian | \n3422/3638 | \nC1858T | \nSusceptible | \n[214] | \n
Mixed\n*\n\n | \n4367/4771 | \nC1858T | \nSusceptible | \n[107] | \n
Columbian | \n101/434 | \nT-allele | \nNo association | \n[87] | \n
Spanish | \n54/55 | \nC1858T | \nNo association | \n[219] | \n
Association of PTPN22 C1858T polymorphism with systemic sclerosis susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Swedish | \n409/1557 | \nC1858T | \nSusceptible | \n[228] | \n
German | \n125/301 | \nC1858T | \nSusceptible | \n[229] | \n
European | \n649/ | \nC1858T | \nSusceptible | \n[230] | \n
Mixed\n*\n\n | \n2802/3730 | \nC1858T | \nSusceptible | \n[221] | \n
Hungarian, German | \n282/379 | \nT-allele | \nSusceptible | \n[231] | \n
French | \n470/296 | \nC1858T | \nSusceptible | \n[232] | \n
European\n#\n\n | \n532/2128 | \nC1858T | \nSusceptible | \n[235] | \n
Chinese | \n79/50 | \nC1858T | \nNo association | \n[2] | \n
Turkish | \n416/293 | \nC1858T | \nNo association | \n[234] | \n
Italian | \n356/439 | \nC1858T | \nNo association | \n[233] | \n
Association of PTPN22 C1858T polymorphism with myasthenia gravis susceptibility.
Meta-analysis.
Genome-wide association study.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Spanish | \n404/1517 | \nC1858T | \nNo association | \n[243] | \n
Turkish | \n134/177 | \nC1858T | \nNo association | \n[242] | \n
UK and Middle East | \n270/203 | \nC1858T | \nProtective | \n[241] | \n
Mixed\n*\n\n | \n1922/11,505 | \nC1858T | \nNo association | \n[76] | \n
Association of PTPN22 (C1858T) polymorphism with Behcet’s disease susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReference | \n
---|---|---|---|---|
Italian | \n132/232 | \nC1858T | \nSusceptible | \n[252] | \n
Italian | \n132/359 | \nT-allele | \nSusceptible | \n[253] | \n
Italian | \n130/250 | \nC1858T | \nSusceptible | \n[254] | \n
Brazilian | \n140/180 | \nC1858T | \nSusceptible | \n[255] | \n
Mixed\n*\n\n | \n971/1181 | \nT-allele | \nSusceptible | \n[246] | \n
Polish | \n171/310 | \nC1858T | \nNo association | \n[248] | \n
Association of PTPN22 C1858T polymorphism with endometriosis susceptibility.
Meta-analysis.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
German | \n199/399 | \nT-allele | \nSusceptible | \n[259] | \n
British | \n641/9115 | \nC1858T | \nSusceptible | \n[260] | \n
Italian | \n344/945 | \nC1858T | \nSusceptible | \n[261] | \n
Mixed\n*\n\n | \n1399/9934 | \nC1858T | \nSusceptible in White | \n[262] | \n
Mixed\n*\n\n | \n1922/11,505 | \nC1858T | \nSusceptible | \n[76] | \n
Association of PTPN22 C1858T polymorphism with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis susceptibility.
Meta-analysis.
Population | \nCase/ Controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Spanish | \n95/229 | \nC1858T | \nNo association | \n[263] | \n
Spanish, German, Norwegian | \n911/8136 | \nC1858T | \nSusceptible | \n[265] | \n
European | \n1651/15,306 | \nC1858T | \nSusceptible | \n[266] | \n
Australian | \n209/455 | \nT-allele | \nSusceptible | \n[267] | \n
Association of PTPN22 C1858T polymorphism with giant cell arteritis susceptibility.
Population | \nCase/controls | \nGenotype/allele/polymorphism | \nAssociation | \nReferences | \n
---|---|---|---|---|
Norwegian | \n332/990 | \nT-allele | \nSusceptible | \n[269] | \n
UK and Polish | \n338/665 | \nT-allele | \nSusceptible | \n[270] | \n
English | \n104/429 | \nC1858T | \nSusceptible | \n[151] | \n
Mixed\n*\n\n | \n6 studies | \nT-allele | \nSusceptible | \n[2] | \n
German | \n121/239 | \nC1858T | \nNo association | \n[185] | \n
Mixed\n*\n\n | \n2 studies | \nC1858T | \nNo association | \n[107] | \n
Association of PTPN22 C1858T polymorphism with Addison’s disease susceptibility.
Meta-analysis.
Vitiligo is an acquired, autoimmune skin disorder characterized by melanocyte loss resulting into progressive depigmentation of the skin and hair [15, 16]. The prevalence of vitiligo varies considerably with ethnicity and it affects 0.1–2% of the population worldwide [15, 17]. Vitiligo is associated with an elevated risk of several other autoimmune diseases [18, 19, 20].
\nVitiligo commonly shows familial aggregation and multifactorial mode of inheritance. It is a polygenic disease, and several genes related to autoimmunity have been reported to be associated with the pathogenesis of vitiligo [20, 21, 22, 23, 24, 25].
\nVarious published reports on PTPN22 C1858T polymorphism support the association of the T-allele and vitiligo susceptibility in different ethnic populations (Table 1). However, available literature on the PTPN22 C1858T polymorphism and vitiligo susceptibility is inconsistent [25, 26, 27, 28]. It has been reported to be a risk factor for vitiligo in English, Romanian, North American, Mexican, and South Indian Tamil populations [20, 25, 29, 30]. PTPN22 C1858T polymorphism is strongly associated with vitiligo susceptibility in Saudis also [in press]. A genome-wide association study indicates that PTPN22 C1858T is associated with vitiligo in European-derived white patients [Jin et al. 2010]. A meta-analysis utilizing data from different ethnicities shows an association of PTPN22 C1858T with vitiligo in European but not in Asian population [28].
\nIn contrast, no significant association of PTPN22 C1858T polymorphism with susceptibility to generalized vitiligo was found in Indian Gujarat population, Jordanian, Egyptian female, and Turkish population [27, 32, 33, 34]. Available literature shows that the variant of PTPN22 C1858T is responsible for increased risk of vitiligo in Caucasian patients; however, among non-Caucasians/Asians, inconsistency exits, and even the two populations of same country differ in association of PTPN22 C1858T with vitiligo indicating the role of ethnicity. The heterozygous CT genotype of the PTPN22 C1858T has a strong association with non-segmental vitiligo in South Indian Tamils, while there is no association of this polymorphism in Indian Gujarat population [25, 32]. This difference in the results of this polymorphism in Asians or non-Caucasians can be attributed to ethnic differences.
\nAA is a dermatological condition in which hair is lost from certain or all areas of the body, typically from certain areas of the scalp, more frequent in young ones [35]. The characteristic feature of AA is circular or oval bald spots which may progress and spread to the entire scalp (alopecia totalis) or entire body (alopecia universalis). Sometimes hair loss is localized to the sides and lower back of the scalp which is known as alopecia ophiasis [36]. The prevalence of AA in the general population varies between 0.1 and 6.9% depending on the ethnic group [37].
\nAlopecia areata is an autoimmune disease mediated by T cells to the hair follicles. There are enough evidences indicating that AA is a complex multigenetic trait with components of inherited predisposition. Molecular biology studies have led to the identification of a number of candidate genes in humans that confer susceptibility to AA. Recently, PTPN22 gene has been reported to be an additional immunoregulatory gene associated with AA. PTPN22 C1858T polymorphism has been associated with susceptibility of AA in Belgian, English, Egyptian, German, and Mexican populations (Table 2) [38, 39, 40, 41, 42, 43]. Two meta-analyses have also indicated an association with AA susceptibility [42, 43]. However, no association of PTPN22 C1858T has been found in Iranian patients [44].
\nPsoriasis is a chronic, complex autoimmune disease with characteristic reddish patches covered by silvery-white scales. It affects approximately 120–180 million people worldwide [45]. The prevalence of psoriasis varies significantly depending mainly on race, geographical location, genetics, environmental factors, and ethnicity [46, 47, 48, 49, 50].
\nThe etiology of psoriasis involves both genetic and environmental factors indicating a multifactorial nature. Moreover, a number of characteristic features of psoriasis are also found in other autoimmune diseases indicating a common etiology [51, 52].
\nThough the pathogenesis of psoriasis and comorbidities has been studied at the molecular level and a number of gene loci have been associated with susceptibility/severity of psoriasis [50, 51, 52, 53], genes identified till date to be associated with it do not fully account for it. Psoriasis is highly heritable, and it has been suggested in several association studies that skin barrier function, innate and adaptive immunity, and gene-gene and gene-environment interactions are involved in the pathogenesis of psoriasis [52].
\nRecently an association of T-allele of the PTPN22 C1858T with susceptibility to psoriasis in Saudi population was reported (Table 3) [53]. Earlier it has been suggested that PTPN22 may be among the true psoriasis susceptibility risk genes [54]. However, another study analyzed 15 SNPs from 7 putative psoriasis-risk genes and could not find any significant association of PTPN22 C1858T polymorphism with psoriasis. On the other hand, they found a significant association with another polymorphism (rs3789604) in PTPN22 gene and suggested that PTPN22 is one of the significant risk genes for psoriasis [55]. Chen and Chang [56] reported a strong association of PTPN22 + 1858T allele with PsA but no association with psoriasis and suggested that attention should be given to the studies dealing with gene-environment interaction besides keeping in consideration the clinical heterogeneity of the disease and population stratification.
\nEarlier Hüffmeier et al. [57] found gender variations in susceptibility of PTPN22 (+1858T allele) with psoriasis and suggested that other susceptibility locus/loci within noncoding regions of PTPN22 or its proximity might exist and act independently as a risk factor. They excluded the direct link of T-allele in psoriasis susceptibility in German psoriasis patients.
\nPsA is a chronic inflammatory arthritis associated with psoriasis. PsA is a chronic skin and joint condition that considerably affects patient’s quality of life. PsA is a complex disease with environmental and genetic risk factors contributing to it. Several studies have demonstrated different associations of genetic polymorphisms in the pathogenic process of PsA.
\nPTPN22 C1858T polymorphism has also been strongly associated with PsA (Table 4) in Toronto admix and Swedish population [61, 62]. Several non-HLA loci including PTPN22 have been suggested to affect the susceptibility to PsA [63, 64]. A complete genetic overlap has been suggested between psoriasis and PsA susceptibility loci as about a third of people who have psoriasis gets PsA. It has been noticed that subjects with severe psoriasis have a greater chance of getting PsA and about 40% of patients with PsA have relatives with it or with psoriasis, while other earlier studies reported no association of PTPN22 C1858T polymorphism and PsA in Newfoundland, the UK, and German Caucasian [57, 61, 65]. Though no significant differences were observed in allele distribution with different manifestations of disease, there is gender difference, and male PsA patients has higher frequency of T-allele than in the subgroup of female patients [66].
\nJIA is the most common inflammatory disease of the joints in children. Its etiology is complex and involves both genetic and environmental factors. It has been suggested that genetic factors play a significant role in the susceptibility to JIA [67]. While associations between JIA and variants in HLA are well established, non-HLA genetic variants also play a role in JIA susceptibility and have increasingly been identified by genome-wide and candidate gene studies [68, 69]. Many of the genetic associations have been confirmed recently by the International JIA Immunochip consortium, and several novel loci have also been identified showing a genome-wide association.
\nSeveral reports indicate that PTPN22 C1858T polymorphism has been consistently associated with JIA (Table 5). PTPN22 C1858T polymorphism is associated with JIA in Australians [70, 71], Americans of European ancestry [67], Czech [72], Europeans [69], Greek [73], Norwegians [74], UK population [65], and Egyptians [75]. Two separate meta-analyses also indicated that PTPN22 C1858T is associated with susceptibility to JIA [76, 77]. However, it is not associated with JIA in Finish and Hungarian patients [78, 79]. These variations may be due to ethnic variations; however, methodological error in genotyping cannot be ruled out.
\nRA is a chronic autoimmune disorder of bone joints caused by the complex interplay between several factors like body physiology and the environment with genetic background [80, 81]. RA is characterized by synovial inflammation, hyperplasia, cartilage and bone destruction, autoantibody production (rheumatoid factor), anticyclic citrullinated peptide (CCP), and the decreased quality of life [82]. Its prevalence is approximately 0.51% worldwide and afflicts people of all races.
\nRA shares a number of pathogenic mechanisms with other autoimmune disorders. More than 100 loci have been associated with RA as shown in a meta-analysis of GWAS. Out of these majority (97%) are located in the noncoding region, and the remaining 3% are in various non-HLA genes including PTPN22 (Trp620Arg) [83].
\nSeveral studies have been performed on the association of PTPN22 C1858T variants with RA susceptibility in different ethnic populations (Table 6). Various studies have demonstrated that allelic heterogeneity distribution has an increasing north-south gradient in the frequencies of the 1858T alleles in different European populations [84]. PTPN22 C1858T polymorphism has been associated with susceptibility to RA in Algerian [85], Colombian [86, 87], Egyptian [88, 89, 90], Iranian [84, 91], Italian [92], Mexican [93, 94, 95], Spanish [96], Turkish [97], and UK Caucasian populations [65].
\nOn the other hand, some studies reported that it is not associated with RA in Chinese [98, 99], Egyptian [100], and Iranian populations [101]. A number of meta-analyses have also shown that T-allele of PTPN22 C1858T is associated with RA susceptibility in Caucasians but not in Asians and Africans (Table 6) [102, 103, 104]. The different allele frequency of T-allele is very important in determining the population attributable risk of this allele for the autoimmune diseases in different populations. It also affects any suggested screening or predictive testing protocol for these diseases [101]. The absence of this association in Asians undermines the importance of this locus as a susceptibility locus for the RA and other autoimmune diseases.
\nSLE is a heterogeneous autoimmune inflammatory disease characterized by loss of self-tolerance with hyperactivation of autoreactive T and B cells with a predominance of Th2 inflammatory response [109]. The SLE incidence rate varies from 1 to 10 per 100,000 person/years, and the prevalence varies from 20 to 70 per 100,000 persons. SLE affects more than 300,000 people in the United States (USA) and millions worldwide [110]. It is characterized by multisystem involvement, autoantibody formation, and dysregulation of the complement system. The onset of SLE is postulated to be triggered by environmental and hormonal factors in genetically susceptible individuals [111, 112].
\nThe genetic contribution to the development of SLE is considerably high, which is estimated to be 66% of heritability in twin studies. Genome-wide association studies (GWASs) have greatly improved our understanding of the genetic basis of SLE [113]. A high-density SNP analysis has identified and facilitated to focus on disease-associated loci where patients and healthy controls exhibit different frequencies of trait-associated alleles which are potential disease-causal variants or their proxies [113]. To date, about 100 SLE susceptibility loci have been identified, mostly in European and Asian populations [112], explaining the heritability of SLE up to around 30% [114, 115]. The highly polygenic etiology of SLE is supported by a large number of disease-associated loci that have modest effect sizes but surpass the genome-wide significance threshold for the genetic association with SLE as reviewed by Kwon et al. [112].
\nPTPN22 C1858T polymorphism has been associated with the pathogenesis of SLE in various populations (Table 7). This polymorphism is significantly associated with susceptibility to SLE in American [116, 117, 118], Columbian [86, 87], Crete [119], Spanish [96], Swedish [120], Polish [121, 122], Egyptian populations [123, 124].
\nSeveral meta-analyses also indicated that PTPN22 C1858T polymorphism is associated with SLE susceptibility [2, 107, 125, 126, 127, 128]. On the other hand, it is not associated with SLE in Asians [118], Chinese [99, 129], Hispanics, African-Americans [118], Mexican mestizos [130], and Turkish patients [131, 132].
\nAutoimmune thyroid disease (AITD) is a complex disease which includes GD and Hashimoto’s thyroiditis (HT). Its susceptibility is influenced by both genetic and environmental factors. The interaction of specific susceptibility genes and environmental exposures have been associated with AITD [135]. Both GD and HT are characterized by the production of thyroid autoantibodies and the invasion of thyroid lymphocytes. AITD is found in 5% of the general population and is one of the most prevalent autoimmune diseases. The incidence of GD and HT is influenced by genetic factors as well as environmental factors including geographical locations [136]. Approximately 37% of families with AITD exhibit either of these two disorders [137].
\nPrevious molecular studies on genetic etiology of AITD have expanded the field of thyroid autoimmunity. Previous studies have shown that PTPT22 C1858T is associated with AITD [138, 139] (Table 8). Some reports have indicated a positive correlation [140, 141, 142], while others have indicated no correlation between PTPN22 C1858T and AITD in Japanese [143, 144], Korean [145], Jordanian, [146], and Polish populations [147].
\nPTPN22 C1858T polymorphism has been associated with GD (Table 9). It is susceptible to GD in Latin-American [148], Polish [149, 150], and English Caucasian populations [140, 151, 152]. Two separate meta-analyses confirmed the association of PTPN22 + 1858C/T polymorphism with Graves’ disease [2, 139]. However, some reports have indicated no correlation between PTPN22 + 1858C/T and Graves’ disease in Chinese Han, Polish, and Indian Kashmiri populations [153, 154, 155].
\nJacobson et al. [156] reported that the PTPN22 + 1858C/T is related to the occurrence of HT. Another variant in PTPN22 gene has been found to be associated with HT using whole-exome sequencing [157] indicating the role of PTPN22 in autoimmune thyroid disease. However, the functional mechanism involved in the association remains to be found out.
\nIBD is a complex, multifactorial, chronic inflammatory disorder of the gastrointestinal tract in which immune dysregulation caused by genetic and/or environmental factors plays an important role. IBD refers to two chronic inflammatory disorders of the gastrointestinal tract: UC and CD.
\nThe IBD is a complex autoimmune disease. Its etiology is characterized by immune dysregulation caused by genetic and/or environmental factors [158, 159]. A genetically susceptible person develops IBD as a result of the immunogenic responses against environmental factors and/or microbes inhabiting the distal ileum and colon. It is believed that genetic factors contribute significantly to the pathogenesis of IBD [160, 161, 162]. Genome-wide scans performed in patients with IBD have failed to find a major unique susceptibility locus and have prompted the general agreement that these diseases are polygenic entities in which several genes may contribute to susceptibility [162].
\nSfar et al. [163] reported an association of PTPN22 C1858T polymorphism with IBD in Tunisian patients. Recently a meta-analysis utilizing 8182 patients and 13,356 controls indicated that this is associated with CD susceptibility only and there is no association with UC [164]. No association of PTPN22 C1858T polymorphism with IBD was found in British, Canadian, Czech, German, Italian, Moroccan, New Zealander, and Spanish populations (Table 10). Another study on Spanish patients showed that this polymorphism is protective to CD while there is no association with UC [165]. A meta-analysis also indicated that PTPN22 C1858T polymorphism is associated with reduced susceptibility to CD with no association with UC [2]. Despite the association of PTPN22 C1858T SNP with CD and several different autoimmune disorders, a role for this polymorphism in susceptibility to IBD does not establish.
\nThus, it is plausible that this genetic discrepancy in PTPN22 influences a range of diseases in which the phenotypic spectrum includes an aberrant or hyperactive immune response [5, 166]. However, these variations in the association reports of PTPN22 C1858T polymorphism with IBD may be due to ethnic variations in genetic makeup of the different populations. It has been suggested that the presence of T-allele of PTPN22 C1858T makes an individual susceptible to autoimmune diseases by helping the production of antibodies associated with these diseases, resulting in the disease development [116].
\nType 1 diabetes is an autoimmune disease in which the insulin-producing cells are attacked by the body’s defense system resulting in no insulin or very little insulin production. Although the exact cause of the T1DM is not clear yet, it has been associated with both genetic and environmental factors. It usually develops in children or young adults but can affect people of all age group. The patient will die if there is no access to insulin. Therefore, daily injection of insulin is required to control the blood glucose levels in patients with T1DM.
\nThe International Diabetes Federation (IDF) has reported that there were 382 million people living with diabetes worldwide in 2013 and this number is expected to rise to 592 million by 2035 [176]. Most people with diabetes live in low- and middle-income countries, where rapid changes in lifestyle have increased the prevalence of diabetes, cardiovascular diseases, and cancer, and these countries are expected to experience the greatest increase in cases of diabetes in the next 20 years. The global prevalence of diabetes was reported as 8.8% of the world’s population (95% confidence interval 7.2–11.3%) in 2017, and it is expected to increase to 9.9% in 2045 [177]. At present in every seventh second, someone dies from diabetes or its complications. Fifty percent of these deaths are under the age of 60 years.
\nAccording to a report, 424.9 million people were having diabetes worldwide in 2017 which is expected to increase to 628.6 million people in 2045. The prevalence of diabetes is continuously increasing since the IDF Diabetes Atlas first was launched in 2000, and about 50% of the diabetes cases remain undiagnosed especially in developing countries which is a matter of concern [177].
\nA positive association between PTPN22 C1858 T polymorphism and susceptibility to the development of T1DM has been reported in a large number of studies from several populations (Table 11) with the exception of a few such as a single study from Chinese [178], Greek [179], Indian [180], and Iranian populations [181] where no association was found.
\nThe review by Prezioso et al. [182] evaluated the role of the PTPN22 C1858 T in the prognosis of disease. On the basis of the potential role of C1858 T as a target for tertiary prevention trials and new therapeutic strategies, such as the Lyp inhibitors, they suggested that PTPN22 can be a promising target for therapeutic interventions and identification of at-risk subjects in autoimmune diseases such as T1DM.
\nIt has been shown that several SNPs could potentially contribute to susceptibility to various autoimmune disorders including T1DM. However, 1858C/T SNP is the most stable, where T-allele correlates with T1DM (Table 11) [7, 142, 152, 183]. Habib et al. [211] demonstrate a role of PTPN22 1858T in signaling defects in both transitional and naïve B cells in healthy subjects resulting in an increased resistance to BCR-driven apoptosis in these cells and peripheral reservoir of autoreactive cells [212].
\nSSc is a complex disease with an autoimmune origin in which extensive fibrosis, vascular alterations, and autoantibodies against various cellular antigens are among the principal features [213]. Although the etiopathogenesis is not yet well understood, the results of numerous genetic association studies support genetic contributions as an important factor to SSc.
\nSSc occurs in persons who are genetically predisposed and have faced specific environmental factors with or without other randomly distributed factors [214, 215]. It has been consistently associated with the major histocompatibility complex variants. Non-HLA genes associated with immunity have also been associated with SSc susceptibility [214].
\nIn spite of these findings, the complete genetic background of SSc, the nature of its genetic determinants, and how they contribute to SSc susceptibility and clinical manifestations are poorly understood. Interestingly, PTPN22 has emerged as an important genetic risk factor for human autoimmunity. The PTPN22 C1858T polymorphism in SSc has also been investigated and shows a trend of association (Table 12). It has been associated with SSc susceptibility in French [216], Caucasian [214], and White, Black, and Hispanic American [217]. A meta-analysis showed that PTPN22 1858T is susceptible to SSc [107]. Some other report shows the absence of any association between this polymorphism and SSc in French [218], Columbian [87], and Spanish [219].
\nMG is an antibody-mediated autoimmune disease against antigens at the neuromuscular junction. Both genetic and environmental factors contribute to the susceptibility of MG. The annual incidence of MG is reported to be 0.25–4 patients per 100,000 population, with the first peak of onset around the second and third decades of life and the second peak around the fifth and sixth decades [220, 221]. The exact mechanism of the autoimmunity in MG is unknown. It is caused mostly by the autoantibodies directed toward the skeletal muscle acetylcholine receptor (AChR), but there are cases in which autoimmune attack targets non-AChR components of the postsynaptic muscle endplate [222, 223, 224, 225]. It has been suggested that genetic factors might play an important role in the development of MG [226, 227]. Some studies showed that PTPN22 C1858T polymorphism is associated with MG risk (Table 13).
\nPTPN22 C1858T polymorphism is associated with MG susceptibility in Swedish [228], German [229], European [230], Hungarian [231], and French patients [232]. However, the association between this polymorphism and the risk of MG was controversial and inconclusive in Chinese, Italian, and Turkish patients [2, 233, 234].
\nBD is characterized by recurrent orogenital ulcers, cutaneous inflammation, and uveitis. It is a chronic autoimmune/inflammatory disorder with typical mucocutaneous and ocular manifestations. It also targets musculoskeletal, nervous, vascular, and gastrointestinal systems [236]. The prevalence of BD varies with geographical locations. It is more prevalent in countries along the silk route, particularly in the East Asia and the Middle East. Prevalence is highest in Turkey, followed by Egypt, Morocco, Iraq, Saudi Arabia, Japan, Iran, Korea, and China [237, 238]. Available reports indicate that autoimmunity, genetic factors, and environmental factors are involved in the pathogenesis of BD; however, the specific etiology remains to be determined [236, 239, 240].
\nBeing an autoimmune disease, BD is considered to be affected by PTPN22 C1858T polymorphism. However, there is no significant association of this gene in susceptibility to BD (Table 14). Baranathan et al. [241] suggested that PTPN22 C1858T is inversely associated with BD in the UK population indicating its protective role in BD. However, this does not hold for Middle Eastern patients in whom PTPN22 C1858T expression does not associate with BD, possibly due to a very low prevalence of the polymorphism in this population.
\nThe prevalence of PTPN22 C1858T is very low in the general population, and the absence of any correlation with BD indicates that PTPN22 C1858T polymorphism has a limited role in the pathogenesis of autoimmunity [242]. Recently
Endometriosis is a chronic inflammatory disease and one of the most common benign gynecological disorders. It is a condition in which a tissue that is histologically similar to the endometrium, with glands and/or stroma, grows outside the uterine cavity [244]. It presents a multisystem involvement affecting several organs, most commonly in the peritoneum and pelvis, especially the ovaries, and less often in the rectovaginal septum. This results in pelvic pain, dysmenorrhea, and infertility [245].
\nAlthough various hypotheses have been proposed to explain the etiology of endometriosis, the explanation of symptoms and presence of ectopic endometrial tissue and stroma at various sites is not very clear [246].
\nThe etiology of endometriosis is complex and characterized by genetic and environmental factors similar to other autoimmune diseases. The immunological changes such as an increase in the number and cytotoxicity of macrophages, increase in the activity of B lymphocytes, abnormalities in the functions and concentrations of B and T lymphocytes, and reduction in the number or the activity of natural killer cells have been indicated in endometriosis. Anti-endometrial and anti-ovary antibodies have been also found in endometriosis [247]. As genetic factors and immunological predispositions are involved in the etiology of the disease, therefore the variants of genes associated with autoimmune diseases are possible candidates for endometriosis development [247]. PTPN22 C1858T polymorphism and its association with endometriosis have been studied in only three populations (Brazilian, Italian, and Polish) so far (Table 15).
\nThe PTPN22 C1858T polymorphism has been reported to be associated with altered risk of endometriosis in Italian and Brazilian populations, but no significant association was found in Polish patients. However, on exploratory analyses
A meta-analysis showed overall increased risk associations of up to 5.6-fold in endometriosis. In the presence of endometriosis, the PTPN22 C1858T polymorphism may cooperate with clinical and genetic factors to influence the course of disease and immune reactions. These cooperative interactions could result in a statistical association between PTPN22 C1858T and endometriosis [246].
\nThe lymphoid tyrosine phosphatase enzyme is encoded by PTPN22 gene and is a regulator of signaling through the T-cell receptor and forms a complex with the kinase Csk in T cells. The variant of PTPN22 C1858T polymorphism does not bind kinases properly and results in a gain-of-function enzyme [246, 249, 250]. The increased inhibition of T-cell receptor signaling caused by the PTPN22 C1858T polymorphism could predispose toward autoimmunity, either by affecting the thymic deletion of autoreactive T cells or by affecting the development or function of peripheral regulatory T cells [251].
\nAntineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is an uncommon inflammatory disease, characterized by inflammation in small- to medium-sized vessels, necrosis, and association with detectable circulating ANCAs. Though the manifestations in the lungs and kidneys are common, any organ or system can be affected. AAV refers to a group of small-vessel vasculitis, including granulomatosis with polyangiitis (GPA, formerly known as Wegener’s granulomatosis), microscopic polyangiitis (MPA), and eosinophilic GPA (EGPA, formerly Churg-Strauss syndrome) [256].
\nAAV is a complex disease with both genetic and environmental factors involved in pathogenesis [257]. There is increasing evidence that susceptibility loci are shared between autoimmune diseases. The candidate gene association studies and the GWASs have shown the genetic basis of AAV. The significant association of AAV with HLA polymorphisms has confirmed the central role of autoimmunity in the development of AAV. All the three main subtypes mentioned above have been reported to be associated with distinct HLA variants [258].
\nThe role of PTPN22 C1858T in AAV provided the basis for the three main PTPN22 genetic association studies performed so far (Table 16). The first, which included a German cohort, showed an association of this variant with the disease; the association was even more significant in the ANCA-positive subgroup [259]. This result has been subsequently replicated in two independent cohorts of British [260] and Italian AAV patients [261]. However, the study on Italian patients showed that the association is restricted to the GPA patients only, as almost similar frequency of the T-allele of PTPN22 C1858T was found in the MPA or the EGPA patients and controls.
\nThree independent meta-analyses indicated that PTPN22 C1858T polymorphism is significantly associated with susceptibility of AAV in Caucasian population [76, 262].
\nGCA is a form of vasculitis. It is very common in elderly people and may cause blindness and stroke [263]. The environmental, infectious, and genetic risk factors have been associated with GCA development; however, the pathogenesis is not clear yet. PTPN22 is a gene of interest which is proposed to be an “archetypal non-HLA autoimmunity gene” [251, 264]. The T-allele of a functional PTPN22 C1858T polymorphism has been reported to be associated with biopsy-proven GCA in Spanish patients (Table 17), with supporting data from three replicate Northern European studies [265]. Recently, this observation has been extended with additional patients and controls and studies encompassing European, Scandinavian, UK, and American patients [266], though an earlier report from Spanish patients does not support the potential involvement of PTPN22 gene polymorphism in the susceptibility or clinical expression of GCA [263].
\nThough Lester et al. [267] could not find any significant difference in the distribution of alleles and genotypes of PTPN22 C1858T polymorphism between patients and control groups, they suggested that there is a significant association between the minor allele of PTPN22 C1858T polymorphism and GCA.
\nAAD occurs due to autoimmune destruction of the adrenal cortex. Approximately half of the patients have additional autoimmune components. The prevalence of AAD varies from 110 to 144 cases per million in the developed countries. In adult patients, AAD is the most common etiological form (80%), followed by post-tuberculosis AD (10–15%) and vascular, neoplastic, or rare genetic forms (5%) [268]. AAD commonly coexists with thyroid autoimmunity and/or type I diabetes and is called as autoimmune polyendocrine syndrome type II (APS II).
\nSeveral genetic determinants have long been suspected to be involved in various autoimmune diseases. PTPN22 C1858T polymorphism has been studied in AAD patients with inconsistent results (Table 18). Velaga et al. [151] reported an association for the T-allele in patients from northeast England, whereas Kahles et al. [185] found no association in German patients. This inconsistency may be due to small sample size. The 1858T allele is associated with susceptibility to AAD in Norwegians [269], UK cohort, and the Polish population [270]. Meta-analysis of the results, together with those from three other populations, showed that the 1858T allele is associated with AAD susceptibility.
\nConfounding factors must be considered particularly when polymorphisms identified in one study cannot be duplicated in a similar ethnic group. One confounding factor is population stratification. This may occur with an unbalanced ethnic admixture.
\nIt is clear that the inheritance of a coding variant of PTPN22 gene is associated with increased susceptibility to autoimmunity. The mechanism by which the PTPN22 C1858T variant modulates disease risk has been studied. PTPN22 is capable of both enzymatic activities and adaptor functions. It exerts its effects in multiple biochemical pathways and cell types. PTPN22 regulates signaling through both antigen and innate immune receptors. It is involved in the development and activation of lymphocyte, establishment of tolerance, and innate immune cell-mediated host defense and immunoregulation. The PTPN22 C1858T variant protein is involved in the pathogenesis of autoimmunity at multiple levels. The action of PTPN22 C1858T during immature B-cell selection disrupts the establishment of a tolerant B-cell repertoire and alters mature T-cell responsiveness. When an autoimmune attack initiates tissue injury, the TPN22C1858T fosters inflammation by regulating the level of cytokines produced by a myeloid cell.
\nThe PTPN22 C1858T is one of the strongest and most consistent genetic associations with autoimmune diseases. However, available literature on PTPN22 C1858T polymorphism and autoimmune diseases shows ethnic variations. It is conceivable that the relation of any locus with the autoimmune disease will be small as interactions between gene and gene and gene and environment might also be operating. Further well-designed studies from different populations and cohorts to detect small genetic risk will help in drawing better conclusion on the development of autoimmune diseases. Therefore, further genetic studies on patients suffering from various autoimmune diseases from different ethnicities and PTPN22 gene polymorphisms are expected to help better understand the pathogenesis and will contribute to the development of more targeted therapies and biomarkers.
\nAuthors wish to thank the MSD administration for facilities and support.
\nNo conflicts of interests.
The plant growth, development, and yield are negatively affecting by abiotic stresses such as drought, salinity, chilling, and high temperature. About 50% of plant productivity is under the influence of these abiotic stresses [1]. Among these abiotic stresses, salinity is considered as one of the most harmful agents for the plant life cycle. Salinity is an excess amount of salt in the soil, water, and plant. Salinity is frequently an underrated problem in the agriculture sector. It is estimated that salt affected area (sodic and saline) about 6% irrigated and 20% of world’s total cultivable land is under the influence of salinity [2]. The irrigated areas of many countries are affected due to salinity in the world (Table 1) [3]. Salinity problem is caused by the natural and anthropogenic activities and increasing with time. It is also estimated that 50% of the cultivable land will effect due to salinity by 2050 [2]. On the contrary side, with the current speed of population increase in the world, also need to produce more food up-to 70% till 2050 to feed the increasing mouths of the world [2].
\nCountry | \nSalt-affected area of irrigated in the world | \n|
---|---|---|
\n | Mha | \n% | \n
China | \n6.7 | \n15 | \n
India | \n7.0 | \n17 | \n
Soviet Union | \n3.7 | \n18 | \n
United States | \n4.2 | \n23 | \n
Pakistan | \n4.2 | \n26 | \n
Iran | \n1.7 | \n30 | \n
Thailand | \n0.4 | \n10 | \n
Egypt | \n0.9 | \n33 | \n
Australia | \n0.2 | \n9 | \n
Argentina | \n0.6 | \n34 | \n
South Africa | \n0.1 | \n9 | \n
Subtotal | \n29.6 | \n20 | \n
World | \n45.4 | \n20 | \n
Global estimate of secondary salinity in irrigated lands of the world.
where, mha = million hectare, % = percentage area. Source: Ghassemi et al. [3].
Many major field crops such as wheat (Triticum aestivum L.), rice (Oryza sative L.), maize (Zea mays L.), sorghum (Sorghum bicolor (L.) Moench), cotton (Gossypium hirsutum), and sugarcane (Saccharum officinarum), etc. show negative response towards salinity. However, plant performance and grain yield may not decrease until a ‘threshold’ salinity level is reached. Threshold levels of salinity are generally defined as the maximum amount of salt that a plant can tolerate in its root zone without impacting growth (Table 2). Plant physiology is very susceptible to high salinity in its rhizosphere and affects germination rate, growth stages, and ultimately plant yield [1]. Similarly, many other growth hampering effects on plants due salinity are low net CO2 assimilation to plant tissues, leaf area, leaf cell enlargement, dry matter production, and relative growth, poor development of spikelets (rice and wheat), boll (cotton), etc. [4, 5]. There are many reasons for hampering of plant production under salinity. Generally, salinity affects plant growth in three ways, such as osmotic stress, ionic stress or ion imbalance, and oxidative stress [6]. Osmotic stress disturbs the salt water balance, which results in a high concentration of salts and loses of water in plant cell sap and tissues. This imbalance causes ion toxicity within plant tissues, and plant shows leaf burn or wilting symptoms due to Na+ and Cl− accumulation. Ionic stress also causes nutrients disequilibrium and results in reduce final germination percentage (FG %), decrease vegetative and reproductive growth, decline yield, and yield components of the plant under salinity. Similarly, ionic stress in the plant due to salinity causes reduction of photosynthesis activity, alteration of enzymatic activities, oxidative stress, disrupted the biochemical membrane structure and function, destroy the ultrastructural cellular components, and hormonal imbalance are the primary reason for the reduction of overall plant’s growth and development [7, 8].
\nSoil types | \nECe (dS/m) | \nESP | \nSAR | \npHs | \n
---|---|---|---|---|
Normal soil | \n<4 | \n<15 | \n<15 | \n4.5–7.5 | \n
Saline soil | \n>4 | \n<15 | \n<15 | \n<8.5 | \n
Sodic soil | \n<4 | \n>15 | \n>15 | \n>8.5 | \n
Saline-sodic soil | \n>4 | \n>15 | \n>15 | \n>8.5 | \n
The USDA classification system of salt affected soils.
Whereas, ECe = electrical conductivity, ESP = exchangeable sodium percentage, SAR = sodium adsorption ratio, and pHs = negative log of H+ ion [12].
For better plant performance under salinity stress, natural adaptation responses at physiological, molecular, and cellular levels to tolerate salinity stress is of great concern. These adaptations are an osmotic adjustment, closure of stomata, Na+ exclusion from older leaves, maintenance of K+/N+ equilibrium, and cytosolic K+, transpiration efficiency, and increased antioxidant defense system are very important for ideal plant growth under salinity. Besides these, various other management strategies have been embraced on a scientific basis to improve plant growth efficiency under salinity. These strategies are genetic modification, identification, sequencing of gene, microarray analysis, and plant transformation, and agronomic strategies to reduce salinity stress by soils reclamation via water and nutrients management, seed priming, and usage of hormone regulator to create homeostasis in hormonal production under salinity. These management strategies are being useful for stress management, including salinity. In this book chapter, we will review the latest information about the ‘Salinity Stress in Arid and Semi-Arid Climates: Effects and Management in Field Crops, which could be a good advantage to the scientific community and farmers for the understanding of salinity issue in the field crops and their solution.
\nThe ecological anxieties (biotic and abiotic stresses) have turned into essential threats to plant growth, development, and survival. Among these ecological anxieties, abiotic stresses, for example, drought, chilling or high temperature, and salinity inactively influencing the growth, biomass generation, and yield of many field crops. These threats are ending up more deteriorated by regular or human-made activities, which result in the excessive soluble salts accumulation in the underground water and soil. As concern salinity stress, about 20% of the world’s land, and about 33% of the world’s irrigated zone is under the impact of salinity [9]. Besides, salinity influenced areas are expanding at a rate of 10% yearly. The expanding of salinity issues are because of low precipitation, high surface evaporation, weathering of native rocks, irrigation with saline water, and poor agronomic practices. Salt influenced soils have various sorts that negative effect on agricultural production, for instance, irrigation-induced salinity and ‘transient’ dry-land salinity have been arranged in detail with different perspectives considered by [10], and illuminate that salinity in the soil is one of the vast abiotic stress that hamper the agricultural production in the world. The estimation has been done that >50% of the agricultural land would be affected by agricultural till 2050 [11].
\nSalinity is the issue of almost all the continents and under a wide range of climates. However, the salinity issue is more in arid and semi-arid climate contrasted with the humid climate where yearly precipitation is not as much as evapotranspiration in the world. It is need of great importance to comprehend the mode and sources of salinity with classification, and its role in the plant life cycle. The characteristic critical source of salinity is the primary minerals in exposed layers of the earth crust by weathering process with the assistance of atmospheric CO2. The weathering of these primary mineral rocks in the earth crust is the primary source of all the dissolvable salts present in the soils and ocean. However, there are several other anthropogenic sources of salinity in the soil or water. Under arid to and semi-arid climates, the products from the weathering procedure of mineral and rocks accumulate in the soil and result in the advancement of salt-influenced soils (saline or sodic soil). Though, under a humid atmosphere, salt could not collect in-situ and filter down through the soil and transport to the close-by streams and waterways and caused the salinity in the water bodies [12]. The US Salinity Lab staffs (1954) group the salt-influenced soils (Table 2). These salt-affected soils types have unique nature of soluble salts. For instance, saline soil has Cl−and SO42− and CO32− present and sodic or alkali soil has HCO3− of Na+, and in exceptional cases with high CO32− concentration with the capacity of alkaline hydrolysis. So also, saline sodic soil has predominant soluble salts of Na+ with Cl− and SO42− with an average intensity of NaHCO3 and Na2CO3 in a trace concentration. An ordinary soil has maximum nutrients for development and improvement of the plant. On the inverse, Salinity is one of the significant environmental element influencing plant growth and production. As indicated by FAO report, a saline soil is characterized as having a high concentration of soluble salts for the most of Sodium (Na+), Calcium (Ca2+), magnesium (Mg2+) chloride (Cl−) and sulfate (SO42−). Magnesium sulphate (MgSO4) and sodium chloride (NaCl, table salt), are among the most well-known soluble salts which are sufficiently high to influence plant growth and development.
\nSalinity influence crops in these ways: osmotic effect, specific ion effect, ion imbalance, and oxidative stress [6]. Salinity decline water uptake limit of plant, and causes a decrease in plant development. It might be explicit salt effects. If a high concentration of salt enters the plant, this high concentration of salt will increase at last ascent to a toxic level in older leaves causing early senescence and diminished the photosynthetic leaf area of a plant to a dimension that cannot support plant development [14]. Salinity seems to influence plant growth mechanism in two different ways, water relations, and ionic relations. Firstly, plants face water stress, which in cause decline leaf expansion. Secondly, long-term salt stress in soil and plant, plants involvement (Na+ and Cl−) ionic stress, which can prompt early senescence of older leaves [15] (Figure 1).
\nSalinity response adaptations in plant. Extracted from Kumar et al. [17] and Hussain et al. [18].
Plants experience the ill effects of the presentation of salinity until maturity [16]. Generally, the markers of salinity impacts in plants are impeded growth and small plants with fewer and smaller leaves. Munns [16] depicted salinity consequences for various plant development stages under a different period of the plant growth mechanism and development. After a couple of minute’s introduction of salinity stress, dehydration and shrinkage of the cell begin, and following a couple of hours after the fact recovers their original volume. Regardless of this recovering of the original volume, cell elongation and cell division are diminished, prompting slower rates of root and leaf development. On the following days, a diminishing in cell division and lengthening change into slower leaf inception and size. Plants that are harshly salt influenced regularly build up obvious salt damage. As exposure of salinity extends to half a month, secondary shoot growth is influenced, and following a couple of months, clear changes observed in development and injury between salt-stressed plants and control. To comprehend these time-sensitive changes in light of salinity in plant development stages, the ‘two-phase growth response to salinity idea created by [16]. The first phase of growth decline occurs within minutes after exposure to salinity. The decline of growth is because of the osmosis stress, osmotic changes outside the root surface, causing changes in osmotic impacts. In the wake of taking some days, weeks or even months the other slower impact (explicit salt impact), bringing about the aggregation of salt in leaves, basically in older leaves and salt toxicity in the plant. This salt toxicity in the plant can cause the death of leaves and decrease the total photosynthetic leaf area. Thus, there is a decrease in the availability of photosynthate to the plant and influence the overall carbon (CO2) balance essential for sustainable plant growth and development [16] (Figure 1).
\nThe important harmful effect of salinity is the sodium and chloride ions accumulation in plant tissues and soil [19]. The higher concentration of soluble salts in the soil profile may cause physiological drought to plant, that is, reduction in uptake of water due to salt accumulation in the root zone [20]. The entrance of sodium and chloride ions into the plant cell from soil causes ion imbalance in plant and soil and excessive uptake of these ions by plant causing many problems related to the physiology of plant’s tissues such as root, leaf, grain, fruit, or fiber [21]. Similarly, the reduction of plant osmotic potential, excessive uptake of Na+ and Cl− in the cell, and disruption of cell metabolic functions is due to ion toxicity [21]. Excessive sodium ion in plant tissues harms the cell membrane and plant organelles, and as a result, cell death of plant [22]. These physiological changes in the plant include the membranes disruption, reactive oxygen species (ROS) production, reduction of photosynthesis rate (Pn), and scavenging of antioxidants [21]. Consequently, the accumulation of soluble salts in the rhizosphere is one of the main reasons for low crop productivity.
\nSalinity has direct effects on nutrients imbalance between soil and plant. The most important harmful effect of salinity is the sodium and chloride ions accumulation in plant tissues and soil [19]. High sodium ion (Na+) concentration has an antagonistic effect on potassium (K+) ions [23]. Moreover, N uptake reduction by the plant has also been observed under high salt conditions [24]. Similarly, salinity has an antagonistic effect on P, K+, Zn, Fe, Ca2+, and Mn while it has a synergistic effect on N and Mg in field crops such as rice [23, 25].
\nThe production of reactive oxygen species (ROS), like oxygen radical (O2−), superoxide (OH−), and H2O2 under salinity is high [30]. These oxidative species can interrupt the routine functions of various cellular plant modules. For example, DNA, proteins, and lipids, are interfering metabolism of the plant [26].
\nThe phytohormones are naturally produced in a chemical form called plant growth regulators. The phytohormones are active signal compounds which show response against salinity stress and reduce the plant growth [27]. Under salinity stress, the ethylene, cytokinin, and gibberellic acid concentration decreased, and abscisic acid contents increased. This alteration of hormones effects plant growth, such as germination, tiller formation, and reproductive growth. For example, poor development of rice and wheat spikelets, boll of cotton, etc.
\nFulfill the food demand and livelihood of the increasing population by 2050, a remarkable increase about 50% more yield in the form of grain, fiber, sugar, etc. is required from major field crops such as wheat, rice, and maize sorghum, cotton, and sugarcane [28]. However, the purpose of competing for the demands of human beings on the globe while combating abiotic stresses, including salinity. The different crop has different responses against abiotic stresses such as salinity. Salinity suppresses the crop plants growth, development, and productivity. The sensitivity of the crops varies from low to high concentration of soluble salts or EC (Table 3). At low salt concentrations, yields are slightly affected or not affected at all in some crops [29]. Whereas the most plants, glycophytes, including the most crop plants, decrease yield towards zero or even plant death as soluble salt concentrations increase by 100–200 mM NaCl due to low resistance and tolerance capacity of plants [30] (Table 3).
\nCrop type | \nTolerance based on | \nThreshold EC levels (dS m−1) | \n25% yield loss (dS m−1) | \n50% yield loss (dS m−1) | \nZero yield (dS m−1) | \nRanking | \nReferences | \n
---|---|---|---|---|---|---|---|
Wheat | \nGrain yield | \n6–8 | \n6.3 | \n10 | \n16–24 | \nMT | \n[31] | \n
Rice | \nGrain yield | \n3 | \n3.2 | \n3.5–4 | \n8–16 | \nS | \n[32] | \n
Maize | \nEar FW | \n1.8 | \n2.5–6.8 | \n8.6 | \n15.3 | \nMS | \n[33] | \n
Sorghum | \nGrain yield | \n6.8 | \n7 | \n10 | \n30 | \nMT | \n[34] | \n
Cotton | \nSeed cotton | \n7.7 | \n8.3 7 | \n17.0 | \n16–24 | \nT | \n[35] | \n
Sugarcane | \nShoot DW | \n1.7 | \n3.9 | \n13.3 | \n16–24 | \nMS | \n[36] | \n
Salt tolerance classification of major field crop.
Where EC = electrical conductivity, FW = fresh weight, DW = dry weight, S = sensitive, MS = moderately sensitive, MT = moderately tolerant, and T = tolerant.
Rice is monocot and belongs to a C3 plant with salinity responsive behavior as compared to other field crops [37]. Rice is vital to the lives of billions of people around the globe. Rice is grown in many parts of the world, especially in Asia, Latin America, and Africa, and taken as a chief food item for more than 50% population of the world [38]. Rice is among the first five major carbohydrate crops for the population of the world, particularly for Asian countries. Only Asia contributes 90% of total rice cultivation in the world. From this 90%, China contributes 30%, India (21%), and Pakistan (18%) respectively, while remaining 30% is contribution belongs to Japan, Thailand, Indonesia, and Burma [39]. Rice is a high yielding crop. However, the current average yield is 8–10 t/ha for indica rice, 10–15% yield is lower than its potential [40]. This rice production gap is due to many reasons, such as environmental stresses (biotic or abiotic), management strategies, and nutrients deficiencies.
\nAmong the abiotic stresses, especially salinity is among the essential causes of this low yield. The morphological characteristics of rice are severely affected by salinity [41]. Rice plant responds differently against salinity compared to other field crops. The intent of salinity in rice plant life cycle varies from growth stages, and cultivar to cultivar, that is, the early seedling growth stage is more sensitive than the tillering stage in rice plant [14]. The threshold level of salt stress for rice is 3 dS m−1 [42]. However, a significant reduction in seedling growth and fresh weight were observed with increased salt stress from 1.9 to 6.1 dSm−1 and 5 to 7.5 dSm−1, respectively [43]. Many studies also exposed that salinity stress decrease rice stand density and production of seedling biomass, which shows the high sensitivity against salinity [4, 44].
\nThe first organ of the rice plant that keeps in contact with soluble salt is a root [45]. The root is responsible for the entrance of hydrogen peroxide (H2O2) and solutes by through different pathways such as symplastic, apoplastic, and transcellular, respectively. So, transport of water and solutes through the apoplastic pathway is vital in rice [46]. Mostly Na+ transport in rice shoots via the apoplastic passage where Na+ transports by apoplast through Casparian tubes [47]. As a result of this Na+ accumulation, a significant reduction in numbers of root per plant, root length, and shoot length occurred under increased salinity [48]. Based on these proofs, the reduced root and shoot lengths are considered two indicators of rice plant response to salinity.
\nMoreover, cell division and cell elongation in rice plant are severely affected by salinity, which results in a reduction of the root, leaf growth, and yield [16]. Rice plant shows response very soon after the exposure of salinity stress and affects plant growth. For example, rice leaf mortality boosted with increased salinity in almost all rice cultivars at early seedling stage [14]. Some rice cultivars showed leaf mortality up to 0–300% after 1 week of salinity exposure [16]. Salinity effect cause panicle sterility and poor development of inferior and superior spikelets, which result in the reduction of rice grain yield [4]. Many rice cultivars showed panicle sterility at pollination and fertilization stages due to some genetic mechanisms and nutrient deficiencies resulting from salinity stress [49], which leads to a decrease in grain setting rate, pollen viability, and decline of the stigmatic surface.
\nPlant physiological traits are susceptible to the high soluble salts in its rhizosphere. Salinity has bunch of adverse effects on physiology of rice plants, such as hinder the net photosynthesis (Pn), stomatal conductance (Gs), transpiration rate (Tr), photosynthetically active radiation (PAR), degradation of pigment and relative water content (RWC) as well as affect the water use efficiency (WUE) [50]. As far as photosynthesis activity is a concern, rice plants under salinity have decreased photosynthetic efficiency through the complex of photosystem II (PSII). Furthermore, chlorophyll contents in rice leave tissues are damaged by the excessive accumulation of Na+ and Cl−, which hamper the primary electron transport in PSII [51]. The chlorophyll contents (chl a, b, and carotenoids) in rice leaves were significantly declined under salinity [52]. High salinity also reduces the quantum yield of the complex PSII, and to decrease K+/Na+ ratio. All these factors cause adverse pleiotropic effects on rice physiology and development at the molecular and biochemical levels [53], and cause abnormal rice growth, development, and ultimately plant death [19].
\nIon imbalance is the ultimate effect of salinity. Under salinity, the severe competition of Na+ and Cl− with K+, Ca2+, and NO3− occurs. Generally, high NaCl concentration in the soil and plant decrease the reduce N, P, K, Ca, Mg, and Mn in rice root and shoot, and increases Na+ and Cl−, and increases Na+/K+ and Na+/Ca2+, Ca2+/Mg2+, and Cl−/NO3− ratio leads to specific ion (Na+ and Cl−) toxicity in plant’s organelles [54, 55]. Similarly, boron (B), silicon (Si), and zinc (Zn) availability decreased to the rice plant, and increased cadmium (Cd) toxicity subjected to salinity [56, 57].
\nWheat is a worldwide staple food belongs to the Poaceae family. Wheat ranks as the first position in grain production globally. About 36% population of the world consume Wheat as a staple food and provides carbohydrates (55%) and 20% of the food calories (20%), and protein contents (13%), which is higher than other cereals crops worldwide [58]. However, wheat production is severely affected by salinity. Wheat is susceptibility to salinity starts at 6 dS m−1. Under salinity, water potential in soil lower down and Na+ concentration within plant tissues increases, and as a result wheat plant faces osmotic and ionic stresses. Salinity stress having passive impacts on agronomic, physiology, and chemical characteristics of the wheat plant. As salinity level crosses the threshold level (6 dS m−1) of the wheat plant, germination rate, net photosynthesis rate, transpiration rate decrease, and yield, and increases the Na+ and Cl− in the wheat plant which disturbs the normal metabolism of the plant [58]. Similarly, water use efficiency (WUE), production of reactive oxygen species (ROS) and scavenging of antioxidants are attributes of the wheat plant affected by salinity.
\nSalinity stress hinders the germination rate (GR) and speed of germination, which is the vital process of the plant cycle, and an important indicator of growth and yield components of the plant, but depend on nature of cultivar. For example, at 125–200 mM NaCl and 12.5–16 dS m−1 salinity levels, germination time increased and decreased the GR and germination index [59, 60, 61]. During the germination process under salinity, seed faces the osmotic stress, which imbalance the enzymatic activities necessary for nucleic acid and protein metabolism, hormonal imbalance, and ultimate the disturb the seed reserves [62]. Along with these germination characteristics, salinity also affects the other agronomic parameters such as root length, shoot length, root and shoot dry weight, plant height, leaf area, tillering dynamics, and spikes numbers per plant at the early seedling stage. At the early growth stage of the wheat plant, plant shows high sensitivity at 120, 125, 150 mM NaCl, and 16 dS m−1, even seedlings death occurs [11, 63]. Furthermore, wheat seedlings also reduce its growth; even exposure to salinity stress is for a few days (7–10 days) at 100 mM NaCl salt level. Similarly, yield components such as the number of spikes per plant, spikes length, and the number of spikelets per spike, above ground biomass, 1000-grain yield, harvest index, and grain yield per plant decreased with increased salinity stress [64]. However, when the wheat plant cross the threshold level of salinity (6 dS m−1), wheat grain yield reduces at the rate of 7.1% with increasing salinity of per dS m−1 and significant yield reduction occurs at 15 dS m−1 [65].
\nPhotosynthesis activities such as net photosynthesis rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), intercellular CO2 concentration, and water use efficiency (WUE) affected by salinity. The Pn badly influenced by the high accumulation of Na+ and Cl− in the chloroplast tissues [66]. These parameters (Pn, Tr, Gs, intercellular CO2 concentration) are reduced under 150 mM NaCl salinity level. Similarly, a decrease in photosynthesis pigments was observed at 320 mM NaCl concertation, and after 10 days exposure of NaCl, the chlorophyll contents (chl a, b, and carotenoids) decreased [67]. WUE and RWC also affect by osmotic stress caused by salinity. Water potential lower down with increased salinity levels and as a result relative RWC in the wheat plant decreased by 3.5% in the salt tolerant cultivar and 6.7% in salt-sensitive cultivar after 6 days exposure of NaCl (100 mM NaCl) [68]. Along with this leaf water potential and WUE also decrease in 150 mM NaCl and 16 dS m−1 salinity levels. For example, water content percentage in root reduced and increased in shoots and spike of wheat cultivar Banysoif 1. Similarly, at 320 mM NaCl, the RWChas decreased in leaves of wheat cultivar T. monococcum seedlings [69].
\nReactive oxygen species (ROS) increase under salinity in the plant. However, when plant faces high salinity, the production of ROS reduces the scavenging system and stops the oxidative stress. This change occurs in plants due to the reduction of CO2 availability in leaves and inhibits fixation of carbon, and excitation energy enhance which expose the chloroplast, all these happened due to stomatal closure. ROS such as H2O2, superoxide (O2•–), hydroxyl radical (OH•), and singlet oxygen (1O2) are produced under increasing salinity stress in the plant [62, 65]. Osmotic stress caused by salinity is the leading cause of ROS production and results in the cellular damage by oxidation of lipids, proteins, and nucleic acid. The oxidative stress is caused by an imbalance in ROS production and scavenging of antioxidants in plant tissue. As a result of ROS production, phytotoxic reactions in plants occur such as lipid peroxidation, protein degradation, as well as DNA mutation [70]. For example, exposure of salinity levels 5.4 and 10.6 dS m−1 for about 2 months caused a significant increase in lipid peroxidation and hydrogen peroxide (H2O2) in seedlings of the wheat-sensitive cultivar [71]. Similarly, H2O2 (60%) and MDA (73%) increased at 300 mM NaCl salinity level, and decreased ascorbic acid (AsA) content (52%) in wheat seedlings [67]. For a short period salinity exposure such as after 5 days, MDA contents increased by 35%, and after 10 days, MDA contents increased by 68% at 100 mM NaCl salinity level in wheat leaves. Along with these, the concentration of salt levels in term of EC levels such as 2, 4, 8, and 16 dS m−1 EC effects the lipid peroxidation, MDA increased significantly and varied from cultivar to cultivar.
\nPlants also have an anti-oxidative system to compete against adverse salinity conditions. Therefore, under unfavorable conditions (salinity) plant produce antioxidant enzymes in an excessive amount such as superoxide dismutase (SOD), POD, CAT, GR, and APX, etc. which reduce the damage caused by salinity. A study showed that, under increased salinity stress, the SOD, CAT, POD, GR, ascorbic acid (AsA) and APX activities increased irrespective to the nature of wheat cultivar [68]. After 10 days of salinity stress at 100 mM of NaCl showed significant higher POD and SOD contents and non-significant increase in the CAT and APX contents with a decrease in GR and DHAR contents in wheat seedlings [67].
\nSalinity stress also causes an imbalance in ion uptake and ion toxicity in the plant. Na+ absorption varies from nature of wheat cultivars against salinity stress [68]. Salinity increase the intake of Na+ and Cl− and reduced the K+ and Ca2+ uptake along with the lower accumulation of NO3− and PO43− in wheat seedlings under 125 mM of NaCl level for one-week exposure, and decreased the K+/Na+ ratio in wheat shoots at 120 mM of NaCl [11, 65, 66]. Similarly at high EC 15–16 dS m−1, K+ accumulation significantly decreased, and under medium salinity stress, Na+ and Cl− accumulation increase and decreased the uptake of K+, Ca2+, and Zn2+ [64, 65, 72].
\nMaize is an important cereal crop which is being cultivated over a large area under a wide spectrum of edaphic and climatic conditions. It is categorized as a C4 plant of the Poaceae family and is moderately sensitive to salinity [73]; nevertheless, a considerable intraspecific genetic potential against salinity also exists in the maize. The threshold level of salinity for maize is 0.25 mM NaCl or 1.8 dS m−1, and a further increase in salinity may stunt growth and cause severe damages [74].
\nSalinity significantly induces the detrimental changes in growth and development of maize, but the response of maize varies with the crop growth stage and degree of stress. The short term exposure to salinity may influence the growth of maize plants duet to osmotic stress without causing the ionic toxicity. The germination and early seedling stages of maize are more sensitive to salinity than later developmental stages. Generally, salinity during germination period delays the initiation, reduces the rate, and increases the dispersion of germination phases [75]. Salinity induces the detrimental impact on seed germination; (a) by sufficiently reducing the osmotic potential of the soil, leading to retard the water absorption by seed, and (b) by inducing Na+ or Cl− or both ions toxicity to the seed embryo. Therefore, hyper-osmotic effects and toxic stress of Na+ and Cl− ions on germinating seeds under saline conditions may delay or reduce germination [75]. Maize as a salt-sensitive crop, the shoot growth in maize is sharply reduced during the osmotic stress phase [76]. However, Schubert et al. [77] proved that it was cell wall extensibility, which limited the cell extension growth during osmotic stress phase than turgor in the cells. In crux, salinity-induced growth reduction in maize is primarily due to the suppressed leaf initiation and expansion, as well as internode growth and also by increased leaf abscission. Additionally, Salinity reduced the grain number and weight, leading to low grain yield of maize. This reduction was due to the limitation of the sink and reduced activity of acid inverses in developing maize grains lead to poor kernel setting as well as reduced grain numbers.
\nCotton is grown as the most important fiber oilseed crop, providing 35% of the total fiber used globally [78]. About 29.5 million hectares of cotton were grown during 2016–2017 with a total production reaching to 106.49 million bales during 2017 [79] worldwide. Gossypium hirsutum is giving over 90% of the world cotton crop annually, after spreading from its origin in Mesoamerica to more than 50 countries in Northern and Southern hemispheres.
\nCotton is mostly grown in arid and semi-arid regions of the world, where water shortage is a dominant factor [80]. In general, salinity severely hinders cotton growth and development, including the reduced plant height, fresh and dry weights of shoot and roots, leaf area index, node number, canopy development, photosynthesis, transpiration rate, stomatal conductance, yield, fiber quality, and root development [81]. However, cotton is considered a moderately salt tolerant crop which can withstand EC up to 7.7 dS m−1 [34]. Generally, salinity effects on cotton at all ontogenetical levels, from molecular to organismal, which lead towards the reduced plant growth, economic yield, and fiber quality. But these effects depend on the timing and intensity of salt stress, the plant growth stage, and the species. Therefore, seed germination and early seedling stage of cotton are considered as the most sensitive stages to salinity [1]. It has been advocated that plants having a higher tolerance to salinity generally maintain lower Na+/K+ ratio in their tissues [82]. Furthermore, Wang et al. [83] found that soil ECe and sodium absorption ratio (SAR) values of root zone were significantly and linearly correlated with the final germination percentage of the cotton. The FG% was adversely affected by increasing EC and SAR. These results also show that the vulnerability of cotton plants towards salinity increases with increase in plant age. Therefore, cotton plant is more sensitive to the salinity during peak flowing period, leading to less number of bolls, boll weight, and lint yield [84]. Many studies [34, 85] also reported up to 50% yield reduction when the salinity level was increased from 7.7 to 17.0 dS m−1. Soil salinity also induces a wide range of morpho-physiological and biochemical changes that adversely affect the cotton growth and productivity. Additionally, plant biomass accumulation and the final output are pre-determined by the rate of photosynthesis, salinity induced a direct impact on both stomatal and mesophyll conductance [86].
\nThe production of higher fiber quality is a key objective of cotton breeding and genetics programs globally [87]. However, salinity induced lower lint percentage and fiber quality parameters, including fiber length, strength, and micronaire [84]. However, salinity during the flowering season imposed no detrimental impacts on fiber quality, but salinity after flowering resulted in reduced fiber quality.
\nSorghum is monocot species, and C4 plant with high photosynthetic capability and productivity has a spot with Poaceae family. The most of the sorghum species found in Australia and the rest of the world (Asia, Africa, Mesoamerica, India, and Pacific Oceans). Sorghum is the extremely beneficial yield, which can be used for essentialness source, human sustenance (grain), domesticated animals feed (grain and biomass), and mechanical reason (fiber or paper and treatment of natural side-effect). The sorghum biomass is used as fuel (ethanol generation) and sugar substrate through aging (methane creation) [88].
\nThe sorghum plant has an extraordinary adjustment potential to abiotic stresses, particularly high salinity, which is significant for genotypes developing in an extreme environment [89, 90]. By and large, sorghum is considered as a respectable salinity tolerant species with genotypic varies from cultivar to cultivar. The threshold level of salinity for grain sorghum is (6.8 dS m−1), and the reduction reaches 25% and 50% at 7 and 10 dSm−1 respectively [34]. Salinity also influences the sorghum plant’s physiological procedures, for example, seed germination rate, K+ take-up, net photosynthesis rate (Pn), biomass amassing, and biochemical qualities (chlorophyll substance or electrolyte leakage). In sorghum plants, a notable salinity induced phenotype of plant growth was observed after 4 days of exposure of 200 mM NaCl salinity stress [91]. Similarly, in sweet sorghum, salinity increase the duration of germination and reduced germination percentage [92].
\nUnder salinity stress, the production of reactive oxygen species (ROS) and an increase in the antioxidant enzymatic activity is a vital component of salt tolerance capacity of the plant. Salinity stress is linked with associated with enhanced antioxidant activity. Salinity decreased superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), peroxidase (POX), and glutathione reductase (GR), and total antioxidant and phenol contents of tissues in sorghum cultivars [93]. The stem yield and soluble carbohydrate contents decreased as salinity level increased in sweet sorghums cultivars such as Keller and Sofra, and in one-grain sorghum cultivar Kimia, whereas it is also reported that at the higher salinity stress the sorghum cultivar ‘Keller’ showed high sucrose contents and stem yield [90].
\nThe large aggregation of toxic ions such as Na+ and Cl− causes unsettling influence in ion uptake and K+ status of plant tissues. In this manner, it is the high K+/Na+ perception and the conservation of low Na+/K+ ratio in plant tissues, which describe as salt-tolerant genotypes [94]. The Na+ content in sorghum plant’s tissue enhanced with excessive Na+ contents, and as a result of significant contrasts in Na+ contents of root and shoot among genotypes. Lesser accumulation of Na+ in the shoot might be due to lower Na+ uptake by the root or from the variation in the Na+ transfer rate to the shoot. For example, salt-tolerant sorghum variety (Jambo) amassed less Na+ concentration in the root and shoot tissues than the salt-sensitive genotypes and kept up lower Na+/K+ ratios both in the root and shoot [95]. Particular testimony of Na+ ions in the shoot depends on leaf base [96], and enhancing levels of Ca2+ in the control condition increased plant growth and brought down Na+ take-up of sorghum plants [97]. The high Ca2+ accumulation in leaf and root tissues were observed in the salt-tolerant genotype Jambo than the salt sensitive varieties, Payam and Kimia [98].
\nSugarcane is a key commercial and irrigated crop of the tropical and subtropical areas of the world [99]. Sugarcane is propagated further by setts from the stem cuttings of mature plants (one-year-old crop). Sugarcane is an important source of sugar in Asia and Europe. It also supplied the basic raw material for the production of jaggery (Gur), white sugar, and khandsari. Further, sugarcane juice is widely being used for drinking and beverage purposes.
\nThe salinity is a major environmental concern, responsible for a significant decline in sugarcane yield [100]. The sugarcane production is low under less fertile soil caused by salinity stress. This plant is categorized as a moderately salt sensitive species which can withstand the ECe up to 1.7 dS m−1. But, a further increase in EC could induce the adverse effects on its production. The detrimental impacts of salinity at germination or bud emergence stage mainly varied across the different species. Akhta et al. [101] reported a significant reduction in sprout emergence at different days after sowing under moderate and severe salinity stress depends on the nature of cultivars.
\nUnder severe salinity stress conditions, growth could be significantly influenced by the accumulation of active oxygen species [102]. Vasantha et al. [103] observed the reduced leaf area index (LAI) of sugarcane by 36% during Formative Growth Phase (FGP) and by 21% during Grand Growth Period (GGP). Additionally, they observed it decreased in biomass accumulation by 44% during FGP and 32% during GGP. The significant reduction in shoot and root biomass accumulation in sugarcane sprouts with increasing salinity level from normal to 120 mM NaCl [101]. Similarly, the increasing NaCl level resulted in a reduction of the shoot, root length, root volume, and leaf area of sugarcane seedlings by 36–41, 29–42, and 52–66%, and chlorophyll contents by 20.0–45.0% respectively [104]. The other factors which directly reflect the depletion of growth of sugarcane are linked with alterations in gas exchange parameters, and reduced transpiration and photosynthetic rates due to stomatal closure. As concern sugarcane yield and related traits, the sucrose juice (6%) of sugarcane was significantly reduced induced during Grand Growth Period (GGP) and so also the brix [103]. Similar to the millable canes (MC) and cane yield were reduced drastically under salinity. The MC decreased by 8.0–100% by exposing under salinity. Additionally, salinity caused negative impacts on cane yield, cane length, and single cane weight. Hence, the different field crops showed a different level of response to salinity stress depends on their genetic nature and as EC increased from 32 dS m−1, the yield is unacceptable from the most of the field crops (Figure 2) [105].
\nClassification of field crops subjected to salinity stress. Extracted from Maas and Grattan [105].
There are two groups of management strategies against salinity, first one natural adaptation responses towards salinity, and second are human-made management strategies to handle the salinity stress in field crops or plants. Tolerance or resistance of rice plant to salt stress involves many adaptive responses at molecular, cellular, and physiological levels. Among the natural management strategies by the plants to salinity stress based on three strategies: (i) exclusion of Na+ from the cytoplasm due to low uptake, or pumping out of the ion from the cell by active mechanisms, (ii) requisitioning of Na+ into the vacuole and (iii) preferential accumulation in the leaf tissues. However, the genotypes with high leaf Na contents proved to be generally salt sensitive, and only those can tolerate high tissue concentrations, which can sequester Na+ into the vacuoles of leaf cells. The essential processes leading to plant adaptation to high salinity include ionic, metabolic, and osmotic adjustments. The salt-resistant genotypes can successfully cope with osmotic and ionic stresses caused by the excess of NaCl; they can effectively reduce the oxidative damage and can detoxify the harmful metabolites [106].
\nOsmotic adjustment is the best and favorable plant physiological strategy to endure concentration of toxic ion (Na+ and Cl−) in cytoplasm and compartmentalization in vacuoles, and define the salinity tolerance limits for plant [107]. Under osmotic stress, accumulation of free sugar, glycine betaine, organic solutes, and the proline in the plant’s cytoplasm is also an important strategy to cope with the salinity stress [108]. This phenomenon is important to handle the antagonistic abiotic stresses, including salinity and maintain the homeostasis in osmotic or ionic signaling [17]. Similarly, leaf area or leaf architecture is also an important trait of the plant, which can reduce the excessive amount of Na+ in leaves through dilution effects and the transpiration force [109].
\nThe ultimate response of plant subjected to salt stress is the closure of stomata [110]. The carbon dioxide assimilation decrease, as EC level increase (0–20 dS m−1) which results in plant growth reduction as well as the closure of stomata. This closure of stomata decreased the intracellular (Ci) CO2 partial pressure leading to hampering the Pn [5]. High salinity stress in rhizosphere decrease the transpiration rate (Tr), reduce the root water potential. Salinity stress enhances the biosynthesis of abscisic acid (ABA) and closes the stomata after reaching the guard cells. ABA passage from root to shoot causes closure of stomata and save the leave tissue from dehydration [54, 111]. Mostly, salinity hinders Pn in various crop plants. However, the sound reasons for lower Pn are stomatal closure, lower sink activity, reduced efficiency of rubisco, dislocation of vital cations from the membrane structure of leaf which lead to changes in permeability, and swelling and inefficiency of the grana [112], or might be due to the direct effects of salinity on conductance of stomata through a decrease in guard cell turgidity and CO2 partial pressure within plant cell [113]. Closure of stomata plays a vital role to survive with salinity stress. Chen and Gallie [114] studied that the ascorbate or ascorbic acid (AsA) redox state controls the transpiration rate and conductance of stomata. Stomatal guard cells control through Na+ which control transpiration rate according to the concentration of salt presented in soil environment [115].
\nSalinity occurs because of excessive accumulation of soluble salts via soil chemical properties and irrigated water. As a result of salinity stress and ion (Na+ and Cl−) toxicity, the disturbance of ion imbalance occurs. By adopting some measures, these problems can manage plant growth by adopting some agronomic strategies such as water and nutrient management to improve soil health, plant growth, and input use efficiency (IUE) under salinity [116].
\nIrrigation water with high electrical conductivity (EC), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), and pH value also causes of salinity stress and plant growth reduction [117]. For the better survival of plant against salinity stress, a wise water management strategy is indispensable. Availability of good quality irrigated water is very vital for the survival of crop plant and yield [118]. The usage of good quality water is a good option to drain or leeched down the soluble salts from the root zone for better soil management and plant growth [118]. The canal water is a good replacement of brackish underground water for irrigation of field crops. If canal water is unavailable, the use of gypsum with brackish underground water is the best option, and it increased 25–294% rice yield and 182% wheat production under salinity [119]. Similarly application of canal water with 100% gypsum help to lower the ECe, pH value, and SAR of soil at 0–30 cm depths than saline water with 100% gypsum in field crops [120]. In case of less availability of good quality water, then the 25% gypsum amendment with unfit irrigating water is the best option. The wise use of less good quality is than never mix up with the unfit underground water or tub well water, and follows the irrigation scheduling [119].
\nThe management of salinity stress by nutrient management is the wise use of calcium (Ca2+) source in the form of gypsum (CaSO4·2H2O) and to improve soil water infiltration and better plant growth. Application of gypsum (100%), a combination of gypsum + farmyard manure (FYM) + H2SO4, CaSO4·2H2O + FYM + chiseling, pyrite, and humic acid (HA), in rice, wheat, sorghum crop improved soil properties, plant biomass, and yield [118, 121]. Application of N, P, K, S, Zn, B, and Mn separately or with different combination increased rice total above ground biomass and grain production under salt-affected soils [122, 123]. Humic acid improves nutrients availability by chelating with unavailable nutrients (P, K, Ca, Fe, Zn, and Cu) and buffered pH value, and enhanced soil microbial, enzymatic and physiological activities, and plant growth under salinity [121, 124]. The combined effect of humic acid (HA) with gypsum (24 and 48 kg/ha) in rice was higher than the alone effect of HA on ECe and SAR due to its chelating effect with other nutrients subjected to salinity [125]. The use by-product of sugarcane (press-mud), green manure, poultry manure, and Sesbania as a cover crop for amendment of soil to reduce the effect of salinity which is a source of macro and micronutrients especially Zn and S in crops are also good options [126]. There are some other useful agronomic practices to reduce the effect of salt stress on the plant are periodic use of fresh water, subsoiling, deep tillage, sanding, and application of organic and inorganic fertilizers, and adopting crop rotation [118].
\nThe hormonal imbalance is one of the salinity effects on plants. There are many plant growth regulators being used as hormones regulator or plant growth regulators such as aminoethoxyvinylglycine (AVG), ethephon, and 1-methylcyclopropene (1-MCP) for ethylene inhibitor under salt stress and enhance the boles and spikelets development in rice and cotton respectively [4]. Similarly, exogenous applications of abscisic acid (ABA), brassinosteroids (BRs) or their analogs (D-31, D-100, etc.) are good option to improve plant performance under salinity [127, 128].
\nTo meet the demand for food and livelihood of the increasing population on the globe, the increase in the agriculture production is indispensable. Therefore, many efforts have been made to improve salinity tolerance capacity of the crops through conventional plant breeding and biotechnology [129]. Salinity tolerance is a complex trait both at the genetic and physiological level and controlled by polygenes. It has been speculated that salinity tolerance seems to be regulated by independent genes at different growth stages [130]. Traditional breeding has been considered as a more promising and efficient approach to improve the salt tolerance. Conventional breeding involves identification of QTLs using closely linked markers along with their phenotypic evaluation. One of the best-studied QTL for salt tolerance; saltol was identified by the conventional breeding approach in rice [131]. This QTL was found to control shoot Na+/K+ ratio at the seedling stage. So, the identification of new QTLs and later pyramiding of these QTLs would lead to the development of the more promising salt tolerant line. Marker-assisted backcrossing (MAB), which is one of the best traditional breeding approaches that involve the transfer of the specific allele at target locus from donor to recipient parent, can be used for this purpose. Traditional breeding mainly relied on the use of diverse germplasm resources to identify the landraces showing salt tolerance and then map the locus responsible for salt tolerance. This can be seen as an advantage as well as a disadvantage. Salt tolerance is an outcome of involvement of diverse cellular processes like ion transport and homeostasis, osmoregulation, and oxidative stress protection. Identification and characterization of key genes for salt tolerance would need the collective application of advanced molecular mapping, genomics, transcriptomics, and proteomics approaches.
\nMany salt tolerance genes have been discovered by using traditional breeding techniques, such as subtractive hybridization, differential hybridization, and through genetic information from the model organism. Furthermore, protein crystallography, a proteomic study has enabled researchers to the exploration of the protein’s structure and function for salt tolerant genes. After salt tolerance gene identification, many latest techniques for foreign gene transformation to the desired plant can help to improve field crop production. Such as CRISPR CAS9, PEG-mediated gene transfer, electroporation, partial or the micro projectile bombardment, microinjection, and Agrobacterium-mediated gene transfer. These techniques are available for many crops.
\nSalinity stress is the one of the key growth hampering agents for field crops. Salinity not only effects the plant growth but also affect yield by creating osmotic, ionic, and oxidative stresses. From this chapter, it is concluded that, the rice (sensitive), sugarcane and maize (moderately sensitive, wheat and sorghum (moderately tolerant), and cotton (tolerant) subjected to salinity. There are many management strategies, including traditional soil, water, and nutrient management strategies as well as genetic modification and by using molecular breeding, tools are suitable for producing salt tolerance cultivars. The bunch of information in this chapter wills able the scientific community to understand the role of salinity stress in field crops and their management options [115].
\nSajid Hussain is thankful to China National Rice Research Institute for the necessary facilities and to Chinese Academy of Agricultural Sciences, China for the award of Postdoctoral Fellowships. SH is giving special thanks to Prf. Dr. Qianyu Jin and Junhua Zhang for motivated me to write this chapter and provided my friendly environment to complete this task. We are also highly thankful to Dr. M. Ashraf and M. Shaukat, for contributing in chapter write up and providing us supporting material.
\nAuthors are listed below with their open access chapters linked via author name:
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\n\n\n\n\n\n\n\n\n\nJocelyn Chanussot (chapter to be published soon...)
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