List of transcriptome and whole genome sequencing using NGS technologies for development of genomic resources in Solanaceae crop plants
Abstract
Next-generation sequencing (NGS) technologies make possible the sequencing of the whole genome of a species decoding a complete gene catalogue and transcriptome to allow the study of expression pattern of entire genes. The huge data generated through whole genome and transcriptome sequencing not only provide a basis to study variation at gene sequence (such as single-nucleotide polymorphism and InDels) and expression level but also help to understand the evolutionary relationship between different crop species. Furthermore, NGS technologies have made possible the quick correlations of phenotypes with genotypes in different crop species, thereby increasing the precision of crop improvement. The Solanaceae family represents the third most economically important family after grasses and legumes due to high nutritional components. The current advances in NGS technology and their application in Solanaceae crops made several progresses in the identification of genes responsible for economically important traits, development of molecular markers, and understanding the genome organization and evolution in Solanaceae crops. The combination of high-throughput NGS technologies with conventional crop breeding has been shown to be promising in the Solanaceae translational genomics research. As a result, NGS technologies has been seen to be adopted in a large scale to study the molecular basis of fruit and tuber development, disease resistance, and increasing quantity and quality of crop production.
Keywords
- Solanaceae
- NGS
- capsicum
- eggplant
- tomato
- potato
1. Introduction
In developing countries, “population” and “food security” are the two major issues. These problems get worse with the sudden climate changes that hamper production, yield, and quality of food crops. Therefore, to keep in mind the food security for billions of peoples, an initiative is required for improving the quality and yield of important crops. Several traditional plant-breeding practices have been carried out for producing new varieties that can withstand with such changing climatic conditions besides increasing the productivity. These time-consuming practices could make considerable progress in crop improvement using selective germplasm, however, resulted in loss of biodiversity in the process. The recent advances in crop genomics, particularly the use of high throughput next-generation sequencing (NGS) technologies, look promising to identify causal genetic factors at genome by sequencing the whole genome and transcriptome of a species. As a result, the complete gene catalogue of a crop species and functional genes in different tissues could be identified besides allowing studying the genetic pathways involved in growth and development and biochemical pathways that eventually could be correlated with the crop phenotypes [1, 2]. Furthermore, the sequence data generated in vast amount provide a basis of genetic variation such as single-nucleotide polymorphisms (SNPs), which ultimately provide a relationship between genotype and phenotype in different species.
The Solanaceae family comprises approximately 2500 flowering plant species under 102 genera. The family represents the third most economically important family after grasses and legumes. Among the most important plants of this family are the potato (
Here in this chapter, an attempt has been made to compile current research progress made based on NGS technology in four most important Solanaceae crop plants: tomato, potato, eggplant, and pepper. Furthermore, the application of NGS technology on those four crops toward translational research has been discussed.
2. Next-generation sequencing technologies
Knowing the genome sequence of a species has an advantage in crop breeding. This became possible with the revolution of DNA sequencing technologies. The Sanger method [3] was the first-generation sequencing method based on DNA chain termination method of the single-pass sequencing of one clone at a time. With the advent of NGS technologies, the sequencing of complete genome or transcriptome of a species/genotype has become possible within a few hours. Utilizing various NGS platforms that are based on diverse chemistry and detection methods, several crop genomes, including major Solanaceae crops have been sequenced [4–7]. Among the various NGS technologies, three widely utilized platforms are Roche/454, Illumina Genome Analyzer (GA), and ABI SOLiD. The Roche/454 GSFLX chemistry is based on pyrosequencing and can produce up to 1 million reads of 600 bp to 1 kb [8]. The ABI SOLiD chemistry is based on emulsion polymerase chain reaction and sequencing by ligation technology, which can sequence up to 100 million reads of 50 bp in size [9]. The Illumina/Solexa GA based on sequencing by synthesis method produces 320 to 640 million reads of 100–150 bp [10].
The third- and the fourth-generation sequencing technologies are being developed, the majority of which allow the detection of single molecules with real-time sequencing. The popular third-generation sequencing platforms are Ion Torrents/Life Technologies, HeliScope™/Helicos Biosciences, and PacBio RS/Pacific Biosciences. The fourth generation is nanopore sequencing technology (Roche/IBM and Oxford). Ion Torrent company introduced a very different approach in 2010 as “Personal Genomic Machine,” which was later commercialized by Life Technology. The chemistry is based on the real-time detection of the pH change (release of hydrogen ions), with the incorporation of a nucleotide into a growing DNA strand by a silicon detector [11]. The technology provides an average read length of
The development of nanopore sequencing technology [15] begins an era of fourth-generation sequencing technology and has promised a cheap and fast method of sequencing. The principle involves threading a single-stranded DNA/RNA molecule electrophoretically through a nanopore that causes altering the pore’s electrical properties and thereby modulating the ionic current through the nanopore. Braha et al. [16] designed a biosensor using “α-hemolysin,” a toxin isolated from
3. Application of NGS technology in Solanaceae genetics and genomics studies
NGS technologies have numerous potential applications in plant genetics and genomics, which include generation of genomic resources, complete decoding of a species genome, differential gene expression studies, whole genome association studies (WGAS), genomics assisted breeding (GAB), etc. (Figure 1).
3.1. Transcriptome profiling of Solanaceae
Transcriptome sequencing of a species is the first step to access the functionally active genes. The transcriptome sequencing either by first-generation Sanger sequencing or by high throughput NGS approaches provides an insight into the expression of genes in a particular tissue/or different developmental stages of a species. The vast amount of sequencing data serve as a useful resource for the identification of sequence variations for the development of various markers, which would enable the mapping of candidate genes/QTLs for important traits. These applications have been discussed below in four important Solanaceae crops.
3.1.1. Potato
Potato (
3.1.2. Tomato
Tomato is an important vegetable crop that supplies vitamins and nutrients and consumed in different forms around the world. Whole transcriptome sequencing of six tomato accessions
3.1.3. Pepper (Capsicum)
The capsicum is a diploid, 2
3.1.4. Eggplant
Eggplant or brinjal (
3.2. Whole genome and transcriptome sequencing of Solanaceae spp.
Whole genome sequencing of a species reveals the structural organization of genome, including a number of protein-coding and non-protein-coding genes and repetitive elements and serves as the basis for finding genome-wide analysis of genetic variation, QTL mapping, diversity analysis, association mapping of agronomically important traits for crop improvement, and comparative study of genome evolution between different species.
3.2.1. Potato genome
The draft sequence of 844 Mb genome of a homozygous double-monoploid genotype named DM (DM1-3 516R44) was sequenced using three methods, namely, Sanger method, Roche/454 Pyrosequencing, and Illumina sequencing-by-synthesis method and assembled using the SOAPdenovo assembly algorithm (PGSC; The Potato Genome Sequencing Consortium, 2011) [6]. A heterozygous diploid line, i.e., RH (RH89-039-16) was also sequenced using shotgun sequencing of BACs and WGS, and its reads were mapped to the reference assembly of DM genome (http://potatogenome.net). About 86% of the genome was anchored and assembled into pseudomolecules. A total of 39,031 protein-coding genes were obtained; of them, 90% were located on 12 pseudomolecules. To overcome the problem of heterozygosity and inbreeding depression, which is the major drawback in potato improvement using traditional breeding practices, the researchers selected a homozygous, double-monoploid form, referred as DM for sequencing and integrated with sequence data of heterozygous diploid line RH. The potato genome was the first among the asterid species to be sequenced, and a total of 2642 high-confidence asterid-specific and 3372 potato lineage-specific genes were identified and also found the collinearity with 97.5% identity between DM and RH genome. Furthermore, they identified 3.67 million SNPs and 275 gene-specific presence/absence variations and concluded that the homozygous alleles were the reason for the reduced level of vigor in DM line. They also studied the evolution of tuber development, which revealed that about 15,235 genes were found to be expressed in developing tubers.
3.2.2. Tomato genome
In the year 2012, the Tomato Genome Consortium (TGC, 2012) [5] reported the draft genome sequence of inbred cultivar of tomato “Heinz 1706” using a combination of NGS technologies (454/Roche GS FLX, Illumina Genome Analyser, and SOLiD sequencing). They predicted the genome size of 900 Mb, which were assembled in 91 scaffolds aligned to 12 chromosomes. The data revealed only 0.6% nucleotide divergence (in two tomato genotypes) compared to 8% divergence with potato. The alignment of tomato–potato orthologous regions confirmed nine large inversions during evolution. They predicted about 34,727 (in tomato) and 35,004 (in potato) protein-coding genes. The analysis suggested that the genome triplications could have added new gene family members such as RIN (ripening-inhibitor), CNR (colorless nonripening), ACS (associated with ethylene biosynthesis), PHYB1/PHYB2 for red light photoreceptors, and PSY1/PSY2 (phytoene synthase) for lycopene biosynthesis that mediate important fruit-specific functions such as fleshiness and color. Further, the study reported the presence of noncoding RNAs (ncRNA) with the identification of 96 miRNA genes in tomato and 120 miRNA genes in potato genome. In another study, Aflitos et al. [60] performed the resequencing of 84 tomato accessions and explored the genetic variability present among those cultivated tomato and its wild progenitor. They identified more than 10 million SNPs in wild species, signifying the dramatic genetic erosion of tomato. Furthermore, through comparative sequence alignment, group-, species-, and accession-specific polymorphism was observed, which may be linked to agronomically important fruit traits. Such information may be easily used by recent high-throughput genotyping methods for the detection of genetic variability across extensive populations. The genomic information provided by these projects could be used for comparative genetic and genomic studies and in-depth sequence analysis in Solanaceae.
3.2.3. Pepper genome
The recent advancement in the sequencing and development of NGS technologies has accelerated the genetics and genomics studies of capsicum. Recently, a draft genome sequence of a diploid hot pepper, i.e., “
To provide a better understanding of evolution and domestication of capsicum, Qin et al. [61] reported two reference genome sequences of cultivated Zunla-1 (
3.2.4. Eggplant genome
To elucidate the genome structure and complexity, a draft genome sequence of eggplant has recently been published in which the whole genome shotgun sequencing of eggplant variety named as “Nakate-Shinkuro” was carried out using HiSeq 2000 sequencer (Illumina) [62]. The high-quality reads were assembled using SOAPdenovo v1.05 into 1,321,157 scaffolds and presented a draft genome assembly “SME_r2.5.1” that spanned approximately 74% (833.1 Mb) of the total 1127 Mb of the eggplant genome. Also, transcriptome sequencing of “AE-P03” and “LS1934” was carried out using Roche/454 FLX sequencer (Roche Diagnostics, Basel, Switzerland). By merging the two data sets, a hybrid assembly was produced using PCAP.rep that constituted 81,273 hybrid scaffolds of a total of 836.8 Mb in size. They predicted about 42,035 protein-coding genes in SME_r2.5.1 by Augustus 2.7. A total of 16,573 genes were located on superscaffolds and showed an orthologous relationship with tomato.
3.3. Sequence-based molecular marker discovery and genetic mapping
Sequence-based molecular markers have been used in many comparative and functional genomics studies because of their preferable features like genome-wide distribution, chromosome-specific location, co-dominant inheritance, and reproducibility. The high-throughput NGS technologies produce a huge amount of data, which is highly suitable for the identification of a large number of sequence variations in genome or transcriptome. For SNP identification, various SNP calling programs such as SOAPsnp [63], MAQ [64], Atlas-SNP2 [65], SAMtools [66], and GATK [67, 68] have been used commonly [69].
In tomato, Sim et al. [70] developed the first large-scale SNP genotyping array using 8784 SNPs based on NGS-derived transcriptome sequences of six different genotypes [71]. They constructed three high-density linkage maps using interspecific F2 populations (with various accessions of
In eggplant, Barchi et al. [73] mapped QTLs associated with anthocyanin pigmentation using inter- and intraspecific linkage maps. They used a combination of the restriction site-associated DNA (RAD) strategy with high throughput sequencing (Illumina) to generate SNPs. A total of 415 of the 431 markers were assembled into twelve major and one minor linkage group, covering 1390 cM distance.
Very recently, in pepper, Devran et al. [74] developed molecular markers tightly linked to
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1 | Transcriptome profiling | TF68 ( |
751 | 1536 SNPs 101 InDels |
454 GS-FLX | [39] |
2 | Transcriptome profiling | Yolo Wonder and Criollo de Morelos 334 (both |
853 | 11,849 | 454 GS-FLX and Illumina |
[40] |
3 | Transcriptome profiling | Bukang ( First assembly |
2,489 | 4,236 | Illumina | [41] |
Second assembly | 10,398 | 22,000 | Illumina | |||
4 | Transcriptome profiling | Xiaomila ( |
4,072 | 9,150 | Illumina | [43] |
5 | Transcriptome profiling | Mandarin ( |
– | 1025 | 454 GS-FLX | [44] |
Blackcluster ( |
– | 1059 | ||||
6 | Whole genome re-sequencing | BA3 ( |
– | 154,519 InDels |
Illumina | [76] |
BA07 ( |
– | 149,755 InDels | ||||
7 | Genome sequencing with BSA | SR231 and Criollo de Morelos334 ( |
– | 5,000 SNV | Illumina HiSeq 2500 | [74] |
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1 | Whole genome re-sequencing | Ailsa Craig, Furikoma, M82, Tomato Chuukanbonhon Nou 11, Ponderosa and Regina (All are inbred lines of |
– | 1536 SNPs were selected for genotyping of which 1293 successfully genotyped and 1248 found polymorphic | Re-sequencing with ABI SOLiD and Genotyping by Illumina GoldenGate Assay | [77] |
2 | Whole transcriptome sequencing | 8 accessions of ( |
– | 62,576 non redundant putative SNPs | Illumina | [30] |
3 | Whole genome re-sequencing and transcriptome re-sequencing | Several accessions of |
– | 4,812,432 non-redundant SNPs | Illumina and 454 GS-FLX | [78] |
4 | Whole genome sequencing |
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– | 4,680,647 | Illumina and 454 GS-FLX | [78] |
5 | Whole genome re-sequencing | ‘Micro-Tom’ and ‘Heinz 1706’ of |
– | 1,231,191 | Illumina and 454 | [79] |
6 | Genome sequencing and transcriptome sequencing |
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– | 6,000 (identified) 5528 (validated) | Illumina and 454 | [80] |
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1 | Genome sequencing | accessions of |
2,000 putative SSRs | 10,089 SNPs 874 (InDels) |
Illumina | [81] |
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1 | Transcriptome sequencing |
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– | 575,340 SNPs | Illumina | [26] |
2 | Genome sequencing |
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– | 111,212 SNPs 13,094 InDels |
Illumina | [82] |
3.4. Epigenomics during the age of next-generation sequencing technologies
Molecular breeding has a crucial role in the improvement of crops. Although conventional breeding program brought a substantial increment of food production, however, with rapid population growth worldwide, crop improvement should be accelerated so that climate resilient, biotic stress-resistant, high-nutritional, and high-productivity cultivars could be developed. The advent of NGS made it possible to study phenotypic variations caused by genetic and epigenetic modification to facilitates crop improvement. The term epigenotype was first introduced by Conrad H. Waddington to demonstrate the sum of interrelated developmental pathways that enable one genome to give rise to multiple epigenomes and consequently to multiple cell types that make up the whole organism. Nowadays, the term epigenetics is commonly referred to all kinds of heritable changes that are not caused by changes in the alteration of DNA sequences but are triggered by chemical modifications on the DNA (cytosine methylation) or on histone modifications (e.g., acetylation, methylation) bringing about modulation of chromatin structure and function [83]. In recent years, small RNAs have been emerged as key players in controlling epigenetic changes throughout the plant genome.
3.4.1. DNA methylation
DNA methylation refers to the covalent addition of methyl group to the cytosine base at position 5 by the action of DNA methyl transferases. In mammals, cytosine methylation occurs mostly at CG sites and rarely at non-CG sites, while in plants, cytosine methylation can occur in both CG and non-CG contexts. Non-CG methylation involves both symmetrical and asymmetrical sites, CHG and CHH, respectively (H = A, T, or C). Much of our knowledge with respect to DNA methylation is based on the studies performed on model plant
The first ever single-base resolution methylomes of tomato fruits were established, which revealed that fruit epigenome is not static, and the changes occur continuously during different stages of fruit development. The whole genome bisulfite sequencing was employed to study four different stages of fruit development. This study identified 52,095 differentially methylated regions of the 90% of the genome covered in this analysis in wild-type tomato fruits. Comparative analysis of fruits from two nonripening mutants of tomato viz ripening-inhibitor (rin) and Colorless nonripening (Cnr) demonstrated the changes in the methylation patterns in the wild type and the mutants [85]. The
3.4.2. Histone modifications
The interaction between DNA and proteins has a crucial role in the regulation of gene expression. Chromatin immunoprecipitation (ChIP) can be employed to study such interactions. These interactions can be explored using a technique called ChIP, microarray platforms (ChIP-on-chip or ChIP-chip) [89, 90]. More recently, NGS-based techniques are being used for studying histone modifications where ChIP-Seq combines ChIP with massively parallel direct sequencing. ChIP-enriched DNA is sequenced directly, using the Solexa/Illumina platform, and the readings were mapped to the reference genome. Histone modification phenomenon includes methylation, acetylation, phosphorylation, ubiquitination, sumoylation, and ADP-ribosylation. These modifications bring changes directly and cause structural changes to the chromatin or indirectly through the mediator proteins. All histone modifications are reversible and provide versatile ways for regulating gene expression during plant development and their responses to environmental stimuli. The study found that the reversible acetylation and deacetylation of specific
3.5. Noncoding RNA (ncRNAs) in crop improvement
Recent advances in next-generation genome and transcriptome sequencing with thorough bioinformatics and computational analysis laid to the discovery of numerous RNA types. The ncRNAs are one of the great examples of such techniques. The ncRNAs has emerged as a key product of eukaryotic transcriptionary machinery with a critical role in the regulatory mechanism. The ncRNAs are being classified as housekeeping ncRNAs and regulatory ncRNAs [96]. The rRNAs, tRNAs, small nuclear RNAs (snRNAs), and small nucleolar RNAs (snoRNAs) are under the “housekeeping” ncRNAs, whereas the “regulatory” ncRNAs are known as small ncRNAs (such as miRNAs and siRNAs) and long noncoding RNA (lncRNAs) [96, 97].
3.5.1. Role of long noncoding RNAs in Solanaceae
The lncRNAs are defined as a non-protein-coding functional RNAs of more than 200 bp in length with regulatory function and principally transcribed by RNA polymerase II. The identification of lncRNA in plants and especially in Solanaceae is still at infancy as compared with the human/animal genome. The application of high-throughput NGS technologies toward identification and the characterizations of lncRNAs are being reported. Recently, by analyzing around 200
3.5.2. Role of miRNAs in regulation of gene expression
MicroRNAs (miRNAs) are approximately 21 nucleotides long in length, and they are a class of noncoding RNAs that play an important role in regulating gene expression in plants [105–107]. Plant miRNAs mostly exert their effects by cleavage of target mRNA with full complementarity, and their target sites are mostly found in coding regions thus altering the gene expression [105–107]. Recent studies have shown that plant miRNAs also repress translation via a slicer-independent mechanism and, therefore, mediates the expression of the genes posttranscriptionally [108, 109].
There are mainly two major approaches for identifying miRNAs in plants: (1) experimental and (2) bioinformatic approaches. An experimental approach includes forward genetics, direct cloning, and next-generation high-throughput sequencing. High-throughput sequencing technology showed significant progress in small RNA identification and has become commonly available and affordable tool nowadays. A large number of miRNAs have been identified by means of high-throughput sequencing and available in online database (http://www.mirbase.org, accessed June 21, 2014), which currently holds 35,828 mature miRNA products from 223 species. The majority of miRNAs identified so far have been obtained from only a few model plant species, such as
Kim et al. [114] identified miRNAs and their target genes by analyzing expressed sequence tag (EST) data from five different species of Solanaceae, wherein they revealed the presence of at least 11 miRNAs and 54 target genes in pepper (
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miRBase | Database of published miRNA sequences and their annotation | http://www.mirbase.org/ | [118–122] |
deepBase | A platform for annotating and discovering small and long ncRNAs (microRNAs, siRNAs, and piRNAs) from next generation sequencing data | http://deepbase.sysu.edu.cn/ | [123] |
miRanda-microRNA.org | Database for predicted microRNA targets, target downregulation scores and experimentally observed expression patterns | http://www.microrna.org/microrna/home.do | [124] |
DIANA-mirGen 2.0 | Database of miRNA genomic information and regulation | http://diana.cslab.ece.ntua.gr/mirgen/ | [125] |
miRNAMap | miRNAMap Genomic maps of miRNA genes and their target genes in human, mouse, rat, and other metazoan genomes | http://mirnamap.mbc.nctu.edu.tw/ | [126, 127] |
PMRD | Plant miRNA database with large information of plant microRNAs data, consisting of microRNA sequence and their target genes, secondary dimension structure, expression profiling, genome browser, etc. | http://bioinformatics.cau.edu.cn/PMRD/ | [128] |
3.5.3. miRNAs in plant growth and development
To investigate the role of miRNAs in ovary and fruit development of tomatoes, transgenic plants were generated by overexpressing MIR167. The transgenic plants showed a reduction in leaf size and internode length as well as shortened petals, stamens, and styles. The RNA-Seq analysis identified many genes with altered expression patterns in tomato. Of these,
Several miRNAs have been identified in the fruit tissue. However, no miRNA has been experimentally validated to be involved in fruit ripening. Recently,
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starBase | Interaction Networks of lncRNAs, miRNAs, competing endogenous RNAs (ceRNAs), RNA-binding proteins (RBPs), and mRNAs from large-scale CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, and CLASH) data | http://starbase.sysu.edu.cn/ | [132, 133] |
miRwalk 2.0 | Database with collection of predicted and experimentally verified miRNA–target interactions with various novel and unique feature | http://zmf.umm.uniheidelberg.de/apps/zmf/mirwalk2/index.html | [134] |
targetScan | Database and Webserver for predicted miRNA targets in animals | http://www.targetscan.org/ | [135–137] |
DIANA-TarBase v7.0 | DIANA-TarBase v7.0 provides for the first time hundreds of thousands of high quality manually curated experimentally validated miRNA–gene interactions | http://diana.imis.athenainnovation.gr/DianaTools/index.php?r=tarbase/index | [138, 139] |
DIANA -microT v3.0 | Accurate microRNA target prediction database | http://diana.cslab.ece.ntua.gr/microT/ | [140, 141] |
miRecords | Manually curated database of experimentally validated miRNA–target interactions | http://c1.accurascience.com/miRecords/prediction_query.php | [142] |
picTar | PicTar: a computational method for identifying common targets of microRNAs | http://pictar.mdc-berlin.de/ | [143] |
RNA22 | Web based browser to identity miRNA targets | https://cm.jefferson.edu/rna22/Interactive/ | [144] |
micTarBase | miRTarBase has accumulated more than fifty thousand miRNA–target interactions (MTIs) | http://mirtarbase.mbc.nctu.edu.tw/ | [126, 127] |
RNALogo | Database with novel graphical representation of the patterns in an aligned RNA sequences with a consensus structure | http://rnalogo.mbc.nctu.edu.tw/ | [145] |
miRGator | Database with microRNA diversity, expression profiles, and target relationships | http://mirgator.kobic.re.kr/ | [146–148] |
miRNAMap | miRNAMap Genomic maps of miRNA genes and their target genes in human, mouse, rat, and other metazoan genomes | http://mirnamap.mbc.nctu.edu.tw/ | [112] |
miRDB | Webserver for miRNA target prediction and functional annotation | http://mirdb.org/miRDB/ | [149] |
RNA hybrid | This tool is primarily meant as a means for microRNA target prediction | http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/ | [150] |
miRU, psRNAtarget | A Plant Small RNA Target Analysis Server | http://plantgrn.noble.org/psRNATarget/ | [151] |
miRNEST | miRNEST is an integrative collection of animal, plant and virus microRNA data | http://rhesus.amu.edu.pl/mirnest/copy/browse.php | [152] |
PMTED | Plant MicroRNA Target Expression Database | http://pmted.agrinome.org/by_mirna.jsp | [153] |
MIREX | A platform for comparative exploration of plant pri-miRNA expression data | http://www.comgen.pl/mirex2/ | [154] |
TAPIR | Target prediction for plant microRNAs | http://bioinformatics.psb.ugent.be/webtools/tapir/ | [155] |
PASmiR | A database for miRNA molecular regulation in plant abiotic stress | http://pcsb.ahau.edu.cn:8080/PASmiR/ | [156] |
3.5.4. miRNAs in biotic stress
miRNAs have been identified in many plants with their diverse regulatory roles in biotic stresses. miRNA sequencing was used to investigate the miRNA expression difference between the tomatoes treated with and without
The fungus
3.5.5. miRNAs in abiotic stress
Abiotic stress (such as salt, drought, and heat) is becoming a major constraint to crop production due to the climate change. miRNAs have been found to play a significant role in tolerance to these stresses. For example, in tomato, transgenic lines were generated by the overexpression of miR169 family member: Sly-miR169c that displayed reduced stomatal opening, decreased transpiration rate, reduced water loss, and enhanced drought tolerance [159]. In eggplant, the high-throughput sequencing of salt tolerant species was performed and identified 98 conserved miRNAs from 37 families [160]. Some of them were found to be expressed under salt stress. These studies provide a better understanding about the regulation of gene expression under abiotic stresses for genetic improvement of crops.
4. High-throughput genotyping technologies
With the development of various NGS platforms, thousands to millions of SNPs have been identified from whole genome and transcriptome sequence data. Therefore, various high-throughput genotyping platforms were developed simultaneously for large-scale genotyping of SNPs in a large set of individuals. These platforms are the GoldenGate Genotyping Technology (GGGT; Illumina, San Diego, CA, USA) [161], BeadChip-based Infinium assay (Illumina) [162], SNPStream (Beckman Coulter, USA) [163], GeneChip (Affymetrix, USA) [164], and competitive allele-specific PCR, KASPar (KBioscience, UK) [165].
4.1. GoldenGate Genotyping Technology (GGGT)
The Illumina GGGT is a custom-based platform that covers construction of 96-1536 SNPs assay. The method is based on BeadArray technology, which includes immobilization of genomic DNA on avidin-coated particle. A further step is annealing of two allele-specific oligonucleotides and a locus-specific oligonucleotide for each SNP, later allele-specific primer extension for generating allele-specific products followed by PCR amplification with universal primers. It is a custom-based genotyping platform that allows screening of a vast number of samples (up to 3072 SNPs) using a single multiplexed assay. Shirasawa et al. [77] utilized 1536-plex SNP genotyping in tomato, of which 1293 were genotyped successfully. Moreover, 1248 SNPs showed clear polymorphism in 663 accessions. For eggplant, Barchi et al. [73] identified >10,000 potential SNPs. Of these, 384 highest quality SNPs were used to genotype 23 diverse eggplant germplasm with respect to fruit shape and color, and observed polymorphic information content values ranged from 0.29 to 0.5 with a mean value of 0.43.
4.2. BeadChip-based Infinium assay (Illumina)
It includes whole genome amplification followed by hybridization to oligonucleotide probe attached to a bead, extension, and detection of fluorescence by iScan Reader. The assay considers up to four million SNPs in a single sample run, or even up to several hundred thousand multiple samples in the same array. The chemistry involves incubation of samples on bead chip where they anneal to locus-specific 50-mers covalently linked to beads followed by allele-specific single-base extension, fluorescent staining, signal amplification, scanning in a dual-color channel reader, and analysis. This technology is advantageous as one can use a premade array that is easily available commercially for selected species. Hamilton et al. [26] identified 69,011 high confidence SNPs from six potato cultivars and used for genotyping with the Infinium platform. A total of 96 of these SNPs were used to assess allelic diversity in 248 germplasms and found 82 informative SNPs for subsequent analyses. In 2012, Felcher et al. [166] reported “Infinium 8303 Potato Array” comprising of 8303 functional markers which includes 3018 from candidate genes of interest by utilizing the transcriptome data from Hamilton et al. [26]. These were used for the genotyping and development of linkage maps. In tomato, a large-scale SNP genotyping array using 8784 SNPs were obtained from transcriptome sequencing [30] and later used for construction of a high-density linkage map of tomato [70].
4.3. SNPStream (Beckman coulter)
This method involves a single-base extension assay and tag array technology. It starts with a multiplexed SNP-specific PCR followed by a primer extension reaction using tagged primers and fluorescent-labeled nucleotide terminators, i.e., ddNTPs. The products are captured on a tag array, which is then scanned to detect the hybridized extension primers and produce calls. It allows the processing of up to three million genotypes in 384 samples at a time. This genotyping system combines solid-phase primer extension assay and universal tags for SNP genotyping. The instrument allows processing of 4,600–3,000,000 genotypes per day [167].
4.4. GeneChip (Affymetrix, USA)
The GeneChip assays are based on allelic discrimination by the direct hybridization of genomic DNA to arrays containing locus- and allele-specific oligonucleotides (25 mers). Genomic DNA is digested with a restriction endonuclease and ligated to adaptors, which are then amplified by PCR using a single universal primer thereby creating a reduced representation of the genome [168]. These PCR amplicons are fragmented, end-labeled, and hybridized. The fluorescence signal is recorded by the GeneChip 3000 scanner (Affymetrix). The hybridization scanning is evaluated as positive and negative signals. Hill et al. [42] developed a GeneChip® array for analysis of polymorphism and expression in Capsicum. The array was designed from 30,815 unigenes, and hybridization was performed using genomic DNA of 40 diverse lines of
In tomato, an oligonucleotide array was developed with 22,821 probe sets, which correspond to 22,714 unigenes [169]. Genomic DNA isolated from three
4.5. KASPar (KBioscience, UK)
The KBioscience-competitive allele-specific PCR (KASPar) is a simple, cost-effective, and flexible way for determining both SNP and InDel in genotypes. It is a custom-based technology that covers 96-1536‐well plate formats like Illumina’s GGGT. It relies on the discrimination power of a novel form of competitive allele-specific PCR to determine the alleles at a specific locus. The improvement has been made by incorporating a 5′–3′ exonuclease cleaved
5. Genotyping By Sequencing (GBS)
This technology is comparatively new in which genomic DNAs from large mapping populations are sequenced followed by SNP identification. This allows a rapid way for dissecting QTLs for economically important traits in large mapping populations besides allowing genetic diversity and the phylogenetic study between large numbers of accessions/genotypes. This approach is based on reduced representation sequencing, which involves the digestion of genomic DNA with appropriate restriction enzyme to capture a targeted portion of the genome followed by adapter (DNA-barcoded) ligation, PCR amplification, and sequencing of multiplexed libraries [170, 171]. For sequencing, the Illumina’s GAII and HiSeq and latest with the Torrent PGM and Proton (Life Technologies) are used. To analyze the large sequencing data, several automated pipelines are being developed, including TASSEL, UNEAK, and IGST. Besides
6. Genome-Wide Association Study (GWAS)
The advent of NGS technologies provides a large number of sequence variants (mainly SNPs) within a shorter period. These sequence variants can be utilized for QTL mapping, GWAS, and germplasm characterization. The establishment of an association between genotype and phenotype is a very challenging task. For crop improvement, it is necessary to determine the genetic basis of the agronomic trait. GWAS is a powerful technique for detecting natural variation and fine mapping of QTL underlying complex traits [174]. It requires a collection of individuals or a population of diverse genotypes and highly polymorphic markers that showed genome-wide distribution. This is a very robust method, in comparison to biparental cross-mapping, to map multiple traits simultaneously. In tomato, Shirasawa et al. [77] reported the whole genome resequencing of six tomato cultivars and detected 1.5 million SNPs by mapping the reads onto the reference genome (SL2.40). They utilized Illumina GoldenGate assay for genotyping of 1536 SNPs in 663 tomato accessions. There was no population structure observed when analyzing the genetic relationship using the STRUCTURE software. Further, they identified a total of nine SNP loci that were found to be associated with eight morphological traits. To overcome the low polymorphism in cultivated tomato (
7. Next-generation sequencing toward translational research
7.1. Fruit traits (size, shape, ripening, and development)
The transcriptome studies in Solanaceae crops such as potato revealed the identification of transcription factors associated with fruit development. A total of 632 lineage-specific genes were identified, of which 289 genes were asterid specific and 343 were potato specific [23]. They identified 290 genes, including
In tomato, using NGS technologies, several SNPs successfully differentiating between cherry type and round/beef type tomatoes were identified [80]. The SNP data revealed that cherry tomatoes share more SNPs with
7.2. Tuber
The transcriptome of tuber tissue showed the presence of several transcripts that are specific for tuber. Around 90 genes were co-expressed in tuber, including the genes involved in starch biosynthesis pathway such as
7.3. Pungency
Pungency is a special and economically important quality trait only found in pepper fruits, and it has been studied extensively [7, 43]. NGS technology has a wide scope to explore this trait and provides insights into the capsaicinoid pathway revealing the genes/loci associated with pungency. The transcriptome profiling of
7.4. Disease resistance
Using NGS technology, single-nucleotide variants (SNVs) were identified in resistant and susceptible pepper population for potato virus Y and pepper mottle virus. The comparative genomic tools were used to align the SNVs with syntenic region/loci of tomato. Later, the SNVs were converted into PCR-based CAPS (cleaved amplified polymorphic site) marker to map
7.5. Hormone and stress
Global transcriptome profiling of exogenously applied ABA tomato seedling revealed the identification of a large number of genes related to various stress responses [31]. These included several transcription factors, heat shock proteins, and pathogen resistance. Apart from this, salicylic acid, jasmonic acid, and ethylene signaling pathways were upregulated by exogenous ABA. The study suggested the role of ABA in improving pathogen resistance and abiotic stress tolerance. Moreover, the tomato transgenic lines were developed with the overexpression of Sly-miR169c, a miR169 family member. The transgenic plants displayed reduced stomatal opening, decreased transpiration rate, reduced water loss, and enhanced drought tolerance [159].
8. Conclusion and future direction
As the sequencing technologies are advancing at a rapid rate, enormous genomic information is being generated for Solanaceae crop plants. The question at present is how to utilize this enormous NGS-generated information for Solanaceae translational research. The large-scale phenotyping and transcriptome and whole genome resequencing of diverse genotypes from each species and their correlation will help in the identification of genetic region and eventually of candidate genes in the genomes. The integration of classical genetics, QTL mapping, and whole genome and transcriptome sequencing would be helpful in accelerating the Solanaceae translational research. Consideration of noncoding RNAs and epigenetics mechanism while designing breeding strategies would expedite the manipulation of mechanisms underlying various developmental aspects of plant biology in Solanaceae. Furthermore, the use of NGS technology provides an opportunity to investigate and understand the structure and evolution of complex Solanaceae genomes.
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