Comparative analysis of yield-related genes in Arabidopsis, wheat, barley, and maize.
Abstract
This chapter addresses the development and use of molecular markers for yield enhancement in wheat. Since their key goal for breeding is to maximize yield, extensive efforts have been made toward the improvement of yield. Agronomic traits related to yield, yield-related, disease resistance, and abiotic stresses are considered to be quantitative traits (QTLs), also known as complex traits, because they are controlled by numerous genes and are affected by environmental factors. Researchers have been studying such traits in the past decades for the development of molecular markers which can be used in various wheat breeding studies mainly involving restriction fragment length polymorphism (RFLP), simple sequence repeat (SSR), single nucleotide polymorphism (SNP), random amplified polymorphic DNA (RAPD), and amplified fragment length polymorphism (AFLP). Furthermore, the advent of next-generation sequencing (NGS) has accelerated the discovery of agronomically important genes. All of the technologies have enabled great advances for increasing the productivity of wheat. Here, the past history of first-generation sequencing, present status of second-generation sequencing, and future potential of translational genomics linked to the yield will be discussed.
Keywords
- molecular markers
- yield
- quantitative traits (QTLs)
- next-generation sequencing (NGS)
1. Introduction
As the world’s population is projected to reach approximately 9 billion by 2050, grain production of major staple crops needs to double to meet global food needs [1]. Together with rice and maize, wheat is one of the major staple crops widely grown in many countries, providing one-fifth of the calories and the protein for the world’s population. In addition, bioethanol is made primarily from wheat in Europe. Wheat starch is a major component for the production of bread, porridge, cakes, biscuits, and cereals which is a highly versatile crop for the human diet. In 2013, wheat was the third most produced cereal crop (713 million tons), after maize (1016 million tons) and rice (545 million tons). There are two distinct types of wheat, spring wheat and winter wheat, cultivated in many countries based on growing seasons, of which spring wheat is planted in most countries except in the United States and Northern Europe where the predominant crop is winter wheat. The global consumption of wheat has increased at a much faster rate than all other crops, because of the scale-up cultivation in developing countries, particularly in China [2]. Currently, out of the total cultivation area of more than 217 million hectares, the European Union countries has the largest area, followed by China, India, Russia, United States, and Canada [3]. Therefore, there has been an extensive effort over the past decades to increase wheat production through the application of molecular techniques which are powerful tools for enhancing effectiveness in breeding.
The most common or bread wheat species,
In wheat breeding, a strong emphasis has been put toward the improvement of grain yield as it the most important goal in wheat breeding. There have been concerns about the stagnation or decline of the staple crops in some parts of the world. It has been detected that 37% of wheat areas have experienced the yield stagnation [12]. If the breeder develops an improved wheat variety, having a superior of trait, but produces low yields, producers unlikely will grow it because the yield is necessary for economic feasibility. The grain yield is a complex character with low heritability which is influenced not only by genes but also by the effects of the environment. In wheat, it has been documented that the higher yield is inversely related to the protein content and can also delay maturity. Furthermore, abiotic stress factors including drought, salinity, extreme temperatures, and acidity contribute the most to yield loss, ranging between 60 and 82% [13]. As a consequence, extensive efforts have been made to identify the QTLs associated with the yield and its related traits which can be deployed by breeders through marker-assisted selection (MAS). The first report of the genome-wide assessment of molecular marker-based map in the nuclear genome of wheat began in the 1989 with the use of restriction fragment length polymorphism (RFLP) [14]. Subsequent analyses have been performed for construction of genetic maps to improve the efficiency of conventional breeding based on amplified-fragment-length polymorphism (AFLP), single-nucleotide polymorphism (SNP), diversity arrays technology (DArT), simple sequence repeat (SSR) or microsatellite, random DNA marker (RDM), gene targeted marker (GTM), and functional marker (FM). Based on these markers, there are 180 genetic maps extrapolated in wheat, most of which are developed by SSR markers. For example, molecular markers such as SSR and DArT have been used to detect QTLs for fusarium head blight (FHB) resistance, which can further be implemented in breeding studies [14]. Since 2007, a number of research studies have been taken to identify QTLs related to yield based on different mapping populations such as kernel length, kernel width, spike length, spike number, the grain number of spike, sterile spikelet number per spike, fertile spikelet number per spike, and thousand kernel weight [15–22]. However, the development of molecular markers and their applications in breeding have been relatively difficult in wheat because of its three closely related subgenomes and a large genome size consisted of high amounts (80%) of repetitive sequences. In 2012, the availability of wheat whole genome sequences has provided a framework for understanding of polyploidization, and domestication by comparing its sequences with ancestral and progenitor genomes, enabling us to understand the genetic diversity of wheat, which may help accelerate breeding programs [11]. Up to now, there are a total of 217,907 loci and 273,739 transcripts identified, of which 104,091 have been assigned as coding genes and 10,156 as long ncRNAs, according to Ensembl Plants (www.plants.ensembl.org). The chapter addresses molecular areas of research for yield improvement in wheat, focusing on finding QTLs for traits that affect yield. There are three objectives of this chapter as follows: (1) to explore the use of major molecular markers that have been used to identify yield and its-related QTLs in the past; (2) the current progress of molecular markers for linkage map construction; (3) to assess genomic studies of wheat; and (4) to discuss the potential of translational genomics in wheat using well-studied grasses such as rice and barley.
2. First-generation sequencing resources for yield improvement in wheat
2.1. Restriction fragment length polymorphism (RFLP) markers
Earlier molecular studies in wheat have shown that the RFLP markers are the common tools used as the oldest method of molecular markers for the construction of genetic maps. RFLP are typically inherited as simple Mendelian codominant markers, and are not influence by the environment, which could serve as highly heritable genetic markers for the study of inheritance of a trait. Chao et al. created the first linkage maps of the homoeologous group 7 chromosomes on the wheat genome using 18 cDNA clones across six mapping populations from ten varieties [14]. They mapped 31 RFLP loci on chromosomes 7A, 7B, and 7D. In 1991, detailed linkage maps were constructed with a total size of 1800 cm consisting of 197 RFLP loci [23]. Ma et al. [24] and Anderson et al. [25] identified RFLP markers associated with two Hessian fly resistance genes from
Starting from 1998, QTLs for yield and yield-related traits were investigated. The dwarfing genes,
2.2. Random amplified polymorphic DNA (RAPD) markers
The applications of RAPD markers have been beneficial to improve breeding programs in wheat because they are simple and fast PCR based, require no prior knowledge of target DNA sequence, and are analyzed either by the presence or absence of an amplicon via agarose gel electrophoresis. In wheat, RAPD has been used since 1990 [53]. Devos and Gale confirmed that a degree of polymorphism detected by six RAPD primers was comparable with RFLP markers [54]. They identified four RAPD markers with bread wheat cultivar ‘Chinese Spring.’ The application of both bulk segregant analysis (BSA) and RAPD has started in 1994 by Eastwood et al. [55]. Using BSA on DNA enriched for low-copy sequences by RAPD markers, the
2.3. Amplified fragment length polymorphism (AFLP) markers
For assessment of large numbers of polymorphic loci, the AFLP technology has been implemented as a powerful tool because of its advantage of having good levels of reproducibility, insensitivity, fast, and no need of sequence information required for primer design [67]. In 1995, a novel PCR-based assay for plant DNA fingerprinting using AFLP markers has resulted in high levels of DNA polymorphism [68]. In fact, the AFLP technique has observed to be more efficient and less expensive and less labor intensive compared to the RFLP technique in wheat [69]. Earlier AFLP-based marker studies have been found to be informative in assessment of genetic diversity in wheat varieties started in 1998 [70, 71]. Regarding the investigation of traits associated with yield, Goodwin et al. [72] and Hartl et al. [73] initiated the AFLP technique to develop an AFLP marker associated with resistance to Septoria tritici blotch and powdery mildew, respectively. Hartl et al. identified several AFLP markers closely linked to the
2.4. Simple sequence repeat (SSR) and intersimple sequence repeat (ISSR) markers
Among all available markers, SSR (or microsatellite) markers have become the best suited tool in plant breeding programs, because they are practical, convenient, easy to use, and inexpensive. Moreover, SSRs with tandem repeats of a motif of <6 bp are the most polymorphic, codominant, easy for scoring banding patterns, and have wide genomic distribution, high reproducibility, and a multiallelic nature [79]. SSR analysis has been conducted in most of the QTL studies for mapping various traits. Up to 2015, there are more than 4000 SSR markers that have been developed and used for the construction of wheat genetic maps [80]. The high level of variability and Mendelian inheritance of SSR DNA markers have been first reported by Devos et al. [81] and Röder et al. [82]. Moreover, Röder et al. [83] and Stephenson et al. [84] placed SSR loci onto the genetic map, providing a starting point for developing a saturated map of the wheat genome. For example, SSR markers have been implemented for tagging and mapping important yield-related genes such as the dwarfing genes
3. Second-generation sequencing resources for yield improvement in wheat
Researchers have focused on discovering SNPs to be used as genetic markers, because they have many advantages. SNPs act as codominant, single-locus, biallelic markers offering a lower error rate, and higher accuracy than SSR markers. However, the nature of polyploidy and having similar sequences among the A, B, and D genomes makes it difficult to identify SNPs [100]. Therefore, progress in SNP detection has been limited, especially related to yield and its related traits. With the advancement in next-generation sequencing (NGS), sequencing has become increasingly popular due to the rapid development of NGS technologies, including SOLiD/Ion Torrent PGM from Life Science, Genome Analyzer/HiSeq 2000/MiSeq from Illumina, and 454 FLX Titanium/GS Junior by Roche [101]. These technologies have led to the implementation of high-density SNP genotyping in wheat [99, 102].
An important milestone in wheat genomic research was accomplished in 2012 with the completion of
Since the completion of the draft sequence of wheat, extensive efforts have put into the identification of various molecular markers influencing yield to increase MAS efficiency. Based on the genotype by sequencing (GBS) approach, the linkage map of wheat comprised of markers including 538 GBS Bin, 258 AFLPs, 175 SSRs, and an EST has been constructed in 2014 [105]. They identified five QTL regions linked to thylakoid membrane damage (TMD), SPAD chlorophyll content (SCC), and plasma membrane damage (PMD), known as indicatives of high temperature tolerance, on chromosomes 6A, 7A, 1B, 2B and 1D and also detected some of the SSR markers associated with these traits such as the SSR marker
4. Future directions: translational genomics
The wheat genome is very complex as it is a polyploid species consisted of three diploid progenitor genomes. Recent advances in genome sequencing technologies have accelerated efforts to complete genomes of many crop species, which has opened the door for discovery and knowledge of the genetic basis of a number of important agronomic traits, with the final aim of crop improvement and production. Moreover, the completion of sequences has enabled assessment of translational genomics which is an effective way for researchers and breeders to transfer knowledge of genetic and genomic information among related species, such as rice and wheat [110]. The translational genomics tool is known as ‘model to crop’ translation that can be contributed to the implementation of genetic and genomics in crop species [111]. There are three well-characterized model grass species rice [112, 113],
Species | Arabidopsis | Barley | Rice | Wheat | Maize | |||||
---|---|---|---|---|---|---|---|---|---|---|
Trait | Locus | Locus | Identity | Locus | Identity | Locus | Identity | Locus | Identity | |
Flowering | Early flowering | At1g28380 | KR706151 | 42.43 | XM_015770121 | 36.86 | KX161741.1 | 44.78 | EU241899.1 | 41.78 |
At5g44040 | HM133570 | 43.85 | XM_015777033 | 37.49 | KJ711537 | 43.1 | KP202720.1 | 42.53 | ||
Late flowering | At1g01580 | EU331897.1 | 44.13 | XM_015787003 | 38.04 | KJ711539.1 | 43.16 | |||
At1g04400 | AB476614.1 | 43.88 | XM_015756636 | 36.72 | ||||||
Growth | Dwarf/small | At5g19530 | AY750996.1 | 42 | AB630963.1 | 43.05 | AY747606.1 | 43.1 | ||
At1g02730 | EU331690.1 | 43.14 | AY747605.1 | 43.1 | KR816810.1 | 42.96 | ||||
At4g10180 | KT247893.1 | 42.47 | KT750252.1 | 42.82 | ||||||
Growth defective | At4g01690 | AY244509.2 | 42.97 | |||||||
At1g02910 | JF965395.1 | 42.79 | ||||||||
At1g65260 | ||||||||||
Stems | Waxy | At1g09560 | AK366020.1 | 58.91 | FJ487950.1 | 58.98 | KU376264.1 | 58.75 | ||
At1g02205 | AK360068.1 | 58.91 | FJ487949.1 | 58.86 | KU376267.1 | 58.98 | ||||
Fasciation | At1g64670 | AJ567377.2 | 60.29 | FJ501983.1 | 59.64 | EU981913.1 | 59.82 | |||
AK354338.1 | 57.95 | EU981914.2 | 60.39 | |||||||
AK356998.1 | 59.25 | |||||||||
Short petiole | At4g10180 | AK360706.1 | 36.39 | AY585350.1 | 54.03 | M11336.1 | 55.81 | |||
At3g03860 | AK353983.1 | 37.12 | GQ389628.1 | 58.62 | DQ457416.2 | 54.2 | ||||
Twisted petiole | At4g27060 | EF190873.1 | 58.4 | EU189093.1 | 54.23 | |||||
Leaves | Abnormal shape | At3g16830 | JX828333.1 | 58.57 | AY831792.1 | 56.52 | ||||
At1g61940 | JX878122.1 | 58.41 | ||||||||
Rough surface | At5g04660 | |||||||||
At5g11060 | ||||||||||
At1g32640 | ||||||||||
Flowers | Carpel | At4g32551 | AK368072.1 | CT831121.1 | AY887064.1 | NM_001112060.1 | ||||
At5g11320 | AK253078.1 | AK100856.1 | BT008997.1 | AY898650.1 | ||||||
Stamen | At5g48390 | AB085818.1 | AK334664.1 | DQ343238.1 | ||||||
At1g63990 | ||||||||||
At1g05160 | ||||||||||
Petal | At4g32551 | |||||||||
At1g55320 | ||||||||||
Sepal | At2g20860 | |||||||||
Fruits | Short | At2g02000 | EU333863.1 | AP014958.1 | KP749902.1 | FJ573211.1 | ||||
At1g69180 | AK250398.1 | KP749901.1 | NM_001151022.1 | |||||||
At1g68560 | EU968771.1 | |||||||||
Abnormal shape | At4g05200 | |||||||||
At5g04660 | ||||||||||
At1g74720 |
The release of genomic sequence of wheat [11], barley [115], and maize [118], provides a new opportunity for translational genomics. Since comparative genomics focuses on comparing genomes among plant species looking for similarities and differences of DNA sequence, protein sequence, and gene orders, information from well-studied and analyzed species can be applied for less studied crops to improve a specific target trait, which can be implemented in crop breeding and improvement. For example, genome-wide comparative analysis of flowering-related genes in Arabidopsis, wheat, and barley has revealed that there are 900 and 275 putative orthologs in wheat and barley, respectively [119]. In addition, they showed many orthologous genes having similar expression profiles in different tissues of wheat and barley based on their
References
- 1.
Tilman D., Balzer C., Hill J., Befort B.L. Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci U S A. 2011; 108 (50):20260–20264. DOI: 10.1073/pnas.1116437108 - 2.
Kearney J. Food consumption trends and drivers. Phil. Trans. R. Soc. B. 2010; 365 :2793–2807. DOI: 10.1098/rstb.2010.0149 - 3.
Curtis B.C. 'Wheat in the World' in B.C. [Internet]. 2002 [Updated: 2002]. Available from: http://www.fao.org/docrep/006/y4011e/y4011e04.htm [Accessed: 9.1.16] - 4.
Devos K.M., Doležel J., Feuillet C. Genome organization and comparative genomics. Wheat Science and Trade. 2009;327–367. DOI: 10.1002/9780813818832 - 5.
Huang S., Sirikhachornkit A., Faris J.D., Su X., Gill B.S., Haselkorn R., et al. Phylogenetic analysis of the acetyl-CoA carboxylase and 3-phosphoglycerate kinase loci in wheat and other grasses. Plant Mol Biol. 2002; 48 (5–6)DOI: 805–820. - 6.
Dvorak J., Akhunov E.D. Tempos of gene locus deletions and duplications and their relationship to recombination rate during diploid and polyploid evolution in the Aegilops-Triticum alliance. Genetics. 2005; 171 (1):323–332. - 7.
Kihara H. Discovery of the DD-analyser, one of the ancestors of vulgare wheats. Ag. Hort. (Tokyo). 1944; 19 :889–890. - 8.
Feldman M., Lupton F.G.H., Miller T.E. Wheats. In: Smartt J, Simmonds NW, editors. Evolution of crop plants. 2nd ed. 1995: Longman; London. 1995. pp. 184–192. - 9.
Kilian B., Özkan H., Deusch O., Effgen S., Brandolini A., Kohl J., Martin W., Salamini F. Independent wheat B and G genome origins in outcrossing Aegilops progenitor haplotypes. Mol. Biol. Evol. 2007; 24 (1):217–227. - 10.
Bordbar F., Rahiminejad M.R., Saeidi H., Blattner F.R. Phylogeny and genetic diversity of d -genome species of Aegilops and Triticum (Triticeae, Poaceae) from Iran based on microsatellites, ITS, and trnL-F. Pl. Syst. Evol. 2011;291 :117–131. - 11.
Brenchley, R., et al. Analysis of the bread wheat genome using whole-genome shotgun sequencing. Nature. 2012; 491 (7426):705–710. DOI: 10.1038/nature11650 - 12.
Ray D.K., Ramankutty N., Mueller N.D., West P.C., Foley J.A. Recent patterns of crop yield growth and stagnation. Nat Commun. 2012; 3 :1293. DOI: 10.1038/ncomms2296. - 13.
Cakmak I. Role of mineral nutrition in tolerance of crop plants to environmental stress factors. In: Fertigation: optimizing the utilization of water and nutrients; September 20–24; Beijing. China: Fertigation proceedings: Selected papers of the IPI-NATESE-CAU-CAAS; 2005. pp. 35–48. - 14.
Chao S., Sharp P.J., Worland A.J., Warham E.J., Koebner R.M., Gale M.D. RFLP-based genetic maps of wheat homoeologous group 7 chromosomes. Theor Appl Genet. 1989; 78 (4):495–504. DOI: 10.1007/BF00290833 - 15.
Li S.S., Jia J.Z., Wei X.Y., Zhang X.C., Li L.Z., Chen H.M. et al. An intervarietal genetic map and QTL analysis for yield traits in wheat. Mol Breed. 2007; 20 :167–178. DOI: 10.1007/s11032-007-9080-3 - 16.
Sun X.C., Marza F., Ma H.X., Carver B.F., Bai G.H. Mapping quantitative trait loci for quality factors in an inter-class cross of US and Chinese wheat. Theor Appl Genet. 2010; 120 :1041–1051. DOI: 10.1007/s00122-009-1232-x - 17.
Ramya P., Chaubal A., Kulkarni K., Gupta L., Kadoo N., Dhaliwal H.S. QTL mapping of 1,000-kernel weight, kernel length, and kernel width in bread wheat ( Triticum aestivum L.). J Appl Genet. 2010;51 :421–429. DOI: 10.1007/BF03208872 - 18.
Carter A.H., Garland-Campbell K., Kidwell K.K. Genetic mapping of quantitative trait loci associated with important agronomic traits in the spring wheat ( Triticum aestivum L.) ‘Louise’ × ‘Penawawa’. Crop Sci. 2011;51 :84–95. DOI: 10.2135/cropsci2010.03.0185 - 19.
Deng S.M., Wu X.R., Wu Y.Y., Zhou R.H., Wang H.G., Jia J.Z., Liu S.B. Characterization and precise mapping of a QTL increasing spike number with pleiotropic effects in wheat. Theor Appl Genet. 2011; 122 :281–289. DOI: 10.1007/s00122-010-1443-1 - 20.
Heidari B., Sayed-Tabatabaei B.E., Saeidi G., Kearsey M., Suenaga K. Mapping QTL for grain yield, yield components, and spike features in a doubled haploid population of bread wheat. Genome. 2011; 54 (6):517–527. - 21.
Cui F., Ding A.M., Li J., Zhao C.H., Wang L., Wang X.Q. et al. QTL detection of seven spike-related traits and their genetic correlations in wheat using two related RIL populations. Euphytica. 2012; 186 :177–192. DOI: 10.1007/s10681-011-0550-7 - 22.
Liu G., Jia L., Lu L., Qin D., Zhang J., Guan P. Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat. Theor Appl Genet. 2014; 127 :2415–2432. DOI: 10.1007/s00122-014-2387-7 - 23.
Liu Y.G., Tsunewaki K. Restriction fragment length polymorphism (RFLP) analysis in wheat. II. Linkage maps of the RFLP sites in common wheat. Jpn J Genet. 1991; 66 (5):617–633. - 24.
Ma Z.Q., Gill B.S., Sorrells M.E., Tanksley S.D. RELP markers linked to two Hessian fly-resistance genes in wheat ( Triticum aestivum L.) fromTriticum tauschii (coss.) Schmal. Theor Appl Genet. 1993;85 (6–7):750–754. DOI: 10.1007/BF00225015 - 25.
Anderson J.A., Sorrells M.E., Tanksley S.D. RFLP analysis of genomic regions associated with resistance to preharvest sprouting in wheat. Crop Sci. 1993; 33 (3):453–459. DOI: 10.2135/cropsci1993.0011183X003300030008x - 26.
Devos K.M., Gale M.D. Extended genetic maps of the homoeologous group-3 chromosomes of wheat, rye and barley. Theor Appl Genet. 1993; 85 :649–652. - 27.
Williams K.J., Fisher J.M., Langridge P. Identification of RFLP markers linked to the cereal cyst nematode resistance gene (Cre) in wheat. Theor Appl Genet. 1994; 89 (7–8):927–930. DOI: 10.1007/BF00224519. - 28.
Van Deyneze A.E., Dubcovsky J., Gill K.S., Nelson J.C., Sorrells M.E., Dvorak J, et al. Molecular-genetic maps for group 1 chromosomes of Triticeae species and their relation to chromosomes in rice and oat. Genome. 1995; 38 :45–49. - 29.
Nelson J.C., van Deynze A.E., Autrique E., Sorrells M.E., Lu Y.H., Merlino M., et al. Molecular mapping of wheat. Homoeologous group 2. Genome. 1995a; 38 :516–524. - 30.
Nelson J.C., van Deynze A.E., Autrique E., Sorrells M.E., Lu Y.H., Negre S., et al. Molecular mapping of wheat. Homoeologous group 3. Genome. 1995b; 38 :516–524. - 31.
Ogihara Y., Shimizu H., Hasegawa K., Tsujimoto H., Sasakuma T. Chromosome assignment of four photosynthesis-related genes and their variability in wheat species. Theor Appl Genet. 1994; 88 (3–4):383–394. DOI: 10.1007/BF00223649 - 32.
Jia J., Devos K.M., Chao S., Miller T.E., Reader S.M., Gale M.D. RFLP-based maps of the homoeologous group-6 chromosomes of wheat and their application in the tagging of Pm12, a powdery mildew resistance gene transferred from Aegilops speltoides to wheat. Theor Appl Genet. 1996; 92 (5):559–565. DOI: 10.1007/BF00224558 - 33.
Ma Z.Q., Sorrells M.E., Tanksley S.D. RFLP markers linked to powdery mildew resistance genes Pm1, Pm2, Pm3, and Pm4 in wheat. Genome. 1994; 37 (5):871–875. - 34.
Hartl L., Weiss H., Stephan U., Zeller F.J., Jahoor A. Molecular identification of powdery mildew resistance genes in common wheat (Triticum aestivum L.). Theor Appl Genet. 1995; 90 :601–606. - 35.
Marino C.L., Tuleen N.A., Hart G.E., Nelson J.C., Sorrells M.E., Lu Y.H., et al. Molecular genetic maps of the group 6 chromosomes of hexaploid wheat (Triticum aestivum L. em. Thell.). Genome. 1996; 39 (2):359–366. - 36.
Autrique E., Tanksley S.D., Sorrells M.E., Singh R.P. Molecular markers for four leaf rust resistance genes introgressed into wheat from wild relatives. Genome. 1995; 38 (1):75–83. - 37.
Paull J.G., Pallotta M.A., Langridge P., The T.T. RFLP markers associated with Sr22 and recombination between chromosome 7A of bread wheat and the diploid species Triticum boeoticum . Theor Appl Genet. 1994;89 (7–8):1039–1045. DOI: 10.1007/BF00224536 - 38.
Feuillet C., Messmer M., Schachermayr G., Keller B. Genetic and physical characterization of the LR1 leaf rust resistance locus in wheat ( Triticum aestivum L.). Mol Gen Genet. 1995;248 (5):553–562. - 39.
Galiba G., Quarrie S.A., Sutka J., Morgounov A., Snape J.W. RFLP mapping of the vernalization (Vrn1) and frost resistance (Fr1) genes on chromosome 5A of wheat. Theor Appl Genet. 1995; 90 (7-8):1174–1179. DOI: 10.1007/BF00222940 - 40.
Korzun V., Roder M., Worland A.J., Borner A. Intrachromosomal mapping of genes for dwarfing (Rht12) and vernalization response (Vrn1) in wheat by using RFLP and microsatellite markers. Plant Breed. 1997; 116 :227–232. DOI: 10.1111/j.1439-0523.1997.tb00987.x - 41.
Cadalen T., Sourdille P., Charmet G., Tixier H., Gay G., Boeuf C., et al. Molecular markers linked to genes affecting plant height in wheat using a doubled-haploid population. Theor Appl Genet. 1998; 96 (6):933–940. - 42.
Shah M.M., Gill K.S., Baenziger P.S., Yen Y., Kaeppler S.M., Ariyarathne H.M. Molecular mapping of loci for agronomic traits on chromosome 3A of bread wheat. Crop Sci. 1999; 39 :1728–1732. - 43.
Araki E., Miura H., Sawada S. Identification of genetic loci affecting amylose content and agronomic traits on chromosome 4A of wheat. Theor Appl Genet. 1999; 98 (6):977–984. DOI: 10.1007/s001220051158 - 44.
Keller M., Karutz Ch., Schmid J.E., Stamp P., Winzeler M., Keller B., et al. Quantitative trait loci for lodging resistance in a segregating wheat×spelt population. Theor Appl Genet. 1999; 98 (6):1171–1182. DOI: 10.1007/s001220051182 - 45.
Kato K., Miura H., Sawada S. Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat. Theor Appl Genet. 2000; 101 (7):1114–1121. DOI: 10.1007/s001220051587 - 46.
Singh R.P., Nelson J.C., Sorrells M.E. Mapping Yr28 and other genes for resistance to stripe rust in wheat. Crop Sci. 2000; 40 :1148–1155. DOI: 10.2135/cropsci2000.4041148x - 47.
Tao W., Liu D., Liu J., Feng Y., Chen P. Genetic mapping of the powdery mildew resistance gene Pm6 in wheat by RFLP analysis. Theor Appl Genet. 2000; 100 :564–568. - 48.
Rong J.K., Millet E., Manisterski J., Feldman M. A new powdery mildew resistance gene: Introgression from wild emmer into common wheat and RFLP-based mapping. Euphytica. 2000; 115 :121. DOI: 10.1023/A:1003950431049 - 49.
Zeller F.J., Kong L., Hartl L., Mohler V., Hsam S.L.K. Chromosomal location of genes for resistance to powdery mildew in common wheat ( Triticum aestivum L. em Thell.) 7. Gene Pm29 in line Pova. Euphytica. 2002;123 (2):187–194. DOI: 10.1023/A:1014944619304 - 50.
Sourdille P., Tixier M.H., Charmet G., Gay G., Cadalen T., Bernard S. Location of genes involved in ear compactness in wheat ( Triticum aestivum ) by means of molecular markers. Mol Breed. 2000;6 (3):247–255. DOI: 10.1023/A:1009688011563 - 51.
Börner A., Schumann E., Fürste A., Cöster H., Leithold B., Röder S., et al. Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat ( Triticum aestivum L.). Theor Appl Genet. 2002;105 (6–7):921–936. DOI: 10.1007/s00122-002-0994-1 - 52.
Bullrich L., Appendino L., Tranquilli G., Lewis S., Dubcovsky J. Mapping of a thermo-sensitive earliness per se gene on Triticum monococcum chromosome 1A(m). Theor Appl Genet. 2002; 105 (4):585–593. DOI: 10.1007/s00122-002-0982-5 - 53.
Williams J.G., Kubelik A.R., Livak K.J., Rafalski J.A., Tingey S.V. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res. 1990; 18 (22):6531–6535. - 54.
Devos K.M., Gale M.D. The use of random amplified polymorphic DNA markers in wheat. Theor Appl Genet. 1992; 84 (5–6):567–72. DOI: 10.1007/BF00224153 - 55.
Eastwood R.F., Lagudah E.S., Appels R. A directed search for DNA sequences tightly linked to cereal cyst nematode resistance genes in Triticum tauschii . Genome. 1994;37 (2):311–319. - 56.
Penner G.A., Bezte L.J., Leisle D., Clarke J. Identification of RAPD markers linked to a gene governing cadmium uptake in durum wheat. Genome. 1995; 38 (3):543–547. - 57.
Qi L., Cao M., Chen P., Li W., Liu D. Identification, mapping, and application of polymorphic DNA associated with resistance gene Pm21 of wheat. Genome. 1996; 39 (1):191–197. - 58.
Demeke T., Laroche A., Gaudet D.A. A DNA marker for the Bt-10 common bunt resistance gene in wheat. Genome. 1996; 39 (1):51–55. - 59.
Sun G.L.,Fahima T., Korol A.B., Turpeinen T., Grama A., Ronin Y.I., et al. Identification of molecular markers linked to the Yr15 stripe rust resistance gene of wheat originated in wild emmer wheat, Triticum dicoccoides . Theor Appl Genet. 1997;95 (4):622–628. DOI: 10.1007/s001220050604 - 60.
Seo Y.W., Johnson J.W., Jarret R.L. A molecular marker associated with the H21 Hessian fly resistance gene in wheat. Mol Breed. 1997; 3 (3):177–181. DOI: 10.1023/A:1009606304447 - 61.
Dweikat I., Ohm H., Patterson F., Cambron S. Identification of RAPD markers for 11 Hessian fly resistance genes in wheat. Theor Appl Genet. 1997; 94 (3):419–423. DOI: 10.1007/s001220050431 - 62.
Shi A.N., Leath S., Murphy J.P. Identification of RAPD markers linked to two major genes for powdery mildew resistance in Pm12 wheat line. Phytopathol. 1997; 87 :S89. - 63.
William H.M., Hoisington D., Singh R.P., Gonzales-de-Leon D. Detection of quantitative trait loci associated with leaf rust resistance in bread wheat. Genome. 1997; 40 :253–260. - 64.
Hu X.Y., Ohm H.W., Dweikat I. Identification of RAPD markers linked to the gene PM 1 for resistance to powdery mildew in wheat. Theor Appl Genet. 1997; 94 (6):832–840. DOI: 10.1007/s001220050484 - 65.
Myburg A.A., Botha A-M., Wingfield B.D., Wilding W.J.M. Identification and genetic distance analysis of wheat cultivars using RAPD fingerprinting. Cereal Res Commun. 1997; 25 (4):875–882. - 66.
Liu Z.Q., Pei Y., Pu Z.J. Relationship between hybrid performance and genetic diversity based on RAPD markers in wheat. Triticum aestivum L. Plant Breed. 1999;118 (2):119–123. - 67.
Rafalski J.A., Vogel J.M., Morgante M., Powell W., Andre C., Tingery S.V. Generating and using DNA markers in plants. In: Birren B., Lai E., editors. Non-Mammalian Genomic Analysis: A Practical Guide. London: Academic Press; 1996. pp. 75–134. - 68.
Vos P., Hogers R., Bleeker M., Reijans M., van de Lee T., Hornes M., et al. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 1995; 23 (21):4407–4414. - 69.
Ma Z.-Q., Lapitan N.L.V. A comparison of amplified and restriction fragment length polymorphism in wheat. Cereal Res Commun. 1998; 26 (1):7–13. - 70.
Barrett B.A., Kidwell K.K. AFLP-based genetic diversity assessment among wheat cultivars from the Pacific Northwest. Crop Sci. 1998; 38 (5):1261–1271. DOI: 10.2135/cropsci1998.0011183X003800050025x - 71.
Barrett B.A., Kidwell K.K., Fox P.N. Comparison of AFLP and pedigree-based genetic diversity assessment methods using wheat cultivars from the Pacific Northwest. Crop Sci. 1998; 38 (5):1271–1278. DOI: 10.2135/cropsci1998.001183x003800050026x - 72.
Goodwin S.B., Hu X., Shaner G. An AFLP marker linked to a gene for resistance to Septoria tritici blotch in wheat. In: Slinkard A.E., editor. Proceedings of the 9th International Wheat Genetics Symposium; August 2–7; Saskatoon, Saskatchewan. Univ. of Saskatchewan: Univ. Extension Press; 1998. pp. 108–110. - 73.
Hartl L., Mohler V., Zeller F.J., Hsam S.L.K., Schweizer S. Identification of AFLP markers closely linked to the powdery mildew resistance genes Pm1c and Pm4a in common wheat ( Triticum aestivum L.). Genome. 199;42 (2):322–329. DOI: 10.1139/g98-129 - 74.
Shao Y., Niu Y., Zhu L., Zhai W., Xu S., Wu L. Identification of an AFLP marker linked to the stripe rust resistance geneYr10 in wheat. Chinese Sci Bull. 2001; 46 (17):1466–1468. DOI: 10.1007/BF03187033 - 75.
Cao Z.J., Wang X.P., Wang M.N., Cao S.H., Jing J.X., Shang H.S., et al. Genetic analysis and molecular markers of a novel stripe rust resistance gene YrHua in wheat originated from Psathyrostachys huashanica Keng. Yi Chuan Xue Bao. 2005; 32 (7):738–743. - 76.
Diéguez M.J., Altieri E., Ingala L.R., Perera E., Sacco F., Naranjo T. Physical and genetic mapping of amplified fragment length polymorphisms and the leaf rust resistance Lr3 gene on chromosome 6BL of wheat. Theor Appl Genet. 2006; 112 (2):251–257. DOI: 10.1007/s00122-005-0122-0 - 77.
Li X., Yang W., Li Y., Liu D., Yan H., Meng Q., et al. Identification of AFLP Markers Linked to Lr19 Resistance to Wheat Leaf Rust. Agric Sci Chi. 2007; 6 (3):311–315. DOI: 10.1016/S1671-2927(07)60050-9 - 78.
Dhillon N.K., Dhaliwal H.S. Identification of AFLP markers linked to leaf rust resistance genes using near isogenic lines of wheat. Am J Plant Sci. 2011; 2 (5):683–687. DOI: 10.4236/ajps.2011.25082 - 79.
Bruford M.W., Wayne R.K. Microsatellites and their application to population genetic studies. Curr Opin Genetics Dev. 1993; 3 : 939–943. - 80.
Han B., Wang C., Tang Z., Ren Y., Li Y., Zhang D., et al. Genome-wide analysis of microsatellite markers based on sequenced database in Chinese spring wheat ( Triticum aestivum L.). PLoS One. 2015;10 (11):e0141540. DOI: 10.1371/journal.pone.0141540 - 81.
Devos K.M., Bryan G.J., Collins A.J., Stephenson P., Gale M.D. Application of two microsatellite sequences in wheat storage proteins as molecular markers. Theor Appl Genet. 1995; 90 (2):247–252. DOI: 10.1007/BF00222209 - 82.
Röder M.S., Plaschke J., König S.U., Börner A., Sorrells M.E., Tanksley S.D., et al. Abundance, variability and chromosomal location of microsatellites in wheat. Mol Gen Genet. 1995; 246 (3):327–333. - 83.
Röder M.S., Korzun V., Wendehake K., Plaschke J., Tixier M.-H., Leroy P., et al. A microsatellite map of wheat. Genetics. 1998; 149 (4):2007–2023. - 84.
Stephenson P., Bryan G., Kirby J., Collins A., Devos C., Busso C., et al. Fifty new microsatellite loci for the wheat genetic map. Theor Appl Genet. 1998; 97 (5):946–949. DOI: 10.1007/s001220050975 - 85.
Korzun V., Röder M.S., Ganal M.W., Worland A.J., Law C.N. Genetic analysis of the dwarfing gene (Rht8) in wheat. Part I. Molecular mapping of Rht8 on the short arm of chromosome 2D of bread wheat ( Triticum aestivum L.). Theor Appl Genet. 1998;96 (8):1104–1109. DOI: 10.1007/s001220050845 - 86.
Roy J., Prasad M., Varshney R., Balyan H.S., Blake T.K., Dhaliwal H.S., et al. Identification of a microsatellite on chromosome 6B and a STS on 7D of bread wheat showing association with preharvest sprouting tolerance. Theor Appl Genet. 1999; 99 (1):336–340. DOI: 10.1007/s001220051241 - 87.
Peng J., Fahima T., Röder M., Li Y.C., Dahan A., Grama A., et al. Microsatellite tagging of the stripe-rust resistance gene YrH52 derived from wild emmer wheat, Triticum dicoccoides , and suggestive negative crossover interference on chromosome 1B. Theor Appl Genet. 1999;98 (6):862–872. DOI: 10.1007/s001220051145 - 88.
Varshney R., Prasad M., Roy, J., Kumar N., Harjit-Singh, Dhaliwal H.S., et al. Identification of eight chromosomes and a microsatellite marker on 1AS associated with QTL for grain weight in bread wheat. Theor Appl Genet. 2000; 100 (8):1290–-1294. DOI: 10.1007/s001220051437 - 89.
Raupp W.J., Sukhwinder-Singh, Brown-Guedira G.L., Gill B.S. Cytogenetic and molecular mapping of the leaf rust resistance gene Lr39 in wheat. Theor Appl Genet. 2001; 102 (2):347–352. DOI: 10.1007/s001220051652 - 90.
Ammiraju J.S.S., Dholakia B.B., Santra D.K., Singh H., Lagu M.D., Tamhankar S.A., et al. Identification of inter simple sequence repeat (ISSR) markers associated with seed size in wheat. Theor Appl Genet. 2001; 102 (5):726–732. DOI: 10.1007/s001220051703 - 91.
Zhou W.-C., Kolb F.L., Bai G.-H., Domier L.L., Boze L.K., Smith N.J. Validation of a major QTL for scab resistance with SSR markers and use of marker-assisted selection in wheat. Plant Breed. 2003; 122 (1):40–46. DOI: 10.1046/j.1439-0523.2003.00802.x - 92.
Sun Q., Wei Y., Ni Z., Xie C., Yang T. Microsatellite marker for yellow rust resistance gene Yr5 in wheat introgressed from spelt wheat. Plant Breed. 2002; 121 (6):539–541. DOI: 10.1046/j.1439-0523.2002.00754.x - 93.
Wang L., Ma J., Zhou R., Wang X., Jia J. Molecular tagging of the yellow rust resistance gene Yr10 in common wheat, P.I.178383 ( Triticum aestivum L.). Euphytica. 2002;124 (1):71–73. DOI: 10.1023/A:1015689817857 - 94.
Huang X., Wang L., Xu M., Röder M. Microsatellite mapping of the powdery mildew resistance gene Pm5e in common wheat ( Triticum aestivum L.). Theor Appl Genet. 2003;106 (5):858–865. DOI: 10.1007/s00122-002-1146-3 - 95.
Del Blanco I.A., Frohberg R.C., Stack R.W., Berzonsky W.A., Kianian S.F. Detection of QTL linked to Fusarium head blight resistance in Sumai 3-derived North Dakota bread wheat lines. Theor Appl Genet. 2003; 106 :1027–1031. - 96.
Somers D.J., Isaac, P., Edwards, K. A high-density microsatellite consensus map for bread wheat ( Triticum aestivum L.). Theor Appl Genet. 2004;109 (6):1105–1114. DOI: 10.1007/s00122-004-1740-7 - 97.
Cuthbert J.L., Somers D.J., Brûlé-Babel A.L., Brown P.D., Crow G.H. Molecular mapping of quantitative trait loci for yield and yield components in spring wheat ( Triticum aestivum L.). Theor Appl Genet. 2008;117 (4):595–608. DOI: 10.1007/s00122-008-0804-5 - 98.
Liu L., Wang L., Yao J., Zheng Y., Zhao C. Association mapping of six agronomic traits on chromosome 4A of wheat ( Triticum aestivum L.). Mol Plant Breed. 2010;1 (5): pp. 1–10. DOI: 10.5376/mpb.2010.01.0005 - 99.
Akhunov E., Nicolet C., Dvorak J. Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina Golden Gate assay. Theor Appl Genet. 2009; 119 :507–517. DOI: 10.1007/s00122-009-1059-5 - 100.
Chao S., Zhang W., Akhunov E., Sherman J., Ma Y., Luo M.-C., et al. Analysis of gene-derived SNP marker polymorphism in US wheat ( Triticum aestivum L.) cultivars. Mol Breed. 2009;23 (1):23–33. DOI: 10.1007/s11032-008-9210-6 - 101.
Liu L., Li Y., Li S., Hu N., He Y., Pong R., et al. Comparison of Next-Generation Sequencing Systems. J Biomed Biotechnol. 2012;2012:251364. DOI: 10.1155/2012/251364 - 102.
Bérard A., Le Paslier M.C., Dardevet M., Exbrayat-Vinson F., Bonnin I., Cenci A., et al. High-throughput single nucleotide polymorphism genotyping in wheat (Triticum spp.). Plant Biotechnol J. 2009; 7 (4):364–374. DOI: 10.1111/j.1467-7652.2009.00404.x - 103.
Li F., Fan G., Lu C., Xiao G., Zou C., Kohel R.J., et al. Genome sequence of cultivated Upland cotton (Gossypium hirsutum TM-1) provides insights into genome evolution. Nature Biotechnol. 2015; 33 :524–530. DOI: 10.1038/nbt.3208 - 104.
Schmutz J., Cannon S.B., Schlueter J., Ma J., Mitro T., Nelson W., et al. Genome sequence of the palaeopolyploid soybean. Nature. 2010; 463 :178–183. DOI: 10.1038/nature08670 - 105.
Talukder S.K., Babar M.A., Vijayalakshmi K., Poland J., Prasad P.V.V., Bowden R., et al. Mapping QTL for the traits associated with heat tolerance in wheat (Triticum aestivum L.). BMC Genetics. 2014; 15 :97. DOI: 10.1186/s12863-014-0097-4 - 106.
Cavanagh C.R., Chao S., Wang S., Huang B.E., Stephen S., Kiani S., et al. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Nat Acad Sci USA. 2013; 110 :8057–8062. DOI: 10.1073/pnas.1217133110 - 107.
Liu S., Yang X., Zhang D., Bai G., Chao S., Bockus W. Genome-wide association analysis identified SNPs closely linked to a gene resistant to Soil-borne wheat mosaic virus. Theor Appl Genet. 2014; 127 (5):1039–1047. DOI: 10.1007/s00122-014-2277-z - 108.
Gao F., Wen W., Liu J., Rasheed A., Yin G., Xia X., et al. Genome-wide linkage mapping of QTL for yield components, plant height and yield-related physiological traits in the Chinese wheat cross Zhou 8425B/Chinese spring. Front Plant Sci. 2015; 6 :1099. DOI: 10.3389/fpls.2015.01099 - 109.
Hu X., Ren J., Ren X., Huang S., Sabiel S.A., Luo M., et al. Association of agronomic traits with SNP markers in Durum Wheat ( Triticum turgidum L. durum (Desf.)). PLoS One. 2015;10 (6):e0130854. DOI: 10.1371/journal.pone.0130854 - 110.
Valluru R., Reynolds M.P., Salse J. Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat. Theor Appl Genet. 2014; 127 (7):1463–1489. DOI: 10.1007/s00122-014-2332-9 - 111.
Salentijn E.M.J., Pereira A., Argenent G.C., Linden G., Krens F., Smulders J.M., et al. Plant translational genomics: from model species to crops. Mol Breed. 2007; 20 (1):1–13. DOI: 10.1007/s11032-006-9069-3 - 112.
Yu J., Hu S., Wang J., Wong G., Li S., Liu B., et al. A draft sequence of the rice genome ( Oryza sativa L. ssp.indica ). Science. 2002;296 (5565):79–92. DOI: 10.1126/science.1068037 - 113.
Goff S., Ricke D., Lan T.-H., Presting G., Wang R., Dunn M., et al. A draft sequence of the rice genome ( Oryza sativa L. ssp.japonica ). Science. 2002;296 (5565):92–100. DOI: 10.1126/science.1068275 - 114.
The International brachypodium initiative. Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature. 2010; 463 :763–768. 10.1038/nature08747 - 115.
The international barley genome sequencing consortium. A physical, genetic and functional sequence assembly of the barley genome. Nature. 2012; 491 :7426. DOI: 10.1038/nature11543 - 116.
Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. J. Mol. Biol. 1990; 215 (3):403–410. DOI: 10.1016/S0022-2836(05)80360-2 - 117.
Edgar R.C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32 (5):1792–1797. DOI: 10.1093/nar/gkh340 - 118.
Schnable P.S., Ware D., Fulton R.S., Stein J.C., Wei F., Pasternak S., et al. The B73 maize genome: complexity, diversity, and dynamics. Science. 2009; 326 (5956):1112–1115. DOI: 10.1126/science.1178534 - 119.
Peng F.Y., Hu Z., Yang R.-C. Genome-wide comparative analysis of flowering-related genes in arabidopsis, wheat, and barley. Int J Plant Genomics. 2015; 2015 (874361). DOI: 10.1155/2015/874361