Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population

Construction of a high-density genetic map for faba bean (Vicia faba L.) and quantitative trait loci mapping of seed-related traits

Faba bean (Vicia faba L.) is a valuable legume crop and data on its seed-related traits is required for yield and quality improvements. However, basic research on faba bean is lagging compared to that of other major crops. In this study, an F₂ faba bean population, including 121 plants derived from the cross WY7×TCX7, was genotyped using the Faba_bean_130 K targeted next-generation sequencing genotyping platform. The data were used to construct the first ultra-dense faba bean genetic map consisting of 12,023 single nucleotide polymorphisms markers covering 1,182.65 cM with an average distance of 0.098 cM. The map consisted of 6 linkage groups, which is consistent with the 6 faba bean chromosome pairs. A total of 65 quantitative trait loci (QTL) for seed-related traits were identified (3 for 100-seed weight, 28 for seed shape, 12 for seed coat color, and 22 for nutritional quality). Furthermore, 333 candidate genes that are likely to participate in the regulation of seed-related traits were also identified. Our research findings can provide a basis for future faba bean marker-assisted breeding and be helpful to further modify and improve the reference genome.

Fine mapping of KLW1 that conditions kernel weight mainly through regulating kernel length in wheat (Triticum aestivum L.)

KLW1 was localized to a 0.6 cM interval near the centromere of chromosome 4B and found to be dominant in conditioning longer kernels and higher kernel weight. Kernel weight is a major wheat yield component and affected by kernel dimensions, filling process and kernel density. Because of this complexity, the mechanism underlying kernel weight is still far from clear. Qtgw.nau-4B or KLW1 was a major kernel weight QTL identified in the Nanda2419 × Wangshuibai population. We showed that introduction of the Nanda2419 allele into elite cultivar Wenmai6 resulted in longer kernels as well as higher kernel weight, without affecting other traits such as spike number per plant, plant height, spike length, spikelet number per spike, and kernel number per spike. KLW1 was dominant in conditioning higher kernel weight and functioned mainly through affecting kernel length. Using F₂ plants derived from KLW1 NIL, a high-density genetic map covering the QTL was constructed. KLW1 was consequently confined to the 0.6 cM Xwgrc4219-Xwgrc4067 interval by evaluating the recombinant lines in three field trials. KLW1 is complementary to KT1, the QTL on chromosome 5A of Nanda2419 for thicker and heavier kernels, in producing larger kernels with higher commercial value, augmenting its usefulness in wheat breeding.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.)

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F₆ population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Genetic architecture and candidate gene identification for grain size in bread wheat by GWAS

Grain size is a key trait associated with bread wheat yield. It is also the most frequently selected trait during domestication. After the phenotypic characterization of 768 bread wheat accessions in three plots for at least two years, the present study shows that the improved variety showed significantly higher grain size but lower grain protein content than the landrace. Using 55K SNP assay genotyping and large-scale phenotyping population and GWAS data, we identified 5, 6, 6, and 6 QTLs associated with grain length, grain weight, grain area, and thousand grain weight, respectively. Seven of the 23 QTLs showed common association within different locations or years. Most significantly, the key locus associated with grain length, qGL-2D, showed the highest association after years of multi-plot testing. Haplotype and evolution analysis indicated that the superior allele of qGL-2D was mainly hidden in the improved variety rather than in landrace, which may contribute to the significant difference in grain length. A comprehensive analysis of transcriptome and homolog showed that TraesCS2D02G414800 could be the most likely candidate gene for qGL-2D. Overall, this study presents several reliable grain size QTLs and candidate gene for grain length associated with bread wheat yield.

Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map

Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.

Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

BACKGROUND

Wheat (Triticum aestivum L.) is an important cereal crop. Increasing grain yield for wheat is always a priority. Due to the complex genome of hexaploid wheat with 21 chromosomes, it is difficult to identify underlying genes by traditional genetic approach. The combination of genetics and omics analysis has displayed the powerful capability to identify candidate genes for major quantitative trait loci (QTLs), but such studies have rarely been carried out in wheat. In this study, candidate genes related to yield were predicted by a combined use of linkage mapping and weighted gene co-expression network analysis (WGCNA) in a recombinant inbred line population.

RESULTS

QTL mapping was performed for plant height (PH), spike length (SL) and seed traits. A total of 68 QTLs were identified for them, among which, 12 QTLs were stably identified across different environments. Using RNA sequencing, we scanned the 99,168 genes expression patterns of the whole spike for the recombinant inbred line population. By the combined use of QTL mapping and WGCNA, 29, 47, 20, 26, 54, 46 and 22 candidate genes were predicted for PH, SL, kernel length (KL), kernel width, thousand kernel weight, seed dormancy, and seed vigor, respectively. Candidate genes for different traits had distinct preferences. The known PH regulation genes Rht-B and Rht-D, and the known seed dormancy regulation genes TaMFT can be selected as candidate gene. Moreover, further experiment revealed that there was a SL regulatory QTL located in an interval of about 7 Mbp on chromosome 7A, named TaSL1, which also involved in the regulation of KL.

CONCLUSIONS

A combination of QTL mapping and WGCNA was applied to predicted wheat candidate genes for PH, SL and seed traits. This strategy will facilitate the identification of candidate genes for related QTLs in wheat. In addition, the QTL TaSL1 that had multi-effect regulation of KL and SL was identified, which can be used for wheat improvement. These results provided valuable molecular marker and gene information for fine mapping and cloning of the yield-related trait loci in the future.

Fine mapping KT1 on wheat chromosome 5A that conditions kernel dimensions and grain weight

KT1 was validated as a novel thickness QTL with major effects on wheat kernel dimensions and weight and fine mapped to a 0.04 cM interval near the chromosome-5A centromere. Kernel size, the principal grain weight determining factor of wheat and a target trait for both domestication and artificial breeding, is mainly defined by kernel length (KL), kernel width (KW) and kernel thickness (KT), of which KW and KT have been shown to be positively related to grain weight (GW). Qkt.nau-5A, a major QTL for KT, was validated using the QTL near-isogenic lines (NILs) in three genetic backgrounds. Genetic analysis using two F₂ populations derived from the NILs showed that Qkt.nau-5A was dominant for thicker kernel and inherited like a single gene and therefore was designated as Kernel Thickness 1 (KT1). With 77 recombinant lines identified from a total of 19,160 F₂ plants from the two NIL-derived F₂ populations, KT1 was mapped to the 0.04 cM Xwgrb1356-Xwgrb1619 interval, which was near the centromere and displayed strong recombination suppression. The KT1 interval showed positive correlation with KW and GW and negative correlation with KL and therefore could be used in breeding for cultivars with round-shaped kernels that are beneficial to higher flour yield. KT1 candidate identification could be achieved through combination of sequence variation analysis with expression profiling of the annotated genes in the interval.

MicroRNA-mediated regulation of agronomically important seed traits: a treasure trove with shades of grey!

Seed development is an intricate process with multiple levels of regulation. MicroRNAs (miRNAs) have emerged as one of the crucial components of molecular networks underlying agronomically important seed traits in diverse plant species. In fact, loss of function of the genes regulating miRNA biogenesis also exhibits defects in seed development. A total of 21 different miRNAs have experimentally been shown to regulate seed size, nutritional content, vigor, and shattering, and have been reviewed here. The mechanism details of the associated regulatory cascades mediated through transcriptional regulators, phytohormones, basic metabolic machinery, and secondary siRNAs are elaborated. Co-localization of miRNAs and their target regions with seed-related QTLs provides new avenues for engineering these traits using conventional breeding programs or biotechnological interventions. While global analysis of miRNAs using small RNA sequencing studies are expanding the repertoire of candidate miRNAs, recent revelations on their inheritance, transport, and mechanism of action would be instrumental in designing better strategies for optimizing agronomically relevant seed traits.

Exploitation of Tolerance of Wheat Kernel Weight and Shape-Related Traits from Aegilops tauschii under Heat and Combined Heat-Drought Stresses

Kernel weight and shape-related traits are inherited stably and increase wheat yield. Narrow genetic diversity limits the progress of wheat breeding. Here, we evaluated kernel weight and shape-related traits and applied genome-wide association analysis to a panel of wheat multiple synthetic derivative (MSD) lines. The MSD lines harbored genomic fragments from Aegilops tauschii. These materials were grown under optimum conditions in Japan, as well as under heat and combined heat-drought conditions in Sudan. We aimed to explore useful QTLs for kernel weight and shape-related traits under stress conditions. These can be useful for enhancing yield under stress conditions. MSD lines possessed remarkable genetic variation for all traits under all conditions, and some lines showed better performance than the background parent Norin 61. We identified 82 marker trait associations (MTAs) under the three conditions; most of them originated from the D genome. All of the favorable alleles originated from Ae. tauschii. For the first time, we identified markers on chromosome 5D associated with a candidate gene encoding a RING-type E3 ubiquitin-protein ligase and expected to have a role in regulating wheat seed size. Our study provides important knowledge for the improvement of wheat yield under optimum and stress conditions. The results emphasize the importance of Ae. tauschii as a gene reservoir for wheat breeding.

Identification and validation of quantitative trait loci for kernel traits in common wheat (Triticum aestivum L.)

BACKGROUND

Kernel weight and morphology are important traits affecting cereal yields and quality. Dissecting the genetic basis of thousand kernel weight (TKW) and its related traits is an effective method to improve wheat yield.

RESULTS

In this study, we performed quantitative trait loci (QTL) analysis using recombinant inbred lines derived from the cross 'PuBing3228 × Gao8901' (PG-RIL) to dissect the genetic basis of kernel traits. A total of 17 stable QTLs related to kernel traits were identified, notably, two stable QTLs QTkw.cas-1A.2 and QTkw.cas-4A explained the largest portion of the phenotypic variance for TKW and kernel length (KL), and the other two stable QTLs QTkw.cas-6A.1 and QTkw.cas-7D.2 contributed more effects on kernel width (KW). Conditional QTL analysis revealed that the stable QTLs for TKW were mainly affected by KW. The QTLs QTkw.cas-7D.2 and QKw.cas-7D.1 associated with TKW and KW were delimited to the physical interval of approximately 3.82 Mb harboring 47 candidate genes. Among them, the candidate gene TaFT-D1 had a 1 bp insertions/deletion (InDel) within the third exon, which might be the reason for diversity in TKW and KW between the two parents. A Kompetitive Allele-Specific PCR (KASP) marker of TaFT-D1 allele was developed and verified by PG-RIL and a natural population consisted of 141 cultivar/lines. It was found that the favorable TaFT-D1 (G)-allele has been positively selected during Chinese wheat breeding. Thus, these results can be used for further positional cloning and marker-assisted selection in wheat breeding programs.

CONCLUSIONS

Seventeen stable QTLs related to kernel traits were identified. The stable QTLs for thousand kernel weight were mainly affected by kernel width. TaFT-D1 could be the candidate gene for QTLs QTkw.cas-7D.2 and QKw.cas-7D.1.

QTL mapping for grain yield-related traits in bread wheat via SNP-based selective genotyping

We identified four chromosome regions harboring QTL for grain yield-related traits, and breeder-friendly KASP markers were developed and validated for marker-assisted selection. Identification of major stable quantitative trait loci (QTL) for grain yield-related traits is important for yield potential improvement in wheat breeding. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) were evaluated for thousand grain weight (TGW), grain length (GL), grain width (GW), and grain number per spike (GNS) in 10 environments and for grain filling rate in six environments. Sixty RILs, with 30 higher and 30 lower TGW, respectively, were genotyped using the wheat 660 K SNP array for preliminary QTL mapping. Four genetic regions on chromosomes 1AL, 2BS, 3AL, and 5B were identified to have a significant effect on TGW-related traits. A set of Kompetitive Allele Specific PCR markers were converted from the SNP markers on the above target chromosomes and used to genotype all 266 RILs. The mapping results confirmed the QTL named Qgw.caas-1AL, Qgl.caas-3AL, Qtgw.caas-5B, and Qgl.caas-5BS on the targeted chromosomes, explaining 5.0-20.6%, 5.7-15.7%, 5.5-17.3%, and 12.5-20.5% of the phenotypic variation for GW, GL, TGW, and GL, respectively. A novel major QTL for GNS on chromosome 5BS, explaining 5.2-15.2% of the phenotypic variation, was identified across eight environments. These QTL were further validated using BC₁F₄ populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines) and 186 advanced breeding lines. Collectively, selective genotyping is a simple, economic, and effective approach for rapid QTL mapping and can be generally applied to genetic mapping studies for important agronomic traits.

Dissection of genetic factors underlying grain size and fine mapping of QTgw.cau-7D in common wheat (Triticum aestivum L.)

Thirty environmentally stable QTL controlling grain size and/or plant height were identified, among which QTgw.cau-7D was delimited into the physical interval of approximately 4.4 Mb. Grain size and plant height (PHT) are important agronomic traits in wheat breeding. To dissect the genetic basis of these traits, we conducted a quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs). In total, 30 environmentally stable QTL for thousand grain weight (TGW), grain length (GL), grain width (GW) and PHT were detected. Notably, one major pleiotropic QTL on chromosome arm 3DS explained the highest phenotypic variance for TGW, GL and PHT, and two stable QTL (QGw.cau-4B and QGw.cau-7D) on chromosome arms 4BS and 7DS contributed greater effects for GW. Furthermore, the stable QTL controlling grain size (QTgw.cau-7D and QGw.cau-7D) were delimited into the physical interval of approximately 4.4 Mb harboring 56 annotated genes. The elite NILs of QTgw.cau-7D increased TGW by 12.79-21.75% and GW by 4.10-8.47% across all three environments. Collectively, these results provide further insight into the genetic basis of TGW, GL, GW and PHT, and the fine-mapped QTgw.cau-7D will be an attractive target for positional cloning and marker-assisted selection in wheat breeding programs.

Dissecting genetic loci affecting grain morphological traits to improve grain weight via nested association mapping

The quantitative trait loci (QTLs) for grain morphological traits were identified via nested association mapping and validated in a natural wheat population via haplotype analysis. Grain weight, one of the three most important components of crop yield, is largely determined by grain morphological traits. Dissecting the genetic bases of grain morphology could facilitate the improvement of grain weight and yield production. In this study, four wheat recombinant inbred line populations constructed by crossing the modern variety Yanzhan 1 with three semi-wild wheat varieties (i.e., Chayazheda, Yutiandaomai, and Yunnanxiaomai from Xinjiang, Tibet, and Yunnan, respectively) and one exotic accession Hussar from Great Britain were investigated for grain weight and eight morphological traits in seven environments. Eighty-eight QTLs for all measured traits were totally identified through nested association mapping utilizing 14,643 high-quality polymorphic single nucleotide polymorphism (SNP) markers generated by 90 K SNP array. Among them, 64 (72.7%) QTLs have the most favorable alleles donated by semi-wild wheat varieties. For 14 QTL clusters affecting at least two grain morphological traits, nine QTL clusters were located in similar position with known genes/QTL, and the other five were novel. Three important novel QTLs (i.e., qTGW-1B.1, qTGW-1B.2, and qTGW-1A.1) were further validated in a natural wheat population via haplotype analysis. The favorable haplotypes for these three QTLs might be used in marker-assisted selection for the improvement of wheat yield by modifying morphological traits.

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling

Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling

Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession "Iran_249" and the Iranian durum cultivar "Zardak", was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

QTL Detection for Kernel Size and Weight in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

High-density genetic linkage maps are essential for precise mapping quantitative trait loci (QTL) in wheat (Triticum aestivum L.). In this study, a high-density genetic linkage map consisted of 6312 SNP and SSR markers was developed to identify QTL controlling kernel size and weight, based on a recombinant inbred line (RIL) population derived from the cross of Shixin828 and Kenong2007. Seventy-eight putative QTL for kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), and thousand kernel weight (TKW) were detected over eight environments by inclusive composite interval mapping (ICIM). Of these, six stable QTL were identified in more than four environments, including two for KL (qKL-2D and qKL-6B.2), one for KW (qKW-2D.1), one for KDR (qKDR-2D.1) and two for TKW (qTKW-5A and qTKW-5B.2). Unconditional and multivariable conditional QTL mapping for TKW with respect to TKW component (TKWC) revealed that kernel dimensions played an important role in regulating the kernel weight. Seven QTL-rich genetic regions including seventeen QTL were found on chromosomes 1A (2), 2D, 3A, 4B and 5B (2) exhibiting pleiotropic effects. In particular, clusters on chromosomes 2D and 5B possessing significant QTL for kernel-related traits were highlighted. Markers tightly linked to these QTL or clusters will eventually facilitate further studies for fine mapping, candidate gene discovery and marker-assisted selection (MAS) in wheat breeding.

QTL Detection for Kernel Size and Weight in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

High-density genetic linkage maps are essential for precise mapping quantitative trait loci (QTL) in wheat (Triticum aestivum L.). In this study, a high-density genetic linkage map consisted of 6312 SNP and SSR markers was developed to identify QTL controlling kernel size and weight, based on a recombinant inbred line (RIL) population derived from the cross of Shixin828 and Kenong2007. Seventy-eight putative QTL for kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), and thousand kernel weight (TKW) were detected over eight environments by inclusive composite interval mapping (ICIM). Of these, six stable QTL were identified in more than four environments, including two for KL (qKL-2D and qKL-6B.2), one for KW (qKW-2D.1), one for KDR (qKDR-2D.1) and two for TKW (qTKW-5A and qTKW-5B.2). Unconditional and multivariable conditional QTL mapping for TKW with respect to TKW component (TKWC) revealed that kernel dimensions played an important role in regulating the kernel weight. Seven QTL-rich genetic regions including seventeen QTL were found on chromosomes 1A (2), 2D, 3A, 4B and 5B (2) exhibiting pleiotropic effects. In particular, clusters on chromosomes 2D and 5B possessing significant QTL for kernel-related traits were highlighted. Markers tightly linked to these QTL or clusters will eventually facilitate further studies for fine mapping, candidate gene discovery and marker-assisted selection (MAS) in wheat breeding.