Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat

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.

Genetic dissection of a major QTL for kernel weight spanning the Rht-B1 locus in bread wheat

Genetic dissection uncovered a major QTL QTKW.caas-4BS corresponding with a 483 kb deletion that included genes ZnF, EamA and Rht-B1. This deletion was associated with increased grain weight and semi-dwarf phenotype. Previous studies identified quantitative trait loci (QTL) for thousand kernel weight (TKW) in the region spanning the Rht-B1 locus in wheat (Triticum aestivum L.). We recently mapped a major QTL QTKW.caas-4BS for TKW spanning the Rht-B1 locus in a recombinant inbred line (RIL) population derived from Doumai/Shi 4185 using the wheat 90K array. The allele from Doumai at QTKW.caas-4BS significantly increased TKW and kernel number per spike, and conferred semi-dwarf trait, which was beneficial to improve grain yield without a penalty to lodging. To further dissect QTKW.caas-4BS, we firstly re-investigated the genotypes and phenotypes of the RILs and confirmed the QTL using cleaved amplified polymorphic sequence (CAPS) markers developed from flanking SNP markers IWA102 and IWB54814. The target sequences of the CAPS markers were used as queries to BLAST the wheat reference genome RefSeq v1.0 and hit an approximate 10.4 Mb genomic region. Based on genomic mining and SNP loci from the wheat 660K SNP array in the above genomic region, we developed eight new markers and narrowed QTKW.caas-4BS to a genetic interval of 1.5 cM. A 483 kb deletion in Doumai corresponded with QTKW.caas-4BS genetically, including three genes ZnF, EamA and Rht-B1. The other 15 genes with either differential expressions and/or sequence variations between parents were also potential candidate genes for QTKW.caas-4BS. The findings not only provide a toolkit for marker-assisted selection of QTKW.caas-4BS but also defined candidate genes for further functional analysis.

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

BACKGROUND

As one of the most important food crops in the world, increasing wheat (Triticum aestivum L.) yield is an urgent task for global food security under the continuous threat of stripe rust (caused by Puccinia striiformis f. sp. tritici) in many regions of the world. Molecular marker-assisted breeding is one of the most efficient ways to increase yield. Here, we identified loci associated to multi-environmental yield-related traits under stripe rust stress in 244 wheat accessions from Sichuan Province through genome-wide association study (GWAS) using 44,059 polymorphic markers from the 55 K single nucleotide polymorphism (SNP) chip.

RESULTS

A total of 13 stable quantitative trait loci (QTLs) were found to be highly associating to yield-related traits, including 6 for spike length (SL), 3 for thousand-kernel weight (TKW), 2 for kernel weight per spike (KWPS), and 2 for both TKW and KWPS, in at least two test environments under stripe rust stress conditions. Of them, ten QTLs were overlapped or very close to the reported QTLs, three QTLs, QSL.sicau-1AL, QTKW.sicau-4AL, and QKWPS.sicau-4AL.1, were potentially novel through the physical location comparison with previous QTLs. Further, 21 candidate genes within three potentially novel QTLs were identified, they were mainly involved in the regulation of phytohormone, cell division and proliferation, meristem development, plant or organ development, and carbohydrate transport.

CONCLUSIONS

QTLs and candidate genes detected in our study for yield-related traits under stripe rust stress will facilitate elucidating genetic basis of yield-related trait and could be used in marker-assisted selection in wheat yield breeding.

Genetic architecture of grain yield in bread wheat based on genome-wide association studies

BACKGROUND

Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits.

RESULTS

A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS.

CONCLUSIONS

The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

Unleashing floret fertility in wheat through the mutation of a homeobox gene

Floret fertility is a key determinant of the number of grains per inflorescence in cereals. During the evolution of wheat (Triticum sp.), floret fertility has increased, such that current bread wheat (Triticum aestivum) cultivars set three to five grains per spikelet. However, little is known regarding the genetic basis of floret fertility. The locus Grain Number Increase 1 (GNI1) is shown here to be an important contributor to floret fertility. GNI1 evolved in the Triticeae through gene duplication. The gene, which encodes a homeodomain leucine zipper class I (HD-Zip I) transcription factor, was expressed most abundantly in the most apical floret primordia and in parts of the rachilla, suggesting that it acts to inhibit rachilla growth and development. The level of GNI1 expression has decreased over the course of wheat evolution under domestication, leading to the production of spikes bearing more fertile florets and setting more grains per spikelet. Genetic analysis has revealed that the reduced-function allele GNI-A1 contributes to the increased number of fertile florets per spikelet. The RNAi-based knockdown of GNI1 led to an increase in the number of both fertile florets and grains in hexaploid wheat. Mutants carrying an impaired GNI-A1 allele out-yielded WT allele carriers under field conditions. The data show that gene duplication generated evolutionary novelty affecting floret fertility while mutations favoring increased grain production have been under selection during wheat evolution under domestication.

Dissection of Pleiotropic QTL Regions Controlling Wheat Spike Characteristics Under Different Nitrogen Treatments Using Traditional and Conditional QTL Mapping

Optimal spike characteristics are critical in improving the sink capacity and yield potential of wheat even in harsh environments. However, the genetic basis of their response to nitrogen deficiency is still unclear. In this study, quantitative trait loci (QTL) for six spike-related traits, including heading date (HD), spike length (SL), spikelet number (SN), spike compactness (SC), fertile spikelet number (FSN), and sterile spikelet number (SSN), were detected under two different nitrogen (N) supplies, based on a high-density genetic linkage map constructed by PCR markers, DArTs, and Affymetrix Wheat 660 K SNP chips. A total of 157 traditional QTLand 54 conditional loci were detected by inclusive composite interval mapping, among which three completely low N-stress induced QTL for SN and FSN (qSn-1A.1, qFsn-1B, and qFsn-7D) were found to maintain the desired spikelet fertility and kernel numbers even under N deficiency through pyramiding elite alleles. Twenty-eight stable QTL showing significant differencet in QTL detection model were found and seven genomic regions (R2D, R4A, R4B, R5A, R7A, R7B, and R7D) clustered by these stable QTL were highlighted. Among them, the effect of R4B on controlling spike characteristics might be contributed from Rht-B1. R7A harboring three major stable QTL (qSn-7A.2, qSc-7A, and qFsn-7A.3) might be one of the valuable candidate regions for further genetic improvement. In addition, the R7A was found to show syntenic with R7B, indicating the possibly exsting homoeologous candidate genes in both regions. The SNP markers involved with the above highlighted regions will eventually facilitate positional cloning or marker-assisted selection for the optimal spike characteristics under various N input conditions.

A 55 K SNP array-based genetic map and its utilization in QTL mapping for productive tiller number in common wheat

A high-density genetic map constructed with a wheat 55 K SNP array was highly consistent with the physical map of this species and it facilitated the identification of a novel major QTL for productive tiller number. Productive tiller number (PTN) plays a key role in wheat grain yield. In this study, a recombinant inbred line population with 199 lines derived from a cross between '20828' and 'Chuannong16' was used to construct a high-density genetic map using wheat 55 K single nucleotide polymorphism (SNP) array. The constructed genetic map contains 12,109 SNP markers spanning 3021.04 cM across the 21 wheat chromosomes. The orders of the genetic and physical positions of these markers are generally in agreement, and they also match well with those based on the 660 K SNP array from which the one used in this study was derived. The ratios of SNPs located in each of the wheat deletion bins were similar among the wheat 9 K, 55 K, 90 K, 660 K and 820 K SNP arrays. Based on the constructed maps, a novel major quantitative trait locus QPtn.sau-4B for PTN was detected across multi-environments in a 0.55 cM interval on 4B and it explained 17.23-45.46% of the phenotypic variance. Twenty common genes in the physical interval between the flanking markers were identified on chromosome 4B of 'Chinese Spring' and wild emmer. These results indicate that wheat 55 K SNP array could be an ideal tool in primary mapping of target genes and the identification of QPtn.sau-4B laid a foundation for the following fine mapping and cloning work.

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.

Global QTL Analysis Identifies Genomic Regions on Chromosomes 4A and 4B Harboring Stable Loci for Yield-Related Traits Across Different Environments in Wheat (Triticum aestivum L.)

Major advances in wheat production are needed to address global food insecurity under future climate conditions, such as high temperatures. The grain yield of bread wheat (Triticum aestivum L.) is a quantitatively inherited complex trait that is strongly influenced by interacting genetic and environmental factors. Here, we conducted global QTL analysis for five yield-related traits, including spike yield, yield components and plant height (PH), in the Nongda3338/Jingdong6 doubled haploid (DH) population using a high-density SNP and SSR-based genetic map. A total of 12 major genomic regions with stable QTL controlling yield-related traits were detected on chromosomes 1B, 2A, 2B, 2D, 3A, 4A, 4B, 4D, 5A, 6A, and 7A across 12 different field trials with timely sown (normal) and late sown (heat stress) conditions. Co-location of yield components revealed significant tradeoffs between thousand grain weight (TGW) and grain number per spike (GNS) on chromosome 4A. Dissection of a "QTL-hotspot" region for grain weight on chromosome 4B was helpful in marker-assisted selection (MAS) breeding. Moreover, this study identified a novel QTL for heat susceptibility index of thousand grain weight (HSITGW) on chromosome 4BL that explains approximately 10% of phenotypic variation. QPh.cau-4B.2, QPh.cau-4D.1 and QPh.cau-2D.3 were coincident with the dwarfing genes Rht1, Rht2, and Rht8, and haplotype analysis revealed their pleiotropic architecture with yield components. Overall, our findings will be useful for elucidating the genetic architecture of yield-related traits and developing new wheat varieties with high and stable yield.

QTL mapping of flag leaf-related traits in wheat (Triticum aestivum L.)

QTL controlling flag leaf length, flag leaf width, flag leaf area and flag leaf angle were mapped in wheat. This study aimed to advance our understanding of the genetic mechanisms underlying morphological traits of the flag leaves of wheat (Triticum aestivum L.). A recombinant inbred line (RIL) population derived from ND3331 and the Tibetan semi-wild wheat Zang1817 was used to identify quantitative trait loci (QTLs) controlling flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and flag leaf angle (FLANG). Using an available simple sequence repeat genetic linkage map, 23 putative QTLs for FLL, FLW, FLA, and FLANG were detected on chromosomes 1B, 2B, 3A, 3D, 4B, 5A, 6B, 7B, and 7D. Individual QTL explained 4.3-68.52% of the phenotypic variance in different environments. Four QTLs for FLL, two for FLW, four for FLA, and five for FLANG were detected in at least two environments. Positive alleles of 17 QTLs for flag leaf-related traits originated from ND3331 and 6 originated from Zang1817. QTLs with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1B, 4B, and 5A; these are potential target regions for fine-mapping and marker-assisted selection in wheat breeding programs.

A novel allele of TaGW2-A1 is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (Triticum aestivum L.)

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat. Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5' flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

A Genome-Wide Association Study of Wheat Spike Related Traits in China

Rapid detection of allelic variation and identification of advantage haplotypes responsible for spike related traits play a crucial role in wheat yield improvement. The released genome sequence of hexaploid wheat (Chinese Spring) provides an extraordinary opportunity for rapid detection of natural variation and promotes breeding application. Here, selection signals detection and genome-wide association study (GWAS) were conducted for spike related traits. Based on the genotyping results by 90K SNP chip, 192 common wheat samples from southwest China were analyzed. One hundred and forty-six selective windows and one hundred and eighty-four significant SNPs (51 for spike length, 28 for kernels per spike, 39 for spikelet number, 30 for thousand kernel weight, and 36 for spike number per plant) were detected. Furthermore, tightly linkage and environmental stability window clusters and SNP clusters were also obtained. As a result, four SNP clusters associated with spike length were detected on chromosome 2A, 2B, 2D, and 6A. Two SNP clusters correlated to kernels per spike were detected on 2A and 2B. One pleiotropy SNP cluster correlated to spikelet number and kernels per spike was detected on 7B. According to the genome sequence, these SNP clusters and their overlapped/flanking QTLs which have been reported previously were integrated to a physical map. The candidate genes responsible for spike length, kernels per spike and spikelet number were predicted. Based on the genotypes of cultivars in south China, two advantage haplotypes associated with spike length and one advantage haplotype associated with kernels per spike/spikelet number were detected which have not been effectively transited into cultivars. According to these haplotypes, KASP markers were developed and diagnosed across landraces and cultivars which were selected from south and north China. Consequently, KASP assay, consistent with the GWAS results, provides reliable haplotypes for MAS in wheat yield improvement.

Identification of quantitative trait loci for seedling root traits from Tibetan semi-wild wheat (Triticum aestivum subsp. tibetanum)

As a primitive hexaploid wheat resource distributed only in Tibet, Tibetan semi-wild wheat (Triticum aestivum subsp. tibetanum Shao) possesses unique characteristics that could be exploited in wheat breeding programs. Its good root system could offer a stable platform for above-ground components. To detect possible excellent locus for root traits from Tibetan semi-wild wheat, we identified QTLs for root traits using a recombinant inbred line population derived from a cross between Tibetan semi-wild wheat Q1028 and Zhengmai 9023. A total of 15 QTLs on eight chromosomes were detected, including four major QTLs, QMrl.sau-7B, QTrl.sau-4B, QAd.sau-7A, and QSa.sau-4B. The phenotypic variation explained by each of these QTLs ranges from 5.67% to 16.68%. Positive alleles of six QTLs were derived from Q1028. Several novel QTLs for root traits were identified. In addition, significant correlations were detected amongst root traits and agronomic traits. Taken together, these results suggest that Tibetan semi-wild wheat and the newly identified novel QTLs could be useful in future breeding programs.

Dissecting the old Mediterranean durum wheat genetic architecture for phenology, biomass and yield formation by association mapping and QTL meta-analysis

Association mapping was used to identify genome regions affecting yield formation, crop phenology and crop biomass in a collection of 172 durum wheat landraces representative of the genetic diversity of ancient local durum varieties from the Mediterranean Basin. The collection was genotyped with 1,149 DArT markers and phenotyped in Spanish northern and southern locations during three years. A total of 245 significant marker trait associations (MTAs) (P<0.01) were detected. Some of these associations confirmed previously identified quantitative trait loci (QTL) and/or candidate genes, and others are reported for the first time here. Eighty-six MTAs corresponded with yield and yield component traits, 70 to phenology and 89 to biomass production. Twelve genomic regions harbouring stable MTAs (significant in three or more environments) were identified, while five and two regions showed specific MTAs for northern and southern environments, respectively. Sixty per cent of MTAs were located on the B genome and 29% on the A genome. The marker wPt-9859 was detected in 12 MTAs, associated with six traits in four environments and the mean across years. To refine QTL positions, a meta-analysis was performed. A total of 477 unique QTLs were projected onto a durum wheat consensus map and were condensed to 71 meta-QTLs and left 13 QTLs as singletons. Sixty-one percent of QTLs explained less than 10% of the phenotypic variance confirming the high genetic complexity of the traits analysed.

Development of an integrated linkage map of einkorn wheat and its application for QTL mapping and genome sequence anchoring

KEY MESSAGE

An integrated genetic map was constructed for einkorn wheat A genome and provided valuable information for QTL mapping and genome sequence anchoring. Wheat is one of the most widely grown food grain crops in the world. The construction of a genetic map is a key step to organize biologically or agronomically important traits along the chromosomes. In the present study, an integrated linkage map of einkorn wheat was developed using 109 recombinant inbred lines (RILs) derived from an inter sub-specific cross, KT1-1 (T. monococcum ssp. boeoticum) × KT3-5 (T. monococcum ssp. monococcum). The map contains 926 molecular markers assigned to seven linkage groups, and covers 1,377 cM with an average marker interval of 1.5 cM. A quantitative trait locus (QTL) analysis of five agronomic traits identified 16 stable QTL on all seven chromosomes, except 6A. The total phenotypic variance explained by these stable QTL using multiple regressions varied across environments from 8.8 to 87.1 % for days to heading, 24.4-63.0 % for spike length, 48.2-79.6 % for spikelet number per spike, 13.1-48.1 % for plant architecture, and 12.2-26.5 % for plant height, revealing that much of the RIL phenotypic variation had been genetically dissected. Co-localizations of closely linked QTL for different traits were frequently observed, especially on 3A and 7A. The QTL on 3A, 5A and 7A were closely associated with Eps-A ^m 3, Vrn1 and Vrn3 loci, respectively. Furthermore, this genetic map facilitated the anchoring of 237 T. urartu scaffolds onto seven chromosomes with a physical length of 26.15 Mb. This map and the QTL data provide valuable genetic information to dissect important agronomic and developmental traits in diploid wheat and contribute to the genetic ordering of the genome assembly.

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

Haplotypes of the TaGS5-A1 Gene Are Associated with Thousand-Kernel Weight in Chinese Bread Wheat

In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG), which occurred in the Sp1 domain of the promoter sequence. Combined with previous single nucleotide polymorphism (SNP) in the TaGS5-A1 exon sequence, four genotypes were formed at the TaGS5-A1 locus and were designated as TaGS5-A1a-a, TaGS5-A1a-b, TaGS5-A1b-a, and TaGS5-A1b-b, respectively. Analysis of the association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with the TaGS5-A1a-b allele possessed significantly higher thousand-kernel weight (TKW) and lower plant height than cultivars with the TaGS5-A1a-a allele, and cultivars with the TaGS5-A1b-b allele showed higher TKW than cultivars with the TaGS5-A1b-a allele. The differences of these traits between the TaGS5-A1a-a and TaGS5-A1a-b alleles were larger than those of the TaGS5-A1b-a and TaGS5-A1b-b alleles, suggesting that the -1925G insertion plays the more important role in TaGS5-A1a genotypes than in TaGS5-A1b genotypes. qRT-PCR indicated that TaGS5-A1b-b possessed the significantly highest expression level among four TaGS5-A1 haplotypes in mature seeds and further showed a significantly higher expression level than TaGS5-A1b-a at five different developmental stages of the seeds, suggesting that high expression of TaGS5-A1 was positively associated with high TKW in bread wheat. This study could provide a relatively superior genotype in view of TKW in wheat breeding programs and could also provide important information for dissection of the regulatory mechanism of the yield-related traits.

Characterization and fine mapping of a novel barley Stage Green-Revertible Albino Gene (HvSGRA) by Bulked Segregant Analysis based on SSR assay and Specific Length Amplified Fragment Sequencing

Background

Leaf color variations are common in plants. Herein we describe a natural mutant of barley cultivar Edamai No.6, whs18, whose leaf color showed stable and inheritable stage-green-revertible-albino under field condition.

Methods

Bulked Segregant Analysis (BSA) based on SSR assay and Specific Length Amplified Fragment Sequencing (SLAF-seq) was used to map the candidate gene for this trait.

Results

We found that leaf color of whs18 was green at seedling stage, while the seventh or eighth leaf began to show etiolation, and albino leaves emerged after a short period. The newly emerged leaves began to show stripe white before jointing stage, and normal green leaves emerged gradually. The duration of whs18 with abnormal leaf color lasted for about 3 months, which had some negative impacts on yield-related-traits. Further investigations showed that the variation was associated with changes in chlorophyII content and chloroplast development. Genetic analysis revealed that the trait was controlled by a single recessive nuclear gene, and was designed as HvSGRA in this study. Based on the F₂ population derived from Edamai No.9706 and whs18, we initially mapped the HvSGRA gene on the short arm of chromosome 2H using SSR and BSA. GBMS247 on 2HS showed co-segregation with HvSGRA. The genetic distance between the other marker GBM1187 and HvSGRA was 1.2 cM. Further analysis using BSA with SLAF-seq also identified this region as candidate region. Finally, HvSGRA interval was narrowed to 0.4 cM between morex_contig_160447 and morex_contig_92239, which were anchored to two adjacent FP contigs, contig_34437 and contig_46434, respectively. Furthermore, six putative genes with high-confidence in this interval were identified by POPSEQ. Further analysis showed that the substitution from C to A in the third exon of fructokinase-1-like gene generated a premature stop codon in whs18, which may lead to loss function of this gene.

Conclusions

Using SSR and SLAF-seq in conjunction with BSA, we mapped HvSGRA within two adjacent FP contigs of barley. The mutation of fructokinase-1-like gene in whs18 may cause the stage green-revertible albino of barley. The current study lays foundation for hierarchical map-based cloning of HvSGRA and utilizing the gene/trait as a visualized maker in molecular breeding in future.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2015-1) contains supplementary material, which is available to authorized users.

A Single-Nucleotide Polymorphism of TaGS5 Gene Revealed its Association with Kernel Weight in Chinese Bread Wheat

TaGS5 genes were cloned from bread wheat and were physically mapped on 3AS and 3DS. Sequencing results revealed that a SNP was found in the sixth exon of TaGS5-A1 gene. The SNP resulted in amino acid change from alanine to serine at the 303 bp position of TaGS5-A1. These two alleles were designated as TaGS5-A1a (alanine at the 303 bp position) and TaGS5-A1b genes (serine at the 303-bp position). Analysis of association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with TaGS5-A1b possessed wider kernel width and higher thousand-kernel weight, as well as significantly lower plant height, spike length, and internode length below spike than those of cultivars with TaGS5-A1a over 3 years. These trait differences between TaGS5-A1a and TaGS5-A1b genotypes were larger in landraces than in modern cultivars. This finding suggested that TaGS5 gene played an important role in modulating yield-related traits in the landraces, which possibly resulted from numerous superior genes gathering in modern cultivars after strong artificial selection. The preferred TaGS5-A1b haplotype underwent very strong positive selection in Chinese modern wheat breeding, but not in Chinese landraces. Expression analysis of the TaGS5-A1 gene indicated that TaGS5-A1b allele possessed significantly higher expression level than TaGS5-A1b allele in differently developmental seeds. This study could provide relatively superior genotype in view of agronomic traits in wheat breeding programs. Likewise, this study could offer important information for the dissection of molecular and genetic basis of yield-related traits.

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

Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.