Molecular genetic mapping of quantitative trait loci associated with loaf volume in hexaploid wheat (Triticum aestivum)

Identification and Validation of Stable Quantitative Trait Loci for SDS-Sedimentation Volume in Common Wheat (Triticum aestivum L.)

Sodium dodecyl sulfate-sedimentation volume is an important index to evaluate the gluten strength of common wheat and is closely related to baking quality. In this study, a total of 15 quantitative trait locus (QTL) for sodium dodecyl sulfate (SDS)-sedimentation volume (SSV) were identified by using a high-density genetic map including 2,474 single-nucleotide polymorphism (SNP) markers, which was constructed with a doubled haploid (DH) population derived from the cross between Non-gda3753 (ND3753) and Liangxing99 (LX99). Importantly, four environmentally stable QTLs were detected on chromosomes 1A, 2D, and 5D, respectively. Among them, the one with the largest effect was identified on chromosome 1A (designated as QSsv.cau-1A.1) explaining up to 39.67% of the phenotypic variance. Subsequently, QSsv.cau-1A.1 was dissected into two QTLs named as QSsv.cau-1A.1.1 and QSsv.cau-1A.1.2 by saturating the genetic linkage map of the chromosome 1A. Interestedly, favorable alleles of these two loci were from different parents. Due to the favorable allele of QSsv.cau-1A.1.1 was from the high-value parents ND3753 and revealed higher genetic effect, which explained 25.07% of the phenotypic variation, mapping of this locus was conducted by using BC3F1 and BC3F2 populations. By comparing the CS reference sequence, the physical interval of QSsv.cau-1A.1.1 was delimited into 14.9 Mb, with 89 putative high-confidence annotated genes. SSVs of different recombinants between QSsv.cau-1A.1.1 and QSsv.cau-1A.1 detected from DH and BC3F2 populations showed that these two loci had an obvious additive effect, of which the combination of two favorable loci had the high SSV, whereas recombinants with unfavorable loci had the lowest. These results provide further insight into the genetic basis of SSV and QSsv.cau-1A.1.1 will be an ideal target for positional cloning and wheat breeding programs.

Analysis of the Gli-D2 locus identifies a genetic target for simultaneously improving the breadmaking and health-related traits of common wheat

Gliadins are a major component of wheat seed proteins. However, the complex homoeologous Gli-2 loci (Gli-A2, -B2 and -D2) that encode the α-gliadins in commercial wheat are still poorly understood. Here we analyzed the Gli-D2 locus of Xiaoyan 81 (Xy81), a winter wheat cultivar. A total of 421.091 kb of the Gli-D2 sequence was assembled from sequencing multiple bacterial artificial clones, and 10 α-gliadin genes were annotated. Comparative genomic analysis showed that Xy81 carried only eight of the α-gliadin genes of the D genome donor Aegilops tauschii, with two of them each experiencing a tandem duplication. A mutant line lacking Gli-D2 (DLGliD2) consistently exhibited better breadmaking quality and dough functionalities than its progenitor Xy81, but without penalties in other agronomic traits. It also had an elevated lysine content in the grains. Transcriptome analysis verified the lack of Gli-D2 α-gliadin gene expression in DLGliD2. Furthermore, the transcript and protein levels of protein disulfide isomerase were both upregulated in DLGliD2 grains. Consistent with this finding, DLGliD2 had increased disulfide content in the flour. Our work sheds light on the structure and function of Gli-D2 in commercial wheat, and suggests that the removal of Gli-D2 and the gliadins specified by it is likely to be useful for simultaneously enhancing the end-use and health-related traits of common wheat. Because gliadins and homologous proteins are widely present in grass species, the strategy and information reported here may be broadly useful for improving the quality traits of diverse cereal crops.

Marker-assisted selection strategy to pyramid two or more QTLs for quantitative trait-grain yield under drought

BACKGROUND

Marker-assisted breeding will move forward from introgressing single/multiple genes governing a single trait to multiple genes governing multiple traits to combat emerging biotic and abiotic stresses related to climate change and to enhance rice productivity. MAS will need to address concerns about the population size needed to introgress together more than two genes/QTLs. In the present study, grain yield and genotypic data from different generations (F3 to F8) for five marker-assisted breeding programs were analyzed to understand the effectiveness of synergistic effect of phenotyping and genotyping in early generations on selection of better progenies.

RESULTS

Based on class analysis of the QTL combinations, the identified superior QTL classes in F3/BC1F3/BC2F3 generations with positive QTL x QTL and QTL x background interactions that were captured through phenotyping maintained its superiority in yield under non-stress (NS) and reproductive-stage drought stress (RS) across advanced generations in all five studies. The marker-assisted selection breeding strategy combining both genotyping and phenotyping in early generation significantly reduced the number of genotypes to be carried forward. The strategy presented in this study providing genotyping and phenotyping cost savings of 25-68% compared with the traditional marker-assisted selection approach. The QTL classes, Sub1 + qDTY 1.1  + qDTY 2.1  + qDTY 3.1 and Sub1 + qDTY 2.1  + qDTY 3.1 in Swarna-Sub1, Sub1 + qDTY 1.1  + qDTY 1.2 , Sub1 + qDTY 1.1  + qDTY 2.2 and Sub1 + qDTY 2.2  + qDTY 12.1 in IR64-Sub1, qDTY 2.2  + qDTY 4.1 in Samba Mahsuri, Sub1 + qDTY 3.1  + qDTY 6.1  + qDTY 6.2 and Sub1 + qDTY 6.1  + qDTY 6.2 in TDK1-Sub1 and qDTY 12.1  + qDTY 3.1 and qDTY 2.2  + qDTY 3.1 in MR219 had shown better and consistent performance under NS and RS across generations over other QTL classes.

CONCLUSION

"Deployment of this procedure will save time and resources and will allow breeders to focus and advance only germplasm with high probability of improved performance. The identification of superior QTL classes and capture of positive QTL x QTL and QTL x background interactions in early generation and their consistent performance in subsequent generations across five backgrounds supports the efficacy of a combined MAS breeding strategy".

Identification of milling and baking quality QTL in multiple soft wheat mapping populations

Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

Genetic dissection reveals effects of interaction between high-molecular-weight glutenin subunits and waxy alleles on dough-mixing properties in common wheat

The glutenin and waxy loci of wheat are important determinants of dough quality. This study was conducted to evaluate the effects of high-molecular-weight glutenin (HMW-GS) and waxy alleles on dough-mixing properties. Molecular mapping was used to investigate these effects on Mixograph properties in a population of 290 (Nuomai1 x Gaocheng8901) recombinant inbred lines (RILs) from three environments in the harvest years 2008, 2009 and 2011. The results indicated the following: (i) the Glu-A1 and Glu-D1 loci have greater impacts on Mixograph properties compared to the Wx-1 loci and the effects of Glu-D1d and Glu-D1h on dough mixing are better than those of Glu-D1f and Glu-D1new1 in this population; (ii) the interactions between the Glu-1 and Wx-1 loci affected some traits, especially the midline peak value (MPV), and the lack of Wx-B1 or Wx-D1 led to increased MPV for all types of Glu-1 loci; and (iii) 30 quantitative-trait loci (QTL) over nine wheat chromosomes were identified with ICIM analysis based on the genetic map of 498 loci. Eight major QTL and 16 QTL in the Glu-1 loci from the three environments were found. The major QTL clusters were associated with the Glu-1 loci, and also were found in two regions on chromosome 3B and one region on chromosome 6A, which is one of the novel chromosome regions influencing dough-mixing strength. The two QTL for MPV are located around Wx-B1 on chromosome 4A. QMPT-1D.1, QMPI-1D.1 and Q8MW-1D.1 were stable in different environments and could potentially be used in molecular marker-assisted breeding.

Quantitative trait loci influencing endosperm texture, dough-mixing strength, and bread-making properties of the hard red spring wheat breeding lines

Wheat end product quality is determined by a complex group of traits including dough viscoelastic characteristics and bread-making properties. Quantitative trait loci (QTL) mapping and analysis were conducted for endosperm texture, dough-mixing strength, and bread-making properties in a population of 139 (MN99394 × MN98550) recombinant inbred lines that were evaluated at three environments in 2006. Based on the genetic map of 534 loci, six QTL were identified for endosperm texture, with the main QTL on chromosomes 1A (R2 = 6.6%–17.3%), 5A (R2 = 6.1%–17.1%), and 5D (R2 = 15.8%–22%). Thirty-four QTL were identified for eight dough-mixing strength and bread-making properties. Major QTL clusters were associated with the low-molecular weight glutenin gene Glu-A3, the two high-molecular weight glutenin genes Glu-B1 and Glu-D1, and two regions on chromosome 6D. Alleles at these QTL clusters have previously been proven useful for wheat quality, except one of the QTL clusters on chromosome 6D. A QTL cluster on chromosome 6D is one of the novel chromosome regions influencing dough-mixing strength and bread-making properties. The QTL for endosperm texture on chromosomes 1A, 5A, and 5B also influenced flour ash content (12.4%–23.3%), flour protein content (10.5%–12.5%), and flour colour (7.7%–13.5%), respectively.

Analysis of BAC-end sequences (BESs) and development of BES-SSR markers for genetic mapping and hybrid purity assessment in pigeonpea (Cajanus spp.)

BACKGROUND

Pigeonpea [Cajanus cajan (L.) Millsp.] is an important legume crop of rainfed agriculture. Despite of concerted research efforts directed to pigeonpea improvement, stagnated productivity of pigeonpea during last several decades may be accounted to prevalence of various biotic and abiotic constraints and the situation is exacerbated by availability of inadequate genomic resources to undertake any molecular breeding programme for accelerated crop improvement. With the objective of enhancing genomic resources for pigeonpea, this study reports for the first time, large scale development of SSR markers from BAC-end sequences and their subsequent use for genetic mapping and hybridity testing in pigeonpea.

RESULTS

A set of 88,860 BAC (bacterial artificial chromosome)-end sequences (BESs) were generated after constructing two BAC libraries by using HindIII (34,560 clones) and BamHI (34,560 clones) restriction enzymes. Clustering based on sequence identity of BESs yielded a set of >52K non-redundant sequences, comprising 35 Mbp or >4% of the pigeonpea genome. These sequences were analyzed to develop annotation lists and subdivide the BESs into genome fractions (e.g., genes, retroelements, transpons and non-annotated sequences). Parallel analysis of BESs for microsatellites or simple sequence repeats (SSRs) identified 18,149 SSRs, from which a set of 6,212 SSRs were selected for further analysis. A total of 3,072 novel SSR primer pairs were synthesized and tested for length polymorphism on a set of 22 parental genotypes of 13 mapping populations segregating for traits of interest. In total, we identified 842 polymorphic SSR markers that will have utility in pigeonpea improvement. Based on these markers, the first SSR-based genetic map comprising of 239 loci was developed for this previously uncharacterized genome. Utility of developed SSR markers was also demonstrated by identifying a set of 42 markers each for two hybrids (ICPH 2671 and ICPH 2438) for genetic purity assessment in commercial hybrid breeding programme.

CONCLUSION

In summary, while BAC libraries and BESs should be useful for genomics studies, BES-SSR markers, and the genetic map should be very useful for linking the genetic map with a future physical map as well as for molecular breeding in pigeonpea.