Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes

Key message

A stable QTL that may be used in marker-assisted selection in wheat breeding programs was detected for yield, yield components and drought tolerance-related traits in spring wheat association mapping panel.

Abstract

Genome-wide association mapping has become a widespread method of quantitative trait locus (QTL) identification for many crop plants including wheat (Triticum aestivum L.). Its benefit over traditional bi-parental mapping approaches depends on the extent of linkage disequilibrium in the mapping population. The objectives of this study were to determine linkage disequilibrium decay rate and population structure in a spring wheat association mapping panel (n = 285–294) and to identify markers associated with yield and yield components, morphological, phenological, and drought tolerance-related traits. The study was conducted under fully irrigated and rain-fed conditions at Greeley, CO, USA and Melkassa, Ethiopia in 2010 and 2011 (five total environments). Genotypic data were generated using diversity array technology markers. Linkage disequilibrium decay rate extended over a longer genetic distance for the D genome (6.8 cM) than for the A and B genomes (1.7 and 2.0 cM, respectively). Seven subpopulations were identified with population structure analysis. A stable QTL was detected for grain yield on chromosome 2DS both under irrigated and rain-fed conditions. A multi-trait region significant for yield and yield components was found on chromosome 5B. Grain yield QTL on chromosome 1BS co-localized with harvest index QTL. Vegetation indices shared QTL with harvest index on chromosome 1AL and 5A. After validation in relevant genetic backgrounds and environments, QTL detected in this study for yield, yield components and drought tolerance-related traits may be used in marker-assisted selection in wheat breeding programs.     

Phenotypic and genetic analysis of spike and kernel characteristics in wheat reveals long-term genetic trends of grain yield components

Key message

Phenotypic and genetic analysis of six spike and kernel characteristics in wheat revealed geographic patterns as well as long-term trends arising from breeding progress, particularly in regard to spikelet fertility, i.e. the number of kernels per spikelet, a grain yield component that appears to underlie the increase in the number of kernels per spike.

Abstract

Wheat is a staple crop of global relevance that faces continuous demands for improved grain yield. In this study, we evaluated a panel of 407 winter wheat cultivars for six characteristics of spike and kernel development. All traits showed a large genotypic variation and had high heritabilities. We observed geographic patterns for some traits in addition to long-term trends showing a continuous increase in the number of kernels per spike. This breeding progress is likely due to the increase in spikelet fertility, i.e. the number of kernels per spikelet. While the number of kernels per spike and spikelet fertility were significantly positively correlated, both traits showed a significant negative correlation with thousand-kernel weight. Genome-wide association mapping identified only small- and moderate-effect QTL and an effect of the phenology loci Rht-D1 and Ppd-D1 on some of the traits. The allele frequencies of some QTL matched the observed geographic patterns. The quantitative inheritance of all traits with contributions of additional small-effect QTL was substantiated by genomic prediction. Taken together, our results suggest that some of the examined traits were already the basis of grain yield progress in wheat in the past decades. A more targeted exploitation of the available variation, potentially coupled with genomic approaches, may assist wheat breeding in continuing to increase yield levels globally.

     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Relationships between grain protein content and grain yield components through quantitative trait locus analyses in a recombinant inbred line population derived from two elite durum wheat cultivars

Grain protein content (GPC) in durum wheat (Triticum turgidum var. durum) is negatively correlated with grain yield. To evaluate possible genetic interrelationships between GPC and grain yield per spike, thousand-kernel weight and kernel number per spike, quantitative trait loci (QTL) for GPC were mapped using GPC-adjusted data in a covariance analysis on yield components. Phenotypic data were evaluated in a segregating population of 120 recombinant inbred lines derived from crossing the elite cultivars Svevo and Ciccio. The material was tested at five environments in southern Italy. QTL were determined by composite interval mapping based on the Svevo?×?Ciccio linkage map described in Gadaleta et al. (2009) and integrated with DArT markers. The close relationship between GPC and yield components was reflected in the negative correlation between the traits and in the reduction of variance when GPC values were adjusted to yield components. Ten independent genomic regions involved in the expression of GPC were detected, six of which were associated with QTL for one or more grain yield components. QTL alleles with increased GPC effects were associated with QTL alleles with decreased effects on one or more yield component traits, or vice versa (i.e. the allelic effects were in opposite direction). Four QTL for GPC showed always significant effects, and these QTL should represent genes that influence GPC independently from variation in the yield components. Such genes are of special interest in wheat breeding since they would allow an increase in GPC without a concomitant decrease in grain yield.     

Genome-wide association study of heading and flowering dates and construction of its prediction equation in Chinese common wheat

Heading date is one of the most important traits in wheat breeding as it affects adaptation and yield potential. A genome-wide association study (GWAS) using the 90 K iSelect SNP genotyping assay indicated that a total of 306 loci were significantly associated with heading and flowering dates in 13 environments in Chinese common wheat from the Yellow and Huai wheat region. Of these, 105 loci were significantly correlated with both heading and flowering dates and were found in clusters on chromosomes 2, 5, 6, and 7. Based on differences in distribution of the vernalization and photoperiod genes among chromosomes, arms, or block regions, 13 novel, environmentally stable genetic loci were associated with heading and flowering dates, including RAC875_c41145_189 on 1DS, RAC875_c50422_299 on 2BL, and RAC875_c48703_148 on 2DS, that accounted for more than 20% phenotypic variance explained (PVE) of the heading/flowering date in at least four environments. GWAS and t test of a combination of SNPs and vernalization and photoperiod alleles indicated that the Vrn-B1, Vrn-D1, and Ppd-D1 genes significantly affect heading and flowering dates in Chinese common wheat. Based on the association of heading and flowering dates with the vernalization and photoperiod alleles at seven loci and three significant SNPs, optimal linear regression equations were established, which show that of the seven loci, the Ppd-D1 gene plays the most important role in modulating heading and flowering dates in Chinese wheat, followed by Vrn-B1 and Vrn-D1. Additionally, three novel genetic loci (RAC875_c41145_189, Excalibur_c60164_137, and RAC875_c50422_299) also show important effect on heading and flowering dates. Therefore, Ppd-D1, Vrn-B1, Vrn-D1, and the novel genetic loci should be further investigated in terms of improving heading and flowering dates in Chinese wheat. Further quantitative analysis of an F₁₀ recombinant inbred lines population identified a major QTL that controls heading and flowering dates within the Ppd-D1 locus with PVEs of 28.4% and 34.0%, respectively; this QTL was also significantly associated with spike length, peduncle length, fertile spikelets number, cold resistance, and tiller number.     

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

Key message

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number.

Abstract

Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci—6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)—were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79–85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

     

Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments

Key message

We identified 27 stable loci associated with agronomic traits in spring wheat using genome-wide association analysis, some of which confirmed previously reported studies. GWAS peaks identified in regions where no QTL for grain yield per se has been mapped to date, provide new opportunities for gene discovery and creation of new cultivars with desirable alleles for improving yield and yield stability in wheat.

Abstract

We undertook large-scale genetic analysis to determine marker-trait associations (MTAs) underlying agronomic and physiological performance in spring wheat using genome-wide association studies (GWAS). Field trials were conducted at seven sites in three countries (Sudan, Egypt, and Syria) over 2–3 years in each country. Twenty-five agronomic and physiological traits were measured on 188 wheat genotypes. After correcting for population structure and relatedness, a total of 245 MTAs distributed over 66 loci were associated with agronomic traits in individual and mean performance across environments respectively; some of which confirmed previously reported loci. Of these, 27 loci were significantly associated with days to heading, thousand kernel weight, grain yield, spike length, and leaf rolling for mean performance across environments. Despite strong QTL by environment interactions, eight of the loci on chromosomes 1A, 1D, 5A, 5D, 6B, 7A, and 7B had pleiotropic effects on days to heading and yield components (TKW, SM^?2, and SNS). The winter-type alleles at the homoeologous VRN1 loci significantly increased days to heading and grain yield in optimal environments, but decreased grain yield in heat prone environments. Top 20 high-yielding genotypes, ranked by additive main effects and multiplicative interaction (AMMI), had low kinship relationship and possessed 4–5 favorable alleles for GY MTAs except two genotypes, Shadi-4 and Qafzah-11/Bashiq-1–2. This indicated different yield stability mechanisms due to potentially favorable rare alleles that are uncharacterized. Our results will enable wheat breeders to effectively introgress several desirable alleles into locally adapted germplasm in developing wheat varieties with high yield stability and enhanced heat tolerance.

     

Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats

Key message

Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation.

Abstract

Increases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (<?1 cM). QTL identified and validated in this study provide useful information for the improvement of fall-sown spring wheats under full and limited irrigation.

     

Zinc and iron concentration QTL mapped in a Triticum spelta × T. aestivum cross

Key message

Ten QTL underlying the accumulation of Zn and Fe in the grain were mapped in a set of RILs bred from the cross Triticum spelta × T. aestivum . Five of these loci (two for Zn and three for Fe) were consistently detected across seven environments.

Abstract

The genetic basis of accumulation in the grain of Zn and Fe was investigated via QTL mapping in a recombinant inbred line (RIL) population bred from a cross between Triticum spelta and T. aestivum. The concentration of the two elements was measured from grain produced in three locations over two consecutive cropping seasons and from a greenhouse trial. The range in Zn and Fe concentration across the RILs was, respectively, 18.8–73.5 and 25.3–59.5 ppm, and the concentrations of the two elements were positively correlated with one another (rp =+0.79). Ten QTL (five each for Zn and Fe accumulation) were detected, mapping to seven different chromosomes. The chromosome 2B and 6A grain Zn QTL were consistently expressed across environments. The proportion of the phenotype explained (PVE) by QZn.bhu-2B was >16 %, and the locus was closely linked to the SNP marker 1101425|F|0, while QZn.bhu-6A (7.0 % PVE) was closely linked to DArT marker 3026160|F|0. Of the five Fe QTL detected, three, all mapping to chromosome 1A were detected in all seven environments. The PVE for QFe.bhu-3B was 26.0 %.     

Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping

Key message

Using combined linkage and association mapping, 26 stable QTL and six stable SNPs were detected across multiple environments for eight ear and grain morphological traits in maize. One QTL, PKS2, might play an important role in maize yield improvement.

Abstract

In the present study, one bi-parental population and an association panel were used to identify quantitative trait loci (QTL) for eight ear and grain morphological traits. A total of 108 QTL related to these traits were detected across four environments using an ultra-high density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319, and 26 QTL were identified in more than two environments. Furthermore, 64 single nucleotide polymorphisms (SNPs) were found to be significantly associated with the eight ear and grain morphological traits (?log₁₀(P)?>?4) in an association panel of 240 maize inbred lines. Combining the two mapping populations, a total of 17 pleiotropic QTL/SNPs (pQTL/SNPs) were associated with various traits across multiple environments. PKS2, a stable locus influencing kernel shape identified on chromosome 2 in a genome-wide association study (GWAS), was within the QTL confidence interval defined by the RILs. The candidate region harbored a short 13-Kb LD block encompassing four SNPs (SYN11386, PHM14783.16, SYN11392, and SYN11378). In the association panel, 13 lines derived from the hybrid PI78599 possessed the same allele as Qi319 at the PHM14783.16 (GG) locus, with an average value of 0.21 for KS, significantly lower than that of the 34 lines derived from Ye478 that carried a different allele (0.25, P?<?0.05). Therefore, further fine mapping of PKS2 will provide valuable information for understanding the genetic components of grain yield and improving molecular marker-assisted selection (MAS) in maize.

     

Identification and validation of quantitative trait loci for grain protein concentration in adapted Canadian durum wheat populations

Grain protein concentration (GPC) is one of the most important factors influencing pasta-making quality. Durum wheat (Triticum turgidum L. var durum) cultivars with high GPC produce pasta with increased tolerance to overcooking and greater cooked firmness. However, the large environmental effect on expression of GPC and the negative correlation with grain yield have slowed genetic improvement of this important trait. Understanding the genetics and identification of molecular markers associated with high GPC would aid durum wheat breeders in trait selection at earlier generations. The objectives of this study were to identify and validate molecular markers associated with quantitative trait loci (QTL) for elevated GPC in durum wheat. A genetic map was constructed using SSR and DArT^® markers in an F₁-derived doubled haploid (DH) population derived from the cross DT695 × Strongfield. The GPC data were collected from replicated trials grown in six Canadian environments from 2002 to 2005. QTL associated with variation for GPC were identified on the group 1, 2, and 7 chromosomes and on 5B and 6B, but only QGpc.usw-B3 on 2B and QGpc.usw-A3 on 7A were expressed consistently in four and six environments, respectively. Positive alleles for GPC at these loci were contributed by the high-GPC parent Strongfield. The QGpc.usw-A3 QTL was validated in a second DH population, and depending on environment, selection for the Strongfield allele at barc108 resulted in +0.4% to +1.0% increase in GPC, with little effect on yield in most environments. Given the consistent expression pattern in multiple populations and environments, barc108 could be useful for marker-assisted selection for high GPC.     

Earliness per se QTLs and their interaction with the photoperiod insensitive allele Ppd-D1a in the Cutler × AC Barrie spring wheat population

Earliness per se regulates flowering time independent of environmental signals and helps to fine tune the time of flowering and maturity. In this study, we aimed to map earliness per se quantitative trait loci (QTLs) affecting days to flowering and maturity in a population developed by crossing two spring wheat cultivars, Cutler and AC Barrie. The population of 177 recombinant inbred lines (RILs) was genotyped for a total of 488 SSR and DArT polymorphic markers on all 21 chromosomes. Three QTLs of earliness per se affecting days to flowering and maturity were mapped on chromosomes 1B (QEps.dms-1B1 and QEps.dms-1B2) and 5B (QEps.dms-5B1), in individual environments and when all the environments were combined. A QTL affecting flowering time (QFlt.dms-4A1) was identified on chromosome 4A. Two grain yield QTLs were mapped on chromosome 5B, while one QTL was mapped on chromosome 1D. The population segregated for the photoperiod insensitive gene, Ppd-D1a, and it induced earlier flowering by 0.69 days and maturity by 1.28 days. The photoperiod insensitive allele Ppd-D1a interacted in an additive fashion with QTLs for flowering and maturity times. The earliness per se QTL QFlt.dms-5B.1 inducing earlier flowering could help to elongate grain filling duration for higher grain yield. Hence, chromosome 5B possesses promising genomic regions that may be introgressed for higher grain yield with earlier maturity through marker-assisted selection in bread wheat.     

Genetic dissection of wheat panicle traits using linkage analysis and a genome-wide association study

Key message

Coincident regions on chromosome 4B for GW, on 5A for SD and TSS, and on 3A for SL and GNS were detected through an integration of a linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A and 6A were identified with high PVE% on a composite map.

Abstract

The panicle traits of wheat, such as grain number per spike and 1000-grain weight, are closely correlated with grain yield. Superior and effective alleles at loci related to panicles developments play a crucial role in the progress of molecular improvement in wheat yield breeding. Here, we revealed several notable allelic variations of seven panicle-related traits through an integration of genome-wide association mapping and a linkage analysis. The linkage analysis was performed using a recombinant inbred line (RIL) population (173 lines of F_8:9) with a high-density genetic map constructed with 90K SNP arrays, Diversity Arrays Technology (DArT) and simple sequence repeat (SSR) markers in five environments. Thirty-five additive quantitative trait loci (QTL) were discovered, including eleven stable QTLs on chromosomes 1A, 2D, 4B, 5B, 6B, and 6D. The marker interval between EX_C101685 and RAC875_C27536 on chromosome 4B exhibited pleiotropic effects for GW, SL, GNS, FSN, SSN, and TSS, with the phenotypic variation explained (PVE) ranging from 5.40 to 37.70%. In addition, an association analysis was conducted using a diverse panel of 205 elite wheat lines with a composite map (24,355 SNPs) based on the Illumina Infinium assay in four environments. A total of 73 significant marker-trait associations (MTAs) were detected for panicle traits, which were distributed across all wheat chromosomes except for 4D, 5D, and 6D. Consensus regions between RAC875_C27536_611 and Tdurum_contig4974_355 on chromosome 4B for GW in multiple environments, between QTSS5A.7-43 and BS00021805_51 on 5A for SD and TSS, and between QSD3A.2-164 and RAC875_c17479_359 on 3A for SL and GNS in multiple environments were detected through linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A, and 6A were identified with high PVE% on a composite map. This study provides potentially valuable information on the dissection of yield-component traits and valuable genetic alleles for molecular-design breeding or functional gene exploration.

     

QTL mapping of pre-harvest sprouting resistance in a white wheat cultivar Danby

Key message

One major and three minor QTLs for resistance to pre-harvest sprouting (PHS) were identified from a white wheat variety “Danby.” The major QTL on chromosome 3A is TaPHS1, and the sequence variation in its promoter region was responsible for the PHS resistance. Additive?×?additive effects were detected between two minor QTLs on chromosomes 3B and 5A, which can greatly enhance the PHS resistance.

Abstract

Pre-harvest sprouting (PHS) causes significant losses in yield and quality in wheat. White wheat is usually more susceptible to PHS than red wheat. Therefore, the use of none grain color-related PHS resistance quantitative trait loci (QTLs) is essential for the improvement in PHS resistance in white wheat. To identify PHS resistance QTLs in the white wheat cultivar “Danby” and determine their effects, a doubled haploid population derived from a cross of Danby?×?“Tiger” was genotyped using genotyping-by-sequencing markers and phenotyped for PHS resistance in two greenhouse and one field experiments. One major QTL corresponding to a previously cloned gene, TaPHS1, was consistently detected on the chromosome arm 3AS in all three experiments and explained 21.6–41.0% of the phenotypic variations. A SNP (SNP?222) in the promoter of TaPHS1 co-segregated with PHS in this mapping population and was also significantly associated with PHS in an association panel. Gene sequence comparison and gene expression analysis further confirmed that SNP?222 is most likely the causal mutation in TaPHS1 for PHS resistance in Danby in this study. In addition, two stable minor QTLs on chromosome arms 3BS and 5AL were detected in two experiments with allele effects consistently contributed by Danby, while one minor QTL on 2AS was detected in two environments with contradicted allelic effects. The two stable minor QTLs showed significant additive?×?additive effects. The results demonstrated that pyramiding those three QTLs using breeder-friendly KASP markers developed in this study could greatly improve PHS resistance in white wheat.

     

Genetic dissection of sorghum grain quality traits using diverse and segregating populations

Key message

Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping.

Abstract

There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

     

QTL for resistance to root lesion nematode (Pratylenchus thornei) from a synthetic hexaploid wheat source

Key message

A whole genome average interval mapping approach identified eight QTL associated with P. thornei resistance in a DH population from a cross between the synthetic-derived wheat Sokoll and cultivar Krichauff.

Abstract

Pratylenchus thornei are migratory nematodes that feed and reproduce within the wheat root cortex, causing cell death (lesions) resulting in severe yield reductions globally. Genotypic selection using molecular markers closely linked to Pratylenchus resistance genes will accelerate the development of new resistant cultivars by reducing the need for laborious and expensive resistance phenotyping. A doubled haploid wheat population (150 lines) from a cross between the synthetic-derived cultivar Sokoll (P. thornei resistant) and cultivar Krichauff (P. thornei moderately susceptible) was used to identify quantitative trait loci (QTL) associated with P. thornei resistance. The resistance identified in the glasshouse was validated in a field trial. A genetic map was constructed using Diversity Array Technology and the QTL regions identified were further targeted with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. Six significant and two suggestive P. thornei resistance QTL were detected using a whole genome average interval mapping approach. Three QTL were identified on chromosome 2B, two on chromosome 6D, and a single QTL on each of chromosomes 2A, 2D and 5D. The QTL on chromosomes 2BS and 6DS mapped to locations previously identified to be associated with Pratylenchus resistance. Together, the QTL on 2B (QRlnt.sk-2B.1–2B.3) and 6D (QRlnt.sk-6D.1 and 6D.2) explained 30 and 48 % of the genotypic variation, respectively. Flanking PCR-based markers based on SSRs and SNPs were developed for the major QTL on 2B and 6D and provide a cost-effective high-throughput tool for marker-assisted breeding of wheat with improved P. thornei resistance.     

Single nucleotide polymorphism tightly linked to a major QTL on chromosome 7A for both kernel length and kernel weight in wheat

Thousand-kernel weight (TKW) is one of the major components of grain yield in wheat (Triticum aestivum). Identifying major quantitative trait loci (QTLs) for TKW and developing effective markers are prerequisite for success in marker-assisted selection (MAS) to improve wheat yield through breeding. This study mapped a major QTL, designated as TaTKW-7AL, for increasing TKW on the long arm of chromosome 7A of ‘Clark’ to a 1.3-cM interval between single nucleotide polymorphism (SNP) markers IWB13913 and IWA5913. This QTL explained 19.7 % of the phenotypic variation for TKW. A QTL for increasing kernel length (KL), one of the major components of TKW, was mapped in the same interval as TaTKW-7AL, suggesting that increased TKW by the QTL in ‘Clark’ is most likely due to the increased KL. Association analysis on a diversity panel of 200 US winter wheat accessions also identified a haplotype of three SNP markers (IWB13913, IWB6693 and IWA5913) that were tightly associated with the both KL and TKW. The analysis of allele frequencies of the haplotype in the diversity panel suggested that the favorable allele of TaTKW-7AL has not been strongly selected for in practice and has potential to be used to improve grain yield in US hard winter wheat breeding. Two user-friendly flanking KASPar markers, IWB13913 and IWA5913, were developed for MAS of TaTKW-7AL.     

A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds

Key message

We detected a QTL for single seed weight in soybean that was stable across multiple environments and genetic backgrounds with the use of two recombinant inbred line populations.

Abstract

Single seed weight (SSW) in soybean is a key determinant of both seed yield and the quality of soy food products, and it exhibits wide variation. SSW is under genetic control, but the molecular mechanisms of such control remain unclear. We have now investigated quantitative trait loci (QTLs) for SSW in soybean and have identified such a QTL that is stable across multiple environments and genetic backgrounds. Two populations of 225 and 250 recombinant inbred lines were developed from crosses between Japanese and US cultivars of soybean that differ in SSW by a factor of ~2, and these populations were grown in at least three different environments. A whole-genome panel comprising 304 simple sequence repeat (SSR) loci was applied to mapping in each population. We identified 15 significant QTLs for SSW dispersed among 11 chromosomes in the two populations. One QTL located between Sat_284 and Sat_292 on chromosome 17 was detected (3.6 < LOD < 14.1) in both populations grown in all environments. This QTL, tentatively designated qSw17-1, accounted for 9.4–20.9 % of phenotypic variation in SSW, with a dominant allele being associated with increased SSW. Given its substantial effect on SSW, qSw17-1 is an attractive target for positional cloning, and SSR markers closely associated with this locus may prove useful for marker-assisted selection for SSW control in soybean.     

Mapping of QTL conferring resistance to sharp eyespot (Rhizoctonia cerealis) in bread wheat at the adult plant growth stage

Key message

Seven sharp eyespot resistance QTL were detected consistently across five environments and delimited to seven DNA marker intervals, respectively, six of which were independent of plant height and heading time.

Abstract

Sharp eyespot, caused mainly by the soil-borne fungus Rhizoctonia cerealis, is one of the important diseases of bread wheat (Triticum aestivum L.). This disease has escalated into a major threat to wheat production in some regions of the world. Wheat resistance to sharp eyespot can be a potential means to reduce the needs for application of fungicides and agricultural inputs. In the present study, the winter wheat lines, Luke and AQ24788-83, both of which possess quantitative resistance to sharp eyespot, were crossed and a population consisting 241 recombinant-inbred lines (RILs) was constructed. These RILs were assessed for sharp eyespot resistance by conducting five field and greenhouse trials during the period from 2008 to 2012, and they were genotyped with 549 simple-sequence repeat DNA markers. Seven quantitative trait loci (QTL) were detected consistently across the five trial environments to be associated with the sharp eyespot resistance. They were mapped on chromosomes 1A, 2B, 3B, 4A, 5D, 6B, and 7B. Four of these QTL are unequivocally novel, while it is possible that the other three might also be novel. Plant height and heading date of the 241 RILs were recorded in the four field trials. All of the seven disease resistance QTL were independent of plant height and heading time except one that was significantly associated with plant heading time. This association might be attributed genetically to a single QTL, or to different but closely linked QTL. In the case of single QTL, pleiotropism might be involved or the sharp eyespot resistance might be conferred in a physical instead of physiological nature.     

Translational genomics of grain size regulation in wheat

Key message

Identifying and mapping grain size candidate genes in the wheat genome greatly empowers reverse genetics approaches to improve grain yield potential of wheat.

Abstract

Grain size (GS) or grain weight is believed to be a major driving force for further improvement of wheat yield. Although the large, polyploid genome of wheat poses an obstacle to identifying GS determinants using map-based cloning, a translational genomics approach using GS regulators identified in the model plants rice and Arabidopsis as candidate genes appears to be effective and supports a hypothesis that a conserved genetic network regulates GS in rice and wheat. In this review, we summarize the progress in the studies on GS in the model plants and wheat and identify 45 GS candidate loci in the wheat genome. In silico mapping of these GS loci in the diploid wheat and barley genomes showed (1) several gene families amplified in the wheat lineage, (2) a significant number of the GS genes located in the proximal regions surrounding the centromeres, and (3) more than half of candidate genes to be negative regulators, or their expression negatively related by microRNAs. Identifying and mapping the wheat GS gene homologs will not only facilitate candidate gene analysis, but also open the door to improving wheat yield using reverse genetics approaches by mining desired alleles in landraces and wild ancestors and to developing novel germplasm by TILLING and genome editing technologies.