A genome-wide association study of seed protein and oil content in soybean

Background

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

Results

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r ² ) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

Conclusions

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).     

Candidate genes for alcohol preference identified by expression profiling in alcohol-preferring and -nonpreferring reciprocal congenic rats

Background

Selectively bred alcohol-preferring (P) and alcohol-nonpreferring (NP) rats differ greatly in alcohol preference, in part due to a highly significant quantitative trait locus (QTL) on chromosome 4. Alcohol consumption scores of reciprocal chromosome 4 congenic strains NP.P and P.NP correlated with the introgressed interval. The goal of this study was to identify candidate genes that may influence alcohol consumption by comparing gene expression in five brain regions of alcohol-naïve inbred alcohol-preferring and P.NP congenic rats: amygdala, nucleus accumbens, hippocampus, caudate putamen, and frontal cortex.

Results

Within the QTL region, 104 cis-regulated probe sets were differentially expressed in more than one region, and an additional 53 were differentially expressed in a single region. Fewer trans-regulated probe sets were detected, and most differed in only one region. Analysis of the average expression values across the 5 brain regions yielded 141 differentially expressed cis-regulated probe sets and 206 trans-regulated probe sets. Comparing the present results from inbred alcohol-preferring vs. congenic P.NP rats to earlier results from the reciprocal congenic NP.P vs. inbred alcohol-nonpreferring rats demonstrated that 74 cis-regulated probe sets were differentially expressed in the same direction and with a consistent magnitude of difference in at least one brain region.

Conclusions

Cis-regulated candidate genes for alcohol consumption that lie within the chromosome 4 QTL were identified and confirmed by consistent results in two independent experiments with reciprocal congenic rats. These genes are strong candidates for affecting alcohol preference in the inbred alcohol-preferring and inbred alcohol-nonpreferring rats.

     

QTL-seq identifies an early flowering QTL located near Flowering Locus T in cucumber

Key message

Next-generation sequencing enabled a fast discovery of a major QTL controlling early flowering in cucumber, corresponding to the FT gene conditioning flowering time in Arabidopsis.

Abstract

Next-generation sequencing technologies are making it faster and more efficient to establish the association of agronomic traits with molecular markers or candidate genes, which is the requirement for marker-assisted selection in molecular breeding. Early flowering is an important agronomic trait in cucumber (Cucumis sativus L.), but the underlying genetic mechanism is unknown. In this study, we identified a candidate gene for early flowering QTL, Ef1.1 through QTL-seq. Segregation analysis in F₂ and BC₁ populations derived from a cross between two inbred lines “Muromskij” (early flowering) and “9930” (late flowering) suggested quantitative nature of flowering time in cucumber. Genome-wide comparison of SNP profiles between the early and late-flowering bulks constructed from F₂ plants identified a major QTL, designated Ef1.1 on cucumber chromosome 1 for early flowering in Muromskij, which was confirmed by microsatellite marker-based classical QTL mapping in the F₂ population. Joint QTL-seq and traditional QTL analysis delimited Ef1.1 to an 890 kb genomic region. A cucumber gene, Csa1G651710, was identified in this region, which is a homolog of the FLOWERING LOCUS T (FT), the main flowering switch gene in Arabidopsis. Quantitative RT-PCR study of the expression level of Csa1G651710 revealed significantly higher expression in early flowering genotypes. Data presented here provide support for Csa1G651710 as a possible candidate gene for early flowering in the cucumber line Muromskij.     

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

Key message

“To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.”

Abstract

Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F_3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.     

QTL affecting stress response to crowding in a rainbow trout broodstock population

Background

Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL.

Results

A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively.

Conclusions

The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.

     

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.)

Key message

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations.

Abstract

Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F₂ population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.     

Genetic analysis of vegetative branching in sorghum

Key message

We identified quantitative trait loci influencing plant architecture that may be valuable in breeding of optimized genotypes for sustainable food and/or cellulosic biomass production, and advancing resilience to changing climates.

Abstract

We describe a 3-year study to identify quantitative trait loci (QTLs) for vegetative branching of sorghum in a recombinant inbred line population of 161 genotypes derived from two morphologically distinct parents, S. bicolor × S. propinquum. We quantify vegetative branching based on morphological position and physiological status. Different sets of QTLs for different levels of branching were identified. QTLs discovered on chromosomes 1, 3, 7 and 8 affect multiple vegetative branching variables, suggesting that these regions may contain genes that control general axillary meristem initiation. Other regions that only influence one vegetative branching trait could contain genes that influence developmental processes contributing to divergent patterns of plant architecture. We investigate the relationship between vegetative branching patterns and dry biomass, and conclude that tillers with mature panicles and immature secondary branches each show consistent positive correlation with dry biomass. Among 19 branching-related genes from rice, eight sorghum homologs of seven rice genes are in syntenic blocks within branching-related QTL likelihood intervals. Five of these eight genes are within 700 kb of SNPs significantly associated with differences in branching in genome-wide association study of a diversity panel of 377 sorghum accessions, and three contain striking allelic variations between S. bicolor and S. propinquum that are likely to impact gene functions. Unraveling genetic determinants for vegetative branching may contribute to deterministic breeding of optimized genotypes for sustainable food and cellulosic biomass production in both optimal and marginal conditions, which are resilient to future climates that are more volatile and more stressful.     

Genetical genomic determinants of alcohol consumption in rats and humans

Background

We have used a genetical genomic approach, in conjunction with phenotypic analysis of alcohol consumption, to identify candidate genes that predispose to varying levels of alcohol intake by HXB/BXH recombinant inbred rat strains. In addition, in two populations of humans, we assessed genetic polymorphisms associated with alcohol consumption using a custom genotyping array for 1,350 single nucleotide polymorphisms (SNPs). Our goal was to ascertain whether our approach, which relies on statistical and informatics techniques, and non-human animal models of alcohol drinking behavior, could inform interpretation of genetic association studies with human populations.

Results

In the HXB/BXH recombinant inbred (RI) rats, correlation analysis of brain gene expression levels with alcohol consumption in a two-bottle choice paradigm, and filtering based on behavioral and gene expression quantitative trait locus (QTL) analyses, generated a list of candidate genes. A literature-based, functional analysis of the interactions of the products of these candidate genes defined pathways linked to presynaptic GABA release, activation of dopamine neurons, and postsynaptic GABA receptor trafficking, in brain regions including the hypothalamus, ventral tegmentum and amygdala. The analysis also implicated energy metabolism and caloric intake control as potential influences on alcohol consumption by the recombinant inbred rats. In the human populations, polymorphisms in genes associated with GABA synthesis and GABA receptors, as well as genes related to dopaminergic transmission, were associated with alcohol consumption.

Conclusion

Our results emphasize the importance of the signaling pathways identified using the non-human animal models, rather than single gene products, in identifying factors responsible for complex traits such as alcohol consumption. The results suggest cross-species similarities in pathways that influence predisposition to consume alcohol by rats and humans. The importance of a well-defined phenotype is also illustrated. Our results also suggest that different genetic factors predispose alcohol dependence versus the phenotype of alcohol consumption.     

Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg

Key message

A repertoire of the genomic regions involved in quantitative resistance to Leptosphaeria maculans in winter oilseed rape was established from combined linkage-based QTL and genome-wide association (GWA) mapping.

Abstract

Linkage-based mapping of quantitative trait loci (QTL) and genome-wide association studies are complementary approaches for deciphering the genomic architecture of complex agronomical traits. In oilseed rape, quantitative resistance to blackleg disease, caused by L. maculans, is highly polygenic and is greatly influenced by the environment. In this study, we took advantage of multi-year data available on three segregating populations derived from the resistant cv Darmor and multi-year data available on oilseed rape panels to obtain a wide overview of the genomic regions involved in quantitative resistance to this pathogen in oilseed rape. Sixteen QTL regions were common to at least two biparental populations, of which nine were the same as previously detected regions in a multi-parental design derived from different resistant parents. Eight regions were significantly associated with quantitative resistance, of which five on A06, A08, A09, C01 and C04 were located within QTL support intervals. Homoeologous Brassica napus genes were found in eight homoeologous QTL regions, which corresponded to 657 pairs of homoeologous genes. Potential candidate genes underlying this quantitative resistance were identified. Genomic predictions and breeding are also discussed, taking into account the highly polygenic nature of this resistance.

     

Identification of agronomically important QTL in tetraploid potato cultivars using a marker–trait association analysis

Key message

Nineteen tuber quality traits in potato were phenotyped in 205 cultivars and 299 breeder clones. Association analysis using 3364 AFLP loci and 653 SSR-alleles identified QTL for these traits.

Abstract

Two association mapping panels were analysed for marker–trait associations to identify quantitative trait loci (QTL). The first panel comprised 205 historical and contemporary tetraploid potato cultivars that were phenotyped in field trials at two locations with two replicates (the academic panel). The second panel consisted of 299 potato cultivars and included recent breeds obtained from five Dutch potato breeding companies and reference cultivars (the industrial panel). Phenotypic data for the second panel were collected during subsequent clonal selection generations at the individual breeding companies. QTL were identified for 19 agro-morphological and quality traits. Two association mapping models were used: a baseline model without, and a more advanced model with correction for population structure and genetic relatedness. Correction for population structure and genetic relatedness was performed with a kinship matrix estimated from marker information. The detected QTL partly not only confirmed previous studies, e.g. for tuber shape and frying colour, but also new QTL were found like for after baking darkening and enzymatic browning. Pleiotropic effects could be discerned for several QTL.     

Functional mapping imprinted quantitative trait loci underlying developmental characteristics

Background

Genomic imprinting, a phenomenon referring to nonequivalent expression of alleles depending on their parental origins, has been widely observed in nature. It has been shown recently that the epigenetic modification of an imprinted gene can be detected through a genetic mapping approach. Such an approach is developed based on traditional quantitative trait loci (QTL) mapping focusing on single trait analysis. Recent studies have shown that most imprinted genes in mammals play an important role in controlling embryonic growth and post-natal development. For a developmental character such as growth, current approach is less efficient in dissecting the dynamic genetic effect of imprinted genes during individual ontology.

Results

Functional mapping has been emerging as a powerful framework for mapping quantitative trait loci underlying complex traits showing developmental characteristics. To understand the genetic architecture of dynamic imprinted traits, we propose a mapping strategy by integrating the functional mapping approach with genomic imprinting. We demonstrate the approach through mapping imprinted QTL controlling growth trajectories in an inbred F₂ population. The statistical behavior of the approach is shown through simulation studies, in which the parameters can be estimated with reasonable precision under different simulation scenarios. The utility of the approach is illustrated through real data analysis in an F₂ family derived from LG/J and SM/J mouse stains. Three maternally imprinted QTLs are identified as regulating the growth trajectory of mouse body weight.

Conclusion

The functional iQTL mapping approach developed here provides a quantitative and testable framework for assessing the interplay between imprinted genes and a developmental process, and will have important implications for elucidating the genetic architecture of imprinted traits.     

Primate-specific evolution of noncoding element insertion into PLA2G4C and human preterm birth

Background

The use of biological annotation such as genes and pathways in the analysis of gene expression data has aided the identification of genes for follow-up studies and suggested functional information to uncharacterized genes. Several studies have applied similar methods to genome wide association studies and identified a number of disease related pathways. However, many questions remain on how to best approach this problem, such as whether there is a need to obtain a score to summarize association evidence at the gene level, and whether a pathway, dominated by just a few highly significant genes, is of interest.

Methods

We evaluated the performance of two pathway-based methods (Random Set, and Binomial approximation to the hypergeometric test) based on their applications to three data sets of Crohn's disease. We consider both the disease status as a phenotype as well as the residuals after conditioning on IL23R, a known Crohn's related gene, as a phenotype.

Results

Our results show that Random Set method has the most power to identify disease related pathways. We confirm previously reported disease related pathways and provide evidence for IL-2 Receptor Beta Chain in T cell Activation and IL-9 signaling as Crohn's disease associated pathways.

Conclusions

Our results highlight the need to apply powerful gene score methods prior to pathway enrichment tests, and that controlling for genes that attain genome wide significance enable further biological insight.     

Male-like sexual behavior of female mouse lacking fucose mutarotase

Background

Quantitative traits often underlie risk for complex diseases. For example, weight and body mass index (BMI) underlie the human abdominal obesity-metabolic syndrome. Many attempts have been made to identify quantitative trait loci (QTL) over the past decade, including association studies. However, a single QTL is often capable of affecting multiple traits, a quality known as gene pleiotropy. Gene pleiotropy may therefore cause a loss of power in association studies focused only on a single trait, whether based on single or multiple markers.

Results

We propose using principal-component-based multivariate regression (PCBMR) to test for gene pleiotropy with comprehensive evaluation. This method generates one or more independent canonical variables based on the principal components of original traits and conducts a multivariate regression to test for association with these new variables. Systematic simulation studies have shown that PCBMR has great power. PCBMR-based pleiotropic association studies of abdominal obesity-metabolic syndrome and its possible linkage to chromosomal band 3q27 identified 11 susceptibility genes with significant associations. Whereas some of these genes had been previously reported to be associated with metabolic traits, others had never been identified as metabolism-associated genes.

Conclusions

PCBMR is a computationally efficient and powerful test for gene pleiotropy. Application of PCBMR to abdominal obesity-metabolic syndrome indicated the existence of gene pleiotropy affecting this syndrome.     

Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper

Key message

A mixed model framework was defined for QTL analysis of multiple traits across multiple environments for a RIL population in pepper. Detection power for QTLs increased considerably and detailed study of QTL by environment interactions and pleiotropy was facilitated.

Abstract

For many agronomic crops, yield is measured simultaneously with other traits across multiple environments. The study of yield can benefit from joint analysis with other traits and relations between yield and other traits can be exploited to develop indirect selection strategies. We compare the performance of three multi-response QTL approaches based on mixed models: a multi-trait approach (MT), a multi-environment approach (ME), and a multi-trait multi-environment approach (MTME). The data come from a multi-environment experiment in pepper, for which 15 traits were measured in four environments. The approaches were compared in terms of number of QTLs detected for each trait, the explained variance, and the accuracy of prediction for the final QTL model. For the four environments together, the superior MTME approach delivered a total of 47 regions containing putative QTLs. Many of these QTLs were pleiotropic and showed quantitative QTL by environment interaction. MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. The large number of model parameters in the MTME approach was challenging and we propose several guidelines to help obtain a stable final QTL model. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.     

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

Genome-wide gene expression profiling of human mast cells stimulated by IgE or FcεRI-aggregation reveals a complex network of genes involved in inflammatory responses

Background

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.

Results

The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.

Conclusion

The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.     

Genome-wide QTL and bulked transcriptomic analysis reveals new candidate genes for the control of tuber carotenoid content in potato (Solanum tuberosum L.)

Key message

Genome-wide QTL analysis of potato tuber carotenoid content was investigated in populations of Solanum tuberosum Group Phureja that segregate for flesh colour, revealing a novel major QTL on chromosome 9.

Abstract

The carotenoid content of edible plant storage organs is a key nutritional and quality trait. Although the structural genes that encode the biosynthetic enzymes are well characterised, much less is known about the factors that determine overall storage organ content. In this study, genome-wide QTL mapping, in concert with an efficient ‘genetical genomics’ analysis using bulked samples, has been employed to investigate the genetic architecture of potato tuber carotenoid content. Two diploid populations of Solanum tuberosum Group Phureja were genotyped (AFLP, SSR and DArT markers) and analysed for their tuber carotenoid content over two growing seasons. Common to both populations were QTL that explained relatively small proportions of the variation in constituent carotenoids and a major QTL on chromosome 3 explaining up to 71 % of the variation in carotenoid content. In one of the populations (01H15), a second major carotenoid QTL was identified on chromosome 9, explaining up to 20 % of the phenotypic variation. Whereas the major chromosome 3 QTL was likely to be due to an allele of a gene encoding β-carotene hydroxylase, no known carotenoid biosynthetic genes are located in the vicinity of the chromosome 9 QTL. A unique expression profiling strategy using phenotypically distinct bulks comprised individuals with similar carotenoid content provided further support for the QTL mapping to chromosome 9. This study shows the potential of using the potato genome sequence to link genetic maps to data arising from eQTL approaches to enhance the discovery of candidate genes underlying QTLs.     

Complementary epistasis involving Sr12 explains adult plant resistance to stem rust in Thatcher wheat (Triticum aestivum L.)

Key message

Quantitative trait loci conferring adult plant resistance to Ug99 stem rust in Thatcher wheat display complementary gene action suggesting multiple quantitative trait loci are needed for effective resistance.

Abstract

Adult plant resistance (APR) in wheat (Triticum aestivum L.) to stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is desirable because this resistance can be Pgt race non-specific. Resistance derived from cultivar Thatcher can confer high levels of APR to the virulent Pgt race TTKSK (Ug99) when combined with stem rust resistance gene Sr57 (Lr34). To identify the loci conferring APR in Thatcher, we evaluated 160 RILs derived from Thatcher crossed to susceptible cultivar McNeal for field stem rust reaction in Kenya for two seasons and in St. Paul for one season. All RILs and parents were susceptible as seedlings to race TTKSK. However, adult plant stem rust severities in Kenya varied from 5 to 80 %. Composite interval mapping identified four quantitative trait loci (QTL). Three QTL were inherited from Thatcher and one, Sr57, was inherited from McNeal. The markers closest to the QTL peaks were used in an ANOVA to determine the additive and epistatic effects. A QTL on 3BS was detected in all three environments and explained 27–35 % of the variation. The peak of this QTL was at the same location as the Sr12 seedling resistance gene effective to race SCCSC. Epistatic interactions were significant between Sr12 and QTL on chromosome arms 1AL and 2BS. Though Sr12 cosegregated with the largest effect QTL, lines with Sr12 were not always resistant. The data suggest that Sr12 or a linked gene, though not effective to race TTKSK alone, confers APR when combined with other resistance loci.