Association mapping identifies loci for canopy coverage in diverse soybean genotypes

Rapid establishment of canopy coverage decreases soil evaporation relative to transpiration, improves water use efficiency and light interception, and increases soybean competitiveness against weeds. The objective of this study was to identify genomic loci associated with canopy coverage (CC). Canopy coverage was evaluated using a panel of 373 MG IV soybean genotypes that was grown in five environments. Digital image analysis was used to determine canopy coverage two times (CC1 and CC2) during vegetative development approximately 8 to 16 days apart for each environment. After filtration for quality control, 31,260 SNPs with a minor allele frequency (MAF)?≥?5% were used for association mapping with the FarmCPU model. Analysis identified significant SNP-canopy coverage associations including 36 for CC1 and 56 for CC2. Five SNPs for CC1 and 11 SNPs for CC2 were present in at least two environments. The significant SNP associations likely tagged 33 (CC1) and 50 (CC2) different quantitative trait loci (QTLs). Eleven putative loci were identified in which chromosomal regions associated were coincident for CC1 and CC2. Candidate genes identified using these significant SNPs included those with reported functions associated with growth, developmental, and light responses. Favorable alleles from significant SNPs may be an important resource for pyramiding genes to improve canopy coverage and for identifying parental genotypes for use in breeding programs.     

Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean

Background

Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness.

Result

A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria.

Conclusions

This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-809) contains supplementary material, which is available to authorized users.     

Genome-wide association study for soybean mosaic virus SC3 resistance in soybean

Molecular Breeding - Meloidogyne graminicola is one of the most important plant-parasitic nematodes in rice. Breeding for natural resistance and tolerance is considered one of the most economical...     

Genome-wide association mapping of blood cell traits in mice

Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75 Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice.     

Genome-wide association mapping of agronomic traits in sugar beet

Recent results indicate that association mapping in populations from applied plant breeding is a powerful tool to detect QTL which are of direct relevance for breeding. The focus of this study was to unravel the genetic architecture of six agronomic traits in sugar beet. To this end, we employed an association mapping approach, based on a very large population of 924 elite sugar beet lines from applied plant breeding, fingerprinted with 677 single nucleotide polymorphism (SNP) markers covering the entire genome. We show that in this population linkage disequilibrium decays within a short genetic distance and is sufficient for the detection of QTL with a large effect size. To increase the QTL detection power and the mapping resolution a much higher number of SNPs is required. We found that for QTL detection, the mixed model including only the kinship matrix performed best, even in the presence of a considerable population structure. In genome-wide scans, main effect QTL and epistatic QTL were detected for all six traits. Our full two-dimensional epistasis scan revealed that for complex traits there appear to be epistatic master regulators, loci which are involved in a large number of epistatic interactions throughout the genome.     

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a highly recalcitrant endoparasite of soybean roots, causing more yield loss than any other pest. To identify quantitative trait loci (QTL) controlling resistance to SCN (HG type 2.5.7, race 1), a genome-wide association study (GWAS) was performed. The association panel, consisting of 120 Chinese soybean cultivars, was genotyped with 7189 single nucleotide polymorphism (SNPs). A total of 6204 SNPs with minor allele frequency >0.05 were used to estimate linkage disequilibrium (LD) and population structure. The mean level of LD measured by r ² declined very rapidly to half its maximum value (0.51) at 220 kb. The overall population structure was approximately coincident with geographic origin. The GWAS results identified 13 SNPs in 7 different genomic regions significantly associated with SCN resistance. Of these, three SNPs were localized in previously mapped QTL intervals, including rhg1 and Rhg4. The GWAS results also detected 10 SNPs in 5 different genomic regions associated with SCN resistance. The identified loci explained an average of 95.5% of the phenotypic variance. The proportion of phenotypic variance was due to additive genetic variance of the validated SNPs. The present study identified multiple new loci and refined chromosomal regions of known loci associated with SCN resistance. The loci and trait-associated SNPs identified in this study can be used for developing soybean cultivars with durable resistance against SCN.     

Genome-wide association mapping for five major pest resistances in wheat

Insect pests cause substantial damage to wheat production in many wheat-producing areas of the world. Amongst these, Hessian fly (HF), Russian wheat aphid (RWA), Sunn pest (SP), wheat stem saw fly (WSSF) and cereal leaf beetle (CLB) are the most damaging in the areas where they occur. Historically, the use of resistance genes in wheat has been the most effective, environmentally friendly, and cost-efficient approach to controlling pest infestations. In this study, we carried out a genome-wide association study with 2518 Diversity Arrays Technology markers which were polymorphic on 134 wheat genotypes with varying degrees of resistance to the five most destructive pests (HF, RWA, SP, WSSF and CLB) of wheat, using mixed linear model (MLM) analysis with population structure as a covariate. We identified 26 loci across the wheat genome linked to genes conferring resistance to these pests, of which 20 are potentially novel quantitative trait loci with significance values which ranged between 5 × 10^?3 and 10^?11. We used an in silico approach to identify probable candidate genes at some of the genomic regions and found that their functions varied from defense response with transferase activity to several genes of unknown function. Identification of potentially new loci associated with resistances to pests would contribute to more rapid marker-aided incorporation of new and diverse genes to develop new varieties with improved resistance against these pests.     

Identification of genetically diverse genotypes for photoperiod insensitivity in soybean using RAPD markers

Most of the Indian soybean varieties were found to be highly sensitive to photoperiod, which limits their cultivation in only localized area. Identification of genetically diverse source of photoperiod insensitive would help to broaden the genetic base for this trait. Present study was undertaken with RAPD markers for genetic diversity estimation in 44 accessions of soybean differing in response to photoperiod sensitivity. The selected twenty-five RAPD primers produced a total of 199 amplicons, which generated 89.9 % polymorphism. The number of amplification products ranged from 2 to 13 for different primers. The polymorphism information content ranged from 0.0 for monomorphic loci to 0.5 with an average of 0.289. Genetic diversity between pairs of genotypes was 37.7% with a range of 3.9 to 71.6%. UPGMA cluster analysis placed all the accessions of soybean into four major clusters. No discernable geographical patterns were observed in clustering however; the smaller groups corresponded well with pedigree. Mantel’s test (r = 0.915) indicates very good fit for clustering pattern. Two genotypes, MACS 330 and 111/2/1939 made a very divergent group from other accessions of soybean and highly photoperiod insensitive that may be potential source for broadening the genetic base of soybean for this trait.Key words: Genetic diversity, Photoperiod, RAPD, Soybean, UPGMA     

Genome-wide association mapping of loci for antipsychotic-induced extrapyramidal symptoms in mice

Tardive dyskinesia (TD) is a debilitating, unpredictable, and often irreversible side effect resulting from chronic treatment with typical antipsychotic agents such as haloperidol. TD is characterized by repetitive, involuntary, purposeless movements primarily of the orofacial region. In order to investigate genetic susceptibility to TD, we used a validated mouse model for a systems genetics analysis geared toward detecting genetic predictors of TD in human patients. Phenotypic data from 27 inbred strains chronically treated with haloperidol and phenotyped for vacuous chewing movements were subject to a comprehensive genomic analysis involving 426,493 SNPs, 4,047 CNVs, brain gene expression, along with gene network and bioinformatic analysis. Our results identified ~50 genes that we expect to have high prior probabilities for association with haloperidol-induced TD, most of which have never been tested for association with human TD. Among our top candidates were genes regulating the development of brain motor control regions (Zic4 and Nkx6-1), glutamate receptors (Grin1 and Grin2a), and an indirect target of haloperidol (Drd1a) that has not been studied as well as the direct target, Drd2.     

Genome-wide association mapping and agronomic impact of cowpea root architecture

Key message

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.

Abstract

Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

     

Genome-wide association mapping of agronomic traits in relevant barley germplasm in Uruguay

The genetic basis of agronomic traits determining adaptation to specific production conditions is a key factor for the improvement of crops, including malting barley (Hordeum vulgare L.). The aim of this study was to determine the genome-wide genetic components associated with agronomic phenotypes of local and global significance in a population of 76 barley genotypes that have been introduced into Uruguay in different chronological periods. The phenotypic database was obtained from five field experiments, planted in 2 years and in two locations, where a total of 13 agronomic traits were determined. The population was genotyped with 1,033 single nucleotide polymorphisms. We found a total of 41 quantitative trait loci (QTL) in a combined analysis using all datasets and 79 QTL if we considered all the trait/experiment combinations analyzed. The highest concentration of QTL was detected on chromosomes 2H and 4H. Most QTL were detected for grain plumpness and weight. Two linkage disequilibrium (LD) blocks associated with a large number of traits were detected on 2HS. The largest LD block was composed of three haplotypes, possibly derived from three ancestors of different geographical origin. We also detected three genomic regions in different chromosomes (2H, 5H and 7H) in LD between them, associated with agronomic traits. This study provides a contribution to the understanding of the genetics of barley adaptation in the southern cone of South America. Our results showed that elite varieties have favorable alleles at different QTL, indicating that gains can be made through plant breeding.     

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Genome-wide association mapping for adult resistance to powdery mildew in common wheat

Molecular Biology Reports - Blumeria graminis f. sp. tritici, the causal agent of wheat powdery mildew disease, can occur at all stages of the crop and constantly threatens wheat production. To...     

TASSEL: software for association mapping of complex traits in diverse samples

Association analyses that exploit the natural diversity of a genome to map at very high resolutions are becoming increasingly important. In most studies, however, researchers must contend with the confounding effects of both population and family structure. TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) implements general linear model and mixed linear model approaches for controlling population and family structure. For result interpretation, the program allows for linkage disequilibrium statistics to be calculated and visualized graphically. Database browsing and data importation is facilitated by integrated middleware. Other features include analyzing insertions/deletions, calculating diversity statistics, integration of phenotypic and genotypic data, imputing missing data and calculating principal components.     

Genome-wide association study for calving performance using high-density genotypes in dairy and beef cattle

Background

Calving difficulty and perinatal mortality are prevalent in modern-day cattle production systems. It is well-established that there is a genetic component to both traits, yet little is known about their underlying genomic architecture, particularly in beef breeds. Therefore, we performed a genome-wide association study using high-density genotypes to elucidate the genomic architecture of these traits and to identify regions of the bovine genome associated with them.

Results

Genomic regions associated with calving difficulty (direct and maternal) and perinatal mortality were detected using two statistical approaches: (1) single-SNP (single nucleotide polymorphism) regression and (2) a Bayesian approach. Data included high-density genotypes on 770 Holstein-Friesian, 927 Charolais and 963 Limousin bulls. Several novel or previously identified genomic regions were detected but associations differed by breed. For example, two genomic associations, one each on chromosomes 18 and 2 explained 2.49 % and 3.13 % of the genetic variance in direct calving difficulty in the Holstein-Friesian and Charolais populations, respectively. Imputed Holstein-Friesian sequence data was used to refine the genomic regions responsible for significant associations. Several candidate genes on chromosome 18 were identified and four highly significant missense variants were detected within three of these genes (SIGLEC12, CTU1, and ZNF615). Nevertheless, only CTU1 contained a missense variant with a putative impact on direct calving difficulty based on SIFT (0.06) and Polyphen (0.95) scores. Using imputed sequence data, we refined a genomic region on chromosome 4 associated with maternal calving difficulty in the Holstein-Friesian population and found the strongest association with an intronic variant in the PCLO gene. A meta-analysis was performed across the three breeds for each calving performance trait to identify common variants associated with these traits in the three breeds. Our results suggest that a portion of the genetic variation in calving performance is common to all three breeds.

Conclusion

The genomic architecture of calving performance is complex and mainly influenced by many polymorphisms of small effect. We identified several associations of moderate effect size but the majority were breed-specific, indicating that breed-specific alleles exist for calving performance or that the linkage phase between genotyped allele and causal mutation varies between breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0126-4) contains supplementary material, which is available to authorized users.     

Genome-wide association mapping of Fusarium head blight resistance in contemporary barley breeding germplasm

Utilization of quantitative trait loci (QTL) identified in bi-parental mapping populations has had limited success for improving complex quantitative traits with low to moderate heritability. Association mapping in contemporary breeding germplasm may lead to more effective marker strategies for crop improvement. To test this approach, we conducted association mapping of two complex traits with moderate heritability; Fusarium head blight (FHB) severity and the grain concentration of mycotoxin associated with disease, deoxynivalenol (DON). To map FHB resistance in barley, 768 breeding lines were evaluated in 2006 and 2007 in four locations. All lines were genotyped with 1,536 SNP markers and QTL were mapped using a mixed model that accounts for relatedness among lines. Average linkage disequilibrium within the breeding germplasm extended beyond 4 cM. Four QTL were identified for FHB severity and eight QTL were identified for the DON concentration in two independent sets of breeding lines. The QTL effects were small, explaining 1–3% of the phenotypic variation, as might be expected for complex polygenic traits. We show that using breeding germplasm to map QTL can complement bi-parental mapping studies by providing independent validation, mapping QTL with more precision, resolving questions of linkage and pleiotropy, and identifying genetic markers that can be applied immediately in crop improvement.     

Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Salt is a severe abiotic stress causing soybean yield loss in saline soils and irrigated fields. Marker-assisted selection (MAS) is a powerful genomic tool for improving the efficiency of breeding salt-tolerant soybean varieties. The objectives of this study were to uncover novel single-nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with salt tolerance and to confirm the previously identified genomic regions and SNPs for salt tolerance. A total of 283 diverse soybean plant introductions (PIs) were screened for salt tolerance in the greenhouse based on leaf chloride concentrations and leaf chlorophyll concentrations after 12–18 days of 120-mM NaCl treatment. A total of 33,009 SNPs across 283 genotypes from the Illumina Infinium SoySNP50K BeadChip database were employed in the association analysis with leaf chloride concentrations and leaf chlorophyll concentrations. Genome-wide association mapping showed that 45 SNPs representing nine genomic regions on chromosomes (Chr.) 2, 3, 7, 8, 10, 13, 14, 16, and 20 were significantly associated with both leaf chloride concentrations and leaf chlorophyll concentrations in 2014, 2015, and combined years. A total of 31 SNPs on Chr. 3 were mapped at or near the previously reported major salt tolerance QTL. The significant SNP on Chr. 2 was also in proximity to the previously reported SNP for salt tolerance. The other significant SNPs represent seven putative novel QTLs for salt tolerance. The significant SNP markers on Chr. 2, 3, 14, 16, and 20, which were identified in both general linear model and mixed linear model, were highly recommended for MAS in breeding salt-tolerant soybean varieties.