JASPER: Fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression.

Joint association analysis of multiple traits with multiple genetic variants can provide insight into genetic architecture and pleiotropy, improve trait prediction, and increase power for detecting association. Furthermore, some traits are naturally high-dimensional, e.g., images, networks, or longitudinally measured traits. Assessing significance for multitrait genetic association can be challenging, especially when the sample has population sub-structure and/or related individuals. Failure to adequately adjust for sample structure can lead to power loss and inflated type 1 error, and commonly used methods for assessing significance can work poorly with a large number of traits or be computationally slow. We developed JASPER, a fast, powerful, robust method for assessing significance of multitrait association with a set of genetic variants, in samples that have population sub-structure, admixture, and/or relatedness. In simulations, JASPER has higher power, better type 1 error control, and faster computation than existing methods, with the power and speed advantage of JASPER increasing with the number of traits. JASPER is potentially applicable to a wide range of association testing applications, including for multiple disease traits, expression traits, image-derived traits, and microbiome abundances. It allows for covariates, ascertainment, and rare variants and is robust to phenotype model misspecification. We apply JASPER to analyze gene expression in the Framingham Heart Study, where, compared to alternative approaches, JASPER finds more significant associations, including several that indicate pleiotropic effects, most of which replicate previous results, while others have not previously been reported. Our results demonstrate the promise of JASPER for powerful multitrait analysis in structured samples.

Genome-wide association study reveals genetic loci for ten trace elements in foxtail millet (Setaria italica).

KEY MESSAGE: One hundred and fifty-five QTL for trace element concentrations in foxtail millet were identified using a genome-wide association study, and a candidate gene associated with Ni-Co-Cr concentrations was detected. Foxtail millet (Setaria italica) is an important regional crop known for its rich mineral nutrient content, which has beneficial effects on human health. We assessed the concentrations of ten trace elements (Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, and Zn) in the grain of 408 foxtail millet accessions. Significant differences in the concentrations of five elements (Ba, Co, Ni, Sr, and Zn) were observed between two subpopulations of spring- and summer-sown foxtail millet varieties. Moreover, 84.4% of the element pairs exhibited significant correlations. To identify the genetic factors influencing trace element accumulation, a comprehensive genome-wide association study was conducted, identifying 155 quantitative trait locus (QTL) for the ten trace elements across three different environments. Among them, ten QTL were consistently detected in multiple environments, including qZn2.1, qZn4.4, qCr4.1, qFe6.3, qFe6.5, qCo6.1, qPb7.3, qPb7.5, qBa9.1, and qNi9.1. Thirteen QTL clusters were detected for multiple elements, which partially explained the correlations between elements. Additionally, the different concentrations of five elements between foxtail millet subpopulations were caused by the different frequencies of high-concentration alleles associated with important marker-trait associations. Haplotype analysis identified a candidate gene SETIT_036676mg associated with Ni accumulation, with the GG haplotype significantly increasing Ni-Co-Cr concentrations in foxtail millet. A cleaved amplified polymorphic sequence marker (cNi6676) based on the two haplotypes of SETIT_036676mg was developed and validated. Results of this study provide valuable reference information for the genetic research and improvement of trace element content in foxtail millet.

Validation and identification of promising gene specific markers governing foliar disease resistance in groundnut (Arachis hypogaea L.).

BACKGROUND: Groundnut is vulnerable to the major foliar fungal disease viz., late leaf spot (LLS) and rust in kharif season, which results in severe yield losses. Until now, LLS and rust resistance linked markers were developed based on GPBD 4 as a major donor source and were validated in its derivatives only, which restricted their use in marker assisted selection (MAS) involving other donors. METHODS AND RESULTS: The current study focused to validate LLS and rust resistance linked markers employing advanced breeding lines of F6 generation, derived from nine different crosses involving nine diverse parents, to identify potential markers for marker-assisted breeding of LLS and rust resistance in groundnut. Out of 28-trait linked markers used for validation, 8 were polymorphic (28.57%). Marker-trait association (MTA) and Single Marker Analysis (SMA) revealed that the SSR marker pPGPseq5D05 is significantly associated with both LLS (15.8% PVE) and rust (17.5% PVE) resistance, whereas, the marker IPAHM103 is tightly linked with rust resistance (26.8% PVE) alone. In silico analysis revealed that the marker gene for IPAHM103 is a zinc finger protein and the marker gene for pPGPseq5D05 is an ADP-ribosylation factor GTPase-activating protein. Both these protein products impart resistance or tolerance to biotic stress in crop plants. Two other markers namely, GMLQ975 and pPGPseq13A10 were also found to be associated with LLS resistance explaining MTA up to 60%. CONCLUSION: These gene specific markers will enable us to screen more number of germplasm lines or newly developed lines in MAS schemes for LLS and rust resistance using a wide range of resistant sources.

Genome-Wide Association Study for Identification of Marker-Trait Associations Conferring Resistance to Scald from Globally Collected Barley Germplasm.

Scald is one of the major economically important foliar diseases in barley, causing up to 40% yield loss in susceptible varieties. The identification of quantitative trait loci and elite alleles that confer resistance to scald is imperative in reducing the threats to barley production. In this study, genome-wide association studies were conducted using a panel of 697 barley genotypes to identify quantitative trait loci for scald resistance. Field experiments were conducted over three consecutive years. Among different models used for genome-wide association studies analysis, FarmCPU was shown to be the best-suited model. Nineteen significant marker-trait associations related to scald resistance were identified across six different chromosomes. Eleven of these marker-trait associations correspond to previously reported scald resistance genes Rrs1, Rrs4, and Rrs2, respectively. Eight novel marker-trait associations were identified in this study, with the candidate genes encoding a diverse class of proteins, including region leucine-rich repeats, AP2/ERF transcription factor, homeodomain-leucine zipper, and protein kinase family proteins. The combination of identified superior alleles significantly reduces disease severity scores. The results will be valuable for marker-assisted breeding for developing scald-resistant varieties.

Identification of superior haplotypes for flowering time in pigeonpea through candidate gene-based association study of a diverse minicore collection.

KEY MESSAGE: In current study candidate gene (261 genes) based association mapping on 144 pigeonpea accessions for flowering time and related traits and 29 MTAs producing eight superior haplotypes were identified. In the current study, we have conducted an association analysis for flowering-associated traits in a diverse pigeonpea mini-core collection comprising 144 accessions using the SNP data of 261 flowering-related genes. In total, 13,449 SNPs were detected in the current study, which ranged from 743 (ICP10228) to 1469 (ICP6668) among the individuals. The nucleotide diversity (0.28) and Watterson estimates (0.34) reflected substantial diversity, while Tajima's D (-0.70) indicated the abundance of rare alleles in the collection. A total of 29 marker trait associations (MTAs) were identified, among which 19 were unique to days to first flowering (DOF) and/or days to fifty percent flowering (DFF), 9 to plant height (PH), and 1 to determinate (Det) growth habit using 3 years of phenotypic data. Among these MTAs, six were common to DOF and/or DFF, and four were common to DOF/DFF along with the PH, reflecting their pleiotropic action. These 29 MTAs spanned 25 genes, among which 10 genes clustered in the protein-protein network analysis, indicating their concerted involvement in floral induction. Furthermore, we identified eight haplotypes, four of which regulate late flowering, while the remaining four regulate early flowering using the MTAs. Interestingly, haplotypes conferring late flowering (H001, H002, and H008) were found to be taller, while those involved in early flowering (H003) were shorter in height. The expression pattern of these genes, as inferred from the transcriptome data, also underpinned their involvement in floral induction. The haplotypes identified will be highly useful to the pigeonpea breeding community for haplotype-based breeding.

Association mapping in bambara groundnut [Vigna subterranea (L.) Verdc.] reveals loci associated with agro-morphological traits.

BACKGROUND: Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes. RESULTS: The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1). CONCLUSION: These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India.

INTRODUCTION: The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits. METHODS AND RESULTS: The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response. CONCLUSION: These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Multi-environment GWAS identifies genomic regions underlying grain nutrient traits in foxtail millet (Setaria italica).

KEY MESSAGE: A total of 104 foxtail millet accessions were evaluated for 11 nutrients in three environments and 67 high-confidence marker-trait associations (MTAs) were identified. Six SNPs showed pleiotropic effect and associated with two or more nutrients, whereas 24 candidate genes were identified for 28 MTAs involving seven traits. Millets are known for their better nutritional profiles compared to major cereals. Foxtail millet (Setaria italica) is rich in nutrients essential to circumvent malnutrition and hidden hunger. However, the genetic determinants underlying this trait remain elusive. In this context, we evaluated 104 diverse foxtail millet accessions in three different environments (E1, E2, and E3) for 11 nutrients and genotyped with 30K SNPs. The genome-wide association study showed 67 high-confidence (Bonferroni-corrected) marker-trait associations (MTAs) for the nutrients except for phosphorus. Six pleiotropic SNPs were also identified, which were associated with two or more nutrients. Around 24 candidate genes (CGs) were identified for 28 MTAs involving seven nutrients. A total of 17 associated SNPs were present within the gene region, and five (5) were mapped in the exon of the CGs. Significant SNPs, desirable alleles and CGs identified in the present study will be useful in breeding programmes for trait improvement.

A genomic approach identifies sRAGE as a putatively causal protein for asthma.

BACKGROUND: Asthma is a complex respiratory condition caused by environmental and genetic factors. Although lower concentrations of the anti-inflammatory protein soluble receptor for advanced glycation end products (sRAGE) have been associated with asthma in humans and mouse models, it is uncertain whether sRAGE plays a causal role in asthma. OBJECTIVE: We designed a 2-stage study of sRAGE in relation to asthma with association analysis in FHS participants as well as causal inference testing using Mendelian randomization (MR). METHODS: We measured plasma levels of sRAGE and performed cross-sectional analysis to examine the association between plasma sRAGE concentration and asthma status in 6546 FHS participants. We then used sRAGE protein advanced glycation end products (pQTLs) derived from a genome-wide association study of plasma sRAGE levels in ∼7000 FHS participants with UK Biobank asthma genome-wide association study in MR to consider sRAGE as a putatively causal protein for asthma. We also performed replication MR using an externally derived sRAGE pQTL from the INTERVAL study. Last, we conducted colocalization using cis-pQTL variants at the advanced glycosylation end-product specific receptor (AGER) locus with variants from the UK Biobank asthma genome-wide association study. RESULTS: Association analysis revealed that each 1 SD increment in sRAGE concentration was associated with a 14% lower odds of asthma in FHS participants (95% CI 0.76-0.96). MR identified sRAGE as putatively causal for and protective against asthma on the basis of self-reported (odds ratio [per 1 SE increment in inverse-rank-normalized sRAGE] = 0.97, 95% CI 0.95-0.99; P = .005) and doctor-diagnosed asthma (odds ratio = 0.97, 95% CI 0.95-0.99; P = .011). CONCLUSION: Through this genomic approach, we identified sRAGE as a putatively causal, biologically important, and protective protein in relation to asthma. Functional studies in cell/animal models are needed to confirm our findings.

Pinpointing novel risk loci for Lewy body dementia and the shared genetic etiology with Alzheimer's disease and Parkinson's disease: a large-scale multi-trait association analysis.

BACKGROUND: The current genome-wide association study (GWAS) of Lewy body dementia (LBD) suffers from low power due to a limited sample size. In addition, the genetic determinants underlying LBD and the shared genetic etiology with Alzheimer's disease (AD) and Parkinson's disease (PD) remain poorly understood. METHODS: Using the largest GWAS summary statistics of LBD to date (2591 cases and 4027 controls), late-onset AD (86,531 cases and 676,386 controls), and PD (33,674 cases and 449,056 controls), we comprehensively investigated the genetic basis of LBD and shared genetic etiology among LBD, AD, and PD. We first conducted genetic correlation analysis using linkage disequilibrium score regression (LDSC), followed by multi-trait analysis of GWAS (MTAG) and association analysis based on SubSETs (ASSET) to identify the trait-specific SNPs. We then performed SNP-level functional annotation to identify significant genomic risk loci paired with Bayesian fine-mapping and colocalization analysis to identify potential causal variants. Parallel gene-level analysis including GCTA-fastBAT and transcriptome-wide association analysis (TWAS) was implemented to explore novel LBD-associated genes, followed by pathway enrichment analysis to understand underlying biological mechanisms. RESULTS: Pairwise LDSC analysis found positive genome-wide genetic correlations between LBD and AD (rg = 0.6603, se = 0.2001; P = 0.0010), between LBD and PD (rg = 0.6352, se = 0.1880; P = 0.0007), and between AD and PD (rg = 0.2136, se = 0.0860; P = 0.0130). We identified 13 significant loci for LBD, including 5 previously reported loci (1q22, 2q14.3, 4p16.3, 4q22.1, and 19q13.32) and 8 novel biologically plausible genetic associations (5q12.1, 5q33.3, 6p21.1, 8p23.1, 8p21.1, 16p11.2, 17p12, and 17q21.31), among which APOC1 (19q13.32), SNCA (4q22.1), TMEM175 (4p16.3), CLU (8p21.1), MAPT (17q21.31), and FBXL19 (16p11.2) were also validated by gene-level analysis. Pathway enrichment analysis of 40 common genes identified by GCTA-fastBAT and TWAS implicated significant role of neurofibrillary tangle assembly (GO:1902988, adjusted P = 1.55 × 10-2). CONCLUSIONS: Our findings provide novel insights into the genetic determinants of LBD and the shared genetic etiology and biological mechanisms of LBD, AD, and PD, which could benefit the understanding of the co-pathology as well as the potential treatment of these diseases simultaneously.

Association mapping for abiotic stress tolerance using heat- and drought-related syntenic markers in okra.

BACKGROUND: Considerable production losses are caused by heat and drought stress in okra. Germplasm evaluation at genetic level is essential for the selection of promising genotypes. Lack of genomic information of okra limits the use of genetic markers. However, syntenic markers of some related family could be used for molecular characterization of major economic traits. METHODS AND RESULTS: Herein, 56 okra genotypes were evaluated for drought and heat tolerance. Sixty-one expressed sequence tags (ESTs) identified for heat and drought tolerance in cotton were searched from literature surveys and databases. The identified ESTs were BLAST searched into okra unigene database. Primers of selected okra unigenes were synthesized and amplified in all genotypes using standard polymerase chain reaction (PCR) protocol. Marker trait association (MTA) of the syntenic unigenes were identified between genotypic and phenotypic data on the basis of linkage disequilibrium Functional syntenic analysis revealed that out of these 61 cotton ESTs 55 had functional homology with okra unigenes. These 55 unigenes were used as markers for further analysis (amplification). Okra genotypes showed significance variations for all the physo-morphological parameters under heat and drought stress. Genotypes Perbhani Karanti, IQRA-III, Selection Super Green, Anmol and Line Bourd performed better under drought stress whereas genotypes Perbhani Karanti, IQRA-III, Green Gold, OK-1501 and Selection Super Green showed heat tolerance. Fifty markers showed amplification in okra. Fifty-six okra genotypes were clustered into three distinct populations. LD analysis has shown most significant linkage between markers Unigene43786 and Unigene3662. MTAs using MLM and GLM models revealed that 23 markers have significant associations (p < 0.05) with different traits under control and stressed conditions. Relative water content is associated with four markers (Unigene10673, Unigene99547, Unigene152901, and Unigene129684) under drought conditions. Whereas, Electrolyte leakage was associated with 3 markers (Unigene109922, Unigene28667 and Unigene146907) under heat stress. CONCLUSION: These identified unigenes may be helpful in the development of drought and heat tolerant genotypes in okra.

Genetic diversity and marker trait association for phytophthora resistance in chilli.

BACKGROUND: Chilli is an important commercial crop with positive returns tendency. Phytophthora root rot causes drastic damage to chilli plant. Dearth of detecting marker trait associations is a major hinderance in practicing marker assisted selection in chilli breeding. METHODS AND RESULTS: Herein, 110 chilli accessions were assessed for 15 agronomic traits under control and disease infected conditions for two crop seasons (2018-2019). The SSR genotyping revealed high values of major allele frequency (MAF = 0.70), genetic diversity (GD = 0.39) and Polymorphic Information Content (PIC = 0.31). Principal coordinate analysis and population structure analysis showed distribution of diverse genotypes in all groups by dividing 110 genotypes in three populations and nine sub-populations. The UPGMA based Archaeopteryx tree was in concordance with population structure analysis. Linkage disequilibrium analysis evaluated that LD decays within 3-10 bp. Marker trait association (MTA) revealed the associations of 35 SSRs with 14 morphological traits. The significant MTA for marker CAeMS073 with relative leaf damage (RLD, 0.183 R2) under control and treated conditions was consistently observed in both models. The markers, CAMS173 and CAMS194 were found to be strongly associated with RLD and Disease Index (DI), respectively. The absence of MTA was detected for height of first branch. CONCLUSION: The MTAs reported in this study can facilitate marker assisted breeding for developing chilli germplasm resistant against Phytophthora capsici.

Targeted re-sequencing and genome-wide association analysis for wood property traits in breeding population of Eucalyptus tereticornis × E. grandis.

Globally, Eucalyptus plantations occupy 22 million ha area and is one of the preferred hardwood species due to their short rotation, rapid growth, adaptability and wood properties. In this study, we present results of GWAS in parents and 100 hybrids of Eucalyptus tereticornis × E. grandis using 762 genes presumably involved in wood formation. Comparative analysis between parents predicted 32,202 polymorphic SNPs with high average read depth of 269-562× per individual per nucleotide. Seventeen wood related traits were phenotyped across three diverse environments and GWAS was conducted using 13,610 SNPs. A total of 45 SNP-trait associations were predicted across two locations. Seven large effect markers were identified which explained more than 80% of phenotypic variation for fibre area. This study has provided an array of candidate genes which may govern fibre morphology in this genus and has predicted potential SNPs which can guide future breeding programs in tropical Eucalyptus.

Genome-wide association studies for agronomical traits in winter rice accessions of Assam.

The 297 winter rice accessions of Assam, North East India were genotyped by sequencing (GBS). The 50,985 high-quality SNPs were filtered and assigned to 12 rice chromosomes. The population structure analysis revealed three major subgroups SG1, SG2, and SG3 consisting of 30, 8, and 143 accessions respectively. The remaining 116 accessions were grouped as admixture population. Phenotypic data were recorded on13 agronomical traits for genome-wide association studies (GWAS). The 60 significant marker-trait associations (MTAs) were identified for 11 agronomical traits, which explained 0 to 15% of phenotypic variance (PV). A QTL 'hot spot' was detected near the centromeric region on chromosome 6. The identified QTLs may be validated and utilized in 'genomics assisted breeding' for improvement of existing rice cultivars of Assam and North East India.

Genome-Wide Association Study in Bread Wheat Identifies Genomic Regions Associated with Grain Yield and Quality under Contrasting Water Availability.

The objectives of this study were to identify genetic loci in the bread wheat genome that would influence yield stability and quality under water stress, and to identify accessions that can be recommended for cultivation in dry and hot regions. We performed a genome-wide association study (GWAS) using a panel of 232 wheat accessions spanning diverse ecogeographic regions. Plants were evaluated in the Israeli Northern Negev, under two environments: water-limited (D; 250 mm) and well-watered (W; 450 mm) conditions; they were genotyped with ~71,500 SNPs derived from exome capture sequencing. Of the 14 phenotypic traits evaluated, 12 had significantly lower values under D compared to W conditions, while the values for two traits were higher under D. High heritability (H2 = 0.5-0.9) was observed for grain yield, spike weight, number of grains per spike, peduncle length, and plant height. Days to heading and grain yield could be partitioned based on accession origins. GWAS identified 154 marker-trait associations (MTAs) for yield and quality-related traits, 82 under D and 72 under W, and identified potential candidate genes. We identified 24 accessions showing high and/or stable yields under D conditions that can be recommended for cultivation in regions under the threat of global climate change.

Population genetic structure and marker-trait associations in East and West African Striga hermonthica with varying phenotypic response to Fusarium oxysporum f. sp. strigae isolates Foxy-2 and FK3.

To examine the genetic basis for the variable susceptibility of Striga hermonthica from differing zones of sub-Saharan Africa to Fusarium oxysporum f. sp. strigae (Fos) isolates Foxy-2 and FK3, 10 S. hermonthica populations from Eastern and Western Africa were phenotyped for their susceptibility response to Foxy-2 and FK3, and then genotyped with 22 simple sequence repeat (SSR) markers. There is low genetic differentiation between East African and West African S. hermonthica populations (i.e. the proportion of the total genetic variance contained in the subpopulation relative to the total genetic variance, FST  = 0.012, P < 0.05), but intermediate genetic differentiation (FST  = 0.143, P < 0.01) underlies the S. hermonthica groups that are differentiated by their phenotypic responses to Fos isolates. An expressed sequence tag SSR (EST-SSR) marker Y53 (P < 0.01) and a genomic SSR marker E1009 (P < 0.05) were associated with the S. hermonthica class susceptible to Foxy-2 and FK3 (group A). A divergent S. hermonthica class, consisting of groups with intermediate susceptibility to Foxy-2 (group B) and susceptibility to either FK3 (group C) or Foxy-2 (group D), showed no marker-trait association, instead demonstrated linkage disequilibrium decay. Owing to point substitutions and insertion-deletion mutations, the unique, protein-coding nucleotide sequence at the E1009 locus in group A was partly dissimilar to group B, but was totally distinct from groups C and D. These findings implied that the inconsistent effectiveness of a Fos isolate is better explained by genomic variation in S. hermonthica, rather than by S. hermonthica sampling zones.

Genome wide association mapping for heat tolerance in sub-tropical maize.

BACKGROUND: Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. RESULTS: An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. CONCLUSIONS: The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.

Developing Chenopodium ficifolium as a potential B genome diploid model system for genetic characterization and improvement of allotetraploid quinoa (Chenopodium quinoa).

BACKGROUND: Quinoa (Chenopodium quinoa) is a high-value grain known for its excellent nutritional balance. It is an allotetraploid species (AABB, 2n = 4x = 36) formed by the hybridization between AA and BB genome diploid (2n = 2x = 18) species. This study reports genetic studies in Chenopodium ficifolium as a potential B genome diploid model system to simplify the genetic studies of quinoa including gene identification and marker-assisted breeding. RESULTS: Portsmouth, New Hampshire and Quebec City, Quebec accessions of C. ficifolium were used to develop an F2 population segregating for agronomically relevant traits including flowering time, plant height, the number of branches, branch angle, and internode length. Marker-trait associations were identified for the FLOWERING LOCUS T-LIKE 1 (FTL1) marker gene, where the alternate alleles (A1/A2) were segregating among the F2 generation plants in association with flowering time, plant height, and the number of branches. There was a strong correlation of the flowering time trait with both plant height and the number of branches. Thus, a possible multifaceted functional role for FTL1 may be considered. The parental Portsmouth and Quebec City accessions were homozygous for the alternate FTL1 alleles, which were found to be substantially diverged. SNPs were identified in the FTL1 coding sequence that could have some functional significance in relation to the observed trait variation. CONCLUSION: These results draw further attention to the possible functional roles of the FTL1 locus in Chenopodium and justify continued exploration of C. ficifolium as a potential diploid model system for the genetic study of quinoa. We expect our findings to aid in quinoa breeding as well as to any studies related to the Chenopodium genus.

PyBSASeq: a simple and effective algorithm for bulked segregant analysis with whole-genome sequencing data.

BACKGROUND: Bulked segregant analysis (BSA), coupled with next-generation sequencing, allows the rapid identification of both qualitative and quantitative trait loci (QTL), and this technique is referred to as BSA-Seq here. The current SNP index method and G-statistic method for BSA-Seq data analysis require relatively high sequencing coverage to detect significant single nucleotide polymorphism (SNP)-trait associations, which leads to high sequencing cost. RESULTS: We developed a simple and effective algorithm for BSA-Seq data analysis and implemented it in Python; the program was named PyBSASeq. Using PyBSASeq, the significant SNPs (sSNPs), SNPs likely associated with the trait, were identified via Fisher's exact test, and then the ratio of the sSNPs to total SNPs in a chromosomal interval was used to detect the genomic regions that condition the trait of interest. The results obtained this way are similar to those generated via the current methods, but with more than five times higher sensitivity. This approach was termed the significant SNP method here. CONCLUSIONS: The significant SNP method allows the detection of SNP-trait associations at much lower sequencing coverage than the current methods, leading to ~ 80% lower sequencing cost and making BSA-Seq more accessible to the research community and more applicable to the species with a large genome.

Genome-wide association analysis of stripe rust resistance in modern Chinese wheat.

BACKGROUND: Stripe rust (yellow rust) is a significant disease for bread wheat (Triticum aestivum L.) worldwide. A genome-wide association study was conducted on 240 Chinese wheat cultivars and elite lines genotyped with the wheat 90 K single nucleotide polymorphism (SNP) arrays to decipher the genetic architecture of stripe rust resistance in Chinese germplasm. RESULTS: Stripe rust resistance was evaluated at the adult plant stage in Pixian and Xindu in Sichuan province in the 2015-2016 cropping season, and in Wuhan in Hubei province in the 2013-2014, 2016-2017 and 2018-2019 cropping seasons. Twelve stable loci for stripe rust resistance were identified by GWAS using TASSEL and GAPIT software. These loci were distributed on chromosomes 1B, 1D, 2A, 2B, 3A, 3B, 4B (3), 4D, 6D, and 7B and explained 3.6 to 10.3% of the phenotypic variation. Six of the loci corresponded with previously reported genes/QTLs, including Sr2/Yr30/Lr27, while the other six (QYr.hbaas-1BS, QYr.hbaas-2BL, QYr.hbaas-3AL, QYr.hbaas-4BL.3, QYr.hbaas-4DL, and QYr.hbaas-6DS) are probably novel. The results suggest high genetic diversity for stripe rust resistance in this population. The resistance alleles of QYr.hbaas-2AS, QYr.hbaas-3BS, QYr.hbaas-4DL, and QYr.hbaas-7BL were rare in the present panel, indicating their potential use in breeding for stripe rust resistance in China. Eleven penta-primer amplification refractory mutation system (PARMS) markers were developed from SNPs significantly associated with seven mapped QTLs. Twenty-seven genes were predicted for mapped QTLs. Six of them were considered as candidates for their high relative expression levels post-inoculation. CONCLUSION: The resistant germplasm, mapped QTLs, and PARMS markers developed in this study are resources for enhancing stripe rust resistance in wheat breeding.