Dataset Information

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs.

ABSTRACT:

Background

Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop species. Typically, GWAS in crops are performed using a panel of inbred lines, where multiple replicates of the same inbred are measured and the average phenotype is taken as the response variable. Here we describe and evaluate single plant GWAS (sp-GWAS) for performing a GWAS on individual plants, which does not require an association panel of inbreds. Instead sp-GWAS relies on the phenotypes and genotypes from individual plants sampled from a randomly mating population. Importantly, we demonstrate how sp-GWAS can be efficiently combined with a bulk segregant analysis (BSA) experiment to rapidly corroborate evidence for significant SNPs.

Results

In this study we used the Shoepeg maize landrace, collected as an open pollinating variety from a farm in Southern Missouri in the 1960's, to evaluate whether sp-GWAS coupled with BSA can efficiently and powerfully used to detect significant association of SNPs for plant height (PH). Plant were grown in 8 locations across two years and in total 768 individuals were genotyped and phenotyped for sp-GWAS. A total of 306?k polymorphic markers in 768 individuals evaluated via association analysis detected 25 significant SNPs (P???0.00001) for PH. The results from our single-plant GWAS were further validated by bulk segregant analysis (BSA) for PH. BSA sequencing was performed on the same population by selecting tall and short plants as separate bulks. This approach identified 37 genomic regions for plant height. Of the 25 significant SNPs from GWAS, the three most significant SNPs co-localize with regions identified by BSA.

Conclusion

Overall, this study demonstrates that sp-GWAS coupled with BSA can be a useful tool for detecting significant SNPs and identifying candidate genes. This result is particularly useful for species/populations where association panels are not readily available.

SUBMITTER: Gyawali A

PROVIDER: S-EPMC6781408 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs.

Gyawali Abiskar A Shrestha Vivek V Guill Katherine E KE Flint-Garcia Sherry S Beissinger Timothy M TM

BMC plant biology 20191008 1

<h4>Background</h4>Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop species. Typically, GWAS in crops are performed using a panel of inbred lines, where multiple replicates of the same inbred are measured and the average phenotype is taken as the response variable. Here we describe and evaluate single plant GWAS (sp-GWAS) for performing ...[more]

PMID: 31590656

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Project description:BACKGROUND: Single nucleotide polymorphisms (SNPs) are an important class of genetic marker for target gene mapping. As of yet, there is no rapid and effective method to identify SNPs linked with agronomic traits in rapeseed and other crop species. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrate a novel method for identifying SNP markers in rapeseed by deep sequencing a representative library and performing bulk segregant analysis. With this method, SNPs associated with rapeseed pod shatter-resistance were discovered. Firstly, a reduced representation of the rapeseed genome was used. Genomic fragments ranging from 450-550 bp were prepared from the susceptible bulk (ten F2 plants with the silique shattering resistance index, SSRI <0.10) and the resistance bulk (ten F2 plants with SSRI >0.90), and also Solexa sequencing-produced 90 bp reads. Approximately 50 million of these sequence reads were assembled into contigs to a depth of 20-fold coverage. Secondly, 60,396 'simple SNPs' were identified, and the statistical significance was evaluated using Fisher's exact test. There were 70 associated SNPs whose -log(10)p value over 16 were selected to be further analyzed. The distribution of these SNPs appeared a tight cluster, which consisted of 14 associated SNPs within a 396 kb region on chromosome A09. Our evidence indicates that this region contains a major quantitative trait locus (QTL). Finally, two associated SNPs from this region were mapped on a major QTL region. CONCLUSIONS/SIGNIFICANCE: 70 associated SNPs were discovered and a major QTL for rapeseed pod shatter-resistance was found on chromosome A09 using our novel method. The associated SNP markers were used for mapping of the QTL, and may be useful for improving pod shatter-resistance in rapeseed through marker-assisted selection and map-based cloning. This approach will accelerate the discovery of major QTLs and the cloning of functional genes for important agronomic traits in rapeseed and other crop species.

Project description:Waterlogging has increasingly become one of the major constraints to maize productivity in some maize production zones because it causes serious yield loss. Bulked segregant RNA-seq (BSR-seq) has been widely applied to profile candidate genes and map associated Single Nucleotide Polymorphism (SNP) markers in many species. In this study, 10 waterlogging sensitive and eight tolerant inbred lines were selected from 60 maize inbred lines with waterlogging response determined and preselected by the International Maize and Wheat Improvement Center (CIMMYT) from over 400 tropical maize inbred lines. BSR-seq was performed to identify differentially expressed genes and SNPs associated with waterlogging tolerance. Upon waterlogging stress, 354 and 1094 genes were differentially expressed in the tolerant and sensitive pools, respectively, compared to untreated controls. When tolerant and sensitive pools were compared, 593 genes were differentially expressed under untreated and 431 genes under waterlogged conditions, of which 122 genes overlapped. To validate the BSR-seq results, the expression levels of six genes were determined by qRT-PCR. The qRT-PCR results were consistent with BSR-seq results. Comparison of allelic polymorphism in mRNA sequences between tolerant and sensitive pools revealed 165 (normal condition) and 128 (waterlogged condition) high-probability SNPs. We found 18 overlapping SNPs with genomic positions mapped. Eighteen SNPs were contained in 18 genes, and eight and nine of 18 genes were responsive to waterlogging stress in tolerant and sensitive lines, respectively. Six alleles of the 18 originated from tolerant pool were significantly up-regulated under waterlogging, but not those from sensitive pool. Importantly, one allele (GRMZM2G055704) of the six genes was mapped between umc1619 and umc1948 on chromosome 1 where a QTL associated with waterlogging tolerance was identified in a previous research, strongly indicating that GRMZM2G055704 is a candidate gene responsive to waterlogging. Our research contributes to the knowledge of the molecular mechanism for waterlogging tolerance in maize.

Dataset Information

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs.

Background

Results

Conclusion

Publications

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs.

Similar Datasets

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