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ARS Home » Southeast Area » Charleston, South Carolina » Vegetable Research » Research » Publications at this Location » Publication #369851

Research Project: Sustainable Approaches for Pest Management in Vegetable Crops

Location: Vegetable Research

Title: Genome wide association study in sugar profile of sweetpotato

item RICKMAN, TARA - University Of Tennessee
item ADAMS, ALISON - University Of Tennessee
item Wadl, Phillip
item YENCHO, CRAIG - North Carolina State University
item OLUKOLU, BODE - University Of Tennessee

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 12/5/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Sweetpotato, Ipomoea batatas, is a vital crop for combating both visible and invisible hunger. Understanding the genetic diversity of the sweetpotato germplasm and the genetic architecture underlying agronomic traits is crucial to the maintenance and utility of the genetic resources for the crop’s improvement. Genome wide association studies (GWAS) are performed to determine potential associations between observed phenotypic trait data and molecular genotypic data. We performed a GWAS study on ~700 USDA accessions of sweetpotato to determine potential genes and genomic features associated with the sugar profile and culinary traits. GBSpoly performed genotyping-by-sequencing, ngsComposer performed quality filtering of sequence reads, and GBSapp performed single nucleotide polymorphism (SNP) calling and filtering. A total of 80,000 high-quality and dosage-based SNPs were generated, and the phenotypic data were obtained from 20 years of USDA field observations. R software package GWASpoly was used to test marker-trait associations using a mixed linear model while controlling for population structure with a relationship matrix. The associations and relationship matrix accounts for both additive and dominance effects of allele dosage in the polyploid crop. We have successfully determined potential genes of interests that reveal functional annotations relevant to the phenotypes. This information will help enhance the implementation of next-generation breeding in this polyploid crop.