Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding

Nan Wang,Xinhai Li,Yibing Yuan,Manje Gowda,Diansi Yu,Ao Zhang,Hui Wang,Sudha K Nair,Boddupalli M Prasanna,Yubo Liu,Felix San Vicente,Xuecai Zhang,Yanli Lu,Zhuanfang Hao

doi:10.1038/s41598-020-73321-8

Abstract

Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

Highlights

IntroductionLinkage mapping, and association mapping, especially at the whole-genome level, form the foundation of modern molecular breeding[1]
Genetic diversity analysis, linkage mapping, and association mapping, especially at the whole-genome level, form the foundation of modern molecular breeding[1]
2240 individuals from eight tropical maize populations developed at CIMMYT were analyzed using GBS with the following objectives: (i) to assess the efficiency of single nucleotide polymorphisms (SNPs) discovery by GBS for different types of populations; (ii) to ascertain the utility of GBS data in genetic diversity analysis, genome-wide association studies (GWAS), linkage mapping, and genomic prediction (GP); and (iii) to determine the effects on genetic analysis of imputing genotype data

Summary

Introduction

Linkage mapping, and association mapping, especially at the whole-genome level, form the foundation of modern molecular breeding[1]. Genotyping-by-sequencing (GBS) is one of most widely used RRS methods, where in the barcode system was improved to allow discovery genome-wide SNPs with a lower error rate and low cost[9]. Sequence data software and pipelines have been developed to improve the efficiency and versatility of GBS for SNP discovery and mapping[10,12,13]. 2240 individuals from eight tropical maize populations developed at CIMMYT were analyzed using GBS with the following objectives: (i) to assess the efficiency of SNP discovery by GBS for different types of populations; (ii) to ascertain the utility of GBS data in genetic diversity analysis, GWAS, linkage mapping, and GP; and (iii) to determine the effects on genetic analysis of imputing genotype data

Methods

Results

Discussion

Conclusion