Haplotype-based genotyping-by-sequencing in oat genome research
Citation
Bekele, W.A., Wight, C.P., Chao, S., Howarth, C.J., Tinker, N.A. (2018). Haplotype-based genotyping-by-sequencing in oat genome research. Plant Biotechnology Journal, [online] 16(8), 1452-1463. http://dx.doi.org/10.1111/pbi.12888
Plain language summary
This paper provides an in-depth evaluation of new software and approaches to genomic data analysis using a large set of data from cultivated oat. Oat is a major cereal crop that is used for human food or animal feed in many parts of the world. Oat breeders are seeking ways to accelerate their breeding programs. DNA sequence-based tools are being used to assist in identifying candidate varieties/crossing partners in plant/animal breeding. Currently, the sequencing or re-sequencing of large and highly-duplicated genomes such as oat is not feasible. Hence, we used a method called genotyping-by-sequencing (GBS), whereby a small and reproducible proportion of the genome (<1%), comprised of many short fragments from throughout the genome, was re-sequenced in each genetic sample. These short sequences were aligned and compared using the software ‘Haplotag’, which was developed to identify single unique genetic markers from a duplicated genome without the assistance of a fully-sequenced genome. We applied this software to analyze 241,224 sequence variants and to generate the genetic profiles of more than 4600 cultivated oat lines. We then inferred the genetic positions of more than 70,000 variants, thus providing a much denser chromosome map of the oat genome. By analyzing tens of thousands of sequence variants in elite breeding lines, we identified genomic regions that control heading date, while comparing three different statistical approaches to this analysis. Furthermore, we used these variants to predict the performance of oat lines based on a statistical procedure called genomic selection. Through these results, we have demonstrated the practical application of GBS, and provided further foundations and guidelines to optimize its use in genome analysis and variety development.
Abstract
In a de novo genotyping-by-sequencing (GBS) analysis of short, 64-base tag-level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag-level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635-line diversity panel were used to infer chromosome-level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high-resolution genome analysis and genomic selection in oats. A combined genome-wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component-based genome-wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS-derived markers facilitate genome analysis and genomic selection in oat.