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Haplotype-based genotyping-by-sequencing in oat genome research
Wubishet A Bekele1, Charlene P Wight1, Shiaoman Chao2
1Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Plant Biotechnology Journal
|January 19, 2018
Summary
Tag-level (TL) haplotype genotyping-by-sequencing (GBS) in oats significantly improved genome mapping and genomic selection. TL markers outperformed SNPs and chromosome-level (CL) blocks in genome-wide association studies for heading date.
Area of Science:
- Plant genetics
- Genomics
- Agricultural science
Background:
- Genotyping-by-sequencing (GBS) is crucial for understanding crop genetic diversity.
- Developing high-density genetic maps is essential for advanced breeding in cultivated oat (Avena sativa).
Purpose of the Study:
- To evaluate the utility of tag-level (TL) haplotype GBS variants compared to single nucleotide polymorphisms (SNPs) and chromosome-level (CL) blocks.
- To enhance oat genome analysis, mapping, and genomic selection.
- To identify genomic regions under selection in oat populations.
Main Methods:
- Performed de novo GBS analysis on 4657 oat accessions to generate TL genetic variants.
- Increased marker density on an oat consensus map and inferred CL haplotype maps from a diversity panel.
- Conducted genome-wide association studies (GWAS) and genomic selection analyses using TL haplotypes, SNPs, and CL blocks.
Main Results:
- Discovered 164,741 TL variants and added over 70,000 loci to the oat consensus map.
- TL haplotype markers demonstrated superiority in GWAS for heading date compared to SNPs and CL blocks.
- Identified genomic regions with signatures of selection, potentially linked to adaptation.
- Achieved promising prediction accuracies for genomic selection of heading date (up to r=0.74).
Conclusions:
- TL haplotype GBS-derived markers are effective for oat genome analysis and genomic selection.
- TL markers offer advantages for high-resolution genome analysis and marker-assisted breeding in oats.
- This approach facilitates the identification of genes related to local adaptation and improves breeding efficiency.
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