Department of Marine Biotechnology and Resources, National Sun Yat-Sen University, Kaohsiung City, Taiwan.
Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.
Sci Rep. 2020 Feb 25;10(1):3347. doi: 10.1038/s41598-020-60203-2.
Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.
全基因组关联研究（GWAS）和基因组预测（GP）被广泛用于加速遗传增益和鉴定植物育种中的 QTL。在这项研究中，1317 个春大麦和 1325 个冬小麦育种系来自商业育种计划，用 Illumina 9K 大麦或 15K 小麦 SNP 芯片进行了基因分型，并在多年和多个地点进行了表型分析。对于 GWAS，在春大麦中，发现与白粉病和轮枝菌抗性相关的第 4H 染色体上的一个 QTL。第 4H 染色体上有几个 SNP 与产量性状呈全基因组显著相关。在冬小麦中，GWAS 鉴定出第 6A 染色体上的两个 SNP，第 1B 染色体上的一个 SNP，与品质性状水分显著相关，以及第 5B 染色体上的一个 SNP 与种子中的淀粉含量相关。多性状 GWAS 鉴定出的显著 SNP 与单性状 GWAS 中发现的 SNP 大致相同。在模型中包含基因型-位置信息的 GWAS 在每个测试地点都鉴定出了显著的 SNP，而在包括所有地点的 GWAS 中则没有发现这些 SNP。对于 GP，在春大麦中，贝叶斯幂律模型的 GP 在白粉病和产量性状上比 Ridge 回归 BLUP 的准确性更高，而在冬小麦的产量性状上，贝叶斯幂律模型和 rrBLUP 的预测准确性相似。
