Voss-Fels Kai, Snowdon Rod J
Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Giessen, Germany.
Plant Biotechnol J. 2016 Apr;14(4):1086-94. doi: 10.1111/pbi.12456. Epub 2015 Aug 19.
High-resolution genome analysis technologies provide an unprecedented level of insight into structural diversity across crop genomes. Low-cost discovery of sequence variation has become accessible for all crops since the development of next-generation DNA sequencing technologies, using diverse methods ranging from genome-scale resequencing or skim sequencing, reduced-representation genotyping-by-sequencing, transcriptome sequencing or sequence capture approaches. High-density, high-throughput genotyping arrays generated using the resulting sequence data are today available for the assessment of genomewide single nucleotide polymorphisms in all major crop species. Besides their application in genetic mapping or genomewide association studies for dissection of complex agronomic traits, high-density genotyping arrays are highly suitable for genomic selection strategies. They also enable description of crop diversity at an unprecedented chromosome-scale resolution. Application of population genetics parameters to genomewide diversity data sets enables dissection of linkage disequilibrium to characterize loci underlying selective sweeps. High-throughput genotyping platforms simultaneously open the way for targeted diversity enrichment, allowing rejuvenation of low-diversity chromosome regions in strongly selected breeding pools to potentially reverse the influence of linkage drag. Numerous recent examples are presented which demonstrate the power of next-generation genomics for high-resolution analysis of crop diversity on a subgenomic and chromosomal scale. Such studies give deep insight into the history of crop evolution and selection, while simultaneously identifying novel diversity to improve yield and heterosis.
高分辨率基因组分析技术为深入了解作物基因组的结构多样性提供了前所未有的视角。自从下一代DNA测序技术发展以来,利用从全基因组重测序或简化测序、简化代表性测序分型、转录组测序或序列捕获方法等多种方法,所有作物都能够以低成本发现序列变异。如今,利用所得序列数据生成的高密度、高通量基因分型阵列可用于评估所有主要作物物种的全基因组单核苷酸多态性。除了应用于遗传图谱构建或全基因组关联研究以剖析复杂农艺性状外,高密度基因分型阵列非常适合基因组选择策略。它们还能够以前所未有的染色体尺度分辨率描述作物多样性。将群体遗传学参数应用于全基因组多样性数据集能够剖析连锁不平衡,以表征选择性清除背后的基因座。高通量基因分型平台同时为靶向多样性富集开辟了道路,使经过强烈选择的育种群体中低多样性染色体区域得以恢复活力,从而有可能逆转连锁累赘的影响。文中列举了众多近期实例,展示了下一代基因组学在亚基因组和染色体尺度上对作物多样性进行高分辨率分析的强大能力。此类研究深入洞察了作物进化和选择的历史,同时识别出新的多样性以提高产量和杂种优势。