Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD 4072, Australia.
Theor Appl Genet. 2013 Jan;126(1):1-11. doi: 10.1007/s00122-012-1964-x. Epub 2012 Sep 5.
Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.
许多重要的作物物种都具有源自祖先或近期多倍化事件的基因组。在大型和复杂的作物基因组中,多个同源基因拷贝、染色体重排和重复 DNA 的扩增会极大地增加常规正向遗传学方法进行基因组分析和基因发现的难度。另一方面,分子遗传学和基因组学的技术进步为分析和获取更具抗性的基因组提供了前所未有的机会。在这篇综述中,我们描述了下一代测序和数据分析技术,这些技术极大地提高了我们剖析和挖掘基因组以发现关键性状和育种者感兴趣的等位基因变异的因果基因的能力。我们主要关注小麦和油菜籽,这是两种主要多倍体作物基因组的领先范例,它们的大小或复杂性带来了不同的、重大的挑战。在这两种情况下,最新的 DNA 测序技术,应用于非常不同的方法,已经为各自的基因组解开提供了相当大的进展。随着 DNA 测序和处理不断增长的基因组数据的生物信息学工具的发展,我们发现作物基因库中遗传多样性的程度和分布及其与产量和质量相关性状的关系的能力正在迅速增强。在未来十年中,对不同种质资源中基因组和转录组的测序、单核苷酸多态性、存在缺失变异和其他结构染色体变异的发现和高通量筛选,将深入了解多倍体作物的起源、驯化和可用的性状相关变异,从而为基因组辅助育种提供新的方法和可能性。