John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK.
Department of Natural Capital and Plant Health, Royal Botanic Gardens, Kew, Richmond, UK.
Commun Biol. 2020 Nov 25;3(1):712. doi: 10.1038/s42003-020-01413-2.
Crop productivity must increase at unprecedented rates to meet the needs of the growing worldwide population. Exploiting natural variation for the genetic improvement of crops plays a central role in increasing productivity. Although current genomic technologies can be used for high-throughput identification of genetic variation, methods for efficiently exploiting this genetic potential in a targeted, systematic manner are lacking. Here, we developed a haplotype-based approach to identify genetic diversity for crop improvement using genome assemblies from 15 bread wheat (Triticum aestivum) cultivars. We used stringent criteria to identify identical-by-state haplotypes and distinguish these from near-identical sequences (~99.95% identity). We showed that each cultivar shares ~59 % of its genome with other sequenced cultivars and we detected the presence of extended haplotype blocks containing hundreds to thousands of genes across all wheat chromosomes. We found that genic sequence alone was insufficient to fully differentiate between haplotypes, as were commonly used array-based genotyping chips due to their gene centric design. We successfully used this approach for focused discovery of novel haplotypes from a landrace collection and documented their potential for trait improvement in modern bread wheat. This study provides a framework for defining and exploiting haplotypes to increase the efficiency and precision of wheat breeding towards optimising the agronomic performance of this crucial crop.
为了满足全球不断增长的人口需求，农作物的生产力必须以前所未有的速度提高。利用作物的自然变异进行遗传改良在提高生产力方面起着核心作用。尽管目前的基因组技术可用于高通量鉴定遗传变异，但缺乏以有针对性和系统的方式有效利用这种遗传潜力的方法。在这里，我们使用来自 15 个面包小麦（Triticum aestivum）品种的基因组组装，开发了一种基于单倍型的方法来识别用于作物改良的遗传多样性。我们使用严格的标准来识别同态单倍型，并将其与近同态序列（99.95% 的同一性）区分开来。我们表明，每个品种与其他已测序品种共享其基因组的59%，并且我们在所有小麦染色体上检测到包含数百到数千个基因的扩展单倍型块的存在。我们发现，由于其基因中心设计，仅基因序列不足以完全区分单倍型，常用的基于阵列的基因分型芯片也是如此。我们成功地使用这种方法从一个地方品种集合中集中发现新的单倍型，并记录了它们在现代面包小麦中改善性状的潜力。本研究为定义和利用单倍型提供了一个框架，以提高小麦育种的效率和精度，从而优化这种关键作物的农艺性能。
