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植物育种中复杂性状的下一代测序背景下的基因组选择

Genomic Selection in the of Next Generation Sequencing for Complex Traits in Plant Breeding.

作者信息

Bhat Javaid A, Ali Sajad, Salgotra Romesh K, Mir Zahoor A, Dutta Sutapa, Jadon Vasudha, Tyagi Anshika, Mushtaq Muntazir, Jain Neelu, Singh Pradeep K, Singh Gyanendra P, Prabhu K V

机构信息

Division of Genetics, Indian Agricultural Research Institute New Delhi, India.

National Research Centre for Plant Biotechnology New Delhi, India.

出版信息

Front Genet. 2016 Dec 27;7:221. doi: 10.3389/fgene.2016.00221. eCollection 2016.

Abstract

Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencing. These marker technologies have changed the entire scenario of marker applications and made the use of GS a routine work for crop improvement in both model and non-model crop species. The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding. But to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits. Moreover, the continuous decline in sequencing cost will make the WGS feasible and cost effective for GS in near future. Till that time matures the targeted sequencing seems to be more cost-effective option for large scale marker discovery and GS, particularly in case of large and un-decoded genomes.

摘要

基因组选择(GS)是一种利用分子遗传标记来设计新型育种计划并开发基于标记的新模型进行遗传评估的有前景的方法。在植物育种中,它为提高单位时间和成本内复杂性状的遗传增益提供了机会。成本效益平衡是基因组选择在作物中发挥作用的一个重要考量因素。全基因组范围内高通量、经济高效且灵活的标记的可用性,具有低确定偏差,适用于大群体规模,并且适用于有或没有参考基因组序列的模式作物和非模式作物物种,这是其在作物物种中成功有效实施的最重要因素。这些因素是早期标记系统(即SSR和基于芯片的标记系统)的主要限制,在下一代测序(NGS)技术出现之前是难以想象的,下一代测序技术提供了新型SNP基因分型平台,特别是测序基因分型。这些标记技术改变了标记应用的整个局面,并使基因组选择在模式作物和非模式作物物种的作物改良中成为一项常规工作。基于NGS的基因分型在谷物和其他作物物种中比其他既定标记平台提高了基因组估计育种值预测的准确性,并使基因组选择在作物育种中的梦想成真。但是为了充分利用基因组选择的真正益处,这些标记技术将与高通量表型分析相结合,以从复杂性状中获得有价值的遗传增益。此外,测序成本的持续下降将使全基因组测序在不久的将来对基因组选择变得可行且具有成本效益。在那之前成熟的靶向测序似乎是大规模标记发现和基因组选择更具成本效益的选择,特别是在大的未解码基因组的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec1d/5186759/58d6c0e1f421/fgene-07-00221-g001.jpg

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