小柯机器人

墨西哥研究人员利用大规模基因组学改良面包小麦
2019-09-24 13:19

墨西哥国际玉米与小麦改良中心Ravi Prakash Singh研究团队在研究中取得进展。他们利用大规模基因组学技术提高了面包小麦的产量、抗逆性和品质。相关论文2019年9月23日在线发表于《自然—遗传学》。

研究人员报告了35个关键性状的基因组可预测性,并证明了基因组选择对小麦最终质量的潜力。研究人员还进行了一项大型的全基因组关联研究,确定了在南亚、非洲和美洲评估的50个性状的几个重要的标记与性状间的关联。此外,研究人员建立了参考小麦基因型与表型图谱,探索了等位基因频率随时间变化的动态,并为44624条小麦系进行了性状相关标记的指纹分析,从而产生了超过760万个数据点,这些数据将为小麦研究团体提供宝贵的资源来提高生产力和抗逆性。

研究人员表示,使用基因组学工具改良面包小麦对于加速其性状遗传增益至关重要。

附:英文原文

Title: Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics

Author: Philomin Juliana, Jesse Poland, Julio Huerta-Espino, Sandesh Shrestha, Jos Crossa, Leonardo Crespo-Herrera, Fernando Henrique Toledo, Velu Govindan, Suchismita Mondal, Uttam Kumar, Sridhar Bhavani, Pawan K. Singh, Mandeep S. Randhawa, Xinyao He, Carlos Guzman, Susanne Dreisigacker, Matthew N. Rouse, Yue Jin, Paulino Prez-Rodrguez, Osval A. Montesinos-Lpez, Daljit Singh, Mohammad Mokhlesur Rahman, Felix Marza, Ravi Prakash Singh

Issue&Volume: 2019-09-23

Abstract: 

Bread wheat improvement using genomic tools is essential for accelerating trait genetic gains. Here we report the genomic predictabilities of 35 key traits and demonstrate the potential of genomic selection for wheat end-use quality. We also performed a large genome-wide association study that identified several significant marker–trait associations for 50 traits evaluated in South Asia, Africa and the Americas. Furthermore, we built a reference wheat genotype–phenotype map, explored allele frequency dynamics over time and fingerprinted 44,624 wheat lines for trait-associated markers, generating over 7.6 million data points, which together will provide a valuable resource to the wheat community for enhancing productivity and stress resilience.

DOI: 10.1038/s41588-019-0496-6

Source:https://www.nature.com/articles/s41588-019-0496-6

Nature Genetics:《自然—遗传学》,创刊于1992年。隶属于施普林格·自然出版集团,最新IF:41.307
官方网址:https://www.nature.com/ng/
投稿链接:https://mts-ng.nature.com/cgi-bin/main.plex


本期文章:《自然—遗传学》:Online/在线发表

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