周永锋课题组

　　周永锋课题组

　　Yongfeng Zhou Lab

 

　　课题组长

　　周永锋，研究员。2014年博士毕业于芬兰奥卢大学(University of Oulu)，2014-2020年期间先后在奥卢大学与美国加州大学(University of California)从事博士后研究。主要从事作物群体基因组学与遗传育种工作，开展了水稻、葡萄等作物的驯化群体基因组学研究，揭示了作物的驯化成本，以及重要农艺性状相关的适应性变异、有害变异与结构变异。到目前为止，共发表SCI论文20多篇，其中以通讯或第一作者或通讯作者在Nature Plants、PNAS、 Molecular Biology and Evolution等杂志发表SCI论文12篇。

　

　　工作经历

　　2020.06-至今，      中国农业科学院农业基因组研究所，研究员

　　2015.12-2020.06，加州大学尔湾（University of California, Irvine），博士后

　　2014.12-2015.12，奥卢大学 (University of Oulu)，博士后

　　

　　教育经历

　　2012.06–2014.12，奥卢大学，群体遗传学，理学博士

　　2010.11–2012.06，奥卢大学，群体遗传学，理学硕士

　　2007.09–2010.11，兰州大学，生态学，理学博士

　　2003.09–2007.07，兰州大学，生物科学，理学学士

 

　　团队研究方向

　　未来农业面临重大挑战，一方面，人口急剧增长而耕地面积逐年较少，另一方面，全球正在以惊人的速度变暖。如何实现未来粮食安全？本课题组主要结合多组学与气候环境等大数据，应用机器学习与人工智能的算法，检测关键农艺性状相关的适应性变异、有害变异与结构变异。更进一步，借助基因组精准编辑技术（CRISPR-Cas9）实现功能基因组学分析以及快速分子育种。围绕作物群体基因组学与智能育种，主要开展以下工作：（1）水稻、葡萄等作物种质资源收集、保存、评价与创新；（2）重要农艺性状的遗传基础；（3）机器学习与作物基因组设计育种。

　　

　　研究进展

　　围绕作物群体基因组学与育种这一核心，揭示了水稻、葡萄等作物的“驯化成本”（Zhou et al. 2017 PNAS; Liu et al. 2017 MBE），在驯化瓶颈和搭载效应等因素作用下，作物基因组中保留了大量的有害变异，这些有害变异降低了（或者潜在降低）作物的适应性，因此成为作物分子育种的一个新方向（Gaut et al. 2018, Nature Plants）。这种有害变异包括点突变（SNP）、小的插入缺失（Indel）与结构变异（Structural variation, SV）。由于技术瓶颈等因素，早期的研究主要集中在SNP和Indel。我们首次在葡萄驯化中研究了结构变异的群体遗传学，首次揭示了大部分结构变异受到强烈的净化选择作用，以倒位受到的净化选择作用最强（Zhou et al. 2019 Nature Plants）。转座子（TE）作为植物基因组结构变异最主要的组成部分，我们在水稻和葡萄中，首次揭示了不同TE家族受到不同的净化选择作用，其中以SINE受到的净化选择作用最强（Kou et al. 2020 MBE）。结构变异影响了众多作物农艺性状相关的表型，包括葡萄的性别决定与种皮颜色（Zhou et al. 2019 Nature Plants）以及水稻抗洪涝与脱粒等性状（Kou et al. 2020 MBE）。

　　

　　PI

　　Dr. Yongfeng Zhou, research professor, obtained his PhD degree from the University of Oulu in 2014. From 2014 to 2020, he did a postdoc in University of California, Irvine, working on population genomics of crop domestication and breeding. Now he is dedicated to crop population genomics and breeding by combining genomics, epigenomics, transcriptomics, phenomics, environmental variables and machine learning. He had published more than 20 papers. As a first/corresponding author, she has published 12 papers in journals such as Nature Plants, PNAS, and MBE.

　　

　　Working Experience

　　2020–Present    Agricultural Genomics Institute at Shenzhen-CAAS       Research Professor                                                                      

　　2015–2020 University of California, Irvine     Postdoc 

　　2014–2015 University of Oulu    Postdoc 

　　

　　Education

　　University of Oulu          Ph. D. in population genetics  2012.6–2014.12

　　University of Oulu          M. Sc. in population genetics 2010.11–2012.6

　　Lanzhou University        Ph. D. in Ecology      2007.9–2010.11

　　Lanzhou University        B. Sc. in Biology 2003.9–2007.7

　　

　　Research Interest

　　Agriculture is facing major challenges in the future. On the one hand, the population is growing rapidly and the area of farm land is decreasing year by year. On the other hand, the world is warming at an alarming rate. How to achieve future food security? This research group mainly combines big data such as multi-omics and environmental data, and applies machine learning and artificial intelligence algorithms to detect adaptive, deleterious and structural variations associated with major agronomic traits. Furthermore, with the help of precise genome editing technology (CRISPR-Cas9), functional genomic analysis and rapid molecular breeding are realized. Focusing on crop population genomics and intelligent breeding, the following work will mainly conduced: (1) Collection, preservation, evaluation and innovation of crop germplasm resources for crops such as rice, grapes and its rootstocks; (2) The genetic basis of important agronomic traits; (3) Machine learning and genomic breeding of crops.

　　

　　Major Achievements

　　Focusing on crop population genomics and breeding, we had revealed the cost of domestication of rice, grapes and other crops (Zhou et al. 2017 PNAS; Liu et al. 2017 MBE). With the influence of domestication bottlenecks and the hitchhiking effects, a large number of deleterious variants retained in crop genomes, which reduces (or potentially reduces) the fitness of crops, and therefore becomes a new direction of crop molecular breeding (Gaut et al. 2018, Nature Plants). Such deleterious variants include point SNPs, small insertions and deletions (Indel) and structural variation (SV, > 50bp; Zhou et al. 2019 Nature Plants). Due to technical bottlenecks and other factors, early research mainly focused on SNP and Indel. For the first time, we have studied the population genetics of structural variation in grape and rice domestication, revealing that most structural variations are under strong purifying selection, and inversion is the strongest (Zhou et al. 2019 Nature Plants).  Transposable element (TE) is the dominant component of structural variation in plant genomes. In rice and grapes, we have revealed for the first time that different TE families are under different purifying selection. Among them, SINE was under the strongest purifying selection (Kou et al. al. 2020 MBE). Structural variation affects phenotypes associated with crop agronomic traits, including the sex determination and berry color of grapes (Zhou et al. 2019 Nature Plants), and rice resistance to flooding (Kou et al. 2020 MBE).

　　

　　Selected Publications（*corresponding author）　

　　1. Kou Y, Liao Y, Toivainen T, Lv Y, Tian X, Emerson JJ, Gaut BS*, Zhou YF*. 2020. Evolutionary genomics of structural variation in Asian rice (Oryza sativa) domestication. Molecular Biology and Evolution 37:3507–3524.

        2. Zhou YF*, Gaut BS*. 2020. Large chromosomal variants drive adaptation in sunflowers. Nature Plants 6:734–735. 

        3. Zhou YF, Minio A, Solares E, Lyu Y, Cantu D*, Gaut BS* (2019) Population genetics of structural variation in grapevine domestication. Nature Plants, 5, 965–979.

        4. Zhou YF, Muyle A, Gaut BS* (2019) Evolutionary Genomics and the Domestication of Grapes. The Grape Genome, Dario Cantu and M. Andrew Walker (Eds).

        5. Gaut BS, Seymour D, Liu QP, Zhou YF* (2018) Demography and its effects on genomic variation in crop domestication. Nature Plants 4: 512–520.

        6. Zhou YF, Massonnet M, Sanjak J, Cantu D, Gaut BS* (2017) Evolutionary genomics of grape (Vitis vinifera ssp. vinifera) domestication. PNAS 114: 11715-11720.

        7. Liu QP, Zhou YF, Morrell P, Gaut BS* (2017) Deleterious variants in Asian rice and the potential cost of domestication. Molecular Biology and Evolution 34: 908-924.

        8. Zhou YF, Duvaux L, Ren G, Zhang LR, Savolainen O, Liu J* (2017) Importance of incomplete lineage sorting and introgression in the origin of shared genetic variation between two closely related pines with overlapping distributions. Heredity 118: 211-220.

        9. Zhou YF, Zhang LR, Liu JQ, Wu GL, Savolainen O* (2014) Climatic adaptation and ecological divergence between two closely related pines species in Southeast China. Molecular Ecology 23: 3504–3522.

        10. Zhou YF (2014) Demographic history and climatic adaptation in ecological divergence between two closely related parapatric pine species. Acta Universitatis Ouluensis. A, Scientiae rerum naturalium, ISSN: 0355-3191.

        11. Zhou YF, Abbott RJ, Jiang ZY, Du, FK, Milne RI, Liu JQ (2010) Gene flow and species delimitation: a case study of two pine species with overlapping distributions in southeast China. Evolution 64: 2342- 2352.