The strength and pattern of natural selection on gene expression in rice

选择(遗传算法) 生物 基因 自然选择 基因表达 水稻 遗传学 表型 稳定选择 进化生物学 遗传变异 计算机科学 人工智能
作者
Simon C. Groen,Irina Ćalić,Zoé Joly‐Lopez,Adrian E. Platts,Jae Young Choi,Mignon A. Natividad,Katherine Dorph,William M. Mauck,Bernadette Bracken,Carlo L. U. Cabral,Arvind Kumar,Rolando O. Torres,Rahul Satija,Georgina V. Vergara,Amelia Henry,Steven J. Franks,Michael D. Purugganan
出处
期刊:Nature [Nature Portfolio]
卷期号:578 (7796): 572-576 被引量:147
标识
DOI:10.1038/s41586-020-1997-2
摘要

Levels of gene expression underpin organismal phenotypes1,2, but the nature of selection that acts on gene expression and its role in adaptive evolution remain unknown1,2. Here we assayed gene expression in rice (Oryza sativa)3, and used phenotypic selection analysis to estimate the type and strength of selection on the levels of more than 15,000 transcripts4,5. Variation in most transcripts appears (nearly) neutral or under very weak stabilizing selection in wet paddy conditions (with median standardized selection differentials near zero), but selection is stronger under drought conditions. Overall, more transcripts are conditionally neutral (2.83%) than are antagonistically pleiotropic6 (0.04%), and transcripts that display lower levels of expression and stochastic noise7-9 and higher levels of plasticity9 are under stronger selection. Selection strength was further weakly negatively associated with levels of cis-regulation and network connectivity9. Our multivariate analysis suggests that selection acts on the expression of photosynthesis genes4,5, but that the efficacy of selection is genetically constrained under drought conditions10. Drought selected for earlier flowering11,12 and a higher expression of OsMADS18 (Os07g0605200), which encodes a MADS-box transcription factor and is a known regulator of early flowering13-marking this gene as a drought-escape gene11,12. The ability to estimate selection strengths provides insights into how selection can shape molecular traits at the core of gene action.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
慕课魔芋完成签到,获得积分10
1秒前
烟花应助Marciu33采纳,获得10
2秒前
jack完成签到,获得积分10
2秒前
NexusExplorer应助疯狂的海白采纳,获得10
2秒前
2秒前
左丘冬寒完成签到,获得积分10
3秒前
4秒前
鱼头星星发布了新的文献求助10
4秒前
5秒前
xing_xing应助莫莫采纳,获得20
5秒前
5秒前
5秒前
mimi完成签到 ,获得积分10
5秒前
6秒前
小蘑菇应助风格采纳,获得30
6秒前
6秒前
6秒前
小葵完成签到,获得积分20
6秒前
6秒前
正直未来发布了新的文献求助10
7秒前
缪雨阳发布了新的文献求助20
7秒前
小草莓发布了新的文献求助10
7秒前
9秒前
冷静背包应助zheng-homes采纳,获得30
9秒前
上官若男应助小羊许个愿采纳,获得10
10秒前
10秒前
liu发布了新的文献求助50
11秒前
AHA发布了新的文献求助10
11秒前
端无完成签到,获得积分10
11秒前
天天快乐应助sunmenglinn采纳,获得10
12秒前
李nb发布了新的文献求助10
12秒前
小葵发布了新的文献求助10
12秒前
12秒前
leeso应助CCrain采纳,获得30
13秒前
寒冷的问晴完成签到,获得积分20
13秒前
小二郎应助科研通管家采纳,获得10
14秒前
XX应助科研通管家采纳,获得10
14秒前
小蘑菇应助科研通管家采纳,获得30
14秒前
14秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
A Study of the Model by which Principals’ Leadership Behaviour Influences Student Learning Outcomes in Elementary Schools 1000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7710635
求助须知:如何正确求助?哪些是违规求助? 9267286
关于积分的说明 20064620
捐赠科研通 7286829
什么是DOI,文献DOI怎么找? 3296983
关于科研通互助平台的介绍 2451488
邀请新用户注册赠送积分活动 2304020