Phased genomics reveals hidden somatic mutations and provides insight into fruit development in sweet orange

生物 基因组学 基因组 体细胞 遗传学 倍性 参考基因组 种系突变 等位基因 突变 基因
作者
Nan Wang,Peng Chen,Yuanyuan Xu,Ling-Xia Guo,Xianxin Li,Hualin Yi,Robert M. Larkin,Yongfeng Zhou,Xiuxin Deng,Qiang Xu
出处
期刊:Horticulture research [Springer Nature]
卷期号:11 (2) 被引量:2
标识
DOI:10.1093/hr/uhad268
摘要

Abstract Although revisiting the discoveries and implications of genetic variations using phased genomics is critical, such efforts are still lacking. Somatic mutations represent a crucial source of genetic diversity for breeding and are especially remarkable in heterozygous perennial and asexual crops. In this study, we focused on a diploid sweet orange (Citrus sinensis) and constructed a haplotype-resolved genome using high fidelity (HiFi) reads, which revealed 10.6% new sequences. Based on the phased genome, we elucidate significant genetic admixtures and haplotype differences. We developed a somatic detection strategy that reveals hidden somatic mutations overlooked in a single reference genome. We generated a phased somatic variation map by combining high-depth whole-genome sequencing (WGS) data from 87 sweet orange somatic varieties. Notably, we found twice as many somatic mutations relative to a single reference genome. Using these hidden somatic mutations, we separated sweet oranges into seven major clades and provide insight into unprecedented genetic mosaicism and strong positive selection. Furthermore, these phased genomics data indicate that genomic heterozygous variations contribute to allele-specific expression during fruit development. By integrating allelic expression differences and somatic mutations, we identified a somatic mutation that induces increases in fruit size. Applications of phased genomics will lead to powerful approaches for discovering genetic variations and uncovering their effects in highly heterozygous plants. Our data provide insight into the hidden somatic mutation landscape in the sweet orange genome, which will facilitate citrus breeding.
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
刚刚
研友_LXdbaL发布了新的文献求助30
刚刚
思源应助单薄新烟采纳,获得10
1秒前
1秒前
2秒前
Zz完成签到,获得积分10
2秒前
Prandtl完成签到 ,获得积分10
4秒前
5秒前
zfzf0422完成签到 ,获得积分10
6秒前
上官若男应助jackie采纳,获得10
6秒前
6秒前
我是站长才怪应助Benliu采纳,获得20
7秒前
7秒前
zh20130完成签到,获得积分10
7秒前
7秒前
TT发布了新的文献求助10
8秒前
Star1983发布了新的文献求助10
8秒前
研友_LXdbaL完成签到,获得积分10
9秒前
10秒前
在水一方应助66采纳,获得10
11秒前
11秒前
11秒前
缘一发布了新的文献求助10
12秒前
junzilan发布了新的文献求助10
13秒前
CipherSage应助赖道之采纳,获得10
14秒前
ccc完成签到,获得积分10
14秒前
14秒前
14秒前
17秒前
Pauline完成签到,获得积分10
19秒前
jackie发布了新的文献求助10
19秒前
笨笨摇伽发布了新的文献求助10
21秒前
科目三应助皓月繁星采纳,获得10
21秒前
tomato完成签到,获得积分20
23秒前
CodeCraft应助缘一采纳,获得10
24秒前
小二郎应助刘铭晨采纳,获得10
24秒前
24秒前
大个应助风雨1210采纳,获得10
24秒前
一壶清酒完成签到,获得积分10
24秒前
25秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808