Identification and characterization of the CONSTANS (CO)/CONSTANS-like (COL) genes related to photoperiodic signaling and flowering in tomato

生物 基因 龙葵 基因座(遗传学) 遗传学 拟南芥 基因组 植物 突变体
作者
Tongwen Yang,Yu He,Shaobo Niu,Siwei Yan,Yan Zhang
出处
期刊:Plant Science [Elsevier BV]
卷期号:301: 110653-110653 被引量:56
标识
DOI:10.1016/j.plantsci.2020.110653
摘要

CO is an important regulator of photoperiodic response and flowering. However, the biological functions of CO and COL genes in tomato (Solanum lycopersicum) remain elusive. Here we identified 13 members in CO/COL family from the tomato genome. They were divided into three groups, and each group had specific characteristics in gene structures and protein domains. The SlCO/SlCOL genes showed different tissue-specific expression patterns and circadian rhythms, indicating their functional diversity in tomato. Moreover, among 13 members, the expression of SlCOL, SlCOL4a, and SlCOL4b was negatively correlated with flowering time variation in ten tomato lines. Through interaction network prediction, we found three FLOWERING LOCUS T (FT) orthologs, SINGLE FLOWER TRUSS (SFT), FT-like (FTL), and FT-like 1 (FTL1), which functioned as candidate interactors of SlCOL, SlCOL4a, and SlCOL4b. Further expression analyses suggested that SFT coincided with the three SlCOL genes in ten tomato lines with varied flowering time. These findings implied that SlCOL, SlCOL4a, and SlCOL4b are potential flowering inducers in tomato, and SFT may act as their downstream target. Thus, our study built a foundation for understanding the precise roles of SlCO/SlCOL family in plant growth and development of tomato, especially in flowering.
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
英姑应助心灵美的小海豚采纳,获得10
刚刚
搜集达人应助okok采纳,获得10
刚刚
DOC_XIONG应助君无双采纳,获得10
刚刚
无花果应助Anhan采纳,获得10
1秒前
妙蛙完成签到 ,获得积分10
1秒前
WL发布了新的文献求助10
1秒前
2秒前
大水杯子完成签到,获得积分10
2秒前
Do神发布了新的文献求助10
2秒前
orixero应助迅速的蜗牛采纳,获得10
3秒前
3秒前
小巧的师发布了新的文献求助20
4秒前
4秒前
那就发个呆完成签到,获得积分10
4秒前
4秒前
Echo完成签到 ,获得积分10
4秒前
无花果应助地形图采纳,获得10
4秒前
旦皋完成签到 ,获得积分10
5秒前
yao完成签到,获得积分10
5秒前
5秒前
芽芽发布了新的文献求助10
5秒前
growth发布了新的文献求助10
5秒前
5秒前
6秒前
mialabulula发布了新的文献求助10
6秒前
刘zx完成签到,获得积分10
6秒前
Cookies完成签到,获得积分10
6秒前
wanci应助always采纳,获得10
6秒前
ao完成签到,获得积分10
6秒前
认真的蜜粉完成签到,获得积分10
7秒前
7秒前
伊尔发布了新的文献求助10
8秒前
8秒前
Huang驳回了烟花应助
8秒前
香蕉觅云应助天天采纳,获得10
8秒前
666发布了新的文献求助10
8秒前
8秒前
原伯完成签到,获得积分10
9秒前
大苏子哥哥完成签到,获得积分10
9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
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
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Moody's Ratings Rising AI spending narrows the gap, but US hyperscalers retain edge over Chinese peers 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 7695062
求助须知:如何正确求助?哪些是违规求助? 9255537
关于积分的说明 19997301
捐赠科研通 7269262
什么是DOI,文献DOI怎么找? 3292271
关于科研通互助平台的介绍 2448147
邀请新用户注册赠送积分活动 2297850