Too much of a good thing? Finding the most informative genetic data set to answer conservation questions

生物 保护遗传学 遗传多样性 人口 进化生物学 背景(考古学) 濒危物种 微卫星 群体遗传学 遗传学 生态学 等位基因 基因 社会学 人口学 古生物学 栖息地
作者
Elspeth A. McLennan,Belinda Wright,Katherine Belov,Carolyn J. Hogg,Catherine E. Grueber
出处
期刊:Molecular Ecology Resources [Wiley]
卷期号:19 (3): 659-671 被引量:24
标识
DOI:10.1111/1755-0998.12997
摘要

Abstract Molecular markers are a useful tool allowing conservation and population managers to shed light on genetic processes affecting threatened populations. However, as technological advancements in molecular techniques continue to evolve, conservationists are frequently faced with new genetic markers, each with nuanced variation in their characteristics as well as advantages and disadvantages for informing various questions. We used a well‐studied population of Tasmanian devils ( Sarcophilus harrisii ) from Maria Island, Tasmania, to illustrate the issues associated with combining multiple genetic data sets and to help answer a question posed by many population managers: which data set will provide the most precise and accurate estimates of the population processes we are trying to measure? We analysed individual heterozygosity (as internal relatedness, IR) of 96 individuals, calculated using four genetic marker types (putatively neutral microsatellites, major histocompatibility complex‐linked microsatellites, reduced representation sequencing, and candidate region resequencing). We found no correlation in IR values across marker types, suggesting that various genetic markers reflect different aspects of genomic diversity. In addition, some marker types were more informative than others for conservation decision‐making. Reduced representation sequencing provided the highest precision (lowest error) for estimating population‐level genetic diversity, and most closely reflected genome‐wide heterozygosity both theoretically and empirically. Within the conservation context, our results highlight important considerations when choosing a molecular technique for wildlife genetics.

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
1秒前
星辰大海应助朴素的夏云采纳,获得10
2秒前
可爱的函函应助若清采纳,获得10
3秒前
从容友琴完成签到,获得积分10
3秒前
Repher发布了新的文献求助10
3秒前
jiaaa关注了科研通微信公众号
3秒前
所所应助若清采纳,获得10
3秒前
xm发布了新的文献求助20
3秒前
Grace完成签到 ,获得积分10
4秒前
冷酷的芷蝶完成签到,获得积分10
5秒前
5秒前
Orange应助zzq采纳,获得10
7秒前
彭于晏应助个性的雪旋采纳,获得10
7秒前
7秒前
9秒前
狐狸完成签到,获得积分10
10秒前
龚瞩发布了新的文献求助30
11秒前
13秒前
14秒前
334niubi666完成签到 ,获得积分10
16秒前
hunter完成签到 ,获得积分10
16秒前
江亭发布了新的文献求助10
16秒前
18秒前
19秒前
简单完成签到,获得积分10
20秒前
zzq发布了新的文献求助10
20秒前
20秒前
缥缈的剑完成签到,获得积分10
20秒前
咕噜咕噜发布了新的文献求助10
20秒前
aam完成签到,获得积分10
21秒前
21秒前
21秒前
斯文的晓绿完成签到 ,获得积分10
21秒前
lsx666完成签到,获得积分10
22秒前
奋斗绿凝完成签到,获得积分20
22秒前
22秒前
周不是舟发布了新的文献求助10
23秒前
24秒前
25秒前
xu发布了新的文献求助10
25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
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 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 7714475
求助须知:如何正确求助?哪些是违规求助? 9269787
关于积分的说明 20078765
捐赠科研通 7290854
什么是DOI,文献DOI怎么找? 3298178
关于科研通互助平台的介绍 2452416
邀请新用户注册赠送积分活动 2305538