Reliable DNA Barcoding Performance Proved for Species and Island Populations of Comoran Squamate Reptiles

作者
Oliver Hawlitschek,Zoltán T. Nagy,Johannes Berger,Frank Glaw
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:8 (9): e73368-e73368 被引量:35
标识
DOI:10.1371/journal.pone.0073368
摘要

In the past decade, DNA barcoding became increasingly common as a method for species identification in biodiversity inventories and related studies. However, mainly due to technical obstacles, squamate reptiles have been the target of few barcoding studies. In this article, we present the results of a DNA barcoding study of squamates of the Comoros archipelago, a poorly studied group of oceanic islands close to and mostly colonized from Madagascar. The barcoding dataset presented here includes 27 of the 29 currently recognized squamate species of the Comoros, including 17 of the 18 endemic species. Some species considered endemic to the Comoros according to current taxonomy were found to cluster with non-Comoran lineages, probably due to poorly resolved taxonomy. All other species for which more than one barcode was obtained corresponded to distinct clusters useful for species identification by barcoding. In most species, even island populations could be distinguished using barcoding. Two cryptic species were identified using the DNA barcoding approach. The obtained barcoding topology, a Bayesian tree based on COI sequences of 5 genera, was compared with available multigene topologies, and in 3 cases, major incongruences between the two topologies became evident. Three of the multigene studies were initiated after initial screening of a preliminary version of the barcoding dataset presented here. We conclude that in the case of the squamates of the Comoros Islands, DNA barcoding has proven a very useful and efficient way of detecting isolated populations and promising starting points for subsequent research.

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
小米完成签到,获得积分10
刚刚
程志强完成签到 ,获得积分10
1秒前
笑点低的凉面完成签到,获得积分10
2秒前
Susan完成签到,获得积分10
3秒前
香蕉小凡完成签到 ,获得积分10
7秒前
8秒前
kyt_vip完成签到,获得积分10
10秒前
绿竹涛完成签到 ,获得积分10
11秒前
杨杨杨完成签到 ,获得积分10
13秒前
寒冷怜南发布了新的文献求助10
13秒前
偏偏完成签到 ,获得积分10
14秒前
15秒前
绚烂无比的猫完成签到 ,获得积分10
20秒前
XF完成签到 ,获得积分10
21秒前
落后的静曼完成签到,获得积分10
24秒前
想笑的老锅完成签到,获得积分10
27秒前
古月完成签到,获得积分10
28秒前
28秒前
江淮行完成签到,获得积分10
30秒前
小水蜜桃发布了新的文献求助10
32秒前
deng完成签到 ,获得积分10
33秒前
kaiz完成签到,获得积分10
34秒前
共享精神应助科研通管家采纳,获得10
35秒前
sunnyqqz完成签到,获得积分10
35秒前
35秒前
ygmygqdss完成签到 ,获得积分10
36秒前
Xueyu完成签到,获得积分10
40秒前
SilentLight完成签到,获得积分10
46秒前
ilk666完成签到,获得积分10
47秒前
小呵点完成签到 ,获得积分10
47秒前
有终完成签到 ,获得积分10
51秒前
竹签子完成签到 ,获得积分10
51秒前
小伟完成签到,获得积分10
54秒前
Yangyang完成签到,获得积分10
54秒前
小杨完成签到,获得积分10
57秒前
甜美千山完成签到 ,获得积分10
59秒前
1分钟前
zz6532完成签到 ,获得积分10
1分钟前
研友_Z1eDgZ完成签到,获得积分10
1分钟前
翻斗花园李元芳完成签到,获得积分10
1分钟前
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
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Health Psychology 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 500
Electric machines: theory, operating applications, and controls 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 7598332
求助须知:如何正确求助?哪些是违规求助? 9174778
关于积分的说明 19640877
捐赠科研通 7174706
什么是DOI,文献DOI怎么找? 3268256
关于科研通互助平台的介绍 2432872
邀请新用户注册赠送积分活动 2261686