five

Data from: Neutral and adaptive genomic signatures of rapid poleward range expansion

收藏
DataONE2015-11-09 更新2024-06-27 收录
下载链接:
https://search.dataone.org/view/null
下载链接
链接失效反馈
资源简介:
Many species are expanding their range polewards and this has been associated with rapid phenotypic change. Yet, it is unclear to what extent this reflects rapid genetic adaptation or neutral processes associated with range expansion, or selection linked to the new thermal conditions encountered. To disentangle these alternatives, we studied the genomic signature of range expansion in the damselfly Coenagrion scitulum using 4950 newly developed genomic SNPs and linked this to the rapidly evolved phenotypic differences between core and (newly established) edge populations. Most edge populations were genetically clearly differentiated from the core populations and all were differentiated from each other indicating independent range expansion events. In addition, evidence for genetic drift in the edge populations, and strong evidence for adaptive genetic variation in association with the range expansion was detected. We identified one SNP under consistent selection in four of the five edge populations and showed that the allele increasing in frequency is associated with increased flight performance. This indicates collateral, non-neutral evolutionary changes in independent edge populations driven by the range expansion process. We also detected a genomic signature of adaptation to the newly encountered thermal regimes, reflecting a pattern of countergradient variation. The latter signature was identified at a single SNP as well as in a set of covarying SNPs using a polygenic multilocus approach to detect selection. Overall, this study highlights how a strategic geographic sampling design and the integration of genomic, phenotypic and environmental data can identify and disentangle the neutral and adaptive processes that are simultaneously operating during range expansions.
创建时间:
2015-11-09
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

OECD Statistics

OECD Statistics 数据集包含了经济合作与发展组织(OECD)发布的各种统计数据,涵盖了经济、社会、环境、教育、科技等多个领域。数据集提供了详细的指标和时间序列数据,帮助研究人员和政策制定者分析和理解全球经济和社会发展趋势。

stats.oecd.org 收录

学生课堂行为数据集 (SCB-dataset3)

学生课堂行为数据集(SCB-dataset3)由成都东软学院创建,包含5686张图像和45578个标签,重点关注六种行为:举手、阅读、写作、使用手机、低头和趴桌。数据集覆盖从幼儿园到大学的不同场景,通过YOLOv5、YOLOv7和YOLOv8算法评估,平均精度达到80.3%。该数据集旨在为学生行为检测研究提供坚实基础,解决教育领域中学生行为数据集的缺乏问题。

arXiv 收录

The MaizeGDB

The MaizeGDB(Maize Genetics and Genomics Database)是一个专门为玉米(Zea mays)基因组学研究提供数据和工具的在线资源。该数据库包含了玉米的基因组序列、基因注释、遗传图谱、突变体信息、表达数据、以及与玉米相关的文献和研究工具。MaizeGDB旨在支持玉米遗传学和基因组学的研究,为科学家提供了一个集成的平台来访问和分析玉米的遗传和基因组数据。

www.maizegdb.org 收录

AIS数据集

该研究使用了多个公开的AIS数据集,这些数据集经过过滤、清理和统计分析。数据集涵盖了多种类型的船舶,并提供了关于船舶位置、速度和航向的关键信息。数据集包括来自19,185艘船舶的AIS消息,总计约6.4亿条记录。

github 收录

ShapeNet

ShapeNet 是由斯坦福大学、普林斯顿大学和美国芝加哥丰田技术研究所的研究人员开发的大型 3D CAD 模型存储库。该存储库包含超过 3 亿个模型,其中 220,000 个模型被分类为使用 WordNet 上位词-下位词关系排列的 3,135 个类。 ShapeNet Parts 子集包含 31,693 个网格,分为 16 个常见对象类(即桌子、椅子、平面等)。每个形状基本事实包含 2-5 个部分(总共 50 个部分类)。

OpenDataLab 收录