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系统发育基因组学分析揭示后生动物促性腺激素释放激素及其受体的古老起源

Ancient origins of metazoan gonadotropin-releasing hormone and their receptors revealed by phylogenomic analyses.

作者信息

Plachetzki David C, Tsai Pei-San, Kavanaugh Scott I, Sower Stacia A

机构信息

Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA.

Department of Integrative Physiology, University of Colorado, Boulder, CO 80301, USA.

出版信息

Gen Comp Endocrinol. 2016 Aug 1;234:10-9. doi: 10.1016/j.ygcen.2016.06.007. Epub 2016 Jun 16.

DOI:10.1016/j.ygcen.2016.06.007
PMID:27318276
Abstract

The discovery of genes related to gonadotropin-releasing hormones (GnRH) and their receptors from diverse species has driven important advances in comparative endocrinology. However, our view of the evolutionary histories and nomenclature of these gene families has become inconsistent as several different iterations of GnRH and receptor relationships have been proposed. Whole genome sequence data are now available for most of the major lineages of animals, and an exhaustive view of the phylogenies of GnRH and their receptors is now possible. In this paper, we leverage data from publically available whole genome sequences to present a new phylogenomic analysis of GnRH and GnRH receptors and the distant relatives of each across metazoan phylogeny. Our approach utilizes a phylogenomics pipeline that searches data from 36 whole genome sequences and conducts phylogenetic analyses of gene trees. We provide a comprehensive analysis of the major groupings of GnRH peptides, related hormones and their receptors and provide some suggestions for a new nomenclature. Our study provides a framework for understanding the functional diversification of this family of neuromodulatory peptides and their receptors.

摘要

从不同物种中发现与促性腺激素释放激素(GnRH)及其受体相关的基因,推动了比较内分泌学的重要进展。然而,随着GnRH与受体关系的几种不同迭代被提出,我们对这些基因家族进化历史和命名法的看法变得不一致。现在大多数主要动物谱系都有全基因组序列数据,对GnRH及其受体的系统发育进行详尽分析成为可能。在本文中,我们利用公开可用的全基因组序列数据,对GnRH和GnRH受体及其在后生动物系统发育中的远亲进行新的系统基因组分析。我们的方法使用了一个系统基因组流程,该流程搜索来自36个全基因组序列的数据,并对基因树进行系统发育分析。我们对GnRH肽、相关激素及其受体的主要分组进行了全面分析,并为新的命名法提出了一些建议。我们的研究为理解这一神经调节肽及其受体家族的功能多样化提供了一个框架。

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