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对X和Y染色体转录组的分析突出了生殖驱动基因。

Analysis of and X and Y chromosome transcriptome highlights reproductive driver genes.

作者信息

Khan Faheem Ahmed, Liu Hui, Zhou Hao, Wang Kai, Qamar Muhammad Tahir Ul, Pandupuspitasari Nuruliarizki Shinta, Shujun Zhang

机构信息

Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education China, College of Animal Science and Technology Huazhong Agricultural University, Wuhan, China.

College of Informatics, Huazhong Agricultural University, Wuhan, China.

出版信息

Oncotarget. 2017 Apr 13;8(33):54416-54433. doi: 10.18632/oncotarget.17081. eCollection 2017 Aug 15.

Abstract

The biology of sperm, its capability of fertilizing an egg and its role in sex ratio are the major biological questions in reproductive biology. To answer these question we integrated X and Y chromosome transcriptome across different species: and and identified reproductive driver genes based on Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. Our strategy resulted in 11007 and 10445 unique genes consisting of 9 and 11 reproductive modules in and , respectively. The consensus module calculation yields an overall 167 overlapped genes which were mapped to 846 DEGs in to finally get a list of 67 dual feature genes. We develop gene co-expression network of selected 67 genes that consists of 58 nodes (27 down-regulated and 31 up-regulated genes) enriched to 66 GO biological process (BP) including 6 GO annotations related to reproduction and two KEGG pathways. Moreover, we searched significantly related TF (ISRE, AP1FJ, RP58, CREL) and miRNAs (bta-miR-181a, bta-miR-17-5p, bta-miR-146b, bta-miR-146a) which targeted the genes in co-expression network. In addition we performed genetic analysis including phylogenetic, functional domain identification, epigenetic modifications, mutation analysis of the most important reproductive driver genes PRM1, PPP2R2B and PAFAH1B1 and finally performed a protein docking analysis to visualize their therapeutic and gene expression regulation ability.

摘要

精子的生物学特性、其使卵子受精的能力以及在性别比例中的作用是生殖生物学中的主要生物学问题。为了回答这些问题,我们整合了不同物种的X和Y染色体转录组,并基于加权基因共表达网络分析(WGCNA)算法鉴定了生殖驱动基因。我们的策略在[具体物种1]和[具体物种2]中分别产生了11007个和10445个独特基因,分别由9个和11个生殖模块组成。共识模块计算产生了总共167个重叠基因,这些基因被映射到[具体物种1]中的846个差异表达基因(DEG),最终得到了67个双特征基因的列表。我们构建了所选67个基因的基因共表达网络,该网络由58个节点(27个下调基因和31个上调基因)组成,富集到66个基因本体论(GO)生物学过程(BP),包括6个与生殖相关的GO注释和两个京都基因与基因组百科全书(KEGG)途径。此外,我们搜索了与共表达网络中的基因显著相关的转录因子(ISRE、AP1FJ、RP58、CREL)和微小RNA(bta-miR-181a、bta-miR-17-5p、bta-miR-146b、bta-miR-146a)。此外,我们进行了遗传分析,包括系统发育分析、功能域鉴定、表观遗传修饰、最重要的生殖驱动基因PRM1、PPP2R2B和PAFAH1B1的突变分析,最后进行了蛋白质对接分析,以可视化它们的治疗和基因表达调控能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4776/5589591/d4a59fa66749/oncotarget-08-54416-g001.jpg

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