Suppr超能文献

HERVL人类内源性逆转录病毒的进化与亚科

Evolution and subfamilies of HERVL human endogenous retrovirus.

作者信息

Zhang Huan, Frith Martin C

机构信息

Department of Computational Biology and Medical Sciences, University of Tokyo, Chiba 277-8561, Japan.

Artificial Intelligence Research Center, AIST, Tokyo 135-0064, Japan.

出版信息

Bioinform Adv. 2024 Jul 30;4(1):vbae110. doi: 10.1093/bioadv/vbae110. eCollection 2024.

Abstract

BACKGROUND

Endogenous retroviruses (ERVs), which blur the boundary between virus and transposable element, are genetic material derived from retroviruses and have important implications for evolution. This study examines the diversity and evolution of human endogenous retroviruses (HERVs) of the HERVL family, which has long terminal repeats (LTRs) named MLT2.

RESULTS

By probability-based sequence comparison, we uncover systematic annotation errors that conceal the true complexity and diversity of transposable elements (TEs) in the human genome. Our analysis identifies new subfamilies within the MLT2 group, proposes a refined classification scheme, and constructs new consensus sequences. We present an evolutionary analysis including phylogenetic trees that elucidate the relationships between these subfamilies and their contributions to human evolution. The results underscore the significance of accurate TE annotation in understanding genome evolution, highlighting the potential for misclassified TEs to impact interpretations of genomic studies.

AVAILABILITY AND IMPLEMENTATION

Not applicable.

摘要

背景

内源性逆转录病毒(ERVs)模糊了病毒与转座元件之间的界限,是源自逆转录病毒的遗传物质,对进化具有重要意义。本研究考察了人类内源性逆转录病毒(HERVs)中HERVL家族的多样性和进化,该家族具有名为MLT2的长末端重复序列(LTRs)。

结果

通过基于概率的序列比较,我们发现了系统性注释错误,这些错误掩盖了人类基因组中转座元件(TEs)的真正复杂性和多样性。我们的分析在MLT2组内鉴定出了新的亚家族,提出了一种改进的分类方案,并构建了新的共有序列。我们进行了一项进化分析,包括系统发育树,阐明了这些亚家族之间的关系及其对人类进化的贡献。结果强调了准确的TE注释在理解基因组进化中的重要性,突出了错误分类的TEs影响基因组研究解释的可能性。

可用性和实施

不适用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f0/11319637/3908c2b94d1d/vbae110f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验