Insights into gene tissue specificity and protein–protein interactions in the context of purifying selection in humans

IF 1 4区生物学 Q4 GENETICS & HEREDITY

Annals of Human Genetics Pub Date : 2023-01-27 DOI:10.1111/ahg.12497

Massimo Mezzavilla, Massimiliano Cocca

{"title":"Insights into gene tissue specificity and protein–protein interactions in the context of purifying selection in humans","authors":"Massimo Mezzavilla, Massimiliano Cocca","doi":"10.1111/ahg.12497","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>How much are natural selection and gene characteristics, such as the number of protein-protein interactions (PPIs), tissue specificity (𝞽), and expression level, connected?</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>In order to investigate these relationships, we combined different metrics linked to genetic constraints and analyzed their distribution concerning PPIs, 𝞽 and expression levels.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>We discovered a positive correlation between genetic constraints, PPIs, and expression levels in all tissues. On the other hand, we obtained a negative correlation between genetic constraints and 𝞽. Furthermore, the fraction of variance in PPI and 𝞽 explained by the constraints metrics is around 6% and 10%, respectively.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>We observed that the variance of expression of tissue-specific genes seems not related to their level of selection constraints, which is the opposite of what is found on non-tissue-specific genes. Overall these observations would help to elucidate the relationship between natural selection and gene features.</p>\n </section>\n </div>","PeriodicalId":8085,"journal":{"name":"Annals of Human Genetics","volume":"87 1-2","pages":"75-79"},"PeriodicalIF":1.0000,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Human Genetics","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ahg.12497","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}

引用次数: 0

Abstract

Background

How much are natural selection and gene characteristics, such as the number of protein-protein interactions (PPIs), tissue specificity (𝞽), and expression level, connected?

Methods

In order to investigate these relationships, we combined different metrics linked to genetic constraints and analyzed their distribution concerning PPIs, 𝞽 and expression levels.

Results

We discovered a positive correlation between genetic constraints, PPIs, and expression levels in all tissues. On the other hand, we obtained a negative correlation between genetic constraints and 𝞽. Furthermore, the fraction of variance in PPI and 𝞽 explained by the constraints metrics is around 6% and 10%, respectively.

Conclusions

We observed that the variance of expression of tissue-specific genes seems not related to their level of selection constraints, which is the opposite of what is found on non-tissue-specific genes. Overall these observations would help to elucidate the relationship between natural selection and gene features.

查看原文本刊更多论文

在人类净化选择的背景下，深入了解基因组织特异性和蛋白质-蛋白质相互作用

自然选择和基因特征，如蛋白-蛋白相互作用(PPIs)的数量、组织特异性(𝞽)和表达水平之间有多大的联系?方法为了研究这些关系，我们结合了与遗传约束相关的不同指标，并分析了它们在ppi、𝞽和表达水平方面的分布。结果在所有组织中，我们发现遗传约束、PPIs和表达水平呈正相关。另一方面，我们得到了遗传约束与𝞽之间的负相关。此外，由约束指标解释的PPI和𝞽的方差比例分别约为6%和10%。我们观察到，组织特异性基因的表达差异似乎与它们的选择约束水平无关，而非组织特异性基因的表达差异则相反。总的来说，这些观察结果将有助于阐明自然选择和基因特征之间的关系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Annals of Human Genetics 生物-遗传学

CiteScore

4.20

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.