{"title":"Coexpression enhances cross-species integration of single-cell RNA sequencing across diverse plant species","authors":"Michael John Passalacqua, Jesse Gillis","doi":"10.1038/s41477-024-01738-4","DOIUrl":null,"url":null,"abstract":"Single-cell RNA sequencing is increasingly used to investigate cross-species differences driven by gene expression and cell-type composition in plants. However, the frequent expansion of plant gene families due to whole-genome duplications makes identification of one-to-one orthologues difficult, complicating integration. Here we demonstrate that coexpression can be used to trim many-to-many orthology families down to identify one-to-one gene pairs with proxy expression profiles, improving the performance of traditional integration methods and reducing barriers to integration across a diverse array of plant species. To enhance cross-species single-cell analysis, the authors find gene pairs with similar expression patterns across 13 species. These coexpression proxies serve as common features in datasets, improving integrative and comparative cell-type analysis.","PeriodicalId":18904,"journal":{"name":"Nature Plants","volume":null,"pages":null},"PeriodicalIF":15.8000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41477-024-01738-4.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Plants","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41477-024-01738-4","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Single-cell RNA sequencing is increasingly used to investigate cross-species differences driven by gene expression and cell-type composition in plants. However, the frequent expansion of plant gene families due to whole-genome duplications makes identification of one-to-one orthologues difficult, complicating integration. Here we demonstrate that coexpression can be used to trim many-to-many orthology families down to identify one-to-one gene pairs with proxy expression profiles, improving the performance of traditional integration methods and reducing barriers to integration across a diverse array of plant species. To enhance cross-species single-cell analysis, the authors find gene pairs with similar expression patterns across 13 species. These coexpression proxies serve as common features in datasets, improving integrative and comparative cell-type analysis.
期刊介绍:
Nature Plants is an online-only, monthly journal publishing the best research on plants — from their evolution, development, metabolism and environmental interactions to their societal significance.