{"title":"Computational methods for allele-specific expression in single cells.","authors":"Guanghao Qi, Alexis Battle","doi":"10.1016/j.tig.2024.07.003","DOIUrl":null,"url":null,"abstract":"<p><p>Allele-specific expression (ASE) is a powerful signal that can be used to investigate multiple molecular mechanisms, such as cis-regulatory effects and imprinting. Single-cell RNA-sequencing (scRNA-seq) enables ASE characterization at the resolution of individual cells. In this review, we highlight the computational methods for processing and analyzing single-cell ASE data. We first describe a bioinformatics pipeline to obtain ASE counts from raw reads synthesized from previous literature. We then discuss statistical methods for detecting allelic imbalance and its variability across conditions using scRNA-seq data. In addition, we describe other methods that use single-cell ASE to address specific biological questions. Finally, we discuss future directions and emphasize the need for an integrated, optimized bioinformatics pipeline, and further development of statistical methods for different technologies.</p>","PeriodicalId":54413,"journal":{"name":"Trends in Genetics","volume":null,"pages":null},"PeriodicalIF":13.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11537817/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tig.2024.07.003","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/10 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Allele-specific expression (ASE) is a powerful signal that can be used to investigate multiple molecular mechanisms, such as cis-regulatory effects and imprinting. Single-cell RNA-sequencing (scRNA-seq) enables ASE characterization at the resolution of individual cells. In this review, we highlight the computational methods for processing and analyzing single-cell ASE data. We first describe a bioinformatics pipeline to obtain ASE counts from raw reads synthesized from previous literature. We then discuss statistical methods for detecting allelic imbalance and its variability across conditions using scRNA-seq data. In addition, we describe other methods that use single-cell ASE to address specific biological questions. Finally, we discuss future directions and emphasize the need for an integrated, optimized bioinformatics pipeline, and further development of statistical methods for different technologies.
等位基因特异性表达(ASE)是一种强大的信号,可用于研究多种分子机制,如顺式调控效应和印记。单细胞 RNA 测序(scRNA-seq)可以在单个细胞的分辨率上描述 ASE 的特征。在本综述中,我们将重点介绍处理和分析单细胞 ASE 数据的计算方法。我们首先介绍了一种生物信息学管道,它能从以前文献合成的原始读数中获得 ASE 计数。然后,我们讨论了利用 scRNA-seq 数据检测等位基因不平衡及其在不同条件下的变异性的统计方法。此外,我们还介绍了利用单细胞 ASE 解决特定生物学问题的其他方法。最后,我们讨论了未来的发展方向,并强调了集成优化生物信息学管道的必要性,以及进一步开发适用于不同技术的统计方法的必要性。
期刊介绍:
Launched in 1985, Trends in Genetics swiftly established itself as a "must-read" for geneticists, offering concise, accessible articles covering a spectrum of topics from developmental biology to evolution. This reputation endures, making TiG a cherished resource in the genetic research community. While evolving with the field, the journal now embraces new areas like genomics, epigenetics, and computational genetics, alongside its continued coverage of traditional subjects such as transcriptional regulation, population genetics, and chromosome biology.
Despite expanding its scope, the core objective of TiG remains steadfast: to furnish researchers and students with high-quality, innovative reviews, commentaries, and discussions, fostering an appreciation for advances in genetic research. Each issue of TiG presents lively and up-to-date Reviews and Opinions, alongside shorter articles like Science & Society and Spotlight pieces. Invited from leading researchers, Reviews objectively chronicle recent developments, Opinions provide a forum for debate and hypothesis, and shorter articles explore the intersection of genetics with science and policy, as well as emerging ideas in the field. All articles undergo rigorous peer-review.