Human embryonic stem cells(hESCs)can be classified as having naive and primed pluripotency states.While several studies have reported different gene expression networks between these two pluripotency states,the role o...Human embryonic stem cells(hESCs)can be classified as having naive and primed pluripotency states.While several studies have reported different gene expression networks between these two pluripotency states,the role of alternative splicing(AS)in regulating these differences has not been well characterized.In this study,we performed RNA sequencing and identified differential AS events in 784 genes between naive and primed hESCs.Among these,KIAA1522,whose function has not been well studied,has state-specific isoforms regulated by alternative first exon(AFE).This splicing event resulted in isoforms with distinct N-terminal domains and subcellular localization.Notably,the sequences and alternative isoform patterns of KIAA1522 were conserved between humans and mice.Further investigation using cleavage under targets and tagmentation(CUT&Tag)experiments in cells with specific-isoform overexpression or knockdown revealed the opposite activity of long terminal repeat retrotransposons(LTR-RTs)and motif enrichment profiles.The naive-specific(N-P)isoform upregulated naive marker gene expression and preferentially activated LTR-RTs by binding to the motifs enriched for POU and FOX family transcription factor binding sites.Conversely,the primed-specific(P-P)isoform promoted primed marker gene expression and suppressed LTR-RTs activity by binding to the motifs enriched for zinc finger protein binding sites.Collectively,KIAA1522 regulates the balance between naive and primed pluripotency states through isoform-specific regulation of LTR-RTs activity and collaboration with distinct transcriptional regulators.In summary,our results characterize the splicing atlas of hESCs in naive and primed states and reveal the regulatory function and mechanism of AFE usage by KIAA1522.展开更多
Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revoluti...Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.展开更多
基金supported by the National Key Research and Development Program of China(2023YFA1802000,2022YFA1104100,2018YFA0109700,2018YFE0201102,2019YFA0110000)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA16010503)+4 种基金the Youth Innovation Promotion Association,CAS(Y2023020)the National Natural Science Foundation of China(62127811)Strategic Collaborative Research Program of the Ferring Institute of Reproductive Medicine,Ferring Pharmaceuticals,Chinese Academy of Sciences(FIRMD181101)Informatization Plan of Chinese Academy of Sciences(CAS-WX2021SF-0101)Initiative Scientific Research Program,Institute of Zoology,Chinese Academy of Sciences(2023IOZ0302)。
文摘Human embryonic stem cells(hESCs)can be classified as having naive and primed pluripotency states.While several studies have reported different gene expression networks between these two pluripotency states,the role of alternative splicing(AS)in regulating these differences has not been well characterized.In this study,we performed RNA sequencing and identified differential AS events in 784 genes between naive and primed hESCs.Among these,KIAA1522,whose function has not been well studied,has state-specific isoforms regulated by alternative first exon(AFE).This splicing event resulted in isoforms with distinct N-terminal domains and subcellular localization.Notably,the sequences and alternative isoform patterns of KIAA1522 were conserved between humans and mice.Further investigation using cleavage under targets and tagmentation(CUT&Tag)experiments in cells with specific-isoform overexpression or knockdown revealed the opposite activity of long terminal repeat retrotransposons(LTR-RTs)and motif enrichment profiles.The naive-specific(N-P)isoform upregulated naive marker gene expression and preferentially activated LTR-RTs by binding to the motifs enriched for POU and FOX family transcription factor binding sites.Conversely,the primed-specific(P-P)isoform promoted primed marker gene expression and suppressed LTR-RTs activity by binding to the motifs enriched for zinc finger protein binding sites.Collectively,KIAA1522 regulates the balance between naive and primed pluripotency states through isoform-specific regulation of LTR-RTs activity and collaboration with distinct transcriptional regulators.In summary,our results characterize the splicing atlas of hESCs in naive and primed states and reveal the regulatory function and mechanism of AFE usage by KIAA1522.
文摘Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.
