Mo Li, Xue Zeng, Chentian Jin, S. Jin, W. Dong, Martina Brueckner, R. Lifton, Q. Lu, Hongyu Zhao
Background Whole-exome sequencing (WES) studies have identified multiple genes enriched for de novo mutations (DNMs) in congenital heart disease (CHD) probands. However, risk gene identification based on DNMs alone remains statistically challenging due to heterogenous etiology of CHD and low mutation rate in each gene. Methods In this manuscript, we introduce a hierarchical Bayesian framework for gene-level association test which jointly analyzes de novo and rare transmitted variants. Through integrative modeling of multiple types of genetic variants, gene-level annotations, and reference data from large population cohorts, our method accurately characterizes the expected frequencies of both de novo and transmitted variants and shows improved statistical power compared to analyses based on DNMs only. Results Applied to WES data of 2,645 CHD proband-parent trios, our method identified 15 significant genes, half of which are novel, leading to new insights into the genetic bases of CHD. Conclusion These results showcase the power of integrative analysis of transmitted and de novo variants for disease gene discovery.
{"title":"Integrative modeling of transmitted and de novo variants identifies novel risk genes for congenital heart disease.","authors":"Mo Li, Xue Zeng, Chentian Jin, S. Jin, W. Dong, Martina Brueckner, R. Lifton, Q. Lu, Hongyu Zhao","doi":"10.15302/j-qb-021-0248","DOIUrl":"https://doi.org/10.15302/j-qb-021-0248","url":null,"abstract":"Background\u0000Whole-exome sequencing (WES) studies have identified multiple genes enriched for de novo mutations (DNMs) in congenital heart disease (CHD) probands. However, risk gene identification based on DNMs alone remains statistically challenging due to heterogenous etiology of CHD and low mutation rate in each gene.\u0000\u0000\u0000Methods\u0000In this manuscript, we introduce a hierarchical Bayesian framework for gene-level association test which jointly analyzes de novo and rare transmitted variants. Through integrative modeling of multiple types of genetic variants, gene-level annotations, and reference data from large population cohorts, our method accurately characterizes the expected frequencies of both de novo and transmitted variants and shows improved statistical power compared to analyses based on DNMs only.\u0000\u0000\u0000Results\u0000Applied to WES data of 2,645 CHD proband-parent trios, our method identified 15 significant genes, half of which are novel, leading to new insights into the genetic bases of CHD.\u0000\u0000\u0000Conclusion\u0000These results showcase the power of integrative analysis of transmitted and de novo variants for disease gene discovery.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"9 2 1","pages":"216-227"},"PeriodicalIF":3.1,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47316490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Early bioinformatics research in China","authors":"Runsheng Chen","doi":"10.15302/j-qb-021-0255","DOIUrl":"https://doi.org/10.15302/j-qb-021-0255","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive total variation constraint hypergraph regularized NMF for single-cell RNA-seq data analysis","authors":"","doi":"10.15302/j-qb-021-0261","DOIUrl":"https://doi.org/10.15302/j-qb-021-0261","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background : Genome-wide association studies (GWAS) have succeeded in identifying tens of thousands of genetic variants associated with complex human traits during the past decade, however, they are still hampered by limited statistical power and dif fi culties in biological interpretation. With the recent progress in expression quantitative trait loci (eQTL) studies, transcriptome-wide association studies (TWAS) provide a framework to test for gene-trait associations by integrating information from GWAS and eQTL studies. Results : In this review, we will introduce the general framework of TWAS, the relevant resources, and the computational tools. Extensions of the original TWAS methods will also be discussed. Furthermore, we will brie fl y introduce methods that are closely related to TWAS, including MR-based methods and colocalization approaches. Connection and difference between these approaches will be discussed. Conclusion : Finally, we will summarize strengths, limitations, and potential directions for TWAS. Author summary: Transcriptome-wide association studies (TWAS) provide an important framework to test for gene-trait associations by integrating information from GWAS and eQTL studies. In this review, we systematically review the general framework and methods of transcriptome-wide association studies, and discuss their strengths, limitations, and potential future directions.
背景:在过去的十年中，全基因组关联研究(GWAS)已经成功地鉴定了数以万计的与复杂人类性状相关的遗传变异，然而，它们仍然受到有限的统计能力和生物学解释困难的阻碍。随着表达数量性状位点(eQTL)研究的进展，转录组全关联研究(transcriptome-wide association studies, TWAS)通过整合GWAS和eQTL研究的信息，提供了一个检测基因-性状相关性的框架。结果:在这篇综述中，我们将介绍TWAS的总体框架、相关资源和计算工具。还将讨论原始TWAS方法的扩展。此外，我们将简要介绍与TWAS密切相关的方法，包括基于mr的方法和共定位方法。将讨论这些方法之间的联系和区别。结论:最后总结了TWAS的优势、局限性和潜在的发展方向。作者总结:转录组全关联研究(Transcriptome-wide association studies, TWAS)通过整合来自GWAS和eQTL研究的信息，为检测基因-性状关联提供了一个重要的框架。在这篇综述中，我们系统地回顾了转录组关联研究的一般框架和方法，并讨论了它们的优势、局限性和潜在的未来方向。
{"title":"Transcriptome wide association studies: general framework and methods","authors":"Yu-Xiao Xie, N. Shan, Hongyu Zhao, Lin Hou","doi":"10.15302/J-QB-020-0228","DOIUrl":"https://doi.org/10.15302/J-QB-020-0228","url":null,"abstract":"Background : Genome-wide association studies (GWAS) have succeeded in identifying tens of thousands of genetic variants associated with complex human traits during the past decade, however, they are still hampered by limited statistical power and dif fi culties in biological interpretation. With the recent progress in expression quantitative trait loci (eQTL) studies, transcriptome-wide association studies (TWAS) provide a framework to test for gene-trait associations by integrating information from GWAS and eQTL studies. Results : In this review, we will introduce the general framework of TWAS, the relevant resources, and the computational tools. Extensions of the original TWAS methods will also be discussed. Furthermore, we will brie fl y introduce methods that are closely related to TWAS, including MR-based methods and colocalization approaches. Connection and difference between these approaches will be discussed. Conclusion : Finally, we will summarize strengths, limitations, and potential directions for TWAS. Author summary: Transcriptome-wide association studies (TWAS) provide an important framework to test for gene-trait associations by integrating information from GWAS and eQTL studies. In this review, we systematically review the general framework and methods of transcriptome-wide association studies, and discuss their strengths, limitations, and potential future directions.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: A traditional Chinese medicine formula, Youdujing (YDJ) ointment, is widely used for treatment of human papilloma virus-related diseases, such as cervical cancer. However, the underlying mechanisms by which active compounds of YDJ alleviates cervical cancer are still unclear. Methods: We applied a comprehensive network pharmacology approach to explore the key mechanisms of YDJ by integrating potential target identi fi cation, network analysis, and enrichment analysis into classical molecular docking procedures. First, we used network and enrichment analyses to identify potential therapeutic targets. Second, we performed molecular docking to investigate the potential active compounds of YDJ. Finally, we carried out a network-based analysis to unravel potentially effective drug combinations. Results: Network analysis yielded four potential therapeutic targets: ESR1, NFKB1, TNF, and AKT1. Molecular docking highlighted that these proteins may interact with four potential active compounds of YDJ: E4, Y2, Y20, and Y21. Finally, we found that Y2 or Y21 can act alone or together with E4 to trigger apoptotic cascades via the mitochondrial apoptotic pathway and estrogen receptors. Conclusion: Our study not only explained why YDJ is effective for cervical cancer treatment, but also lays a strong foundation for future clinical studies based on this traditional medicine. summary: mechanisms underlying the effect of remained unclear, so we developed a network pharmacology method to investigate the active compounds and their possible combinations by integrating network and enrichment analyses with molecular docking. In this paper, we found four potential active compounds and four potential therapeutic targets of YDJ. However, these fi ndings should be con fi rmed by further experiments in vitro and in vivo , whose results can be integrated in the present bioinformatic algorithm in order to optimize our method in the future.
{"title":"Exploring the underlying mechanism of action of a traditional Chinese medicine formula, Youdujing ointment, for cervical cancer treatment","authors":"Lei Zhang, Jinli Lv, Ming Xiao, Li Yang, Le Zhang","doi":"10.15302/j-qb-021-0236","DOIUrl":"https://doi.org/10.15302/j-qb-021-0236","url":null,"abstract":"Background: A traditional Chinese medicine formula, Youdujing (YDJ) ointment, is widely used for treatment of human papilloma virus-related diseases, such as cervical cancer. However, the underlying mechanisms by which active compounds of YDJ alleviates cervical cancer are still unclear. Methods: We applied a comprehensive network pharmacology approach to explore the key mechanisms of YDJ by integrating potential target identi fi cation, network analysis, and enrichment analysis into classical molecular docking procedures. First, we used network and enrichment analyses to identify potential therapeutic targets. Second, we performed molecular docking to investigate the potential active compounds of YDJ. Finally, we carried out a network-based analysis to unravel potentially effective drug combinations. Results: Network analysis yielded four potential therapeutic targets: ESR1, NFKB1, TNF, and AKT1. Molecular docking highlighted that these proteins may interact with four potential active compounds of YDJ: E4, Y2, Y20, and Y21. Finally, we found that Y2 or Y21 can act alone or together with E4 to trigger apoptotic cascades via the mitochondrial apoptotic pathway and estrogen receptors. Conclusion: Our study not only explained why YDJ is effective for cervical cancer treatment, but also lays a strong foundation for future clinical studies based on this traditional medicine. summary: mechanisms underlying the effect of remained unclear, so we developed a network pharmacology method to investigate the active compounds and their possible combinations by integrating network and enrichment analyses with molecular docking. In this paper, we found four potential active compounds and four potential therapeutic targets of YDJ. However, these fi ndings should be con fi rmed by further experiments in vitro and in vivo , whose results can be integrated in the present bioinformatic algorithm in order to optimize our method in the future.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67350874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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