{"title":"大规模并行分析和定量序列-函数关系。","authors":"Justin B Kinney, David M McCandlish","doi":"10.1146/annurev-genom-083118-014845","DOIUrl":null,"url":null,"abstract":"<p><p>Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and <i>cis</i>-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.</p>","PeriodicalId":8231,"journal":{"name":"Annual review of genomics and human genetics","volume":"20 ","pages":"99-127"},"PeriodicalIF":7.7000,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-genom-083118-014845","citationCount":"12","resultStr":"{\"title\":\"Massively Parallel Assays and Quantitative Sequence-Function Relationships.\",\"authors\":\"Justin B Kinney, David M McCandlish\",\"doi\":\"10.1146/annurev-genom-083118-014845\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and <i>cis</i>-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.</p>\",\"PeriodicalId\":8231,\"journal\":{\"name\":\"Annual review of genomics and human genetics\",\"volume\":\"20 \",\"pages\":\"99-127\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2019-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1146/annurev-genom-083118-014845\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual review of genomics and human genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-genom-083118-014845\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/5/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual review of genomics and human genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1146/annurev-genom-083118-014845","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/5/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Massively Parallel Assays and Quantitative Sequence-Function Relationships.
Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and cis-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.
期刊介绍:
Since its inception in 2000, the Annual Review of Genomics and Human Genetics has been dedicated to showcasing significant developments in genomics as they pertain to human genetics and the human genome. The journal emphasizes genomic technology, genome structure and function, genetic modification, human variation and population genetics, human evolution, and various aspects of human genetic diseases, including individualized medicine.