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Rinn, John The Leslie Orgel Professor in RNA Science

Positions

Research Areas research areas

Research

research overview

  • It has become increasingly clear that the mammalian genome encoded numerous long noncoding RNA (lncRNA) genes. Our research program continues to push the forefront in understanding long noncoding RNAs (lncRNAs) from identifying and mapping thousands of lncRNA loci -- to developing numerous mutant lncRNA mouse models demonstrating the important impact of lncRNA loci in development and disease -- to dissecting the molecular modalities and mechanisms of lncRNAs in transcriptional and epigenetic regulation. Central to our approach is to bridge the computational and experimental sciences to identify functional long noncoding RNAs. This combinatorial and multi-faceted approach is critical to advance our understanding of how lncRNAs influence cell fate, transcriptional regulation and nuclear architecture. Underscoring the importance of this approach many of the lncRNAs we study are found to be implicated in human disease.

keywords

  • lncRNA, lincRNA, noncoding RNA, ncRNA, epigenetics, noncoding DNA, nuclear organization, RNA, DNA, Genome, Chromatin, epigenetic, splicing

Publications

selected publications

Teaching

courses taught

  • BCHM 4631 - Statistical and Computational Analysis of the Human Genome
    Primary Instructor - Spring 2020 / Spring 2021
    This lab course covers fundamental statistical and computational approaches to large scale data. Students will learn the unix command line to: access public human genome data, learn what statistics apply to which types of data and apply them to study specific regions of the human genome involved in development and disease. This lab course will cover fundamental aspects of Virtual computing, Container analysis pipelines (e.g. NextFlow, GitHub) in an intuitive and practical learning framework. Same as BCHM 4631.
  • BCHM 5631 - Statistical and Computational Analysis of the Human Genome
    Primary Instructor - Spring 2020 / Spring 2021
    This lab course covers fundamental statistical and computational approaches to large scale data. Students will learn the unix command line to: access public human genome data, learn what statistics apply to which types of data and apply them to study specific regions of the human genome involved in development and disease. This lab course will cover fundamental aspects of Virtual computing, Container analysis pipelines (e.g. NextFlow, GitHub) in an intuitive and practical learning framework. Same as BCHM 4631.
  • BCHM 6901 - Research in Biochemistry
    Primary Instructor - Fall 2019 / Spring 2020
    May be repeated up to 15 total credit hours.
  • CHEM 5781 - Advanced General Biochemistry 2
    Primary Instructor - Spring 2018 / Spring 2019
  • CHEM 6901 - Research in Chemistry
    Primary Instructor - Fall 2018 / Spring 2019
    May be repeated up to 15 total credit hours.

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