Recent advances in regulatory genomics, especially 3D genome organization in cell nucleus, suggest that existing methods for cross-species comparisons are limited in their ability to fully understand the evolution of non-coding genome function. In particular, it is known that genomes are compartmentalized to distinct compartments in the nucleus such as nuclear lamina and nuclear speckles. Such nuclear compartmentalization is an essential feature of higher-order genome organization and is linked to various important genome functions such as DNA replication timing and transcription. Unfortunately, to date no study exists that directly compares nuclear compartmentalization between human and other mammals. In addition, there are no computational models available that consider the continuous nature of multiple features of nuclear compartmentalization and function, which is critical to integrate genome-wide functional genomic data and datasets that measure cytological distance to multiple compartments across species. In this project, we will develop novel algorithms and generate new datasets to directly address two key questions: (1) How to identify the evolutionary patterns of nuclear compartmentalization? (2) What types of sequence evolution may drive spatial localization changes across species? The proposed project represents the first endeavor in comparative genomics for nuclear compartmentalization.
Our Specific Aims are: (1) Developing new probabilistic models for identifying evolutionary patterns of nuclear compartmentalization. (2) Identifying genome-wide evolutionary patterns of nuclear compartmentalization in primate species based on TSA-seq and Repli-seq. (3) Developing new algorithms to connect sequence features to nuclear compartmentalization through cross-species comparisons. Successful completion of these aims will result in novel computational tools and new datasets that will be highly valuable for the comparative genomics community. Integrating the new computational tools and unique datasets will provide invaluable insights into the relationship between sequence evolution and changes in nuclear genome organization in mammalian species. Therefore, the proposed research is expected to advance comparative genomics to a new frontier and provide new perspectives for studying human genome function

Public Health Relevance

The proposed research is relevant to public health because the outcome of the project is expected to enhance the analyses of nuclear genome organizations across primate species to better understand genome function and human biology. Thus, the proposed research is relevant to NIH?s mission that seeks to obtain fundamental knowledge that will help to improve human health.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
2R01HG007352-05
Application #
9765970
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Wellington, Christopher
Project Start
2014-09-01
Project End
2024-03-31
Budget Start
2019-06-18
Budget End
2020-03-31
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
Schools of Arts and Sciences
DUNS #
052184116
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Rajaraman, Ashok; Ma, Jian (2018) Toward Recovering Allele-specific Cancer Genome Graphs. J Comput Biol 25:624-636
Tasan, Ipek; Sustackova, Gabriela; Zhang, Liguo et al. (2018) CRISPR/Cas9-mediated knock-in of an optimized TetO repeat for live cell imaging of endogenous loci. Nucleic Acids Res 46:e100
Kim, Young-Chae; Seok, Sunmi; Byun, Sangwon et al. (2018) AhR and SHP regulate phosphatidylcholine and S-adenosylmethionine levels in the one-carbon cycle. Nat Commun 9:540
Chen, Yu; Zhang, Yang; Wang, Yuchuan et al. (2018) Mapping 3D genome organization relative to nuclear compartments using TSA-Seq as a cytological ruler. J Cell Biol 217:4025-4048
Seok, Sunmi; Kim, Young-Chae; Byun, Sangwon et al. (2018) Fasting-induced JMJD3 histone demethylase epigenetically activates mitochondrial fatty acid ?-oxidation. J Clin Invest 128:3144-3159
Zhang, Ruochi; Wang, Yuchuan; Yang, Yang et al. (2018) Predicting CTCF-mediated chromatin loops using CTCF-MP. Bioinformatics 34:i133-i141
Yang, Yang; Gu, Quanquan; Zhang, Yang et al. (2018) Continuous-Trait Probabilistic Model for Comparing Multi-species Functional Genomic Data. Cell Syst 7:208-218.e11
Ma, Sai; Hsieh, Yuan-Pang; Ma, Jian et al. (2018) Low-input and multiplexed microfluidic assay reveals epigenomic variation across cerebellum and prefrontal cortex. Sci Adv 4:eaar8187
Yang, Yang; Zhang, Ruochi; Singh, Shashank et al. (2017) Exploiting sequence-based features for predicting enhancer-promoter interactions. Bioinformatics 33:i252-i260
Singh, Deepak K; Gholamalamdari, Omid; Jadaliha, Mahdieh et al. (2017) PSIP1/p75 promotes tumorigenicity in breast cancer cells by promoting the transcription of cell cycle genes. Carcinogenesis 38:966-975

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