Literature DB >> 33390838

Genome-to-phenome research in rats: progress and perspectives.

Amy L Zinski1, Shane Carrion1, Jennifer J Michal1, Maria A Gartstein2, Raymond M Quock2, Jon F Davis3, Zhihua Jiang1.   

Abstract

Because of their relatively short lifespan (<4 years), rats have become the second most used model organism to study health and diseases in humans who may live for up to 120 years. First-, second- and third-generation sequencing technologies and platforms have produced increasingly greater sequencing depth and accurate reads, leading to significant advancements in the rat genome assembly during the last 20 years. In fact, whole genome sequencing (WGS) of 47 strains have been completed. This has led to the discovery of genome variants in rats, which have been widely used to detect quantitative trait loci underlying complex phenotypes based on gene, haplotype, and sweep association analyses. DNA variants can also reveal strain, chromosome and gene functional evolutions. In parallel, phenome programs have advanced significantly in rats during the last 15 years and more than 10 databases host genome and/or phenome information. In order to discover the bridges between genome and phenome, systems genetics and integrative genomics approaches have been developed. On the other hand, multiple level information transfers from genome to phenome are executed by differential usage of alternative transcriptional start (ATS) and polyadenylation (APA) sites per gene. We used our own experiments to demonstrate how alternative transcriptome analysis can lead to enrichment of phenome-related causal pathways in rats. Development of advanced genome-to-phenome assays will certainly enhance rats as models for human biomedical research. © The author(s).

Entities:  

Keywords:  Alternative transcriptomes; Genetic variation; Genome sequencing; Genome-to-phenome; Phenome collection; Rat

Mesh:

Year:  2021        PMID: 33390838      PMCID: PMC7757052          DOI: 10.7150/ijbs.51628

Source DB:  PubMed          Journal:  Int J Biol Sci        ISSN: 1449-2288            Impact factor:   6.580


  89 in total

1.  Quantitative phenotype analysis to identify, validate and compare rat disease models.

Authors:  Yiqing Zhao; Jennifer R Smith; Shur-Jen Wang; Melinda R Dwinell; Mary Shimoyama
Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

2.  The Rat: A Model Used in Biomedical Research.

Authors:  Jennifer R Smith; Elizabeth R Bolton; Melinda R Dwinell
Journal:  Methods Mol Biol       Date:  2019

Review 3.  Genetic Models in Applied Physiology. HXB/BXH rat recombinant inbred strain platform: a newly enhanced tool for cardiovascular, behavioral, and developmental genetics and genomics.

Authors:  Morton P Printz; Martin Jirout; Rebecca Jaworski; Adamu Alemayehu; Vladimir Kren
Journal:  J Appl Physiol (1985)       Date:  2003-06

4.  Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats.

Authors:  Leah C Solberg Woods; Katie L Holl; Daniel Oreper; Yuying Xie; Shirng-Wern Tsaih; William Valdar
Journal:  Physiol Genomics       Date:  2012-09-04       Impact factor: 3.107

5.  The Rat Genome Database (RGD): developments towards a phenome database.

Authors:  Norberto de la Cruz; Susan Bromberg; Dean Pasko; Mary Shimoyama; Simon Twigger; Jiali Chen; Chin-Fu Chen; Chunyu Fan; Cindy Foote; Gopal R Gopinath; Glenn Harris; Aubrey Hughes; Yuan Ji; Weihong Jin; Dawei Li; Jedidiah Mathis; Natalya Nenasheva; Jeff Nie; Rajni Nigam; Victoria Petri; Dorothy Reilly; Weiye Wang; Wenhua Wu; Angela Zuniga-Meyer; Lan Zhao; Anne Kwitek; Peter Tonellato; Howard Jacob
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

6.  Genomic landscape of rat strain and substrain variation.

Authors:  Roel Hermsen; Joep de Ligt; Wim Spee; Francis Blokzijl; Sebastian Schäfer; Eleonora Adami; Sander Boymans; Stephen Flink; Ruben van Boxtel; Robin H van der Weide; Tim Aitman; Norbert Hübner; Marieke Simonis; Boris Tabakoff; Victor Guryev; Edwin Cuppen
Journal:  BMC Genomics       Date:  2015-05-06       Impact factor: 3.969

7.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

8.  Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

Authors:  Santosh S Atanur; Ana Garcia Diaz; Klio Maratou; Allison Sarkis; Maxime Rotival; Laurence Game; Michael R Tschannen; Pamela J Kaisaki; Georg W Otto; Man Chun John Ma; Thomas M Keane; Oliver Hummel; Kathrin Saar; Wei Chen; Victor Guryev; Kathirvel Gopalakrishnan; Michael R Garrett; Bina Joe; Lorena Citterio; Giuseppe Bianchi; Martin McBride; Anna Dominiczak; David J Adams; Tadao Serikawa; Paul Flicek; Edwin Cuppen; Norbert Hubner; Enrico Petretto; Dominique Gauguier; Anne Kwitek; Howard Jacob; Timothy J Aitman
Journal:  Cell       Date:  2013-07-25       Impact factor: 41.582

9.  Tissue-specific DNA methylation is conserved across human, mouse, and rat, and driven by primary sequence conservation.

Authors:  Jia Zhou; Renee L Sears; Xiaoyun Xing; Bo Zhang; Daofeng Li; Nicole B Rockweiler; Hyo Sik Jang; Mayank N K Choudhary; Hyung Joo Lee; Rebecca F Lowdon; Jason Arand; Brianne Tabers; C Charles Gu; Theodore J Cicero; Ting Wang
Journal:  BMC Genomics       Date:  2017-09-12       Impact factor: 3.969

10.  Alternative polyadenylation drives genome-to-phenome information detours in the AMPKα1 and AMPKα2 knockout mice.

Authors:  Shuwen Zhang; Yangzi Zhang; Xiang Zhou; Xing Fu; Jennifer J Michal; Guoli Ji; Min Du; Jon F Davis; Zhihua Jiang
Journal:  Sci Rep       Date:  2018-04-24       Impact factor: 4.379

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