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Latest reference genome rat strain‐specific variants provide new insight into human diseases
Author(s) -
Tutaj Monika,
Smith Jennifer R,
De Pons Jeffrey L,
Laulederkind Stanley J,
Tutaj Marek A,
Hayman G Thomas,
Wang ShurJen,
Petri Victoria,
Dwinell Melinda R,
Shimoyama Mary E
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.984.4
Subject(s) - genome , indel , reference genome , human genome , computational biology , whole genome sequencing , biology , dna sequencing , personal genomics , genetics , cancer genome sequencing , gene , genomics , single nucleotide polymorphism , genotype
Popularization of DNA sequencing technologies and increasing amount of data generated by researchers demand efficient methods to search and analyze sequence data. As part of a large corpus of genomic, genetic, phenotype and disease data, the Rat Genome Database (RGD) provides information about strain‐specific variants, including copy number variations, single nucleotide variants (SNVs), indels and mutations, generated from whole genome sequencing (WGS) of rat strains used as models for a variety of common human diseases. These variants were originally analyzed against previous rat genomic assemblies (RGSC 3.4 and RGSC 5.0). To bring this up to date, RGD is re‐analyzing available rat strain whole‐genome sequences using the newest version of the rat reference assembly (RGSC 6.0, released in 2014). Difficulties with correct variant identification and developing reliable calling algorithms require extensive validation. To accomplish this, we are developing an analysis pipeline which utilizes state‐of‐the‐art tools for variant calling and effect prediction. In addition, we are expanding our current search tools to include the ability to use the combination of a variant position in the genome with the functional annotations assigned to RGD genes and strains. The combination of improved variant data and disease, phenotype, pathway, function and chemical interaction information will help researchers find appropriate models for disease research and drug testing. Support or Funding Information The National Heart, Lung, and Blood Institute of the National Institutes of Health, Grant #R01HL064541