Title |
Application of quantitative trait locus mapping and transcriptomics to studies of the senescence-accelerated phenotype in rats
|
---|---|
Published in |
BMC Genomics, December 2014
|
DOI | 10.1186/1471-2164-15-s12-s3 |
Pubmed ID | |
Authors |
Elena E Korbolina, Nikita I Ershov, Leonid O Bryzgalov, Natalia G Kolosova |
Abstract |
Etiology of complex disorders, such as cataract and neurodegenerative diseases including age-related macular degeneration (AMD), remains poorly understood due to the paucity of animal models, fully replicating the human disease. Previously, two quantitative trait loci (QTLs) associated with early cataract, AMD-like retinopathy, and some behavioral aberrations in senescence-accelerated OXYS rats were uncovered on chromosome 1 in a cross between OXYS and WAG rats. To confirm the findings, we generated interval-specific congenic strains, WAG/OXYS-1.1 and WAG/OXYS-1.2, carrying OXYS-derived loci of chromosome 1 in the WAG strain. Both congenic strains displayed early cataract and retinopathy but differed clinically from OXYS rats. Here we applied a high-throughput RNA sequencing (RNA-Seq) strategy to facilitate nomination of the candidate genes and functional pathways that may be responsible for these differences and can contribute to the development of the senescence-accelerated phenotype of OXYS rats. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 5% |
Unknown | 21 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 6 | 27% |
Student > Ph. D. Student | 4 | 18% |
Researcher | 4 | 18% |
Student > Master | 2 | 9% |
Unspecified | 1 | 5% |
Other | 3 | 14% |
Unknown | 2 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 8 | 36% |
Medicine and Dentistry | 3 | 14% |
Computer Science | 3 | 14% |
Chemistry | 2 | 9% |
Nursing and Health Professions | 1 | 5% |
Other | 3 | 14% |
Unknown | 2 | 9% |