ArticleGenetics2014
Rapid identification of major-effect genes using the collaborative cross.
Article in Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Article
- Identification of a genetic region linked to tolerance to MRSA infection using Collaborative Cross mice.PLoS genetics · 2024Article
- The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop.Frontiers in toxicology · 2024Article
- Age-dependent genetic regulation of osteoarthritis: independent effects of immune system genes.Arthritis research & therapy · 2023Article
- Genetic Mapping of Behavioral Traits Using the Collaborative Cross Resource.International journal of molecular sciences · 2022Article
- Loss of LAMP5 interneurons drives neuronal network dysfunction in Alzheimer's disease.Acta neuropathologica · 2022Article
- Elucidating Mechanisms of Tolerance tomBio · 2022Article
- Genetic connection of carotid atherosclerosis with coat color and body weight in an intercross between hyperlipidemic mouse strains.Physiological genomics · 2022Article
- Genetic Connection between Hyperglycemia and Carotid Atherosclerosis in Hyperlipidemic Mice.Genes · 2022Article
- Novel spontaneous myelodysplastic syndrome mouse model.Animal models and experimental medicine · 2021Article
- Loci discovery, network-guided approach, and genomic prediction for drought tolerance index in a multi-parent advanced generation intercross (MAGIC) cowpea population.Horticulture research · 2021Article
- How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers.Frontiers in oncology · 2021Review
- E2f8 and Dlg2 genes have independent effects on impaired insulin secretion associated with hyperglycaemia.Diabetologia · 2020Article
- Determinants of QTL Mapping Power in the Realized Collaborative Cross.G3 (Bethesda, Md.) · 2019Article
- Variable outcomes of human heart attack recapitulated in genetically diverse mice.NPJ Regenerative medicine · 2019Article
- Advanced Genetic Approaches in Discovery and Characterization of Genes Involved With Osteoporosis in Mouse and Human.Frontiers in genetics · 2019Review
- Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.Animal models and experimental medicine · 2018Article
- The Collaborative Cross mouse model for dissecting genetic susceptibility to infectious diseases.Mammalian genome : official journal of the International Mammalian Genome Society · 2018Review
- Profiling and genetic control of the murine immunoglobulin G glycome.Nature chemical biology · 2018Article
- Gene Expression Networks in the Murine Pulmonary Myocardium Provide Insight into the Pathobiology of Atrial Fibrillation.G3 (Bethesda, Md.) · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The Collaborative Cross (CC) was designed to facilitate rapid gene mapping and consists of hundreds of recombinant inbred lines descended from eight diverse inbred founder strains. A decade in production, it can now be applied to mapping projects. Here, we provide a proof of principle for rapid identification of major-effect genes using the CC. To do so, we chose coat color traits since the location and identity of many relevant genes are known. We ascertained in 110 CC lines six different coat phenotypes: albino, agouti, black, cinnamon, and chocolate coat colors and the white-belly trait. We developed a pipeline employing modifications of existing mapping tools suitable for analyzing the complex genetic architecture of the CC. Together with analysis of the founders' genome sequences, mapping was successfully achieved with sufficient resolution to identify the causative genes for five traits. Anticipating the application of the CC to complex traits, we also developed strategies to detect interacting genes, testing joint effects of three loci. Our results illustrate the power of the CC and provide confidence that this resource can be applied to complex traits for detection of both qualitative and quantitative trait loci.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.