scholarly journals In silico candidate variant and gene identification using inbred mouse strains

2020 ◽  
Author(s):  
Matthias Munz ◽  
Mohammad Khodaygani ◽  
Zouhair Aherrahrou ◽  
Hauke Busch ◽  
Inken Wohlers

ABSTRACTMice are the most widely used animal model to study genotype to phenotype relationships. Inbred mice are genetically identical, which eliminates genetic heterogeneity and makes them particularly useful for genetic studies. Many different strains have been bred over decades and a vast amount of phenotypic data has been generated. In addition, recently whole genome sequencing-based genome-wide genotype data for many widely used inbred strains has been released. Here, we present an approach for in silico fine-mapping that uses genotypic data of 37 inbred mouse strains together with phenotypic data provided by the user to propose candidate variants and genes for the phenotype under study. Public genome-wide genotype data covering more than 74 million variant sites is queried efficiently in real-time to provide those variants that are compatible with the observed phenotype differences between strains. Variants can be filtered by molecular consequences and by corresponding molecular impact. Candidate gene lists can be generated from variant lists on the fly. Fine-mapping together with annotation or filtering of results is provided in a Bioconductor package called MouseFM. In order to characterize candidate variant lists under various settings, MouseFM was applied to two expression data sets across 20 inbred mouse strains, one from neutrophils and one from CD4+ T cells. Fine-mapping was assessed for about 10,000 genes, respectively, and identified candidate variants and haplotypes for many expression quantitative trait loci (eQTLs) reported previously based on these data. For albinism, MouseFM reports only one variant allele of moderate or high molecular impact that only albino mice share: a missense variant in the Tyr gene, reported previously to be causal for this phenotype. Performing in silico fine-mapping for interfrontal bone formation in mice using four strains with and five strains without interfrontal bone results in 12 genes. Of these, three are related to skull shaping abnormality. Finally performing fine-mapping for dystrophic cardiac calcification by comparing 9 strains showing the phenotype with 8 strains lacking it, we identify only one moderate impact variant in the known causal gene Abcc6. In summary, this illustrates the benefit of using MouseFM for candidate variant and gene identification.

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11017
Author(s):  
Matthias Munz ◽  
Mohammad Khodaygani ◽  
Zouhair Aherrahrou ◽  
Hauke Busch ◽  
Inken Wohlers

Mice are the most widely used animal model to study genotype to phenotype relationships. Inbred mice are genetically identical, which eliminates genetic heterogeneity and makes them particularly useful for genetic studies. Many different strains have been bred over decades and a vast amount of phenotypic data has been generated. In addition, recently whole genome sequencing-based genome-wide genotype data for many widely used inbred strains has been released. Here, we present an approach for in silico fine-mapping that uses genotypic data of 37 inbred mouse strains together with phenotypic data provided by the user to propose candidate variants and genes for the phenotype under study. Public genome-wide genotype data covering more than 74 million variant sites is queried efficiently in real-time to provide those variants that are compatible with the observed phenotype differences between strains. Variants can be filtered by molecular consequences and by corresponding molecular impact. Candidate gene lists can be generated from variant lists on the fly. Fine-mapping together with annotation or filtering of results is provided in a Bioconductor package called MouseFM. In order to characterize candidate variant lists under various settings, MouseFM was applied to two expression data sets across 20 inbred mouse strains, one from neutrophils and one from CD4+ T cells. Fine-mapping was assessed for about 10,000 genes, respectively, and identified candidate variants and haplotypes for many expression quantitative trait loci (eQTLs) reported previously based on these data. For albinism, MouseFM reports only one variant allele of moderate or high molecular impact that only albino mice share: a missense variant in the Tyr gene, reported previously to be causal for this phenotype. Performing in silico fine-mapping for interfrontal bone formation in mice using four strains with and five strains without interfrontal bone results in 12 genes. Of these, three are related to skull shaping abnormality. Finally performing fine-mapping for dystrophic cardiac calcification by comparing 9 strains showing the phenotype with eight strains lacking it, we identify only one moderate impact variant in the known causal gene Abcc6. In summary, this illustrates the benefit of using MouseFM for candidate variant and gene identification.


Bone ◽  
2008 ◽  
Vol 42 (2) ◽  
pp. 439-451 ◽  
Author(s):  
Ilya Sabsovich ◽  
J. David Clark ◽  
Guochun Liao ◽  
Gary Peltz ◽  
Derek P. Lindsey ◽  
...  

1978 ◽  
Vol 32 (2) ◽  
pp. 183-193 ◽  
Author(s):  
Steven J. Self ◽  
Bryan G. Winchester ◽  
James R. Archer

SUMMARYTen glycosidases were measured in suspensions of spermatozoa from the vasa deferentia of two inbred mouse strains and their intercrosses. Eight of these glycosidases were associated with the sperm cells and all of these showed genetical variation between the strains except α-l-fucosidase with optimal activity at pH 5·4. In contrast liver enzyme activities showed no significant variation except α-l-fucosidase. Genetic studies indicated that the variation of spermatozoal β-d-hexosaminidase, α-d-mannosidase, α-l-fucosidase and β-d-galactosidase are inherited at autosomal loci and α-d-galactosidase variation shows X-linked inheritance. We propose a new provisional gene symbol (Afuc-2) for a spermatozoal variant of α-l-fucosidase.


1992 ◽  
Vol 262 (6) ◽  
pp. R1025-R1032 ◽  
Author(s):  
D. B. West ◽  
C. N. Boozer ◽  
D. L. Moody ◽  
R. L. Atkinson

The effect of 7 wk consumption of a diet containing 32.6% of kilocalories as fat [condensed milk (CM) diet] on body composition and energy intake was evaluated in nine strains of inbred mice (AKR/J, C57L/J, A/J, C3H/HeJ, DBA/2J, C57BL/6J, SJL/J, I/STN, and SWR/J). Control animals were fed a high-carbohydrate diet containing 11.6% of energy as fat (Purina Rodent Chow diet). Relative to Chow diet controls, the CM diet significantly increased carcass lipid content in six strains (AKR/J, C57L/J, A/J, C3H/HeJ, DBA/2J, and C57BL/6J), but had no or a marginal effect on adiposity in three strains of mice (SJL/J, I/STN, and SWR/J). The obesity produced by the CM diet in six strains was not due to hyperphagia. Only one of six (AKR/J) of the strains that increased adiposity on the CM diet consumed more energy than controls during the 7 wk of the experiment. The identification of inbred mouse strains that are sensitive to dietary obesity, vs. others that are resistant, provides a useful tool to pursue the metabolic and genetic basis of this trait in the mouse.


Author(s):  
Ahmed Arslan ◽  
Yuan Guan ◽  
Xinyu Chen ◽  
Robin Donaldson ◽  
Wan Zhu ◽  
...  

AbstractBackgroundGenetic factors affecting multiple biomedical traits in mice have been identified when GWAS data, which measured responses in panels of inbred mouse strains, was analyzed using haplotype-based computational genetic mapping (HBCGM). Although this method was previously used to analyze one dataset at a time; but now, a vast amount of mouse phenotypic data is now publicly available, which could enable many more genetic discoveries.ResultsHBCGM and a whole genome SNP map covering 43 inbred strains was used to analyze 8300 publicly available datasets of biomedical responses (1.52M individual datapoints) measured in panels of inbred mouse strains. As proof of concept, causative genetic factors affecting susceptibility for eye, metabolic and infectious diseases were identified when structured automated methods were used to analyze the output. One analysis identified a novel genetic effector mechanism; allelic differences within the mitochondrial targeting sequence affected the subcellular localization of a protein. We also found allelic differences within the mitochondrial targeting sequences of many murine and human proteins, and these could affect a wide range of biomedical phenotypes.ImplicationsThese initial results indicate that genetic factors affecting biomedical responses could be identified through analysis of very large datasets, and they provide an early indication of how this type of ‘augmented intelligence’ can facilitate genetic discovery.


Genetics ◽  
2010 ◽  
Vol 185 (3) ◽  
pp. 1081-1095 ◽  
Author(s):  
Andrew Kirby ◽  
Hyun Min Kang ◽  
Claire M. Wade ◽  
Chris Cotsapas ◽  
Emrah Kostem ◽  
...  

2020 ◽  
Author(s):  
Meiyue Wang ◽  
Gary Peltz

AbstractPopulation structure (PS) has been shown to cause false positive signals in genome-wide association studies (GWAS). Since PS correction is routinely used in human GWAS, it was assumed that it should be utilized for murine GWAS. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been thoroughly investigated. We examined 8223 datasets characterizing biomedical responses in panels of inbred mouse strains to assess the impact of PS on murine GWAS. Surprisingly, we found that PS had a minimal impact on datasets characterizing responses in ≤20 strains; and relatively little impact on the majority of datasets characterizing >20 strains. Moreover, there were examples where association signals within known causative genes could be rejected if PS correction methods were utilized. PS assessment should be carefully used, and considered in conjunction with other criteria, for assessing the candidate genes that are identified in murine GWAS.


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