A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder

Ashbrook, David G.; Williams, Robert W.; Lu, Lu; Hager, Reinmar

doi:10.3389/fnbeh.2015.00171

Cited by 24 publications

(23 citation statements)

References 128 publications

(172 reference statements)

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“…In addition, strict p-value threshold with high multiple testing corrections was also believed to lose many positive loci [35,36]. Joint analysis of human GWAS and mouse genetics would help to "rescue" some of the 'missing' heritability [5,34,[37][38][39]. In the present study, we identified 48 genes in the trait-associated modules which have been reported in human GWAS with p < 10 -4 .…”

Section: Discussionmentioning

confidence: 64%

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-expression Profiling Analysis

Wang¹,

Hu³

et al. 2019

Preprint

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Background Dyslipidemia is the major risk factor of cardiovascular disease. Although many genetic factors have been unveiled, large fraction of the phenotypic variance still needs further investigation. Chromosome 1 (Chr 1) harbors multiple gene loci related to blood lipid regulation, nevertheless, it’s challenging to identify the functional genes. Results We constructed a mouse population, chromosome 1 substitution lines (C1SLs), of which Chr 1 differ from recipient C57BL/6J (B6) mouse while others remain the same. Therefore, any phenotype variance between C1SLs and B6 can be easily inferred to Chr 1. In the current study, we assayed plasma lipids and glucose in 13 C1SLs and their recipient strain B6. Through weighted gene co-expression network analysis of the liver transcriptome and “guilty-by-association” study, eight associated modules of plasma lipids and glucose were identified. Further joint analysis of human genome wide association studies revealed 48 candidate blood lipids or glucose regulating genes. In addition, 38 genes on Chr 1 were also uncovered, in which 13 have been functional validated in mouse models. Conclusions These results suggest that C1SLs are ideal mouse models to study the complex traits and identify the candidate genes on Chr 1 with gene co-expression network analysis.

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Section: Discussionmentioning

confidence: 64%

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-expression Profiling Analysis

Wang¹,

Hu³

et al. 2019

Preprint

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“…Some previous studies have linked GWAS results to evidence from mice. [43][44][45] By systematically linking well-powered GWAS summary results with corresponding phenotypes in thousands of mice and using additional databases to evaluate their expression during murine renal development, our approach is very comprehensive.…”

Section: Discussionmentioning

confidence: 99%

Combination of mouse models and genomewide association studies highlights novel genes associated with human kidney function

Jing

Pattaro

Hoppmann

et al. 2016

Kidney International

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Genomewide association studies have identified numerous chronic kidney disease-associated genetic variants, but often do not pinpoint causal genes. This limitation was addressed by combining Mouse Genome Informatics with human genomewide association studies of kidney function. Genes for which mouse models showed abnormal renal physiology, morphology, glomerular filtration rate (GFR), or urinary albumin-to-creatinine ratio were identified from Mouse Genome Informatics. The corresponding human orthologs were then evaluated for GFR-associated single-nucleotide polymorphisms in 133,814 individuals and urinary albumin-to-creatinine ratio-associated SNPs in 54,451 individuals in genome-wide association studies meta-analysis of the CKDGen Consortium. After multiple testing corrections, significant associations with estimated GFR in humans were identified for single-nucleotide polymorphisms in 2, 7, and 17 genes causing abnormal GFR, abnormal physiology, and abnormal morphology in mice, respectively. Genes identified for abnormal kidney morphology showed significant enrichment for estimated GFR-associated single-nucleotide polymorphisms. In total, 19 genes contained variants associated with estimated GFR or the urinary albumin-to-creatinine ratio of which 16 mapped into previously reported genomewide significant loci. CYP26A1 and BMP4 emerged as novel signals subsequently validated in a large, independent study. An additional gene, CYP24A1, was discovered after conditioning on a published nearby association signal. Thus, our novel approach to combine comprehensive mouse phenotype information with human genomewide association studies data resulted in the identification of candidate genes for kidney disease pathogenesis.

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“…First, it is possible to map Mendelian traits and even quantitative traits with modest LOD scores with good precision, even when using a small numbers of strains [75][76][77] . Second, a good way to transition from QTLs to specific genes, variants, and mechanisms is often to use complementary resources such as panels of common inbred strains, Collaborative Cross (CC), or Diversity Outbred (DO) cases, efficient screens of candidate genes using in vitro and in vivo assays 48,76 , and even human genome-wide association study (GWAS) data [78][79][80][81][82] . But the most obvious way to improve precision and power is to simply use a larger numbers of strains.…”

Section: Improved Mapping Of Bxd Phenome and Omics Datamentioning

confidence: 99%

The expanded BXD family of mice: A cohort for experimental systems genetics and precision medicine

Ashbrook

Arends

Prins

et al. 2019

Preprint

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The challenge of precision medicine is to model complex interactions among DNA variants, sets of phenotypes, and complex environmental factors and confounders.We have expanded the BXD family, creating a powerful and extensible test bed for experimental precision medicine and an ideal cohort to study gene-by-environmental interactions.These BXD segregate for over 6 million variants, with a mean minor allele frequency close to 0.5. We have increased the family two-fold to 150 inbred strains, all derived from C57BL/6J and DBA/2J. We have also generated updated and comprehensive genotypes and an unrivaled deep phenome.Approximately 10,000 recombinations have been located, allowing precision of quantitative trait loci mapping of ±2.0 Mb over much of the genome and ±0.5 Mb for Mendelian loci. The BXD phenome includes more than 100 'omics data sets and >7000 quantitative and clinical phenotypes, all of which is publicly available.The BXD family is an enduring, collaborative, and replicable resource to test causal and mechanistic links between genomes and phenomes at many stages and under a wide variety of treatments and interventions. Background The origin of the BXD familyRecombinant inbred strains of mice, and the BXD family in particular, have been used for 45 years to map Mendelian and quantitative trait loci 1-5 . Production was started in 1971 by Benjamin A. Taylor by crossing a female C57BL/6J (B6 or B) and a male DBA/2J (D2 or D)-hence BXD. The first set of 26 (expanded in the 1990s to 35) recombinant inbred strains were intended mainly for mapping Mendelian loci 1,6 , but the family was soon used to map more complex quantitative traits-cancer susceptibility 7-9 , neuroanatomical traits 10-13 , and behavioral differences 14,15 , and pharmacological responses to toxicants and drugs [16][17][18][19] . All of these strains are still available from The Jackson Laboratory (JAX) and carry the strain suffix "/TyJ".Production of BXD43 through BXD102 started in the late 1990s at the University of Tennessee Health Science Center (UTHSC) 20,21 . These new strains were derived from advanced intercross (AI) progeny that had been bred for as many as 14 generations before inbreeding 22 (Figure 1; Supplementary figure 1; Supplementary table 1). AI-derived BXDs incorporate roughly twice as many fixed cross-over events (recombinations) between B and D parental genomes compared to F2-derived BXDs-80 versus 40 [22][23][24][25][26] (Figure 2). This improved both power and precision. statistic (LRS) scores at three cut-offs: 15 (suggestive), 20 (significant) and 25 (highly significant) ( Table 1). The new genotype files increase the number of QTLs detected at suggestive and significant LRS levels, increasing the percentage detected by 17-19% and 24-26% respectively. However, there is a much smaller increase (2% and 10% respectively) at the highly significant cutoff (LRS >25) because large effect QTLs and Mendelian loci are relatively insensitive to low marker density.

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A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder

Cited by 24 publications

References 128 publications

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-expression Profiling Analysis

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-expression Profiling Analysis

Combination of mouse models and genomewide association studies highlights novel genes associated with human kidney function

The expanded BXD family of mice: A cohort for experimental systems genetics and precision medicine

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