Identification of a Functional Non-coding Variant in the GABA

GABA type-A (GABA-A) receptors containing the α2 subunit (GABRA2) are expressed in most brain regions and are critical in modulating inhibitory synaptic function. Genetic variation at the GABRA2 locus has been implicated in epilepsy, affective and psychiatric disorders, alcoholism and drug abuse. Gabra2 expression varies as a function of genotype and is modulated by sequence variants in several brain structures and populations, including F2 crosses originating from C57BL/6J (B6J) and the BXD recombinant inbred family derived from B6J and DBA/2J. Here we demonstrate a global reduction of GABRA2 brain protein and mRNA in the B6J strain relative to other inbred strains, and identify and validate the causal mutation in B6J. The mutation is a single base pair deletion located in an intron adjacent to a splice acceptor site that only occurs in the B6J reference genome. The deletion became fixed in B6J between 1976 and 1991 and is now pervasive in many engineered lines, BXD strains generated after 1991, the Collaborative Cross, and the majority of consomic lines. Repair of the deletion using CRISPR-Cas9-mediated gene editing on a B6J genetic background completely restored brain levels of GABRA2 protein and mRNA. Comparison of transcript expression in hippocampus, cortex, and striatum between B6J and repaired genotypes revealed alterations in GABA-A receptor subunit expression, especially in striatum. These results suggest that naturally occurring variation in GABRA2 levels between B6J and other substrains or inbred strains may also explain strain differences in anxiety-like or alcohol and drug response traits related to striatal function. Characterization of the B6J private mutation in the Gabra2 gene is of critical importance to molecular genetic studies in neurobiological research because this strain is widely used to generate genetically engineered mice and murine genetic populations, and is the most widely utilized strain for evaluation of anxiety-like, depression-like, pain, epilepsy, and drug response traits that may be partly modulated by GABRA2 function

Identification of a Functional Non-coding Variant in the GABAA Receptor α2 Subunit of the C57BL/6J Mouse Reference Genome: Major Implications for Neuroscience Research

GABA type-A (GABA-A) receptors containing the α2 subunit (GABRA2) are expressed in most brain regions and are critical in modulating inhibitory synaptic function. Genetic variation at the GABRA2 locus has been implicated in epilepsy, affective and psychiatric disorders, alcoholism and drug abuse. Gabra2 expression varies as a function of genotype and is modulated by sequence variants in several brain structures and populations, including F2 crosses originating from C57BL/6J (B6J) and the BXD recombinant inbred family derived from B6J and DBA/2J. Here we demonstrate a global reduction of GABRA2 brain protein and mRNA in the B6J strain relative to other inbred strains, and identify and validate the causal mutation in B6J. The mutation is a single base pair deletion located in an intron adjacent to a splice acceptor site that only occurs in the B6J reference genome. The deletion became fixed in B6J between 1976 and 1991 and is now pervasive in many engineered lines, BXD strains generated after 1991, the Collaborative Cross, and the majority of consomic lines. Repair of the deletion using CRISPR-Cas9-mediated gene editing on a B6J genetic background completely restored brain levels of GABRA2 protein and mRNA. Comparison of transcript expression in hippocampus, cortex, and striatum between B6J and repaired genotypes revealed alterations in GABA-A receptor subunit expression, especially in striatum. These results suggest that naturally occurring variation in GABRA2 levels between B6J and other substrains or inbred strains may also explain strain differences in anxiety-like or alcohol and drug response traits related to striatal function. Characterization of the B6J private mutation in the Gabra2 gene is of critical importance to molecular genetic studies in neurobiological research because this strain is widely used to generate genetically engineered mice and murine genetic populations, and is the most widely utilized strain for evaluation of anxiety-like, depression-like, pain, epilepsy, and drug response traits that may be partly modulated by GABRA2 function

The Genetic Basis of Baculum Size and Shape Variation in Mice

The rapid divergence of male genitalia is a preeminent evolutionary pattern. This rapid divergence is especially striking in the baculum, a bone that occurs in the penis of many mammalian species. Closely related species often display diverse baculum morphology where no other morphological differences can be discerned. While this fundamental pattern of evolution has been appreciated at the level of gross morphology, nearly nothing is known about the genetic basis of size and shape divergence. Quantifying the genetic basis of baculum size and shape variation has been difficult because these structures generally lack obvious landmarks, so comparing them in three dimensions is not straightforward. Here, we develop a novel morphometric approach to quantify size and shape variation from three-dimensional micro-CT scans taken from 369 bacula, representing 75 distinct strains of the BXD family of mice. We identify two quantitative trait loci (QTL) that explain ∼50% of the variance in baculum size, and a third QTL that explains more than 20% of the variance in shape. Together, our study demonstrates that baculum morphology may diverge relatively easily, with mutations at a few loci of large effect that independently modulate size and shape. Based on a combination of bioinformatic investigations and new data on RNA expression, we prioritized these QTL to 16 candidate genes, which have hypothesized roles in bone morphogenesis and may enable future genetic manipulation of baculum morphology

Multiomic profiling of the liver across diets and age in a diverse mouse population

We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wildtype and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent Diversity Outbred mouse liver dataset segregating for similar diets, with ~80–90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections

Multiomic profiling of the liver across diets and age in adiverse mouse population

We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wild-type and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent diversity outbred mouse liver dataset segregating for similar diets, with 80%-90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.ISSN:2405-472

Genetic Variation in the Social Environment Contributes to Health and Disease

<div><p>Assessing the impact of the social environment on health and disease is challenging. As social effects are in part determined by the genetic makeup of social partners, they can be studied from associations between genotypes of one individual and phenotype of another (social genetic effects, SGE, also called indirect genetic effects). For the first time we quantified the contribution of SGE to more than 100 organismal phenotypes and genome-wide gene expression measured in laboratory mice. We find that genetic variation in cage mates (i.e. SGE) contributes to variation in organismal and molecular measures related to anxiety, wound healing, immune function, and body weight. Social genetic effects explained up to 29% of phenotypic variance, and for several traits their contribution exceeded that of direct genetic effects (effects of an individual’s genotypes on its own phenotype). Importantly, we show that ignoring SGE can severely bias estimates of direct genetic effects (heritability). Thus SGE may be an important source of “missing heritability” in studies of complex traits in human populations. In summary, our study uncovers an important contribution of the social environment to phenotypic variation, sets the basis for using SGE to dissect social effects, and identifies an opportunity to improve studies of direct genetic effects.</p></div

Ignoring SGE leads to biased estimates of DGE (heritability) in the outbred mice dataset.

<p>(A,B) DGE estimates for all organismal phenotypes. The colour of the dots indicates the sign of the covariance between DGE and SGE (blue: negative; red: positive; see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006498#sec006" target="_blank">Methods</a>); the intensity of the colour indicates the magnitude of SGE. (A) Comparison of DGE estimates from model with DGE only (x-axis) and full model with DGE, SGE, (y-axis). (B) Comparison of DGE estimates from model with DGE and cage effects (x-axis) and full model (y-axis). (C) Difference between estimated and simulated DGE. The contribution of SGE to simulated phenotypes varied and is shown on the x-axis. See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006498#sec006" target="_blank">Methods</a> for values given to other parameters. Simulations were analyzed with three different models: DGE only (red), DGE + cage effects (green), DGE + SGE + cage effects + social environmental effects (blue).</p

Gene set enrichment analysis based on the contribution of SGE to gene expression in the prefrontal cortex (PFC) in the experiment with inbred strains.

<p>The analysis was carried out in B6 and D2 focal mice separately. Enrichment was calculated based on the contribution of SGE to gene expression variance (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006498#sec006" target="_blank">Methods</a>). The 5 most significant GO terms for each of strain are shown. * dopamine measured by HPLC in the midbrain is also strongly affected by SGE (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006498#pgen.1006498.t001" target="_blank">Table 1</a>).</p