Genetic architecture of protein expression and its regulation in the mouse brain

Background Natural variation in protein expression is common in all organisms and contributes to phenotypic differences among individuals. While variation in gene expression at the transcript level has been extensively investigated, the genetic mechanisms underlying variation in protein expression have lagged considerably behind. Here we investigate genetic architecture of protein expression by profiling a deep mouse brain proteome of two inbred strains, C57BL/6 J (B6) and DBA/2 J (D2), and their reciprocal F1 hybrids using two-dimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) technology. Results By comparing protein expression levels in the four mouse strains, we observed 329 statistically significant differentially expressed proteins between the two parental strains and characterized the genetic basis of protein expression. We further applied a proteogenomic approach to detect variant peptides and define protein allele-specific expression (pASE), identifying 33 variant peptides with cis-effects and 17 variant peptides showing trans-effects. Comparison of regulation at transcript and protein levels show a significant divergence. Conclusions The results provide a comprehensive analysis of genetic architecture of protein expression and the contribution of cis- and trans-acting regulatory differences to protein expression.

MoG+: a database of genomic variations across three mouse subspecies for biomedical research

Laboratory mouse strains have mosaic genomes derived from at least three major subspecies that are distributed in Eurasia. Here, we describe genomic variations in ten inbred strains: Mus musculus musculus-derived BLG2/Ms, NJL/Ms, CHD/Ms, SWN/Ms, and KJR/Ms; M. m. domesticus-derived PGN2/Ms and BFM/Ms; M. m. castaneus-derived HMI/Ms; and JF1/Ms and MSM/Ms, which were derived from a hybrid between M. m. musculus and M. m. castaneus. These strains were established by Prof. Moriwaki in the 1980s and are collectively named the “Mishima Battery”. These strains show large phenotypic variations in body size and in many physiological traits. We resequenced the genomes of the Mishima Battery strains and performed a comparative genomic analysis with dbSNP data. More than 81 million nucleotide coordinates were identified as variant sites due to the large genetic distances among the mouse subspecies; 8,062,070 new SNP sites were detected in this study, and these may underlie the large phenotypic diversity observed in the Mishima Battery. The new information was collected in a reconstructed genome database, termed MoG+ that includes new application software and viewers. MoG+ intuitively visualizes nucleotide variants in genes and intergenic regions, and amino acid substitutions across the three mouse subspecies. We report statistical data from the resequencing and comparative genomic analyses and newly collected phenotype data of the Mishima Battery, and provide a brief description of the functions of MoG+, which provides a searchable and unique data resource of the numerous genomic variations across the three mouse subspecies. The data in MoG+ will be invaluable for research into phenotype-genotype links in diverse mouse strains.

Transmission distortion and genetic incompatibilities between alleles in a multigenerational mouse advanced intercross line

While direct additive and dominance effects on complex traits have been mapped repeatedly, additional genetic factors contributing to the heterogeneity of complex traits have been scarcely investigated. To assess genetic background effects, we investigated transmission ratio distortions (TRDs) of alleles from parent to offspring using an advanced intercross line (AIL) of an initial cross between the mouse inbred strains C57BL/6NCrl (B6N) and BFMI860-12 (BFMI). 341 males of generation 28 and their respective 61 parents and 66 grandparents were genotyped using Mega Mouse Universal Genotyping Arrays (MegaMUGA). TRDs were investigated using allele transmission asymmetry tests, and pathway overrepresentation analysis was performed. Sequencing data was used to test for overrepresentation of non-synonymous SNPs in TRD regions. Genetic incompatibilities were tested using the Bateson-Dobzhansky-Muller two-locus model. 62 TRD regions were detected, many in close proximity to the telocentric centromere. TRD regions contained 44.5% more non-synonymous SNPs than randomly selected regions (182 vs. 125.9 ± 17.0, P < 1x10−4). Testing for genetic incompatibilities between TRD regions identified 29 genome-wide significant incompatibilities between TRD regions (P(BF) < 0.05). Pathway overrepresentation analysis of genes in TRD regions showed that DNA methylation, epigenetic regulation of RNA, and meiotic/meiosis regulation pathways were affected independent of the parental origin of the TRD. Paternal BFMI TRD regions showed overrepresentation in the small interfering RNA (siRNA) biogenesis and in the metabolism of lipids and lipoproteins. Maternal B6N TRD regions harbored genes involved in meiotic recombination, cell death, and apoptosis pathways. The analysis of genes in TRD regions suggests the potential distortion of protein-protein interactions influencing obesity and diabetic retinopathy as a result of disadvantageous combinations of allelic variants in Aass, Pgx6 and Nme8. Using an AIL significantly improves the resolution at which we can investigate TRD. Our analysis implicates distortion of protein-protein interactions as well as meiotic drive as the underlying mechanisms leading to the observed TRD in our AIL. Furthermore, genes with large amounts of non-synonymous SNPs located in TRD regions are more likely to be involved in pathways that are related to the phenotypic differences between the parental strains. Genes in these TRD regions provide new targets for investigating genetic adaptation, protein-protein interactions, and determinants of complex traits such as obesity.

Genetic and genomic architecture in eight strains of the laboratory opossum Monodelphis domestica

The gray short-tailed opossum (Monodelphis domestica) is an established laboratory-bred marsupial model for biomedical research. It is a critical species for comparative genomics research, providing the pivotal phylogenetic outgroup for studies of derived vs. ancestral states of genomic/epigenomic characteristics for eutherian mammal lineages. To characterize the current genetic profile of this laboratory marsupial, we examined 79 individuals from eight established laboratory strains. Double digest restriction-site associated DNA sequencing (ddRAD-seq) and whole-genome resequencing experiments were performed to investigate the genetic architecture in these strains. A total of 66,640 high-quality single nucleotide polymorphisms (SNPs) were identified. We analyzed SNP density, average heterozygosity, nucleotide diversity, and population differentiation parameter Fst within and between the eight strains. Principal component and population structure analysis clearly resolve the strains at the level of their ancestral founder populations, and the genetic architecture of these strains correctly reflects their breeding history. We confirmed the successful establishment of the first inbred laboratory opossum strain LSD (inbreeding coefficient F > 0.99) and a nearly inbred strain FD2M1 (0.98 < F < 0.99), each derived from a different ancestral background. These strains are suitable for various experimental protocols requiring controlled genetic backgrounds and for intercrosses and backcrosses that can generate offspring with informative SNPs for studying a variety of genetic and epigenetic processes. Together with recent advances in reproductive manipulation and CRISPR/Cas9 techniques for M. domestica, the existence of distinctive inbred strains will enable genome editing on different genetic backgrounds, greatly expanding the utility of this marsupial model for biomedical research.

SVJAM: Joint Analysis of Structural Variants Using Linked Read Sequencing Data

Linked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.

Strain-Specific Liver Metabolite Profiles in Medaka

The relationship between genetic variation and phenotypic traits is often poorly understood since specific genotypes do not always easily translate into associated phenotypes, especially for complex disorders. The genetic background has been shown to affect metabolic pathways and thus contribute to variations in the metabolome. Here, we tested the suitability of NMR metabolomics for comparative analysis of fish lines as a first step towards phenotype-genotype association studies. The Japanese rice fish, medaka (Oryzias latipes), is a widely used genetic vertebrate model with several isogenic inbred laboratory strains. We used liver extracts of medaka iCab and HO5 strains as a paradigm to test the feasibility of distinguishing the metabolome of two different inbred strains. Fifteen metabolites could be detected in uni- and multivariate analyses that showed strain-specific levels. Differences could be assigned to specific metabolic pathways. Our results show that NMR spectroscopy is a suitable method to detect variance of the metabolome caused by subtle genetic differences. Thus, it has the potential to address genotype–phenotype associations in medaka, providing an additional level of phenotypic analysis.

The Effect of Population Structure on Murine Genome-Wide Association Studies

The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 – 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated.

Higher Intercellular Variation in Genome-Wide Recombination Rate in Female Mice

Meiotic recombination affects fertility, shuffles genomes, and modulates the effectiveness of natural selection. Despite conservation of the recombination pathway, the rate of recombination varies among individuals and along chromosomes. Recombination rate also differs among cells from the same organism, but this form of variation has received less attention. To identify patterns that characterize intercellular variation in the genome-wide recombination rate, we counted foci of the MLH1 recombination-associated protein in oocytes and spermatocytes from a panel of wild-derived inbred strains of house mice. Females show higher intercellular variation in MLH1 focus count than males from the same inbred strains. This pattern is consistent across strains from multiple subspecies, including 2 strains in which the average MLH1 focus count is higher in males. The sex difference in genome-wide recombination rate we report suggests that selection targeting recombination rate will be more efficient in males than in females.

Genetic and genomic architecture in eight strains of the laboratory opossum Monodelphis domestica

The gray short-tailed opossum is an established laboratory-bred marsupial model for biomedical research. It serves as a critical species for comparative genomics research, providing the pivotal phylogenetic outgroup for studies of derived vs. ancestral states of genomic/epigenomic characteristics for all eutherian mammal lineages. To characterize the current genetic profile of this laboratory marsupial, we examined 79 individuals from eight established laboratory strains. Double digest restriction-site associated DNA sequencing (ddRAD-seq) and whole-genome resequencing experiments were performed to investigate the genetic architecture in these strains. A total of 66,640 high-quality single nucleotide polymorphisms (SNPs) were identified. We analyzed SNP density, average heterozygosity, nucleotide diversity, and population differentiation parameter Fst within and between the eight strains. Principal component and population structure analysis clearly resolve the strains at the level of their ancestral founder populations, and the genetic architecture of these strains correctly reflects their breeding history. We confirmed the successful establishment of the first inbred laboratory opossum strain LSD (inbreeding coefficient F > 0.99) and a nearly inbred strain FD2M1 (0.98 < F < 0.99), each derived from a different ancestral background. These strains are suitable for various experimental protocols requiring controlled genetic backgrounds and for intercrosses and backcrosses that can generate offspring with informative SNPs for studying a variety of genetic and epigenetic processes. Together with recent advances in reproductive manipulation and CRISPR/Cas9 techniques for M. domestica, the existence of distinctive inbred strains will enable genome editing on different genetic backgrounds, greatly expanding the utility of this marsupial model for biomedical research.