Mammals exhibit marked interindividual variations in their gut microbiota, but it remains unclear if this is primarily driven by host genetics or by extrinsic factors like dietary intake. To address ...this, we examined the effect of dietary perturbations on the gut microbiota of five inbred mouse strains, mice deficient for genes relevant to host-microbial interactions (MyD88−/−, NOD2−/−, ob/ob, and Rag1−/−), and >200 outbred mice. In each experiment, consumption of a high-fat, high-sugar diet reproducibly altered the gut microbiota despite differences in host genotype. The gut microbiota exhibited a linear dose response to dietary perturbations, taking an average of 3.5 days for each diet-responsive bacterial group to reach a new steady state. Repeated dietary shifts demonstrated that most changes to the gut microbiota are reversible, while also uncovering bacteria whose abundance depends on prior consumption. These results emphasize the dominant role that diet plays in shaping interindividual variations in host-associated microbial communities.
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•Diet reproducibly alters the gut microbiota of mice with diverse genotypes•The gut microbiota exhibits a linear dose response to dietary perturbations•Postperturbation, most bacterial taxa reach a new steady state in 3 days•Most changes are reversible, but some taxa reflect prior diets (hysteresis)
Diet-induced manipulation of gut microbes holds therapeutic potential, but the reproducibility of effects across individuals remains unknown. Carmody et al. show that diet reproducibly alters the gut microbiota despite differences in host genotype. Although most bacteria respond rapidly and consistently to repeated dietary shifts, some exhibit dependence on past diet.
Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we ...combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein-protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice.
R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to ...include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework.
The JAX Diversity Outbred population is a new mouse resource derived from partially inbred Collaborative Cross strains and maintained by randomized outcrossing. As such, it segregates the same ...allelic variants as the Collaborative Cross but embeds these in a distinct population architecture in which each animal has a high degree of heterozygosity and carries a unique combination of alleles. Phenotypic diversity is striking and often divergent from phenotypes seen in the founder strains of the Collaborative Cross. Allele frequencies and recombination density in early generations of Diversity Outbred mice are consistent with expectations based on simulations of the mating design. We describe analytical methods for genetic mapping using this resource and demonstrate the power and high mapping resolution achieved with this population by mapping a serum cholesterol trait to a 2-Mb region on chromosome 3 containing only 11 genes. Analysis of the estimated allele effects in conjunction with complete genome sequence data of the founder strains reduced the pool of candidate polymorphisms to seven SNPs, five of which are located in an intergenic region upstream of the Foxo1 gene.
We present CloudNeo, a cloud-based computational workflow for identifying patient-specific tumor neoantigens from next generation sequencing data. Tumor-specific mutant peptides can be detected by ...the immune system through their interactions with the human leukocyte antigen complex, and neoantigen presence has recently been shown to correlate with anti T-cell immunity and efficacy of checkpoint inhibitor therapy. However computing capabilities to identify neoantigens from genomic sequencing data are a limiting factor for understanding their role. This challenge has grown as cancer datasets become increasingly abundant, making them cumbersome to store and analyze on local servers. Our cloud-based pipeline provides scalable computation capabilities for neoantigen identification while eliminating the need to invest in local infrastructure for data transfer, storage or compute. The pipeline is a Common Workflow Language (CWL) implementation of human leukocyte antigen (HLA) typing using Polysolver or HLAminer combined with custom scripts for mutant peptide identification and NetMHCpan for neoantigen prediction. We have demonstrated the efficacy of these pipelines on Amazon cloud instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics Cloud, which provides graphical interfaces for running and editing, infrastructure for workflow sharing and version tracking, and access to TCGA data.
The CWL implementation is at: https://github.com/TheJacksonLaboratory/CloudNeo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics Cloud platform (https://cgc.sbgenomics.com/, recommended version) can be obtained by contacting the authors.
jeff.chuang@jax.org.
Supplementary data are available at Bioinformatics online.
Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide ...predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.
We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.
We demonstrate MAGIC maize's value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.
The diversity outbred mouse population Churchill, Gary A.; Gatti, Daniel M.; Munger, Steven C. ...
Mammalian genome,
10/2012, Letnik:
23, Številka:
9-10
Journal Article
Recenzirano
Odprti dostop
The Diversity Outbred (DO) population is a heterogeneous stock derived from the same eight founder strains as the Collaborative Cross (CC) inbred strains. Genetically heterogeneous DO mice display a ...broad range of phenotypes. Natural levels of heterozygosity provide genetic buffering and, as a result, DO mice are robust and breed well. Genetic mapping analysis in the DO presents new challenges and opportunities. Specialized algorithms are required to reconstruct haplotypes from high-density SNP array data. The eight founder haplotypes can be combined into 36 possible diplotypes, which must be accommodated in QTL mapping analysis. Population structure of the DO must be taken into account here. Estimated allele effects of eight founder haplotypes provide information that is not available in two-parent crosses and can dramatically reduce the number of candidate loci. Allele effects can also distinguish chance colocation of QTL from pleiotropy, which provides a basis for establishing causality in expression QTL studies. We recommended sample sizes of 200–800 mice for QTL mapping studies, larger than for traditional crosses. The CC inbred strains provide a resource for independent validation of DO mapping results. Genetic heterogeneity of the DO can provide a powerful advantage in our ability to generalize conclusions to other genetically diverse populations. Genetic diversity can also help to avoid the pitfall of identifying an idiosyncratic reaction that occurs only in a limited genetic context. Informatics tools and data resources associated with the CC, the DO, and their founder strains are developing rapidly. We anticipate a flood of new results to follow as our community begins to adopt and utilize these new genetic resource populations.
Mutations in
are responsible for 80% of cases of X-linked Alport Syndrome (XLAS). Although genes that cause AS are well characterized, people with AS who have similar genetic mutations present with a ...wide variation in the extent of kidney impairment and age of onset, suggesting the activities of modifier genes.
We created a cohort of genetically diverse XLAS male and female mice using the Diversity Outbred mouse resource and measured albuminuria, GFR, and gene expression. Using a quantitative trait locus approach, we mapped modifier genes that can best explain the underlying phenotypic variation measured in our diverse population.
Genetic analysis identified several loci associated with the variation in albuminuria and GFR, including a locus on the X chromosome associated with X inactivation and a locus on chromosome 2 containing
. Subsequent analysis of genetically reduced
expression in
knockout mice showed a decrease in albuminuria, podocyte effacement, and podocyte protrusions in the glomerular basement membrane, which support the candidacy of
as a modifier gene for AS.
With this novel approach, we emulated the variability in the severity of kidney phenotypes found in human patients with Alport Syndrome through albuminuria and GFR measurements. This approach can identify modifier genes in kidney disease that can be used as novel therapeutic targets.
Biomedical research is becoming increasingly data driven. New technologies that generate large-scale, complex data are continually emerging and evolving. As a result, there is a concurrent need for ...training researchers to use and understand new computational tools. Here we describe an efficient and effective approach to developing curriculum materials that can be deployed in a research environment to meet this need.
Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort ...focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10-12) BMD locus on Chromosome 3@52.5 Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- mice displayed increased osteogenic differentiation. Lhfp-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10-5) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass.
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