Biology subjects

Holl, K.

Publications and source records attributed to Holl, K..

9 recordsLinked to original sources

bioRxiv2025

Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats

The intestinal microbiome influences health and disease. Its composition is affected by host genetics and environmental exposures. Understanding host genetic effects is critical but challenging in humans, due to the difficulty of detecting, mapping and interpreting them. To address this, we analysed host genetic effects in four cohorts of outbred laboratory rats exposed to distinct but controlled environments. We found that polygenic host genetic effects were consistent across environments. We identified three replicated microbiome-associated loci, one of which involved a sialyltransferase gene and Paraprevotella. We found a similar association in a human cohort, between ST6GAL1 and Paraprevotella, both of which have been linked with immune and infectious diseases. Moreover, we found evidence of indirect genetic effects on microbiome phenotypes, which substantially increased their total genetic variance. Finally, we identified a novel mechanism whereby indirect genetic effects can contribute to "missing heritability".

genetics↗

bioRxiv2023

Exponential increase in QTL detection with increased sample size.

Power analyses are often used to determine the number of animals required for a genome wide association analysis (GWAS). These analyses are typically intended to estimate the sample size needed for at least one locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real dataset that consisted of 3,173 male and female adult N/NIH heterogeneous stock (HS) rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in sub-samples of the full dataset. The sub-sampling analysis was conducted for four traits with low (0.15 {+/-} 0.03), medium (0.31 {+/-} 0.03 and 0.36 {+/-} 0.03) and high (0.46 {+/-} 0.03) SNP-based heritabilities. For each trait, we sub-sampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

genetics↗

bioRxiv2022

Polygenic Transcriptome Risk Scores Can Translate Genetic Results Between Species

Genome-wide association studies (GWAS) have implicated specific alleles and genes as risk factors for numerous complex traits. However, translating GWAS results into biologically and therapeutically meaningful discoveries remains extremely challenging. Most GWAS results identify noncoding regions of the genome, suggesting that differences in gene regulation are the major driver of trait variability. To better integrate GWAS results with gene regulatory polymorphisms, we previously developed PrediXcan (also known as "transcriptome-wide association studies" or TWAS), which maps SNPs to predicted gene expression using GWAS data. In this study, we developed RatXcan, a framework that extends this methodology to outbred heterogeneous stock (HS) rats. RatXcan accounts for the close familial relationships among HS rats by modeling the relatedness with a random effect that encodes the genetic relatedness. RatXcan also corrects for polygenic-driven inflation because of the equivalence between a relatedness random effect and the infinitesimal polygenic model. To develop RatXcan, we trained transcript predictors for 8,934 genes using reference genotype and expression data from five rat brain regions. We found that the cis genetic architecture of gene expression in both rats and humans was sparse and similar across brain tissues. We tested the association between predicted expression in rats and two example traits (body length and BMI) using phenotype and genotype data from 5,401 densely genotyped HS rats and identified a significant enrichment between the genes associated with rat and human body length and BMI. Thus, RatXcan represents a valuable tool for identifying the relationship between gene expression and phenotypes across species and paves the way to explore shared biological mechanisms of complex traits. Author SummaryUnderstanding how genetic variation affects phenotypic variation is critical to leveraging the wealth of genetic studies to make biologically and therapeutically useful discoveries. Since most of the genetic loci associated with complex diseases are regulatory in nature--meaning that they do not alter protein coding but rather subtly affect gene expression--transcriptome-wide association studies have been developed. However, these apply only to human data where large samples of unrelated individuals are available. For animal models, relatedness is much higher, causing higher false-positive rates. We propose a computationally efficient method to address this problem and find shared biology between humans and rats. Taken together, our development paves the way to further explore shared biological mechanisms of complex traits across species.

genomics↗

bioRxiv2022

Transcriptome-wide Analyses of Adipose Tissue in Outbred Rats Reveal Genetic Regulatory Mechanisms Relevant for Human Obesity

Transcriptomic analysis in metabolically active tissues allows a systems genetics approach to identify causal genes and networks involved in metabolic disease. Outbred heterogeneous stock (HS) rats are used for genetic mapping of complex traits, but to-date, a systems genetics analysis of metabolic tissues has not been done. We investigated whether adiposity-associated genes and gene co-expression networks in outbred heterogeneous stock (HS) rats overlap those found in humans. We analyzed RNAseq data from adipose tissue of 415 male HS rats, correlated these transcripts with body weight (BW) and compared transcriptome signatures to two human cohorts: the African American Genetics of Metabolism and Expression and Metabolic Syndrome in Men. We used weighted gene co-expression network analysis to identify adiposity-associated gene networks and mediation analysis to identify genes under genetic control whose expression drives adiposity. We identified 554 orthologous "consensus genes" whose expression correlates with BW in the rat and with body mass index (BMI) in both human cohorts. Consensus genes fell within eight co-expressed networks and were enriched for genes involved in immune system function, cell growth, extracellular matrix organization and lipid metabolic processes. We identified 19 consensus genes for which genetic variation may influence BW via their expression, including those involved in lipolysis (e.g., Hcar1), inflammation (e.g., Rgs1), adipogenesis (e.g., Tmem120b) or no previously known role in obesity (e.g., St14, Msa4a6). Strong concordance between HS rat and human BW/BMI associated transcripts demonstrates translational utility of the rat model, while identification of novel genes expands our knowledge of the genetics underlying obesity.

genomics↗

bioRxiv2022

Genetic mapping of multiple metabolic traits identifies novel genes for adiposity, lipids and insulin secretory capacity in outbred rats

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids and other metabolic traits. Physiological traits were measured in 1519 male HS rats, with liver and adipose transcriptomes measured in over 410 rats. Genotypes were imputed from low coverage whole genome sequence. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), employing both SNP- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 15 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 11 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for a fat pad weight pQTL on Chr1, Krtcap3 for fat pad weight and serum lipids pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20 and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knock-down/out models, thereby shedding light on novel regulators of obesity.

genetics↗

bioRxiv2021

Genome-wide association study of open fieldbehavior in outbred heterogeneous stock ratsidentifies multiple loci implicated inpsychiatric disorders

Many personality traits are influenced by genetic factors. Rodents models provide an efficient system for analyzing genetic contribution to these traits. Using 1,246 adolescent heterogeneous stock (HS) male and female rats, we conducted a genome-wide association study (GWAS) of behaviors measured in an open field, including locomotion, novel object interaction, and social interaction. We identified 30 genome-wide significant quantitative trait loci (QTL). Using multiple criteria, including the presence of high impact genomic variants and co-localization of cis-eQTL, we identified 13 candidate genes (Adarb2, Ankrd26, Cacna1c, Clock, Crhr1, Ctu2, Cyp26b1, Eva1a, Fam114a1, Kcnj9, Mlf2, Rab27b, Sec11a) for these traits. Most of these genes have been implicated by human GWAS of various psychiatric traits. For example, Cacna1c, a gene known to be critical for social behavior in rodents and implicated in human schizophrenia and bipolar disorder, is a candidate gene for distance to the social zone. In addition, the QTL region for total distance to the novel object zone, on Chr1 at 144 Mb, is syntenic to a hotspot on human Chr15 (82.5-90.8 Mb) that contains 14 genes associated with psychiatric or substance abuse traits. Although some of the genes identified by this study appear to replicate findings from prior human GWAS, others likely represent novel findings that can be the catalyst for future molecular and genetic insights into human psychiatric diseases. Together, these findings provide strong support for the use of the HS population to study psychiatric disorders.

genetics↗

bioRxiv2018

Genome wide association study of body weight, body mass index, adiposity, and fasting glucose in 3,173 outbred rats

Objective Obesity is influenced by genetic and environmental factors. Despite success of human genome wide association studies (GWAS), the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify genetic loci underlying obesity and related morphometric and metabolic traits.Methods We measured obesity-relevant traits including body weight, body length, body mass index, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat GWAS to date. Genetic loci were identified using a linear mixed model that accounted for the complex family relationships of the HS and covariate to account for differences among the three phenotyping centers.Results We identified 32 independent loci, several of which contained only a single gene (e.g. Epha5, Nrg1 and Klhl14) or obvious candidate genes (Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and extensive pleiotropy at individual loci.Conclusions These studies demonstrate utility of HS rats for investigating the genetics of obesity related traits across institutions and identify several candidate genes for future functional testing.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genetics↗

bioRxiv2018

Dissociating addiction-related endophenotypes: Incentive salience attribution, sensation-seeking and novelty-seeking are independent traits in male and female heterogeneous stock rats

There are a number of traits that are thought to increase susceptibility to addiction, and some of these are modeled in preclinical studies. For example, \"sensation-seeking\" is predictive of the initial propensity to take drugs; whereas \"novelty-seeking\" predicts compulsive drug-seeking behavior. In addition, the propensity to attribute incentive salience to reward cues can predict the propensity to approach drug cues, and reinstatement or relapse, even after relatively brief periods of drug exposure. The question addressed here is the extent to which these three vulnerability factors are related; that is, predictive of one another. Some relationships have been reported in small samples, but here a large sample of 1,598 outbred male and female heterogeneous stock rats were screened for Pavlovian conditioned approach behavior (to obtain an index of incentive salience attribution; sign-tracking), and subsequently tested for sensation-seeking and novelty-seeking. Despite the large N there were no significant correlations between these traits, in either males or females. There were, however, novel relationships between multiple measures of incentive salience attribution and, based on these findings, we generated a new metric that captures \"incentive value\". Furthermore, there were sex differences on measures of incentive salience attribution and sensation-seeking behavior that were not previously apparent.

animal behavior and cognition↗

bioRxiv2018

Extended regions of suspected mis-assembly in the rat reference genome

We performed whole-genome sequencing for eight inbred rat strains commonly used in genetic mapping studies, and they are the founders of the NIH heterogeneous stock (HS) outbred colony. We provide their sequences and variant calls to the rat genomics community. When analyzing the variant calls we identified regions with unusually high heterozygosity. We show that these regions are consistent across the eight inbred strains, including the BN strain, which was the basis of the rat reference genome. These regions show significantly higher read depth than other regions in the genome. The evidence suggests that these regions may contain segmental duplications that are incorrectly overlaid in the reference genome. We provide masks for these suspected regions of mis-assembly as a resource for the community to flag potentially false interpretations of mapping results or functional data.

genomics↗