QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern

BACKGROUND Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. RESULTS We have successfully used the package to analyze many datasets, including F₃₄ body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. CONCLUSIONS QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis.This project was supported by NIH grants R01DA021336, R01MH079103 and R21DA024845

Genome-wide association study in two cohorts from a multi-generational mouse advanced intercross line highlights the difficulty of replication due to study-specific heterogeneity

There has been extensive discussion of the Replication Crisis in many fields, including genome-wide association studies

Novel Resampling Improves Statistical Power for Multiple-Trait QTL Mapping

Multiple-trait analysis typically employs models that associate a quantitative trait locus (QTL) with all of the traits. As a result, statistical power for QTL detection may not be optimal if the QTL contributes to the phenotypic variation in only a small proportion of the traits. Excluding QTL effects that contribute little to the test statistic can improve statistical power. In this article, we show that an optimal power can be achieved when the number of QTL effects is best estimated, and that a stringent criterion for QTL effect selection may improve power when the number of QTL effects is small but can reduce power otherwise. We investigate strategies for excluding trivial QTL effects, and propose a method that improves statistical power when the number of QTL effects is relatively small, and fairly maintains the power when the number of QTL effects is large. The proposed method first uses resampling techniques to determine the number of nontrivial QTL effects, and then selects QTL effects by the backward elimination procedure for significance test. We also propose a method for testing QTL-trait associations that are desired for biological interpretation in applications. We validate our methods using simulations and Arabidopsis thaliana transcript data

Methamphetamine-induced conditioned place preference in LG/J and SM/J mouse strains and an F45/F46 advanced intercross line

The conditioned place preference (CPP) test is frequently used to evaluate the rewarding properties of drugs of abuse in mice. Despite its widespread use in transgenic and knockout experiments, there are few forward genetic studies using CPP to identify novel genes contributing to drug reward. In this study, we tested LG/J and SM/J inbred strains and the parents/offspring of 10 families of an F(45)/F(46) advanced intercross line (AIL) for methamphetamine-induced CPP (MA-CPP) once per week over 2 weeks. Both LG/J and SM/J mice exhibited significant MA-CPP that was not significantly different between the two strains. Furthermore, LG/J mice showed significantly less acute MA-induced locomotor activity as well as locomotor sensitization following subsequent MA injections. AIL mice (N = 105) segregating LG/J and SM/J alleles also demonstrated significant MA-CPP that was equal in magnitude between the first and second week of training. Importantly, MA-CPP in AIL mice did not correlate with drug-free or MA-induced locomotor activity, indicating that MA-CPP was not confounded by test session activity and implying that MA-CPP is genetically distinct from acute psychomotor sensitivity. We estimated the heritability of MA-CPP and locomotor phenotypes using midparent-offspring regression and maximum likelihood estimates derived from the kinship coefficients of the AIL pedigree. Heritability estimates of MA-CPP were low (0-0.21) and variable (SE = 0-0.33) which reflected our poor power to estimate heritability using only 10 midparent-offspring observations. In sum, we established a short-term protocol for MA-CPP in AIL mice that could reveal LG/J and SM/J alleles important for MA reward. The use of highly recombinant genetic populations like AIL should facilitate the identification of these genes and may have implications for understanding psychostimulant abuse in humans.This work was supported by R01DA021336 and K99DA029635

QTLRel: An R package for genome-wide association studies in which relatedness is a concern

Abstract Background: Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. Results: We have successfully used the package to analyze many datasets, including F 34 body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. Conclusions: QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis

Hnrnph1 Is A Quantitative Trait Gene for Methamphetamine Sensitivity.

Psychostimulant addiction is a heritable substance use disorder; however its genetic basis is almost entirely unknown. Quantitative trait locus (QTL) mapping in mice offers a complementary approach to human genome-wide association studies and can facilitate environment control, statistical power, novel gene discovery, and neurobiological mechanisms. We used interval-specific congenic mouse lines carrying various segments of chromosome 11 from the DBA/2J strain on an isogenic C57BL/6J background to positionally clone a 206 kb QTL (50,185,512-50,391,845 bp) that was causally associated with a reduction in the locomotor stimulant response to methamphetamine (2 mg/kg, i.p.; DBA/2J < C57BL/6J)-a non-contingent, drug-induced behavior that is associated with stimulation of the dopaminergic reward circuitry. This chromosomal region contained only two protein coding genes-heterogeneous nuclear ribonucleoprotein, H1 (Hnrnph1) and RUN and FYVE domain-containing 1 (Rufy1). Transcriptome analysis via mRNA sequencing in the striatum implicated a neurobiological mechanism involving a reduction in mesolimbic innervation and striatal neurotransmission. For instance, Nr4a2 (nuclear receptor subfamily 4, group A, member 2), a transcription factor crucial for midbrain dopaminergic neuron development, exhibited a 2.1-fold decrease in expression (DBA/2J < C57BL/6J; p 4.2 x 10-15). Transcription activator-like effector nucleases (TALENs)-mediated introduction of frameshift deletions in the first coding exon of Hnrnph1, but not Rufy1, recapitulated the reduced methamphetamine behavioral response, thus identifying Hnrnph1 as a quantitative trait gene for methamphetamine sensitivity. These results define a novel contribution of Hnrnph1 to neurobehavioral dysfunction associated with dopaminergic neurotransmission. These findings could have implications for understanding the genetic basis of methamphetamine addiction in humans and the development of novel therapeutics for prevention and treatment of substance abuse and possibly other psychiatric disorders

Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2

Acknowledgements The authors would like to acknowledge Dr David A. Blizard for his role in the development of the ideas that led to this study and feedback on the manuscript, Professor Helen Macdonald for valuable advice on study design, Dr Leslie R. Noble for help with the UK Biobank data, and Dr Joseph P. Gyekis for help genotyping cohort 2 mice. The authors would like to acknowledge funding from the University of Aberdeen for the Maxwell computer cluster, the Elphinstone and IMS studentship for AIHC; a Schweppe Foundation Career Development Award (AAP), and the NIH (NIAMS (AL: R01AR056280) and NIDA (AAP:R01DA021336, AAP:R21DA024845, AAP:T32MH020065, NMG:F31DA03635803), NIGMS (NMG:T32GM007197), NHGRI (MA:R01HG002899))Peer reviewedPostprin

Global diversity of the Brachypodium species complex as a resource for genome-wide association studies demonstrated for agronomic traits in response to climate

The development of model systems requires a detailed assessment of standing genetic variation across natural populations. The Brachypodium species complex has been promoted as a plant model for grass genomics with translation to small grain and biomass crops. To capture the genetic diversity within this species complex, thousands of Brachypodium accessions from around the globe were collected and genotyped by sequencing. Overall, 1897 samples were classified into two diploid or allopolyploid species, and then further grouped into distinct inbred genotypes. A core set of diverse B. distachyon diploid lines was selected for whole genome sequencing and high resolution phenotyping. Genome-wide association studies across simulated seasonal environments was used to identify candidate genes and pathways tied to key life history and agronomic traits under current and future climatic conditions. A total of 8, 22, and 47 QTL were identified for flowering time, early vigor, and energy traits, respectively. The results highlight the genomic structure of the Brachypodium species complex, and the diploid lines provided a resource that allows complex trait dissection within this grass model species.We are grateful for funding and support from the Australian Research Council Centre of Excellence in Plant Energy Biology (CE140100008). Australian Plant Phenomics Facility is supported under the National Collaborative Research Infrastructure Strategy of the Australian Government. The research was undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government

Genetic determinants for intramuscular fat content and water-holding capacity in mice selected for high muscle mass

Intramuscular fat content and water-holding capacity are important traits in livestock as they influence meat quality, nutritive value of the muscle, and animal health. As a model for livestock, two inbred lines of the Berlin Muscle Mouse population, which had been long-term selected for high muscle mass, were used to identify genomic regions affecting intramuscular fat content and water-holding capacity. The intramuscular fat content of the Musculus longissimus was on average 1.4 times higher in BMMI806 than in BMMI816 mice. This was accompanied by a 1.5 times lower water-holding capacity of the Musculus quadriceps in BMMI816 mice. Linkage analyses with 332 G3 animals of reciprocal crosses between these two lines revealed quantitative trait loci for intramuscular fat content on chromosome 7 and for water-holding capacity on chromosome 2. In part, the identified loci coincide with syntenic regions in pigs in which genetic effects for the same traits were found. Therefore, these muscle-weight-selected mouse lines and the produced intercross populations are valuable genetic resources to identify genes that could also contribute to meat quality in other species