Block network mapping approach to quantitative trait locus analysis

BACKGROUND: Advances in experimental biology have enabled the collection of enormous troves of data on genomic variation in living organisms. The interpretation of this data to extract actionable information is one of the keys to developing novel therapeutic strategies to treat complex diseases. Network organization of biological data overcomes measurement noise in several biological contexts. Does a network approach, combining information about the linear organization of genomic markers with correlative information on these markers in a Bayesian formulation, lead to an analytic method with higher power for detecting quantitative trait loci? RESULTS: Block Network Mapping, combining Similarity Network Fusion (Wang et al., NM 11:333-337, 2014) with a Bayesian locus likelihood evaluation, leads to large improvements in area under the receiver operating characteristic and power over interval mapping with expectation maximization. The method has a monotonically decreasing false discovery rate as a function of effect size, unlike interval mapping. CONCLUSIONS: Block Network Mapping provides an alternative data-driven approach to mapping quantitative trait loci that leverages correlations in the sampled genotypes. The evaluation methodology can be combined with existing approaches such as Interval Mapping. Python scripts are available at http://lbm.niddk.nih.gov/vipulp/ . Genotype data is available at http://churchill-lab.jax.org/website/GattiDOQTL . BMC Bioinformatics 2016 Dec 22; 17(1):544

INTRODUCTION TO BAYESIAN QUANTITATIVE TRAIT LOCUS ANALYSIS FOR POLYPLOIDS

Quantitative Trait Locus (QTL) mapping in polyploids is complicated by the un-observable parental QTL con guration, especially the number of copies (dosage) of the QTL. Existing techniques estimate the parental QTL con guration using a profile likelihood approach and do not address the uncertainty in the estimates. In this paper, a Bayesian method is proposed to jointly model the parameters including the parental QTL configuration, QTL location, and QTL effects. Inference for parameters is obtained by integrating the posterior distribution of the parameters via a Markov chain Monte Carlo (MCMC) sampler, which is a hybrid of the Metropolis-Hastings, Gibbs, and reversible jump samplers. Here, because the size of the parameter space varies for different parental QTL dosages, the reversible jump is utilized in order to allow the sampler to move between parameter spaces with di erent dimensionalities. Additional advantage of this Bayesian technique resides in its flexibility to incorporate prior information and treat missing data augmented. As an example, our method is applied to alfalfa experimental data to identify QTL related to winter hardiness

Quantitative trait locus analysis of parasitoid counteradaptation to symbiont-conferred resistance.

Insect hosts and parasitoids are engaged in an intense struggle of antagonistic coevolution. Infection with heritable bacterial endosymbionts can substantially increase the resistance of aphids to parasitoid wasps, which exerts selection on parasitoids to overcome this symbiont-conferred protection (counteradaptation). Experimental evolution in the laboratory has produced counteradapted populations of the parasitoid wasp Lysiphlebus fabarum. These populations can parasitize black bean aphids (Aphis fabae) protected by the bacterial endosymbiont Hamiltonella defensa, which confers high resistance against L. fabarum. We used two experimentally evolved parasitoid populations to study the genetic architecture of the counteradaptation to symbiont-conferred resistance by QTL analysis. With simple crossing experiments, we showed that the counteradaptation is a recessive trait depending on the maternal genotype. Based on these results, we designed a customized crossing scheme to genotype a mapping population phenotyped for the ability to parasitize Hamiltonella-protected aphids. Using 1835 SNP markers obtained by ddRAD sequencing, we constructed a high-density linkage map consisting of six linkage groups (LGs) with an overall length of 828.3 cM and an average marker spacing of 0.45 cM. We identified a single QTL associated with the counteradaptation to Hamiltonella in L. fabarum on linkage group 2. Out of 120 genes located in this QTL, several genes encoding putative venoms may represent candidates for counteradaptation, as parasitoid wasps inject venoms into their hosts during oviposition

AN INTRODUCTION TO MODEL SELECTION FOR QUANTITATIVE TRAIT LOCUS ANALYSIS IN POLYPLOIDS

Substantial gains have been made in locating regions of agricultural genomes associated with characteristics, diseases, and agroeconomic traits. These gains have relied heavily on the ability to estimate the association between DNA markers and regions of a genome (quantitative trait loci or QTL) related to a particular trait. The majority of these advances have focused on diploid species (two homologous chromosomes per set), even though many important agricultural crops are, in fact, polyploid (more than two homologous chromosomes per set). The purpose of our work is to initiate an algorithmic approach for model selection and QTL detection in polyploid species. This approach involves the enumeration of all possible chromosomal configurations (models) that may result in a gamete, model reduction based on estimation of marker dosage from progeny data, and lastly model selection. While simplified for initial explanation, our approach has demonstrated itself as being extendible to many breeding schemes and less restricted settings

Quantitative trait locus analysis of hybrid pedigrees: variance-components model, inbreeding parameter, and power

<p>Abstract</p> <p>Background</p> <p>For the last years reliable mapping of quantitative trait loci (QTLs) has become feasible through linkage analysis based on the variance-components method. There are now many approaches to the QTL analysis of various types of crosses within one population (breed) as well as crosses between divergent populations (breeds). However, to analyse a complex pedigree with dominance and inbreeding, when the pedigree's founders have an inter-population (hybrid) origin, it is necessary to develop a high-powered method taking into account these features of the pedigree.</p> <p>Results</p> <p>We offer a universal approach to QTL analysis of complex pedigrees descended from crosses between outbred parental lines with different QTL allele frequencies. This approach improves the established variance-components method due to the consideration of the genetic effect conditioned by inter-population origin and inbreeding of individuals. To estimate model parameters, namely additive and dominant effects, and the allelic frequencies of the QTL analysed, and also to define the QTL positions on a chromosome with respect to genotyped markers, we used the maximum-likelihood method. To detect linkage between the QTL and the markers we propose statistics with a non-central χ²-distribution that provides the possibility to deduce analytical expressions for the power of the method and therefore, to estimate the pedigree's size required for 80% power. The method works for arbitrarily structured pedigrees with dominance and inbreeding.</p> <p>Conclusion</p> <p>Our method uses the phenotypic values and the marker information for each individual of the pedigree under observation as initial data and can be valuable for fine mapping purposes. The power of the method is increased if the QTL effects conditioned by inter-population origin and inbreeding are enhanced. Several improvements can be developed to take into account fixed factors affecting trait formation, such as age and sex.</p

Quantitative trait locus analysis identifies Gabra3 as a regulator of behavioral despair in mice

The Tail Suspension Test (TST), which measures behavioral despair, is widely used as an animal model of human depressive disorders and antidepressant efficacy. In order to identify novel genes involved in the regulation of TST performance, we crossed an inbred strain exhibiting low immobility in the TST (RIIIS/J) with two high-immobility strains (C57BL/6J and NZB/BlNJ) to create two distinct F2 hybrid populations. All F2 offspring (n = 655) were genotyped at high density with a panel of SNP markers. Whole-genome interval mapping of the F2 populations identified statistically significant quantitative trait loci (QTLs) on mouse chromosomes (MMU) 4, 6, and X. Microarray analysis of hippocampal gene expression in the three parental strains was used to identify potential candidate genes within the MMUX QTLs identified in the NZB/BlNJ × RIIIS/J cross. Expression of Gabra3, which encodes the GABAA receptor α3 subunit, was robust in the hippocampus of B6 and RIIIS mice but absent from NZB hippocampal tissue. To verify the role of Gabra3 in regulating TST behavior in vivo, mice were treated with SB-205384, a positive modulator of the α3 subunit. SB-205384 significantly reduced TST immobility in B6 mice without affecting general activity, but it had no effect on behavior in NZB mice. This work suggests that GABRA3 regulates a behavioral endophenotype of depression and establishes this gene as a viable new target for the study and treatment of human depression

Quantitative Trait Locus Analysis of Plant Height– Related Traits in Cucumber Using F2:3 Population

In present study, C18 (determinate) and C19 (indeterminate) cucumber lines were crossed and the hybrid plants were self-pollinated to produce the F2:3 generation. Thirteen ISSR (Inter Simple Sequence Repeat) primers, two retrotransposons and two IRAP (Inter-Retrotransposon Amplified Polymorphism) combination primers were screened for QTLs (Quantitative Trait Loci) controlling plant height in cucumber. Five QTLs using SIM (Single Interval Mapping) were identified but only two major of them were observed using CIM (Composite Interval Mapping) method for plant height in F2:3 generation. The distance of one of the identified QTLs to nearest marker was very low and 0.01 CentiMurgan (cM), which showed a high linked marker to this QTL