Regression based fast multi-trait genome-wide QTL analysis

2021 ◽  
pp. 2050044
Author(s):  
Md. Jahangir Alam ◽  
Md. Ripter Hossain ◽  
S. M. Shahinul Islam ◽  
Md. Nurul Haque Mollah
Keyword(s):  
Qtl Analysis ◽  
Expectation Maximization ◽  
Computation Time ◽  
Interval Mapping ◽  
Multivariate Normal ◽  
New Approach ◽  
Multiple Quantitative Trait Locus ◽  
Genome Wide ◽  
Complex Process ◽  
Trait Locus

Multivariate simple interval mapping (SIM) is one of the most popular approaches for multiple quantitative trait locus (QTL) analysis. Both maximum likelihood (ML) and least squares (LS) multivariate regression (MVR) are widely used methods for multi-trait SIM. ML-based MVR (MVR-ML) is an expectation maximization (EM) algorithm based iterative and complex time-consuming approach. Although the LS-based MVR (MVR-LS) approach is not an iterative process, the calculation of likelihood ratio (LR) statistic in MVR-LS is also a time-consuming complex process. We have introduced a new approach (called FastMtQTL) for multi-trait QTL analysis based on the assumption of multivariate normal distribution of phenotypic observations. Our proposed method can identify almost the same QTL positions as those identified by the existing methods. Moreover, the proposed method takes comparatively less computation time because of the simplicity in the calculation of LR statistic by this method. In the proposed method, LR statistic is calculated only using the sample variance–covariance matrix of phenotypes and the conditional probability of QTL genotype given the marker genotypes. This improvement in computation time is advantageous when the numbers of phenotypes and individuals are larger, and the markers are very dense resulting in a QTL mapping with a bigger dataset.

scholarly journals Regression Based Robust QTL Analysis for F2 Population

2016 ◽  
Vol 44 ◽  
pp. 95-99
Author(s):  
Md. Jahangir Alam ◽  
Md. Alamin ◽  
Most. Humaira Sultana ◽  
Md. Amanullah ◽  
Md. Nurul Haque Mollah
Keyword(s):  
Qtl Analysis ◽  
Statistical Approach ◽  
Robust Regression ◽  
Likelihood Function ◽  
Computation Time ◽  
Interval Mapping ◽  
Tuning Parameter ◽  
F2 Population ◽  
Simulation Results ◽  
Trait Locus

This Quantitative trait locus (QTL) analysis is a widely used statistical approach for the detection of important genes in the chromosomes. Maximum likelihood (ML) based interval mapping (IM) is one of the most popular approaches for QTL analysis. However, it is relatively complex and computationally slower than regression based IM. Haley-Knott (HK) and extended Haley-Knott (eHK) regression based IM save computation time and produce similar results as ML-IM. However, these approaches are not robust against phenotypic outliers. In this research, we have developed a robust regression based IM approach by maximizing beta-likelihood function for intercross (F2) population. The proposed method reduces to the HK-IM method when beta ? 0. The tuning parameter beta controls the performance of the proposed method. The simulation results show that the proposed method improves performance over the existing IM approaches in the case of data contaminations; otherwise, it shows almost the same results as the classical IM approaches.

scholarly journals Robust linear regression based simple interval mapping for QTL analysis with backcross population

2018 ◽  
Vol 24 ◽  
pp. 75-81
Author(s):  
MJ Alam ◽  
M Alamin ◽  
MR Hossain ◽  
SMS Islam ◽  
MNH Mollah
Keyword(s):  
Linear Regression ◽  
Robust Regression ◽  
Likelihood Function ◽  
Interval Mapping ◽  
Lod Score ◽  
Backcross Population ◽  
New Approach ◽  
Simple Interval Mapping ◽  
F2 Population ◽  
Trait Locus

Simple interval mapping (SIM) is one of the most important techniques for the identification of quantitative trait locus (QTL). Most of the approaches of SIM are very sensitive to phenotypic outliers and produce misleading results. There is a robust approach of SIM only for F2  population. However, there is no robust SIM method for Backcross population. The objective was to develop a new approach of SIM with Backcross population which is robust against phenotypic outliers and performs almost the same as existing classical methods in absence of outliers. Maximum likelihood (ML) and linear regression (LR) based approaches of SIM are not robust against phenotypic outliers. In this research, we have developed a robust regression based SIM approach by maximizing β-likelihood function for Backcross population. The proposed method reduces to the LR-based SIM method when β = 0. To measure the performance of the proposed method in comparison of ML and LR based SIM with backcross population; we have generated phenotypic and genotypic data for Backcross population using simulation technique. LOD score profile plot shows that the highest peaks of LOD scores occur in the true QTL positions of the true chromosomes at true markers by all three methods for the uncontaminated dataset. However, in presence of outliers, only the proposed method gives the highest LOD score peaks at the true QTL positions on the true chromosomes. The simulation results showed that the proposed method improves performance over the existing SIM methods in presence of phenotypic contaminations.J. bio-sci. 24: 75-81, 2016

scholarly journals An efficient method to identify, date and describe admixture events using haplotype information

2021 ◽  
Author(s):  
Pongsakorn Wangkumhang ◽  
Matthew Greenfield ◽  
Garrett Hellenthal
Keyword(s):  
Roman Empire ◽  
Baltic Sea ◽  
Large Scale ◽  
Computation Time ◽  
North African ◽  
The Baltic Sea ◽  
New Approach ◽  
Genome Wide ◽  
The Baltic ◽  
Haplotype Information

We present fastGLOBETROTTER, an efficient new haplotype-based technique to identify, date and describe admixture events using genome-wide autosomal data. With simulations, we demonstrate how fastGLOBETROTTER reduces computation time by 4-20 fold relative to the haplotype-based technique GLOBETROTTER without suffering loss of accuracy. We apply fastGLOBETROTTER to a cohort of >6000 Europeans from ten countries, revealing previously unreported admixture signals. In particular we infer multiple periods of admixture related to East Asian or Siberian-like sources, starting >2000 years ago, in people living in countries north of the Baltic Sea. In contrast, we infer admixture related to West Asian, North African and/or Southern European sources in populations south of the Baltic Sea, including admixture dated to ≈300-700CE, overlapping the fall of the Roman Empire, in people from Belgium, France and parts of Germany. Our new approach scales to analysing hundreds to thousands of individuals from a putatively admixed populations and hence is applicable to emerging large-scale cohorts of genetically homogeneous populations.

scholarly journals QTL Analysis of Domestication Syndrome in Zombi Pea (Vigna vexillata), an Underutilized Legume Crop

2018 ◽  
Author(s):  
Sujinna Dachapak ◽  
Norihiko Tomooka ◽  
Prakit Somta ◽  
Ken Naito ◽  
Akito Kaga ◽  
...  
Keyword(s):  
Linkage Map ◽  
Seed Size ◽  
Qtl Analysis ◽  
Leaf Size ◽  
Interval Mapping ◽  
Linkage Groups ◽  
Legume Crop ◽  
Vigna Vexillata ◽  
Length Width ◽  
Trait Locus

AbstractZombi pea (Vigna vexillata (L.) A. Rich) is an underutilized crop belonging to the genus Vigna. Two domesticated forms of zombi pea are cultivated as crop plants; seed and tuber forms. The cultivated seed form is present in Africa, while the cultivated tuber form is present in a very limited part of Asia. Genetics of domestication have been investigated in most of cultivated Vigna crops by means of quantitative trait locus (QTL) mapping. In this study, we investigated genetics of domestication in zombi pea by QTL analysis using an F2 population of 139 plants derived from a cross between cultivated tuber form of V. vexillata (JP235863) and wild V. vexillata (AusTRCF66514). A linkage map with 11 linkage groups was constructed from this F2 population using 145 SSR, 117 RAD-seq and 2 morphological markers. Many highly segregation distorted markers were found on LGs 5, 6, 7, 8, 10 and 11. Most of the distorted markers were clustered together and all the markers on LG8 were highly distorted markers. Comparing this V. vexillata linkage map with a previous linkage map of V. vexillata and linkage maps of other four Vigna species demonstrated several macro translocations in V. vexillata. QTL analysis for 22 domestication-related traits was investigated by inclusive composite interval mapping in which 37 QTLs were identified for 18 traits; no QTL was detected for 4 traits. Number of QTLs detected in each trait ranged from 1 to 5 with an average of only 2.3. Tuber traits were controlled by five QTLs with similar effect locating on different linkage groups. Large-effect QTLs (PVE > 20%) were on LG4 (pod length), LG5 (leaf size and seed thickness), and LG7 (for seed-related traits). Comparison of domestication-related QTLs of the zombi pea with those of cowpea (Vigna unguiculata), azuki bean (Vigna angularis), mungbean (Vigna radiata) and rice bean (Vigna umbellata) revealed that there was conservation of some QTLs for seed size, pod size and leaf size between zombi pea and cowpea and that QTLs associated with seed size (weight, length, width and thickness) in each species were clustered on same linkage.

Multilocus evolution

2019 ◽  
pp. 117-144
Author(s):  
Glenn-Peter Sætre ◽  
Mark Ravinet
Keyword(s):  
Quantitative Trait Locus ◽  
Linkage Disequilibrium ◽  
Qtl Analysis ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genetic Evolution ◽  
Highly Active ◽  
Genome Wide ◽  
Trait Locus

Most phenotypic traits are affected by a multitude of genes, which may interact in complex ways. This means that the single locus model explored in chapters 3 and 4 is not always able to capture the full complexity of genetic evolution. In many cases, multiple genes are involved and so this chapter formalizes the analysis of multilocus evolution. Concepts such as linkage disequilibrium and epistasis are introduced, both of which are necessary to properly understand multilocus evolution. The currently highly active field emerging as a result of a crossover between quantitative genetics and genomics is further explored, including methods such as quantitative trait locus (QTL) analysis and genome wide association study (GWAS) that allow phenotypic variation to be associated with likely causative genes and that have made important advances in our understanding of the genetic underpinnings of disease.

scholarly journals Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1984
Author(s):  
Majid Nikpay ◽  
Sepehr Ravati ◽  
Robert Dent ◽  
Ruth McPherson
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Rare Variants ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Search ◽  
Risk Snps ◽  
Trait Locus ◽  
Genomic Regions ◽  
Eqtl Data

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

scholarly journals Integration and Modularity of Quantitative Trait Locus Effects on Geometric Shape in the Mouse Mandible

Genetics ◽  
2004 ◽  
Vol 166 (4) ◽  
pp. 1909-1921
Author(s):  
Christian Peter Klingenberg ◽  
Larry J Leamy ◽  
James M Cheverud
Keyword(s):  
Quantitative Trait ◽  
Parametric Bootstrap ◽  
Interval Mapping ◽  
Procrustes Analysis ◽  
Bootstrap Test ◽  
Mandible Shape ◽  
Trait Locus ◽  
F2 Generation ◽  
Analysis Interval ◽  
Qtl Effects

Abstract The mouse mandible has long served as a model system for complex morphological structures. Here we use new methodology based on geometric morphometrics to test the hypothesis that the mandible consists of two main modules, the alveolar region and the ascending ramus, and that this modularity is reflected in the effects of quantitative trait loci (QTL). The shape of each mandible was analyzed by the positions of 16 morphological landmarks and these data were analyzed using Procrustes analysis. Interval mapping in the F2 generation from intercrosses of the LG/J and SM/J strains revealed 33 QTL affecting mandible shape. The QTL effects corresponded to a variety of shape changes, but ordination or a parametric bootstrap test of clustering did not reveal any distinct groups of QTL that would affect primarily one module or the other. The correlations of landmark positions between the two modules tended to be lower than the correlations between arbitrary subsets of landmarks, indicating that the modules were relatively independent of each other and confirming the hypothesized location of the boundary between them. While these results are in agreement with the hypothesis of modularity, they also underscore that modularity is a question of the relative degrees to which QTL contribute to different traits, rather than a question of discrete sets of QTL contributing to discrete sets of traits.

scholarly journals Genetic Architecture of a Morphological Shape Difference Between Two Drosophila Species

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 299-310 ◽  
Author(s):  
Zhao-Bang Zeng ◽  
Jianjun Liu ◽  
Lynn F Stam ◽  
Chen-Hung Kao ◽  
John M Mercer ◽  
...  
Keyword(s):  
Interval Mapping ◽  
Additive Effect ◽  
Parameter Estimates ◽  
Effect Estimate ◽  
Interspecific Difference ◽  
Posterior Lobe ◽  
Complete Dominance ◽  
Backcross Populations ◽  
History Of ◽  
Trait Locus

AbstractThe size and shape of the posterior lobe of the male genital arch differs dramatically between Drosophila simulans and D. mauritiana. This difference can be quantified with a morphometric descriptor (PC1) based on elliptical Fourier and principal components analyses. The genetic basis of the interspecific difference in PC1 was investigated by the application of quantitative trait locus (QTL) mapping procedures to segregating backcross populations. The parental difference (35 environmental standard deviations) and the heritability of PC1 in backcross populations (>90%) are both very large. The use of multiple interval mapping gives evidence for 19 different QTL. The greatest additive effect estimate accounts for 11.4% of the parental difference but could represent multiple closely linked QTL. Dominance parameter estimates vary among loci from essentially no dominance to complete dominance, and mauritiana alleles tend to be dominant over simulans alleles. Epistasis appears to be relatively unimportant as a source of variation. All but one of the additive effect estimates have the same sign, which means that one species has nearly all plus alleles and the other nearly all minus alleles. This result is unexpected under many evolutionary scenarios and suggests a history of strong directional selection acting on the posterior lobe.

Quantitative Trait Loci for the Monoamine-Related Traits Heart Rate and Headless Behavior inDrosophila melanogaster

Genetics ◽  
2001 ◽  
Vol 157 (1) ◽  
pp. 283-294 ◽  
Author(s):  
Kristie Ashton ◽  
Ana Patricia Wagoner ◽  
Roland Carrillo ◽  
Greg Gibson
Keyword(s):  
Heart Rate ◽  
Genetic Variation ◽  
Recombinant Inbred Lines ◽  
Model Organism ◽  
Interval Mapping ◽  
Activity Levels ◽  
Environmental Variance ◽  
Genome Wide ◽  
A Genome ◽  
Monoamine Receptors

AbstractDrosophila melanogaster appears to be well suited as a model organism for quantitative pharmacogenetic analysis. A genome-wide deficiency screen for haploinsufficient effects on prepupal heart rate identified nine regions of the genome that significantly reduce (five deficiencies) or increase (four deficiencies) heart rate across a range of genetic backgrounds. Candidate genes include several neurotransmitter receptor loci, particularly monoamine receptors, consistent with results of prior pharmacological manipulations of heart rate, as well as genes associated with paralytic phenotypes. Significant genetic variation is also shown to exist for a suite of four autonomic behaviors that are exhibited spontaneously upon decapitation, namely, grooming, grasping, righting, and quivering. Overall activity levels are increased by application of particular concentrations of the drugs octopamine and nicotine, but due to high environmental variance both within and among replicate vials, the significance of genetic variation among wild-type lines for response to the drugs is difficult to establish. An interval mapping design was also used to map two or three QTL for each behavioral trait in a set of recombinant inbred lines derived from the laboratory stocks Oregon-R and 2b.

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