scholarly journals A computationally efficient Bayesian Seemingly Unrelated Regressions model for high-dimensional Quantitative Trait Loci discovery

2018 ◽  
Author(s):  
L. Bottolo ◽  
M. Banterle ◽  
S. Richardson ◽  
M. Ala-Korpela ◽  
M-R. Järvelin ◽  
...  

AbstractMotivationOur work is motivated by the search for metabolite Quantitative Trait Loci (QTL) in a cohort of more than 5,000 people. There are 158 metabolites measured by NMR spectroscopy measured in the 31-year follow-up of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high-throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci.ResultsWe present a computationally efficient Bayesian Seemingly Unrelated Regressions (SUR) model for high-dimensional data, with cell-sparse variable selection and sparse graphical structure for covariance selection. Cell-sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9,000 directly-genotyped Single Nucleotide Polymorphisms, we are able to simultaneously estimate genotype-phenotype associations and the residual dependence structure amongst the metabolites at the same time.Availability and implementationThe R package BayesSUR with full documentation is available at https://cran.r-project.org/web/packages/BayesSUR/[email protected]

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 163-164
Author(s):  
Devin R Jacobs ◽  
Claudia E Silvera-Rojas ◽  
Jennifer M Bormann ◽  
Terry A Gipson ◽  
Arthur L Goetsch ◽  
...  

Abstract Greater selection emphasis has been placed on efficiency than on fitness in livestock populations over the last several decades. Heat stress is a concern in production systems due to the negative effects on production, reproduction, and immunity. The objective of the study was to estimate variance components and identify quantitative trait loci (QTL) for heat stress related traits in sheep. A total of 125 Dorper, Katahdin, and St. Croix ewes originating from four regions of the United States were selected for the experiment. Animals were separated into four trials due to facility limitations. Data were collected for each trial over four consecutive two-week periods in an environmentally controlled facility with targeted heat load index (HLI) for daytime/nighttime of 70/70, 85/77, 90/77, and 95/81. Body weight was collected three times per week and rectal temperature was collected weekly. Black globe temperature and humidity were measured every 15 minutes. Animals were genotyped using the Illumina OvineSNP50 BeadChip. After quality control, 49,396 effective single nucleotide polymorphisms were included in the univariate analysis performed with the BLUPF90 suite of programs. Fixed effects in the models included region of origin, breed, trial, and age as a covariate. Traits analyzed included rectal temperature at 95 HLI (RT95), feed intake at 95 HLI (FI95), and average daily gain for the period for HLI between 90 and 95 (ADG). Heritabilities for RT95, FI95, and ADG were 0.35, 0.10, and 0.10, respectively. Largest effect QTL were identified on chromosomes 23, 9, and 6 for RT95, chromosomes 9, 2, and 20 for FI95, and chromosomes 6, 1, and 5 for ADG. Many of the regions identified have also been associated with weight and carcass traits in other studies, but few had obvious connections to the heat stress related response. In conclusion, results suggest selection could improve heat tolerance in sheep.


Genetics ◽  
2018 ◽  
Vol 211 (2) ◽  
pp. 495-502 ◽  
Author(s):  
Karl W. Broman ◽  
Daniel M. Gatti ◽  
Petr Simecek ◽  
Nicholas A. Furlotte ◽  
Pjotr Prins ◽  
...  

2019 ◽  
Vol 110 (6) ◽  
pp. 727-737 ◽  
Author(s):  
Solomon Boison ◽  
Jingwen Ding ◽  
Erica Leder ◽  
Bjarne Gjerde ◽  
Per Helge Bergtun ◽  
...  

Abstract Cardiomyopathy syndrome (CMS) caused by piscine myocarditis virus is a major disease affecting the Norwegian Atlantic salmon industry. Three different populations of Atlantic salmon from the Mowi breeding program were used in this study. The first 2 populations (population 1 and 2) were naturally infected in a field outbreak, while the third population (population 3) went through a controlled challenged test. The aim of the study was to estimate the heritability, the genetic correlation between populations and perform genome-wide association analysis for resistance to this disease. Survival data from population 1 and 2 and heart atrium histology score data from population 3 was analyzed. A total of 571, 4312, and 901 fish from population 1, 2, and 3, respectively were genotyped with a noncommercial 55,735 Affymetrix marker panel. Genomic heritability ranged from 0.12 to 0.46 and the highest estimate was obtained from the challenge test dataset. The genetic correlation between populations was moderate (0.51–0.61). Two chromosomal regions (SSA27 and SSA12) contained single nucleotide polymorphisms associated with resistance to CMS. The highest association signal (P = 6.9751 × 10−27) was found on chromosome 27. Four genes with functional roles affecting viral resistance (magi1, pi4kb, bnip2, and ha1f) were found to map closely to the identified quantitative trait loci (QTLs). In conclusion, genetic variation for resistance to CMS was observed in all 3 populations. Two important quantitative trait loci were detected which together explain half of the total genetic variance, suggesting strong potential application for marker-assisted selection and genomic predictions to improve CMS resistance.


2009 ◽  
Vol 40 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Michael P. Massett ◽  
Ruzong Fan ◽  
Bradford C. Berk

The genetic factors determining the magnitude of the response to exercise training are poorly understood. The aim of this study was to identify quantitative trait loci (QTL) associated with adaptation to exercise training in a cross between FVB/NJ (FVB) and C57BL/6J (B6) mice. Mice completed an exercise performance test before and after a 4-wk treadmill running program, and changes in exercise capacity, expressed as work (kg·m), were calculated. Changes in work in F2 mice averaged 1.51 ± 0.08 kg·m (94.3 ± 7.3%), with a range of −1.67 to +4.55 kg·m. All F2 mice ( n = 188) were genotyped at 20-cM intervals with 103 single nucleotide polymorphisms (SNPs), and genomewide linkage scans were performed for pretraining, posttraining, and change in work. Significant QTL for pretraining work were located on chromosomes 14 at 4.0 cM [3.72 logarithm of odds (LOD)] and 19 at 34.4 cM (3.63 LOD). For posttraining work significant QTL were located on chromosomes 3 at 60 cM (4.66 LOD) and 14 at 26 cM (4.99 LOD). Suggestive QTL for changes in work were found on chromosomes 11 at 44.6 cM (2.30 LOD) and 14 at 36 cM (2.25 LOD). When pretraining work was used as a covariate, a potential QTL for change in work was identified on chromosome 6 at 68 cM (3.56 LOD). These data indicate that one or more QTL determine exercise capacity and training responses in mice. Furthermore, these data suggest that the genes that determine pretraining work and training responses may differ.


2015 ◽  
Vol 21 (1) ◽  
Author(s):  
Camilo López ◽  
Ruben Eduardo Mora Moreno ◽  
Johana Carolina Soto

<p class="p1"><strong>RESUMEN</strong></p><p class="p2">La yuca (<em>Manihot esculenta</em>) es el cuarto cultivo en importancia a nivel mundial como fuente de calorías para la población humana después del arroz, el azúcar y el maíz, posicionándose por esta razón como un cultivo primordial para la seguridad alimentaria. Su arquitectura ha sido considerada como un factor clave que subyace a la fisiología del rendimiento, relacionando características morfológicas con productividad. En este trabajo se evaluaron diferentes características de arquitectura vegetal en yuca. Los caracteres fueron evaluados en una población F1 compuesta por 133 hermanos completos (familia K) sembrados en dos lugares biogeográficamente diferentes: La Vega (Cundinamarca) y Arauca (Arauca) en Colombia. Las características evaluadas relacionadas con la arquitectura vegetal fueron altura de la planta (AT), número de brotes (NB), longitud entrenudos (LE), número de raíces (NR), peso de raíces (PR), pigmentación del peciolo (PP), área de la hoja (AH) y tipo de hoja (TH). A partir de los datos obtenidos y empleando un mapa genético de alta densidad basado en SNPs (Single Nucleotide Polymorphisms) se llevó a cabo un análisis de QTLs (Quantitative Trait Loci). Se lograron identificar tres QTLs para La Vega asociados con los caracteres altura total, número de brotes y área de la hoja. Para Arauca se detectaron tres QTLs asociados con altura total, longitud de entrenudos y número de brotes. Los QTLs se distribuyeron en cuatro grupos de ligamiento y explicaron entre 18,93 y 41,92 % de la variación genética.</p><p class="p1"><strong>ABSTRACT</strong></p><p class="p2">Cassava (<em>Manihot esculenta</em>) is the fourth most important crop worldwide as a source of calories for the human population after rice, sugar and corn and therefore it is considered as a staple crop. Cassava’s architecture has been considered as a key factor underlying the physiology of yield, relating morphological traits with productivity. In this work different characteristics of plant architecture were evaluated in a cassava F1 population composed by 133 complete siblings (family K) planted in two biogeographically different zones: La Vega (Cundinamarca) and Arauca (Arauca) in Colombia. The characteristics evaluated related to the vegetal architecture were plant height (AT), number of shoots (NB), internodes length (LE), number of roots (NR), root weight (PR), petiole pigmentation (PP), leaf area (AH) and leaf type (TH). From the data obtained and using a SNP- (Single Nucleotide Polymorphism) high-density genetic map a QTLs analysis (Quantitative Trait Loci) was carried out. It was possible to identify three QTLs for La Vega associated with characters plant height, internodes length and leaf area. From the Arauca’s dataset, three QTLs were detected associated with plant height, number of shoots and internodes length. The QTLs were distributed into four linkage groups and explained between 18.93 and 41.92 % of genetic variation.</p><p class="p2"> </p>


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