scholarly journals Genetic and genomic characterization followed by single-step genomic evaluation of withers height in German Warmblood horses

2022 ◽  
Author(s):  
Sarah Vosgerau ◽  
Nina Krattenmacher ◽  
Clemens Falker-Gieske ◽  
Anita Seidel ◽  
Jens Tetens ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Reference Population ◽  
Single Step ◽  
Relationship Matrix ◽  
Nucleotide Polymorphisms ◽  
Step Method ◽  
Genomic Breeding ◽  
Breeding Values ◽  
A Genome ◽  
Estimation System

Abstract  Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from − 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.

Accuracies of direct genomic breeding values for birth and weaning weights of registered Charolais cattle in Mexico

2020 ◽  
Vol 60 (6) ◽  
pp. 772
Author(s):  
Francisco J. Jahuey-Martínez ◽  
Gaspar M. Parra-Bracamonte ◽  
Dorian J. Garrick ◽  
Nicolás López-Villalobos ◽  
Juan C. Martínez-González ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Reference Population ◽  
Single Step ◽  
Bayesian Regression ◽  
Nucleotide Polymorphisms ◽  
Linear Unbiased Prediction ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Charolais Cattle ◽  
Best Linear Unbiased

Context Genomic prediction is now routinely used in many livestock species to rank individuals based on genomic breeding values (GEBV). Aims This study reports the first assessment aimed to evaluate the accuracy of direct GEBV for birth (BW) and weaning (WW) weights of registered Charolais cattle in Mexico. Methods The population assessed included 823 animals genotyped with an array of 77000 single nucleotide polymorphisms. Genomic prediction used genomic best linear unbiased prediction (GBLUP), Bayes C (BC), and single-step Bayesian regression (SSBR) methods in comparison with a pedigree-based BLUP method. Key results Our results show that the genomic prediction methods provided low and similar accuracies to BLUP. The prediction accuracy of GBLUP and BC were identical at 0.31 for BW and 0.29 for WW, similar to BLUP. Prediction accuracies of SSBR for BW and WW were up to 4% higher than those by BLUP. Conclusions Genomic prediction is feasible under current conditions, and provides a slight improvement using SSBR. Implications Some limitations on reference population size and structure were identified and need to be addressed to obtain more accurate predictions in liveweight traits under the prevalent cattle breeding conditions of Mexico.

scholarly journals Simulation studies to optimize genomic selection in honey bees

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Richard Bernstein ◽  
Manuel Du ◽  
Andreas Hoppe ◽  
Kaspar Bienefeld
Keyword(s):  
Genomic Selection ◽  
Genetic Gain ◽  
Honey Bees ◽  
Reference Population ◽  
Breeding Program ◽  
Genomic Relationship Matrix ◽  
Relationship Matrix ◽  
Genomic Relationship ◽  
Genomic Breeding ◽  
Breeding Values

Abstract Background With the completion of a single nucleotide polymorphism (SNP) chip for honey bees, the technical basis of genomic selection is laid. However, for its application in practice, methods to estimate genomic breeding values need to be adapted to the specificities of the genetics and breeding infrastructure of this species. Drone-producing queens (DPQ) are used for mating control, and usually, they head non-phenotyped colonies that will be placed on mating stations. Breeding queens (BQ) head colonies that are intended to be phenotyped and used to produce new queens. Our aim was to evaluate different breeding program designs for the initiation of genomic selection in honey bees. Methods Stochastic simulations were conducted to evaluate the quality of the estimated breeding values. We developed a variation of the genomic relationship matrix to include genotypes of DPQ and tested different sizes of the reference population. The results were used to estimate genetic gain in the initial selection cycle of a genomic breeding program. This program was run over six years, and different numbers of genotyped queens per year were considered. Resources could be allocated to increase the reference population, or to perform genomic preselection of BQ and/or DPQ. Results Including the genotypes of 5000 phenotyped BQ increased the accuracy of predictions of breeding values by up to 173%, depending on the size of the reference population and the trait considered. To initiate a breeding program, genotyping a minimum number of 1000 queens per year is required. In this case, genetic gain was highest when genomic preselection of DPQ was coupled with the genotyping of 10–20% of the phenotyped BQ. For maximum genetic gain per used genotype, more than 2500 genotyped queens per year and preselection of all BQ and DPQ are required. Conclusions This study shows that the first priority in a breeding program is to genotype phenotyped BQ to obtain a sufficiently large reference population, which allows successful genomic preselection of queens. To maximize genetic gain, DPQ should be preselected, and their genotypes included in the genomic relationship matrix. We suggest, that the developed methods for genomic prediction are suitable for implementation in genomic honey bee breeding programs.

EXPRESS: Effect of genetic liability to visceral adiposity on stroke and its subtypes: a Mendelian randomization study

2021 ◽  
pp. 174749302110062
Author(s):  
Bin Yan ◽  
Jian Yang ◽  
Li Qian ◽  
Fengjie Gao ◽  
Ling Bai ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ischemic Stroke ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Visceral Adiposity ◽  
Large Artery ◽  
Nucleotide Polymorphisms ◽  
Genetic Liability ◽  
A Genome ◽  
Increased Risk

Background: Observational studies have found an association between visceral adiposity and stroke. Aims: The purpose of this study was to investigate the role and genetic effect of visceral adipose tissue (VAT) accumulation on stroke and its subtypes. Methods: In this two-sample Mendelian randomization (MR) study, genetic variants (221 single nucleotide polymorphisms; P<5×10-8) using as instrumental variables for MR analysis was obtained from a genome-wide association study (GWAS) of VAT. The outcome datasets for stroke and its subtypes were obtained from the MEGASTROKE consortium (up to 67,162 cases and 453,702 controls). MR standard analysis (inverse variance weighted method) was conducted to investigate the effect of genetic liability to visceral adiposity on stroke and its subtypes. Sensitivity analysis (MR-Egger, weighted median, MR-PRESSO) were also utilized to assess horizontal pleiotropy and remove outliers. Multi-variable MR analysis was employed to adjust potential confounders. Results: In the standard MR analysis, genetically determined visceral adiposity (per 1 SD) was significantly associated with a higher risk of stroke (odds ratio [OR] 1.30; 95% confidence interval [CI] 1.21-1.41, P=1.48×10-11), ischemic stroke (OR 1.30; 95% CI 1.20-1.41, P=4.01×10-10), and large artery stroke (OR 1.49; 95% CI 1.22-1.83, P=1.16×10-4). The significant association was also found in sensitivity analysis and multi-variable MR analysis. Conclusions: Genetic liability to visceral adiposity was significantly associated with an increased risk of stroke, ischemic stroke, and large artery stroke. The effect of genetic susceptibility to visceral adiposity on the stroke warrants further investigation.

scholarly journals An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Misbah Razzaq ◽  
Maria Jesus Iglesias ◽  
Manal Ibrahim-Kosta ◽  
Louisa Goumidi ◽  
Omar Soukarieh ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Genome Wide Association Study ◽  
Susceptibility Gene ◽  
Biological Traits ◽  
Nucleotide Polymorphisms ◽  
Ann Model ◽  
Neural Network Approach ◽  
A Genome ◽  
Increased Risk ◽  
Artificial Neural

AbstractVenous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10–7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.

scholarly journals Genome-Wide Association Study (GWAS) for Examining the Genomics Controlling Prickle Production in Red Raspberry (Rubus idaeus L.)

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 27
Author(s):  
Archana Khadgi ◽  
Courtney A. Weber
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genomic Region ◽  
Rubus Idaeus ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Red Raspberry ◽  
Genome Wide ◽  
A Genome ◽  
Genotype By Sequencing

Red raspberry (Rubus idaeus L.) is an expanding high-value berry crop worldwide. The presence of prickles, outgrowths of epidermal tissues lacking vasculature, on the canes, petioles, and undersides of leaves complicates both field management and harvest. The utilization of cultivars with fewer prickles or prickle-free canes simplifies production. A previously generated population segregating for prickles utilizing the s locus between the prickle-free cultivar Joan J (ss) and the prickled cultivar Caroline (Ss) was analyzed to identify the genomic region associated with prickle development in red raspberry. Genotype by sequencing (GBS) was combined with a genome-wide association study (GWAS) using fixed and random model circulating probability unification (FarmCPU) to analyze 8474 single nucleotide polymorphisms (SNPs) and identify significant markers associated with the prickle-free trait. A total of four SNPs were identified on chromosome 4 that were associated with the phenotype and were located near or in annotated genes. This study demonstrates how association genetics can be used to decipher the genetic control of important horticultural traits in Rubus, and provides valuable information about the genomic region and potential genes underlying the prickle-free trait.

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

scholarly journals Comparison of models for missing pedigree in single-step genomic prediction

2021 ◽  
Vol 99 (2) ◽  
Author(s):  
Yutaka Masuda ◽  
Shogo Tsuruta ◽  
Matias Bermann ◽  
Heather L Bradford ◽  
Ignacy Misztal
Keyword(s):  
Density Function ◽  
Single Step ◽  
Joint Density ◽  
Pedigree Information ◽  
Relationship Matrix ◽  
Genomic Information ◽  
Breeding Values ◽  
Joint Density Function ◽  
Information Updates ◽  
Genetic Trends

Abstract Pedigree information is often missing for some animals in a breeding program. Unknown-parent groups (UPGs) are assigned to the missing parents to avoid biased genetic evaluations. Although the use of UPGs is well established for the pedigree model, it is unclear how UPGs are integrated into the inverse of the unified relationship matrix (H-inverse) required for single-step genomic best linear unbiased prediction. A generalization of the UPG model is the metafounder (MF) model. The objectives of this study were to derive 3 H-inverses and to compare genetic trends among models with UPG and MF H-inverses using a simulated purebred population. All inverses were derived using the joint density function of the random breeding values and genetic groups. The breeding values of genotyped animals (u2) were assumed to be adjusted for UPG effects (g) using matrix Q2 as u2∗=u2+Q2g before incorporating genomic information. The Quaas–Pollak-transformed (QP) H-inverse was derived using a joint density function of u2∗ and g updated with genomic information and assuming nonzero cov(u2∗,g′). The modified QP (altered) H-inverse also assumes that the genomic information updates u2∗ and g, but cov(u2∗,g′)=0. The UPG-encapsulated (EUPG) H-inverse assumed genomic information updates the distribution of u2∗. The EUPG H-inverse had the same structure as the MF H-inverse. Fifty percent of the genotyped females in the simulation had a missing dam, and missing parents were replaced with UPGs by generation. The simulation study indicated that u2∗ and g in models using the QP and altered H-inverses may be inseparable leading to potential biases in genetic trends. Models using the EUPG and MF H-inverses showed no genetic trend biases. These 2 H-inverses yielded the same genomic EBV (GEBV). The predictive ability and inflation of GEBVs from young genotyped animals were nearly identical among models using the QP, altered, EUPG, and MF H-inverses. Although the choice of H-inverse in real applications with enough data may not result in biased genetic trends, the EUPG and MF H-inverses are to be preferred because of theoretical justification and possibility to reduce biases.

scholarly journals Haplotype- and SNP-Based GWAS for Growth and Wood Quality Traits in Eucalyptus cladocalyx Trees under Arid Conditions

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 148
Author(s):  
Camilo E. Valenzuela ◽  
Paulina Ballesta ◽  
Sunny Ahmar ◽  
Sajid Fiaz ◽  
Parviz Heidari ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Wood Quality ◽  
Tree Height ◽  
Mediterranean Ecosystems ◽  
Primary Metabolism ◽  
Arid Environments ◽  
Nucleotide Polymorphisms ◽  
Haplotype Blocks ◽  
A Genome ◽  
Stem Straightness

The agricultural and forestry productivity of Mediterranean ecosystems is strongly threatened by the adverse effects of climate change, including an increase in severe droughts and changes in rainfall distribution. In the present study, we performed a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNPs) and haplotype blocks associated with the growth and wood quality of Eucalyptus cladocalyx, a tree species suitable for low-rainfall sites. The study was conducted in a progeny-provenance trial established in an arid site with Mediterranean patterns located in the southern Atacama Desert, Chile. A total of 87 SNPs and 3 haplotype blocks were significantly associated with the 6 traits under study (tree height, diameter at breast height, slenderness coefficient, first bifurcation height, stem straightness, and pilodyn penetration). In addition, 11 loci were identified as pleiotropic through Bayesian multivariate regression and were mainly associated with wood hardness, height, and diameter. In general, the GWAS revealed associations with genes related to primary metabolism and biosynthesis of cell wall components. Additionally, associations coinciding with stress response genes, such as GEM-related 5 and prohibitin-3, were detected. The findings of this study provide valuable information regarding genetic control of morphological traits related to adaptation to arid environments.

Bisphosphonate-related osteonecrosis of the jaw is associated with polymorphisms of the cytochrome P450 CYP2C8 in multiple myeloma: a genome-wide single nucleotide polymorphism analysis

Blood ◽  
2008 ◽  
Vol 112 (7) ◽  
pp. 2709-2712 ◽  
Author(s):  
Maria E. Sarasquete ◽  
Ramon García-Sanz ◽  
Luis Marín ◽  
Miguel Alcoceba ◽  
Maria C. Chillón ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cytochrome P450 ◽  
Genome Wide Association Study ◽  
Osteonecrosis Of The Jaw ◽  
Bisphosphonate Therapy ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome

Abstract We have explored the potential role of genetics in the development of osteonecrosis of the jaw (ONJ) in multiple myeloma (MM) patients under bisphosphonate therapy. A genome-wide association study was performed using 500 568 single nucleotide polymorphisms (SNPs) in 2 series of homogeneously treated MM patients, one with ONJ (22 MM cases) and another without ONJ (65 matched MM controls). Four SNPs (rs1934951, rs1934980, rs1341162, and rs17110453) mapped within the cytochrome P450-2C gene (CYP2C8) showed a different distribution between cases and controls with statistically significant differences (P = 1.07 × 10−6, P = 4.231 × 10−6, P = 6.22 × 10−6, and P = 2.15 × 10−6, respectively). SNP rs1934951 was significantly associated with a higher risk of ONJ development even after Bonferroni correction (P corrected value = .02). Genotyping results displayed an overrepresentation of the T allele in cases compared with controls (48% vs 12%). Thus, individuals homozygous for the T allele had an increased likelihood of developing ONJ (odds ratio 12.75, 95% confidence interval 3.7-43.5).

scholarly journals Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1897
Author(s):  
Endale G. Tafesse ◽  
Krishna K. Gali ◽  
V. B. Reddy Lachagari ◽  
Rosalind Bueckert ◽  
Thomas D. Warkentin
Keyword(s):  
Association Mapping ◽  
Candidate Genes ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Adaptive Traits ◽  
Flowering Duration ◽  
Genome Wide ◽  
A Genome

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

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