PSVIII-31 Genome-wide estimation of linkage disequilibrium using American mink genotyping-by-sequencing data

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 267-267
Author(s):  
Karim Karimi ◽  
A Hossain Farid ◽  
Mehdi Sargolzaei ◽  
Sean Myles ◽  
Younes Miar
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Average Distance ◽  
American Mink ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Single Nucleotide ◽  
Genome Wide

Abstract Linkage disequilibrium (LD) has been defined as the correlation between alleles at different loci in the genome. The LD levels can be influenced by the evolutionary processes and historical events in populations. The main objective of this study was to estimate the LD levels at different distances of American mink genome using genotyping-by-sequencing (GBS) data. A total of 285 American mink (Neovison vison) were sequenced based on GBS libraries prepared by digesting the genomic DNA with the restriction enzyme ApeKI. After quality control, 13,321 single nucleotide polymorphism (SNP) markers located on 46 Scaffolds were used to determine the extension of LD in the genome. The average r2 was computed for all syntenic SNP pairwise at inter-marker distances from 0 up to 1 Mb. The average r2 between adjacent SNPs was 0.29, ranged from 0.18 to 0.53 across all scaffolds. In addition, the average distance between adjacent markers was 51 kb. The average r2 above 0.3 was observed in less than 1 kb distances and declined with increase in distances between markers. The average r2 was estimated to be less than 0.2 for markers more than 10 kb apart. Furthermore, the average LD level was decreased to 0.08 for inter-marker distances between 0.9 and 1 Mb. The results of this study can be used to determine the optimum maker density required for obtaining enough accuracy and power in both genomic selection and genome-wide association studies.

scholarly journals Challenges of Adjusting Single-Nucleotide Polymorphism Effect Sizes for Linkage Disequilibrium

2021 ◽  
pp. 1-11
Author(s):  
Valentina Escott-Price ◽  
Karl Michael Schmidt
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Statistical Significance ◽  
Ordinary Least Squares ◽  
Effect Sizes ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Tikhonov Regularisation

<b><i>Background:</i></b> Genome-wide association studies (GWAS) were successful in identifying SNPs showing association with disease, but their individual effect sizes are small and require large sample sizes to achieve statistical significance. Methods of post-GWAS analysis, including gene-based, gene-set and polygenic risk scores, combine the SNP effect sizes in an attempt to boost the power of the analyses. To avoid giving undue weight to SNPs in linkage disequilibrium (LD), the LD needs to be taken into account in these analyses. <b><i>Objectives:</i></b> We review methods that attempt to adjust the effect sizes (β<i>-</i>coefficients) of summary statistics, instead of simple LD pruning. <b><i>Methods:</i></b> We subject LD adjustment approaches to a mathematical analysis, recognising Tikhonov regularisation as a framework for comparison. <b><i>Results:</i></b> Observing the similarity of the processes involved with the more straightforward Tikhonov-regularised ordinary least squares estimate for multivariate regression coefficients, we note that current methods based on a Bayesian model for the effect sizes effectively provide an implicit choice of the regularisation parameter, which is convenient, but at the price of reduced transparency and, especially in smaller LD blocks, a risk of incomplete LD correction. <b><i>Conclusions:</i></b> There is no simple answer to the question which method is best, but where interpretability of the LD adjustment is essential, as in research aiming at identifying the genomic aetiology of disorders, our study suggests that a more direct choice of mild regularisation in the correction of effect sizes may be preferable.

scholarly journals Linkage disequilibrium and within-breed genetic diversity in Iranian Zandi sheep

2019 ◽  
Vol 62 (1) ◽  
pp. 143-151 ◽  
Author(s):  
Seyed Mohammad Ghoreishifar ◽  
Hossein Moradi-Shahrbabak ◽  
Nahid Parna ◽  
Pourya Davoudi ◽  
Majid Khansefid
Keyword(s):  
Genetic Diversity ◽  
Linkage Disequilibrium ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Effective Population ◽  
High Genetic Diversity ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Snp Panel ◽  
Zandi Sheep

Abstract. This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), and runs of homozygosity (ROHs) in one of the major Iranian sheep breeds (Zandi) using 96 samples genotyped with Illumina Ovine SNP50 BeadChip. The amount of LD (r2) for single-nucleotide polymorphism (SNP) pairs in short distances (10–20 kb) was 0.21±0.25 but rapidly decreased to 0.10±0.16 by increasing the distance between SNP pairs (40–60 kb). The Ne of Zandi sheep in past (approximately 3500 generations ago) and recent (five generations ago) populations was estimated to be 6475 and 122, respectively. The ROH-based inbreeding was 0.023. We found 558 ROH regions, of which 37 % were relatively long (> 10 Mb). Compared with the rate of LD reduction in other species (e.g., cattle and pigs), in Zandi, it was reduced more rapidly by increasing the distance between SNP pairs. According to the LD pattern and high genetic diversity of Zandi sheep, we need to use an SNP panel with a higher density than Illumina Ovine SNP50 BeadChip for genomic selection and genome-wide association studies in this breed.

scholarly journals The use of genomic data and imputation methods in dairy cattle breeding

2020 ◽  
Vol 65 (No. 12) ◽  
pp. 445-453
Author(s):  
Anita Klímová ◽  
Eva Kašná ◽  
Karolína Machová ◽  
Michaela Brzáková ◽  
Josef Přibyl ◽  
...  
Keyword(s):  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Phenotypic Data ◽  
Single Nucleotide ◽  
Imputation Methods ◽  
Genome Wide ◽  
Dairy Cattle Breeding ◽  
Combine Information

The inclusion of animal genotype data has contributed to the development of genomic selection. Animals are selected not only based on pedigree and phenotypic data but also on the basis of information about their genotypes. Genomic information helps to increase the accuracy of selection of young animals and thus enables a reduction of the generation interval. Obtaining information about genotypes in the form of SNPs (single nucleotide polymorphisms) has led to the development of new chips for genotyping. Several methods of genomic comparison have been developed as a result. One of the methods is data imputation, which allows the missing SNPs to be calculated using low-density chips to high-density chips. Through imputations, it is possible to combine information from diverse sets of chips and thus obtain more information about genotypes at a lower cost. Increasing the amount of data helps increase the reliability of predicting genomic breeding values. Imputation methods are increasingly used in genome-wide association studies. When classical genotyping and genome-wide sequencing data are combined, this option helps to increase the chances of identifying loci that are associated with economically significant traits.

scholarly journals Non-Mendelian inheritance of SNP markers reveals extensive chromosomal translocations in dioecious hops (Humulus lupulus L.)

2016 ◽  
Author(s):  
Dong Zhang ◽  
Nicholi J. Pitra ◽  
Mark C. Coles ◽  
Edward S. Buckler ◽  
Paul D. Matthews
Keyword(s):  
Candidate Genes ◽  
Association Studies ◽  
Genotyping By Sequencing ◽  
Mendelian Inheritance ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Population Structures ◽  
Wild Accessions

AbstractGenome-wide meiotic recombination structures, sex chromosomes, and candidate genes for sex determination were discovered among Humulus spp. by application of a novel, high-density molecular marker system: ~1.2M single nucleotide polymorphisms (SNPs) were profiled with genotyping-by-sequencing (GBS) among 4512 worldwide accessions, including 4396 cultivars and landraces and 116 wild accessions of hops. Pre-qualified GBS markers were validated by inferences on families, population structures and phylogeny. Candidate genes discovered for several traits, including sex and drought stress-resistance, demonstrate the quality and utility of GBS SNPs for genome-wide association studies (GWAS) and Fst analysis in hops. Most importantly, pseudo-testcross mappings in F1 families delineated non-random linkage of Mendelian and non-Mendelian markers: structures that are indicative of unusual meiotic events which may have driven the evolution and cultivation of hops.

scholarly journals Development of SNP markers for grain yield screening of Brazilian rice cultivars

2020 ◽  
Vol 55 ◽  
Author(s):  
Gabriel Feresin Pantalião ◽  
Rosana Pereira Vianello ◽  
Luíce Gomes Bueno ◽  
João Antônio Mendonça ◽  
Alexandre Siqueira Guedes Coelho ◽  
...  
Keyword(s):  
Grain Yield ◽  
Field Experiments ◽  
Association Studies ◽  
Snp Markers ◽  
Joint Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Productive Potential

Abstract: The objective of this work was to identify and validate single-nucleotide polymorphism (SNP) markers related to grain yield in rice (Oryza sativa) core collection. The genome-wide association studies (GWAS) methodology was applied for genotyping of 541 rice accessions by 167,470 SNPs. The grain yield of these accessions was estimated through the joint analysis of nine field experiments carried out in six Brazilian states. Fifteen SNPs were significantly associated with grain yield, and out of the ten SNPs converted to TaqMan assays, four discriminated the most productive accessions. These markers were used for the screening of rice accessions with favorable alleles. The selected accessions were, then, evaluated in field experiments in target environments, in order to select the most productive ones. This screening reduces the number of accessions evaluated experimentally, making it possible to prioritize those with higher productive potential, which allows of the increase of the number of replicates and, consequently, of the experimental accuracy.

scholarly journals Genome wide association analyses to understand genetic basis of flowering and plant height under three levels of nitrogen application in Brassica juncea (L.) Czern & Coss

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Javed Akhatar ◽  
Anna Goyal ◽  
Navneet Kaur ◽  
Chhaya Atri ◽  
Meenakshi Mittal ◽  
...  
Keyword(s):  
Plant Height ◽  
Indian Subcontinent ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Strong Interactions ◽  
N Availability ◽  
Oilseed Crop ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractTimely transition to flowering, maturity and plant height are important for agronomic adaptation and productivity of Indian mustard (B. juncea), which is a major edible oilseed crop of low input ecologies in Indian subcontinent. Breeding manipulation for these traits is difficult because of the involvement of multiple interacting genetic and environmental factors. Here, we report a genetic analysis of these traits using a population comprising 92 diverse genotypes of mustard. These genotypes were evaluated under deficient (N75), normal (N100) or excess (N125) conditions of nitrogen (N) application. Lower N availability induced early flowering and maturity in most genotypes, while high N conditions delayed both. A genotyping-by-sequencing approach helped to identify 406,888 SNP markers and undertake genome wide association studies (GWAS). 282 significant marker-trait associations (MTA's) were identified. We detected strong interactions between GWAS loci and nitrogen levels. Though some trait associated SNPs were detected repeatedly across fertility gradients, majority were identified under deficient or normal levels of N applications. Annotation of the genomic region (s) within ± 50 kb of the peak SNPs facilitated prediction of 30 candidate genes belonging to light perception, circadian, floral meristem identity, flowering regulation, gibberellic acid pathways and plant development. These included over one copy each of AGL24, AP1, FVE, FRI, GID1A and GNC. FLC and CO were predicted on chromosomes A02 and B08 respectively. CDF1, CO, FLC, AGL24, GNC and FAF2 appeared to influence the variation for plant height. Our findings may help in improving phenotypic plasticity of mustard across fertility gradients through marker-assisted breeding strategies.

scholarly journals Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016 ◽  
Vol 283 (1835) ◽  
pp. 20160569 ◽  
Author(s):  
M. E. Goddard ◽  
K. E. Kemper ◽  
I. M. MacLeod ◽  
A. J. Chamberlain ◽  
B. J. Hayes
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Crop Breeding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

scholarly journals A publicly available repository of ROH islands reveals signatures of selection in different livestock and pet species

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Wim Gorssen ◽  
Roel Meyermans ◽  
Steven Janssens ◽  
Nadine Buys
Keyword(s):  
Association Studies ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Future Studies ◽  
Snp Data ◽  
Animal Populations ◽  
Genome Wide ◽  
Starting Point ◽  
Different Populations ◽  
Signatures Of Selection

Abstract Background Runs of homozygosity (ROH) have become the state-of-the-art method for analysis of inbreeding in animal populations. Moreover, ROH are suited to detect signatures of selection via ROH islands and are used in other applications, such as genomic prediction and genome-wide association studies (GWAS). Currently, a vast amount of single nucleotide polymorphism (SNP) data is available online, but most of these data have never been used for ROH analysis. Therefore, we performed a ROH analysis on large medium-density SNP datasets in eight animal species (cat, cattle, dog, goat, horse, pig, sheep and water buffalo; 442 different populations) and make these results publicly available. Results The results include an overview of ROH islands per population and a comparison of the incidence of these ROH islands among populations from the same species, which can assist researchers when studying other (livestock) populations or when looking for similar signatures of selection. We were able to confirm many known ROH islands, for example signatures of selection for the myostatin (MSTN) gene in sheep and horses. However, our results also included multiple other ROH islands, which are common to many populations and not identified to date (e.g. on chromosomes D4 and E2 in cats and on chromosome 6 in sheep). Conclusions We are confident that our repository of ROH islands is a valuable reference for future studies. The discovered ROH island regions represent a unique starting point for new studies or can be used as a reference for future studies. Furthermore, we encourage authors to add their population-specific ROH findings to our repository.

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