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 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 Genetic Diversity, Population Structure, and Andean Introgression in Brazilian Common Bean Cultivars after Half a Century of Genetic Breeding

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1298
Author(s):  
Caléo Panhoca de Almeida ◽  
Jean Fausto de Carvalho Paulino ◽  
Sérgio Augusto Morais Carbonell ◽  
Alisson Fernando Chiorato ◽  
Qijian Song ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Common Bean ◽  
Gene Diversity ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Association Mapping Approach

Brazil is the largest consumer and third highest producer of common beans (Phaseolus vulgaris L.) worldwide. Since the 1980s, the commercial Carioca variety has been the most consumed in Brazil, followed by Black and Special beans. The present study evaluates genetic diversity and population structure of 185 Brazilian common bean cultivars using 2827 high-quality single-nucleotide polymorphisms (SNPs). The Andean allelic introgression in the Mesoamerican accessions was investigated, and a Carioca panel was tested using an association mapping approach. The results distinguish the Mesoamerican from the Andean accessions, with a prevalence of Mesoamerican accessions (94.6%). When considering the commercial classes, low levels of genetic differentiation were seen, and the Carioca group showed the lowest genetic diversity. However, gain in gene diversity and allelic richness was seen for the modern Carioca cultivars. A set of 1060 ‘diagnostic SNPs’ that show alternative alleles between the pure Mesoamerican and Andean accessions were identified, which allowed the identification of Andean allelic introgression events and shows that there are putative introgression segments in regions enriched with resistance genes. Finally, genome-wide association studies revealed SNPs significantly associated with flowering time, pod maturation, and growth habit, showing that the Carioca Association Panel represents a powerful tool for crop improvements.

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 A Genomics Resource for Genetics, Physiology, and Breeding of West African Sorghum

2020 ◽  
Author(s):  
Jacques M. Faye ◽  
Fanna Maina ◽  
Eyanawa A. Akata ◽  
Bassirou Sine ◽  
Cyril Diatta ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
West Africa ◽  
Association Studies ◽  
Crop Improvement ◽  
West African ◽  
Gene Pools ◽  
Genome Wide Association Studies ◽  
High Genetic Diversity ◽  
Canonical Height ◽  
Genome Wide

AbstractLocal landrace and breeding germplasm is a useful source of genetic diversity for regional and global crop improvement initiatives. Sorghum (Sorghum bicolor L. Moench) in West Africa has diversified across a mosaic of cultures and end-uses, and along steep precipitation and photoperiod gradients. To facilitate germplasm utilization, a West African sorghum association panel (WASAP) of 756 accessions from national breeding programs of Niger, Mali, Senegal, and Togo was assembled and characterized. Genotyping-by-sequencing was used to generate 159,101 high-quality biallelic SNPs, with 43% in intergenic regions and 13% in genic regions. High genetic diversity was observed within the WASAP (π = 0.00045), only slightly less than in a global diversity panel (π = 0.00055). Linkage disequilibrium decayed to background level (r2 < 0.1) by ~50 kb in the WASAP. Genome-wide diversity was structured both by botanical type, and by populations within botanical type, with eight ancestral populations identified. Most populations were distributed across multiple countries, suggesting several potential common gene pools across the national programs. Genome-wide association studies of days to flowering and plant height revealed eight and three significant quantitative trait loci (QTL), respectively, with major height QTL at canonical height loci Dw3 and SbHT7.1. Colocalization of two of eight major flowering time QTL with flowering genes previously described in US germplasm (Ma6 and SbCN8) suggests that photoperiodic flowering in WA sorghum is conditioned by both known and novel genes. This genomic resource provides a foundation for genomics-enabled breeding of climate-resilient varieties in West Africa.

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.

scholarly journals Impact of Pre and Post Variant Filtration Strategies on Imputation

2020 ◽  
Author(s):  
Celine Charon ◽  
Rodrigue Allodji ◽  
Vincent Meyer ◽  
Jean-François Deleuze
Keyword(s):  
Quality Control ◽  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Direct Effects ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Conservative Post

Abstract Quality control methods for genome-wide association studies and fine mapping are commonly used for imputation, however, they result in loss of many single nucleotide polymorphisms (SNPs). To investigate the consequences of filtration on imputation, we studied the direct effects on the number of markers, their allele frequencies, imputation quality scores and post-filtration events. We pre-phrased 1,031 genotyped individuals from diverse ethnicities and compared the imputed variants to 1,089 NCBI recorded individuals for additional validation.Without variant pre-filtration based on quality control (QC), we observed no impairment in the imputation of SNPs that failed QC whereas with pre-filtration there was an overall loss of information. Significant differences between frequencies with and without pre-filtration were found only in the range of very rare (5E-04-1E-03) and rare variants (1E-03-5E-03) (p < 1E-04). Increasing the post-filtration imputation quality score from 0.3 to 0.8 reduced the number of single nucleotide variants (SNVs) <0.001 2.5 fold with or without QC pre-filtration and halved the number of very rare variants (5E-04). As a result, to maintain confidence and enough SNVs, we propose here a 2-step post-filtration approach to increase the number of very rare and rare variants compared to conservative post-filtration methods.

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