scholarly journals Linkage disequilibrium and haplotype block patterns in popcorn populations

2019 ◽  
Author(s):  
Andréa Carla Bastos Andrade ◽  
José Marcelo Soriano Viana ◽  
Helcio Duarte Pereira ◽  
Vitor Batista Pinto ◽  
Fabyano Fonseca e Silva
Keyword(s):  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Association Studies ◽  
Breeding Population ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Evolutionary Aspects

AbstractLinkage disequilibrium (LD) analysis provides information on evolutionary aspects of the populations and allows selecting populations and single nucleotide polymorphisms (SNPs) for association studies. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy with genomic selection. The objectives of this study were to compare the degree of LD, the LD decay, the LD decay extent, and the number and length of haplotype blocks in the populations and to elaborate the first LD map for maize, for elucidating if the maize chromosomes also had a pattern of interspaced regions of high and low rates of recombination. We used a biparental temperate population, a tropical synthetic, and a tropical breeding population, genotyped for approximately 75,000 SNPs. The level of LD expressed by the r2 values is surprisingly low (0.02, 0.04, and 0.04), but comparable to some non-isolated human populations. The general evidence is that the synthetic is the population with higher LD. It is not expected a significant advantage of haplotype-based association study and along generations genomic selection due to the reduced number of SNPs in the haplotype blocks (2 to 3). The results concerning LD decay (rapid decay after 5-10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. Our most important result is that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simple simulated LD map provides evidence that this pattern can reflect regions with differences of allele frequencies and LD level (expressed by D’) and not regions with high and low rates of recombination.

scholarly journals Genome-wide patterns of population structure and linkage disequilibrium in farmed Nile tilapia (Oreochromis niloticus)

2019 ◽  
Author(s):  
Grazyella M. Yoshida ◽  
Agustín Barria ◽  
Katharina Correa ◽  
Giovanna Cáceres ◽  
Ana Jedlicki ◽  
...  
Keyword(s):  
Population Structure ◽  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Oreochromis Niloticus ◽  
Nile Tilapia ◽  
Population Genomics ◽  
Association Studies ◽  
Demographic History ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractNile tilapia (Oreochromis niloticus) is one of the most produced farmed fish in the world and represents an important source of protein for human consumption. Farmed Nile tilapia populations are increasingly based on genetically improved stocks, which have been established from admixed populations. To date, there is scarce information about the population genomics of farmed Nile tilapia, assessed by dense single nucleotide polymorphism (SNP) panels. The patterns of linkage disequilibrium (LD) may affect the success of genome-wide association studies (GWAS) and genomic selection and can also provide key information about demographic history of farmed Nile tilapia populations. The objectives of this study were to provide further knowledge about the population structure and LD patterns, as well as, estimate the effective population size (Ne) for three farmed Nile tilapia populations, one from Brazil (POP A) and two from Costa Rica (POP B and POP C). A total of 55, 56 and 57 individuals from POP A, POP B and POP C, respectively, were genotyped using a 50K SNP panel selected from a whole-genome sequencing (WGS) experiment. Two principal components explained about 20% of the total variation and clearly discriminated between the three populations. Population genetic structure analysis showed evidence of admixture, especially for POP C. The contemporary Ne values calculated based to LD values, ranged from 71 to 141. No differences were observed in the LD decay among populations, with a rapid decrease of r2 when increasing inter-marker distance. Average r2 between adjacent SNP pairs ranged from 0.03 to 0.18, 0.03 to 0.17 and 0.03 to 0.16 for POP A, POP B and POP C, respectively. Based on the number of independent chromosome segments in the Nile tilapia genome, at least 4.2 K SNP are required for the implementation of GWAS and genomic selection in farmed Nile tilapia populations.

scholarly journals Approximately independent linkage disequilibrium blocks in human populations

2015 ◽  
Author(s):  
Tomaz Berisa ◽  
Joseph K. Pickrell
Keyword(s):  
Linkage Disequilibrium ◽  
Human Genome ◽  
Association Studies ◽  
Automated Analysis ◽  
Genome Wide Association ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Multiple Genome ◽  
Genome Wide

We present a method to identify approximately independent blocks of linkage disequilibrium (LD) in the human genome. These blocks enable automated analysis of multiple genome-wide association studies.

scholarly journals Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle

2018 ◽  
Vol 63 (No. 2) ◽  
pp. 61-69 ◽  
Author(s):  
M.M.I. Salem ◽  
G. Thompson ◽  
S. Chen ◽  
A. Beja-Pereira ◽  
J. Carvalheira
Keyword(s):  
Linkage Disequilibrium ◽  
Haplotype Block ◽  
Association Studies ◽  
Physical Distance ◽  
Allelic Association ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Haplotype Blocks

The objectives of this study were to estimate linkage disequilibrium (LD), describe and scan a haplotype block for the presence of genes that may affect milk production traits in Portuguese Holstein cattle. Totally 526 animals were genotyped using the Illumina BovineSNP50 BeadChip, which contained a total of 52 890 single nucleotide polymorphisms (SNPs). The final set of markers remaining after considering quality control standards consisted of 37 031 SNPs located on 29 autosomes. The LD parameters historical recombinations through allelic association (D') and squared correlation coefficient between locus alleles frequencies ( r<sup>2</sup>) were estimated and haplotype block analyses were performed using the Haploview software. The averages of D' and r<sup>2</sup> values were 0.628 and 0.122, respectively. The LD value decreased with increasing physical distance. The D' and r<sup>2</sup> values decreased respectively from 0.815 and 0.283 at the distance of 0–30 kb to 0.578 and 0.090 at the distance of 401–500 kb. The identified total number of blocks was 969 and consisted of 4259 SNPs that covered 159.06 Mb (6.24% of the total genome) on 29 autosomes. Several genes inside the haplotype blocks were detected; CSN1S2 gene in haplotype block 51 on BTA 6, IL6 and B4GALT1 genes in haplotype blocks 6 and 33 on BTA 8, IL1B and ID2 genes in haplotype blocks 19 and 29 on BTA 11, and DGAT1 gene in haplotype block 1 on BTA 14. The extension of LD using BovineSNP50 BeadChip did not exceed 500 kb and its parameters r<sup>2</sup> and D’ were less than 0.2 and 0.70, respectively, after 70–100 kb. Consequently, the 50K BeadChip would have a poor power in genome wide association studies at distances between adjacent markers lower than 70 kb.

scholarly journals Pharmacogenomics of Lithium Response in Bipolar Disorder

2021 ◽  
Vol 14 (4) ◽  
pp. 287
Author(s):  
Courtney M. Vecera ◽  
Gabriel R. Fries ◽  
Lokesh R. Shahani ◽  
Jair C. Soares ◽  
Rodrigo Machado-Vieira
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Mood Stabilizer ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Lithium Response ◽  
Genetic Loading ◽  
Long Non Coding Rna

Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.

scholarly journals Transcriptional Regulation of RUNX1: An Informatics Analysis

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1175
Author(s):  
Amarni L. Thomas ◽  
Judith Marsman ◽  
Jisha Antony ◽  
William Schierding ◽  
Justin M. O’Sullivan ◽  
...  
Keyword(s):  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Runx1 Gene ◽  
Gene Regulatory Elements ◽  
Important Regulator ◽  
Aml1 Gene ◽  
Regulatory Landscape

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.

scholarly journals Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders

2021 ◽  
Author(s):  
Robin N Beaumont ◽  
Isabelle K Mayne ◽  
Rachel M Freathy ◽  
Caroline F Wright
Keyword(s):  
Birth Weight ◽  
Statistical Power ◽  
Developmental Disorders ◽  
Association Studies ◽  
Later Life ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Causal Genes

Abstract Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.

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 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.

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