scholarly journals Accuracy of Imputation of Microsatellite Markers from a 50K SNP Chip in Spanish Assaf Sheep

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 86
Author(s):  
Héctor Marina ◽  
Aroa Suarez-Vega ◽  
Rocío Pelayo ◽  
Beatriz Gutiérrez-Gil ◽  
Antonio Reverter ◽  
...  
Keyword(s):  
Microsatellite Markers ◽  
Imputation Accuracy ◽  
Optimum Number ◽  
Low Density ◽  
Nucleotide Polymorphisms ◽  
Common Allele ◽  
Single Nucleotide ◽  
Snp Chip ◽  
Imputation Procedure ◽  
Genotype Concordance

Transitioning from traditional to new genotyping technologies requires the development of bridging methodologies to avoid extra genotyping costs. This study aims to identify the optimum number of single nucleotide polymorphisms (SNPs) necessary to accurately impute microsatellite markers to develop a low-density SNP chip for parentage verification in the Assaf sheep breed. The accuracy of microsatellite marker imputation was assessed with three metrics: genotype concordance (C), genotype dosage (length r2), and allelic dosage (allelic r2), for all imputation scenarios tested (0.5–10 Mb microsatellite flanking SNP windows). The imputation accuracy for the three metrics analyzed for all haplotype lengths tested was higher than 0.90 (C), 0.80 (length r2), and 0.75 (allelic r2), indicating strong genotype concordance. The window with 2 Mb length provides the best accuracy for the imputation procedure and the design of an affordable low-density SNP chip for parentage testing. We additionally evaluated imputation performance under two null models, naive (imputing the most common allele) and random (imputing by randomly selecting the allele), which in comparison showed weak genotype concordances (0.41 and 0.15, respectively). Therefore, we describe a precise methodology in the present article to impute multiallelic microsatellite genotypes from a low-density SNP chip in sheep and solve the problem of parentage verification when different genotyping platforms have been used across generations.

scholarly journals Accuracy of Imputation of Microsatellite Markers from an SNP50K Chip in Spanish Assaf Sheep

2020 ◽  
Author(s):  
Hector Marina ◽  
Aroa Suarez-Vega ◽  
Rocio Pelayo ◽  
Beatriz Gutierrez-Gil ◽  
Antonio Reverter ◽  
...  
Keyword(s):  
Microsatellite Markers ◽  
Snp Array ◽  
Cost Effective ◽  
Snp Markers ◽  
Sheep Breed ◽  
Optimum Number ◽  
Low Density ◽  
Snp Chip ◽  
Imputation Procedure ◽  
Genotype Concordance

Abstract Background: Traditional and new genotyping technologies must be combined by applying bridge methodologies that avoid double genotyping costs. This study aims to identify and evaluate a reliable approach to precisely impute microsatellite markers from SNP-chip panels to perform parental verifications in sheep. Moreover, we will assess the optimum number of SNPs necessary to accurately impute microsatellite markers to develop a low-density SNP chip for parentage verification in the Assaf sheep breed.Results: A total of 4,423 animals belonging to the Spanish Assaf sheep breed were genotyped for 19 microsatellites and an ovine custom 49,897 SNP array. The accuracy of microsatellite marker imputation, performed with BEAGLE v5.1 software, was assessed with three metrics, namely, genotype concordance (C), genotype dosage (length r2), and allelic dosage (allelic r2), for all imputation scenarios tested (0.5-10 Mb microsatellite flanking SNP windows). The accuracy of our imputation results for the three metrics analyzed for all haplotype lengths tested was higher than 0.90 (C), 0.80 (length r2), and 0.75 (allelic r2). Considering that the objective of the study was to assess a SNP window length that provides the best accuracy for the microsatellite imputation procedure to design an affordable low-density SNP chip for parentage testing, we considered 2 Mb to be the best SNP haplotype length for further analyses (SNPs/window =74.05, C= 0.970; length r2= 0.952, allelic r2=0.899). We additionally evaluated imputation performance under two null models, naive and random, which showed weak genotype concordance averages in comparison with imputed microsatellites (0.41 and 0.15, respectively).Conclusions: We presented for the first time a precise methodology in dairy sheep to impute multiallelic microsatellite genotypes from biallelic SNP markers. The use of a 2 Mb SNP flanking window for each microsatellite has been shown to achieve high accuracy in the imputation procedure while providing a low-density SNP chip that could be cost-effective. The results from this study will undoubtedly have a significant impact on sheep breeders overcoming the problem of parentage verification when different genotyping platforms have been used across generations.

Development and evaluation of a low-density single-nucleotide polymorphism chip specific to Bos indicus cattle

2020 ◽  
Vol 60 (15) ◽  
pp. 1769
Author(s):  
J. B. S. Ferraz ◽  
X. -L. Wu ◽  
H. Li ◽  
J. Xu ◽  
R. Ferretti ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Genomic Selection ◽  
Bos Taurus ◽  
Imputation Accuracy ◽  
Bos Indicus ◽  
Zebu Cattle ◽  
Low Density ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Snp Chip

Context Genomic selection has been of increasing interest in the genetic improvement of Zebu cattle, particularly for quantitative traits that are difficult or expensive to measure, such as carcass traits and meat tenderness. The success of genomic selection depends on several factors, and at its core is the availability of single-nucleotide polymorphism (SNP) chips that are appropriately designed for Bos indicus cattle. However, the currently available commercial bovine SNP chips are mostly designed for Bos taurus cattle. There are two commercial Bos indicus SNP chips; namely, GeneSeek genomic profiler high-density Bos indicus (GGP-HDi) SNP chip and a low-density (LD) Bos indicus SNP chip (Z chip), but these two Bos indicus SNP chips were built with mixed contents of SNPs for Bos indicus and Bos taurus cattle, due to limited availability of genotype data from Bos indicus cattle. Aims To develop a new GGP indicus 35000 SNP chip specifically for Bos indicus cattle, which has a low cost, but high accuracy of imputation to Illumina BovineHD chips. Methods The design of the chip consisted of 34000 optimally selected SNPs, plus 1000 SNPs pre-reserved for those on the Y chromosome, ‘causative’ mutations for a variety of economically relevant traits, genetic health conditions and International Society for Animal Genetics globally recognised parentage markers for those breeds of cattle. Key results The present results showed that this new indicus LD SNP chip had considerably increased minor allele frequencies in indicus breeds than the previous Z-chip. It demonstrated with high imputation accuracy to HD SNP genotypes in five indicus breeds, and with considerable predictability on 14 growth and reproduction traits in Nellore cattle. Conclusions This new indicus LD chip represented a successful effort to leverage existing knowledge and genotype resources towards the public release of a cost-effective LD SNP chip specifically for Bos indicus cattle, which is expected to replace the previous GGP indicus LD chip and to supplement the existing GGP-HDi 80000 SNP chip. Implications A new SNP chip specifically designed for Bos indicus, with high power of imputation to Illumina BovineHD technology and with excellent coverage of the whole genome, is now available on the market for Bos indicus cattle, and Bos indicus and Bos taurus crosses.

Assessing single nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle

2021 ◽  
Author(s):  
Simon F Lashmar ◽  
Donagh P Berry ◽  
Rian Pierneef ◽  
Farai C Muchadeyi ◽  
Carina Visser
Keyword(s):  
South African ◽  
Clustering Algorithm ◽  
Imputation Accuracy ◽  
Developed Countries ◽  
Genotype Imputation ◽  
Selection Strategy ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Single Nucleotide Polymorphism Selection ◽  
The Mean

Abstract A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen 1) at random, 2) with even genomic dispersion, 3) by maximizing the mean minor allele frequency (MAF), 4) using a combined score of MAF and linkage disequilibrium (LD), 5) using a partitioning-around-medoids (PAM) algorithm, and finally 6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen versus a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) versus 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01<MAF≤0.1) versus high MAF (0.4<MAF≤0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the South African Drakensberger. Based on the results, a genotyping panel consisting of approximately 10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a less than 3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.

Candidate Genes of the 5-Lipoxygenase Pathway in Acute Coronary Syndrome: A Pilot Study

2008 ◽  
Vol 9 (4) ◽  
pp. 280-292 ◽  
Author(s):  
Shu-Fen Wung ◽  
Bradley E. Aouizerat
Keyword(s):  
Acute Coronary Syndrome ◽  
Pilot Study ◽  
Nucleotide Polymorphisms ◽  
Common Allele ◽  
Lipoxygenase Pathway ◽  
Single Nucleotide ◽  
Coronary Syndrome ◽  
Increased Risk ◽  
Caucasian Patients ◽  
Alox5ap Gene

Purpose. The purpose of this pilot study was to examine arachidonate 5-lipoxygenase (ALOX5) and ALOX5-activating protein (ALOX5AP) gene variations in patients with and without acute coronary syndrome (ACS). Methodology. Four and six single nucleotide polymorphisms spanning the ALOX5 and ALOX5AP genes, respectively, were genotyped in 19 non-Hispanic Caucasian patients with ACS and 27 controls. Results. Presence of the common allele of rs9508835 (ALOX5AP) and the minor allele of rs2029253 (ALOX5) were associated with ACS. After adjustment for age, being a carrier of the rs9508835 common allele was associated with an increased risk of ACS (odds ratio = 2.86). Relevance for nursing practice. Through the inhibition of the ALOX5AP gene by downregulation of the leukotriene pathway, the risk of ACS may be decreased in individuals that carry susceptibility allele(s). Knowledge of the genetic basis of treatments that downregulate the leukotriene pathway may prove essential to the care of individuals with ACS.

scholarly journals IDENTIFICATION OF SINGLE NUCLEOTIDE POLYMORPHISMS ON CATTLE BREEDS IN INDONESIA USING BOVINE 50K

2016 ◽  
Vol 16 (2) ◽  
pp. 59
Author(s):  
Puji Lestari ◽  
Habib Rijzaani ◽  
Dani Satyawan ◽  
Anneke Anggraeni ◽  
Dwinita Wikan Utami ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Beef Cattle ◽  
Dairy Cattle ◽  
Genetic Relatedness ◽  
Bovine Genome ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Snp Chip ◽  
Cattle Breeds ◽  
Base Extension

<p>Single nucleotide polymorphisms (SNPs) abundant in bovine genome influence genetic variation in biological mechanism. The study aimed to identify SNPs on Indonesian cattle breeds and analyze their genetic diversity using Bovine 50K SNP chip. Twenty eight "Ongole Grade" (OG) beef cattle and 20 "Holstein Friesian" (HF) dairy cattle were used for the Infinium II assay test. This assay included amplification of genomic DNA, fragmenta-tion, precipitation, resuspension, hybridization, processing bead chip for single-base extension, and imaging at iScan. Data and clusters were analyzed using GenomeStudio software. The Bovine 50K SNP chip containing 54,609 SNPs was observed spanning all chromosomes of bovine genome. Genotyping for the total SNPs was successfull based on Call Rate, GeneCall and GeneTrain scores. Most SNP markers had alleles that shared among the individuals or breeds, or had specific alleles at distinctive frequencies. Minor allele frequency (MAF) spreads equally with intervals of 0-0.5. The breeds of OG and HF tended to be separated in different clusters without considering their genetic history and twin or normal. This result suggests that most individuals are closely related to one another, regardless of the same breed. Some genes identified on chromosomes 3, 4, 5, 7, 13, 17 and 18 were located in the loci/regions that contained SNPs with specific alleles of either HF or OG breed. These SNPs were more powerful for differentiation of beef cattle and dairy cattle than among individuals in the same breed. These SNP variations and genetic relatedness among individuals and breeds serve basic information for cattle breeding in Indonesia.</p>

scholarly journals Distinguishing Between Nile Tilapia Strains Using a Low-Density Single-Nucleotide Polymorphism Panel

2020 ◽  
Vol 11 ◽  
Author(s):  
Matthew G. Hamilton ◽  
Curtis E. Lind ◽  
Benoy K. Barman ◽  
Ravelina R. Velasco ◽  
Ma. Jodecel C. Danting ◽  
...  
Keyword(s):  
Nile Tilapia ◽  
Molecular Genetic ◽  
Genotyping By Sequencing ◽  
The Philippines ◽  
Primary Objective ◽  
Small Scale ◽  
Low Density ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genetically Improved

Nile tilapia (Oreochromis niloticus) is among the most important finfish in aquaculture, particularly in Asia. Numerous genetically improved strains of Nile tilapia have been developed and disseminated through formal and informal channels to hatcheries, many of which operate at a relatively small scale in developing countries. The primary objective of this study was to assess the extent to which molecular genetic tools can identify different and interrelated strains of Nile tilapia in Bangladesh and the Philippines, two globally significant producers. A tool was developed using a low-density panel of single-nucleotide polymorphisms (SNPs), genotyping-by-sequencing and discriminant analysis of principal components (DAPC). When applied to 2,057 samples from 205 hatcheries in Bangladesh and the Philippines, for hatcheries where the hatchery-identified strain was one of the sampled core populations used to develop the tool, hatchery-identified and DAPC-assigned hatchery-level strains were in agreement in 74.1% of cases in Bangladesh and 80.6% of cases in the Philippines. The dominant hatchery-identified and DAPC-assigned strains were GIFT, in Bangladesh, and GET-ExCEL—a composite strain partially derived from GIFT—in the Philippines.

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