Genomic breed composition of Ningxiang pig via different SNP panels

Abstract Genomic prediction has become the new standard for genetic improvement programs, and currently, there is a desire to implement this technology for the evaluation of Angus cattle in Brazil. Thus, the main objective of this study was to assess the feasibility of evaluating young Brazilian Angus (BA) bulls and heifers for 12 routinely recorded traits using single-step genomic BLUP (ssGBLUP) with and without genotypes from American Angus (AA) sires. The second objective was to obtain estimates of effective population size (Ne) and linkage disequilibrium (LD) in the Brazilian Angus population. The dataset contained phenotypic information for up to 277,661 animals belonging to the Promebo® breeding program, pedigree for 362,900, of which 1,386 were genotyped for 50k, 77k, and 150k SNP panels. After imputation and quality control, 61,666 SNP were available for the analyses. In addition, genotypes from 332 American Angus (AA) sires widely used in Brazil were retrieved from the AA Association database to be used for genomic predictions. Bivariate animal models were used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out with the linear regression method (LR) using young-genotyped animals born between 2013 and 2015 without phenotypes in the reduced dataset and with records in the complete dataset. Validation animals were further split into progeny of BA and AA sires to evaluate if their progenies would benefit by including genotypes from AA sires. The Ne was 254 based on pedigree and 197 based on LD, and the average LD (±SD) and distance between adjacent SNPs across all chromosomes was 0.27 (±0.27) and 40743.68 bp, respectively. Prediction accuracies with ssGBLUP outperformed BLUP for all traits, improving accuracies by, on average, 16% for BA young bulls and heifers. The GEBV prediction accuracies ranged from 0.37 (total maternal for weaning weight and tick count) to 0.54 (yearling precocity) across all traits, and dispersion (LR coefficients) fluctuated between 0.92 and 1.06. Inclusion of genotyped sires from the AA improved GEBV accuracies by 2%, on average, compared to using only the BA reference population. Our study indicated that genomic information could help to improve GEBV accuracies and hence genetic progress in the Brazilian Angus population. The inclusion of genotypes from American Angus sires heavily used in Brazil just marginally increased the GEBV accuracies for selection candidates.

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Genetic Characterization of Cupped Oyster Resources in Europe Using Informative Single Nucleotide Polymorphism (SNP) Panels

Genes ◽

10.3390/genes11040451 ◽

2020 ◽

Vol 11 (4) ◽

pp. 451

Author(s):

Sylvie Lapègue ◽

Serge Heurtebise ◽

Florence Cornette ◽

Erwan Guichoux ◽

Pierre-Alexandre Gagnaire

Keyword(s):

Severe Disease ◽

Interspecific Gene Flow ◽

Crassostrea Angulata ◽

The Pacific ◽

Genetic Diversity And Structure ◽

Cupped Oyster ◽

Evolutionary Genomic ◽

Genome Divergence ◽

Snp Panels

The Pacific oyster, Crassostrea gigas, was voluntarily introduced from Japan and British Columbia into Europe in the early 1970s, mainly to replace the Portuguese oyster, Crassostrea angulata, in the French shellfish industry, following a severe disease outbreak. Since then, the two species have been in contact in southern Europe and, therefore, have the potential to exchange genes. Recent evolutionary genomic works have provided empirical evidence that C. gigas and C. angulata exhibit partial reproductive isolation. Although hybridization occurs in nature, the rate of interspecific gene flow varies across the genome, resulting in highly heterogeneous genome divergence. Taking this biological property into account is important to characterize genetic ancestry and population structure in oysters. Here, we identified a subset of ancestry-informative makers from the most differentiated regions of the genome using existing genomic resources. We developed two different panels in order to (i) easily differentiate C. gigas and C. angulata, and (ii) describe the genetic diversity and structure of the cupped oyster with a particular focus on French Atlantic populations. Our results confirm high genetic homogeneity among Pacific cupped oyster populations in France and reveal several cases of introgressions between Portuguese and Japanese oysters in France and Portugal.

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Development and evaluation of SNP panels for the detection of hybridization between wild and escaped Atlantic salmon (Salmo salar) in the western Atlantic

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2017-0394 ◽

2019 ◽

Vol 76 (5) ◽

pp. 695-704 ◽

Cited By ~ 5

Author(s):

Brendan F. Wringe ◽

Eric C. Anderson ◽

Nicholas W. Jeffery ◽

Ryan R.E. Stanley ◽

Ian R. Bradbury

Keyword(s):

Atlantic Salmon ◽

Salmo Salar ◽

Wild Populations ◽

Western Atlantic ◽

Farmed Salmon ◽

Atlantic Salmon Salmo Salar ◽

Hybrid Class ◽

Snp Panels ◽

The Stability ◽

Development And Validation

Hybridization between wild and escaped cultured Atlantic salmon (Salmo salar) can threaten the stability and persistence of locally adapted wild populations. Here we describe the development and validation of a genomic-based approach to quantify recent hybridization between escapee and wild salmon in the western Atlantic. Based on genome-wide single nucleotide polymorphism (SNP) scans of wild and cultured salmon, collectively diagnostic panels were created for Newfoundland and the Canadian Maritimes. These panels were capable of both discriminating hybrids from nonhybrids and of correctly assigning individuals to hybrid class (i.e., pure wild, pure farm, F1, F2, and backcrosses) with a high degree of accuracy (Newfoundland 96 SNPs > 90%, Maritimes 720 SNPs > 80%). These genomic panels permit the assessment of the impacts of past and future farmed salmon escape events on wild populations and can inform the protection and conservation of wild Atlantic salmon genetic integrity in the western Atlantic.

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Strategies for within-litter selection of piglets using ultra-low density SNP panels

Livestock Science ◽

10.1016/j.livsci.2018.12.027 ◽

2019 ◽

Vol 220 ◽

pp. 173-179

Author(s):

Valdecy Aparecida Rocha da Cruz ◽

Luiz F. Brito ◽

Flávio S. Schenkel ◽

Hinayah Rojas de Oliveira ◽

Mohsen Jafarikia ◽

...

Keyword(s):

Low Density ◽

Snp Panels ◽

Selection Of

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AncestrySNPminer: A bioinformatics tool to retrieve and develop ancestry informative SNP panels

Genomics ◽

10.1016/j.ygeno.2012.05.003 ◽

2012 ◽

Vol 100 (1) ◽

pp. 57-63 ◽

Cited By ~ 16

Author(s):

Sushil Amirisetty ◽

Gurjit K. Khurana Hershey ◽

Tesfaye M. Baye

Keyword(s):

Bioinformatics Tool ◽

Snp Panels

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Massively parallel sequencing of customised forensically informative SNP panels on the MiSeq

Electrophoresis ◽

10.1002/elps.201600190 ◽

2016 ◽

Vol 37 (21) ◽

pp. 2832-2840 ◽

Cited By ~ 11

Author(s):

Bhavik Mehta ◽

Runa Daniel ◽

Chris Phillips ◽

Stephen Doyle ◽

Gareth Elvidge ◽

...

Keyword(s):

Massively Parallel Sequencing ◽

Massively Parallel ◽

Parallel Sequencing ◽

Snp Panels

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Genomic selection for female reproduction in Australian tropically adapted beef cattle

Animal Production Science ◽

10.1071/an13016 ◽

2014 ◽

Vol 54 (1) ◽

pp. 16 ◽

Cited By ~ 18

Author(s):

Y. D. Zhang ◽

D. J. Johnston ◽

S. Bolormaa ◽

R. J. Hawken ◽

B. Tier

Keyword(s):

Genomic Selection ◽

Cross Validation ◽

Population Data ◽

Northern Australia ◽

Female Reproduction ◽

Genetic Complexity ◽

Reproduction Traits ◽

Experimental Populations ◽

Snp Panels ◽

Genomic Predictions

The usefulness of genomic selection was assessed for female reproduction in tropically adapted breeds in northern Australia. Records from experimental populations of Brahman (996) and Tropical Composite (1097) cattle that had had six calving opportunities were used to derive genomic predictions for several measures of female fertility. These measures included age at first corpus luteum (AGECL), at first calving and subsequent postpartum anoestrous interval and measures of early and lifetime numbers of calves born or weaned. In a second population, data on pregnancy and following status (anoestrous or pregnancy) were collected from 27 commercial herds from northern Australia to validate genomic predictions. Cows were genotyped with a variety of single nucleotide polymorphism (SNP) panels and, where necessary, genotypes imputed to the highest density (729 068 SNPs). Genetic parameters of subsets of the complete data were estimated. These subsets were used to validate genomic predictions using genomic best linear unbiased prediction using both univariate cross-validation and bivariate analyses. Estimated heritability ranged from 0.56 for AGECL to 0.03 for lifetime average calving rate in the experimental cows, and from 0.09 to 0.25 for early life reproduction traits in the commercial cows. Accuracies of predictions were generally low, reflecting the limited number of data in the experimental populations. For AGECL and postpartum anoestrous interval, the highest accuracy was 0.35 for experimental Brahman cows using five-fold univariate cross-validation. Greater genetic complexity in the Tropical Composite cows resulted in the corresponding accuracy of 0.23 for AGECL. Similar level of accuracies (from univariate and bivariate analyses) were found for some of the early measures of female reproduction in commercial cows, indicating that there is potential for genomic selection but it is limited by the number of animals with phenotypes.

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KinLinks: Software Toolkit for Kinship Analysis and Pedigree Generation from HTS Datasets

10.1101/046938 ◽

2016 ◽

Cited By ~ 2

Author(s):

Anna Shcherbina ◽

Darrell O. Ricke ◽

Eric Schwoebel ◽

Tara Boettcher ◽

Christina Zook ◽

...

Keyword(s):

High Throughput Sequencing ◽

Software Tool ◽

Kinship Analysis ◽

Fully Integrated ◽

Training Models ◽

Familial Relationships ◽

Sequencing Technologies ◽

Snp Panels ◽

Dna Profiles ◽

Multiple Samples

AbstractThe ability to predict familial relationships from source DNA in multiple samples has a number of forensic and medical applications. Kinship testing of suspect DNA profiles against relatives in a law enforcement database can provide valuable investigative leads, determination of familial relationships can inform immigration decisions, and remains identification can provide closure to families of missing individuals. The proliferation of High-Throughput Sequencing technologies allows for enhanced capabilities to accurately predict familial relationships to the third degree and beyond. KinLinks, developed by MIT Lincoln Laboratory, is a software tool that predicts pairwise relationships and reconstructs kinship pedigrees for multiple input samples using single-nucleotide polymorphism (SNP) profiles. The software has been trained and evaluated on a set of 175 subjects (30,450 pairwise relationships), consisting of three multi-generational families and 52 geographically diverse subjects. Though a panel of 5396 SNPs was selected for kinship prediction, KinLinks is highly modular, allowing for the substitution of expanded SNP panels and additional training models as sequencing capabilities continue to progress. KinLinks builds on the SNP-calling capabilities of Sherlocks Toolkit, and is fully integrated with the Sherlocks Toolkit pipeline.

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