Genomic data reveals large similarities among Canadian and French maternal pig lines

2018 ◽  
Vol 98 (4) ◽  
pp. 809-817 ◽  
Author(s):  
Raphael Boré ◽  
Luiz F. Brito ◽  
Mohsen Jafarikia ◽  
Alban Bouquet ◽  
Laurence Maignel ◽  
...  
Keyword(s):  
Principal Component ◽  
Reference Population ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Very High ◽  
Genomic Relatedness ◽  
Consistency Of Gametic Phase ◽  
Gametic Phase

Combining reference populations from different countries and breeds could be an affordable way to enlarge the size of the reference populations for genomic prediction of breeding values. Therefore, the main objectives of this study were to assess the genetic diversity within and between two Canadian and French pig breeds (Landrace and Yorkshire) and the genomic relatedness among populations to evaluate the feasibility of an across-country reference population for pig genomic selection. A total of 14 756 pigs were genotyped on two single nucleotide polymorphism (SNP) chip panels (∼65K SNPs). A principal component analysis clearly discriminated Landrace and Yorkshire breeds, and also, but to a lesser extent, the Canadian and French purebred pigs of each breed. Linkage disequilibrium (LD) between adjacent SNPs was similar within Yorkshire populations. However, levels of LD were slightly different for Landrace populations. The consistency of gametic phase was very high between Yorkshire populations (0.96 at 0.05 Mb) and high for Landrace (0.88 at 0.05 Mb). Based on consistency of gametic phase, Canadian and French pig maternal lines are genetically close to each other. These results are promising, as they indicate that the accuracy of estimated genomic breeding values may increase by combining reference populations from the two countries.

scholarly journals Simulasi Metode Statistik untuk Seleksi Single Nucleotide Polymorphism pada Populasi Plasmodium

Life Science ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 54-64
Author(s):  
Mohamad Ikhsan Nurulloh ◽  
Yustinus Ulung Anggraito ◽  
Hidayat Trimarsanto ◽  
Endah Peniati ◽  
R. Susanti
Keyword(s):  
Principal Component Analysis ◽  
Single Nucleotide Polymorphism ◽  
Population Structure ◽  
Principal Component ◽  
Selection Method ◽  
Principal Coordinate Analysis ◽  
Neighbor Joining ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Informative Snps

Plasmodium is a pathogen that causes malaria which has high genetic diversity and resistance to antimalarial drugs. Information on the population structure of Plasmodium can be used as molecular markers, one of which is Single Nucleotide Polymorphism (SNP). SNP markers are in large numbers and not entirely informative. The existing method has not been effective in producing informative SNPs, therefore it is necessary to develop an effective SNP selection method. The SNP selection method is developed using FST as the main filter (filter) and combines Linkage Disequilibrium (LD). The population structure of the SNP is known to use Principal Component Analysis (PCA), Principal Coordinate Analysis (PCoA), pairwise FST, and neighbor-joining population trees. Informative SNP criteria known by calculating FST and Minor Allele Frequency (MAF). Statistical methods were tested to determine their effectiveness in producing informative SNPs. The method testing was carried out using genetic data simulation of the Plasmodium population. The results of the study show that the statistical method is effective in producing informative SNPs. The informative SNP criteria are SNPs with MAF 0.2-0.4 and FST 0.1-0.4 and 0.8-1.0.   Plasmodium merupakan patogen penyebab malaria dengan keanekaragaman genetik tinggi dan memiliki resistensi terhadap obat antimalaria. Informasi sturuktur populasi Plasmodium dapat dimanfaatkan sebagai marka molekuler seperti Single Nucleotide Polymorphism (SNP). Marka SNP terdapat dalam jumlah yang banyak dan tidak seluruhnya informatif. Metode yang telah ada belum efektif dalam menghasilkan SNP informatif sehingga perlu dilakukan pengembangan metode seleksi SNP yang efektif. Metode seleksi SNP dikembangkan menggunakan FST sebagai filter (penyaring) utamanya dan gabungkan Linkage Disequilibrium (LD). Struktur populasi dari SNP diketahui menggunakan Principal Component Analysis (PCA), Principal Coordinate Analysis (PCoA), pairwise FST, dan neighbor-joining population tree. Kriteria SNP informatif yang diketahui dengan menghitung FST dan Minor Allele Frequency (MAF). Metode statistika diuji untuk mengetahui keefektifannya dalam menghasilkan SNP informatif. Pengujian metode dilakukan menggunakan simulasi data genetik populasi Plasmodium. Hasil penelitian menunjukkan metode statistika efektif dalam menghasilkan SNP informatif. Kriteria SNP informatif adalah SNP dengan MAF 0.2-0.4 serta FST 0.1-0.4 dan 0.8-1.0.

scholarly journals A study of Genomic Prediction across Generations of Two Korean Pig Populations

Animals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 672 ◽  
Author(s):  
Beatriz Castro Dias Castro Dias Cuyabano ◽  
Hanna Wackel ◽  
Donghyun Shin ◽  
Cedric Gondro
Keyword(s):  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Reference Population ◽  
Relevant Information ◽  
Production Traits ◽  
Genomic Evaluation ◽  
Genomic Breeding ◽  
Breeding Values ◽  
The Relationship ◽  
Dense Marker

Genomic models that incorporate dense marker information have been widely used for predicting genomic breeding values since they were first introduced, and it is known that the relationship between individuals in the reference population and selection candidates affects the prediction accuracy. When genomic evaluation is performed over generations of the same population, prediction accuracy is expected to decay if the reference population is not updated. Therefore, the reference population must be updated in each generation, but little is known about the optimal way to do it. This study presents an empirical assessment of the prediction accuracy of genomic breeding values of production traits, across five generations in two Korean pig breeds. We verified the decay in prediction accuracy over time when the reference population was not updated. Additionally we compared the prediction accuracy using only the previous generation as the reference population, as opposed to using all previous generations as the reference population. Overall, the results suggested that, although there is a clear need to continuously update the reference population, it may not be necessary to keep all ancestral genotypes. Finally, comprehending how the accuracy of genomic prediction evolves over generations within a population adds relevant information to improve the performance of genomic selection.

scholarly journals Using eigenvalues as variance priors in the prediction of genomic breeding values by principal component analysis

2010 ◽  
Vol 93 (6) ◽  
pp. 2765-2774 ◽  
Author(s):  
N.P.P. Macciotta ◽  
G. Gaspa ◽  
R. Steri ◽  
E.L. Nicolazzi ◽  
C. Dimauro ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Genomic Breeding ◽  
Breeding Values

scholarly journals A comparative analysis of proximity measures to determine the Lithuanian population structure

2021 ◽  
Vol 62 ◽  
pp. 86-93
Author(s):  
Alma Molytė ◽  
Alina Urnikytė
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Population Structure ◽  
Comparative Analysis ◽  
Multidimensional Scaling ◽  
Principal Component ◽  
Genetic Data ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Proximity Measures

In this paper the multidimensional scaling, the principal coordinate and principal component methods for the Lithuanian population structure have investigated, taken that the proximity measures are Euclid, Gower, Bray-Curtis, Kulczynski, Jaccard and Morisita. The genome-wide single nucleotide polymorphism genetic data analyzed. A comparative analysis of proximity measures performed. The results of visualization are also presented.

scholarly journals Twins, Tissue, and Time: An Assessment of SNPs and CNVs

2012 ◽  
Vol 15 (6) ◽  
pp. 737-745 ◽  
Author(s):  
Paul Scheet ◽  
Erik A. Ehli ◽  
Xiangjun Xiao ◽  
Catharina E. M. van Beijsterveldt ◽  
Abdel Abdellaoui ◽  
...  
Keyword(s):  
Large Scale ◽  
Deoxyribonucleic Acid ◽  
Dna Analysis ◽  
Tissue Type ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Micro Array ◽  
Very High ◽  
Genotype Inference ◽  
Genotype Concordance

With the desire to assess genetic variation across the lifespan in large-scale collaborative projects, one question is whether inference of copy number (CN) is sensitive to the source of material for deoxyribonucleic acid (DNA) analysis (e.g., blood and buccal) and another question is whether CN is stable as individuals age. Here, we address these questions by applying Affymetrix 6.0 single nucleotide polymorphism (SNP) micro-arrays to 1,472 DNA samples from 710 individuals from the Netherlands Twin Register, including twin and non-twin individuals (372 with buccal and blood derived DNA and 388 with longitudinal data). Similar concordance for CN and genotype inference between samples from the same individual [or from the monozygotic (MZ) co-twins] was found for blood and buccal tissues. There was a small but statistically significant decrease in across-tissue concordance compared with concordance of samples from the same tissue type. No temporal effect was seen on CN variation from the 388 individuals sampled at two time points ranging from 1 to 12 years apart. The majority of our individuals were sampled at age younger than 20 years. Genotype concordance was very high (R2 > 99%) between co-twins from 43 MZ pairs. For 75 dizygotic (DZ) pairs, R2 was ≈65%. CN estimates were highly consistent between co-twins from MZ pairs for both deletions (R2 ≈ 90%) and duplications (R2 ≈ 86%). For DZ, these were similar for within-individual comparisons, but naturally lower between co-twins (R2 ≈ 50–60%). These results suggest that DNA from buccal samples perform as well as DNA from blood samples on the current generation of micro-array technologies.

scholarly journals Mitochondrial DNA single nucleotide polymorphism associated with weight estimated breeding values in Nelore cattle (Bos indicus)

2007 ◽  
Vol 30 (4) ◽  
pp. 1058-1063 ◽  
Author(s):  
Fernando Henrique Biase ◽  
Flávio Vieira Meirelles ◽  
Ricardo Gunski ◽  
Pedro Alejandro Vozzi ◽  
Luiz A.F. Bezerra ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Mitochondrial Dna ◽  
Bos Indicus ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Nelore Cattle
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