scholarly journals Genetic Diversity and Ancestral Study for Korean Native Pigs Using 60K SNP Chip

Animals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 760 ◽  
Author(s):  
Soo Hyun Lee ◽  
Dong Won Seo ◽  
Eun Seok Cho ◽  
Bong Hwan Choi ◽  
Yong Min Kim ◽  
...  
Keyword(s):  
Genetic Resource ◽  
Principal Component ◽  
Northeastern China ◽  
Nucleotide Polymorphism ◽  
Phylogenetic Tree Analysis ◽  
Single Nucleotide ◽  
Korean Native Pig ◽  
Korean Native Pigs ◽  
Native Pigs ◽  
Nei's Genetic Distance

The Korean native pig (KNP; Sus scrofa coreanus) is an indigenous porcine breed in South Korea considered as a valuable but dwindling genetic resource. Studies using diverse methodologies and genetic markers suggest that this population originated from the Manchu province of Northeastern China and migrated approximately 3000 years ago into the Korean peninsula. This study aimed to verify those findings by performing diversity and ancestral analyses using the 60K single-nucleotide polymorphism (SNP) BeadChip on 891 pigs of 47 breeds worldwide. We also performed principal component analysis (PCA), ancestry analyses, phylogenetic tree analysis using SNPhylo, and linkage disequilibrium analysis. Furthermore, we generated heatmap, obtained Nei’s genetic distance and FST values, and explored the heterozygosity of commercial and native Korean pigs. The results demonstrated that KNP pigs are more closely related to European breeds than to Chinese breeds. In addition, as previous studies have suggested, our admixture analyses indicated that KNP pigs showed distinguishable genetic structure.

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 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 Molecular Fingerprinting and Hybridity Authentication in Cowpea Using Single Nucleotide Polymorphism Based Kompetitive Allele-Specific PCR Assay

2021 ◽  
Vol 12 ◽  
Author(s):  
Patrick Obia Ongom ◽  
Christian Fatokun ◽  
Abou Togola ◽  
Stella Salvo ◽  
Oluwaseye Gideon Oyebode ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Principal Component ◽  
Snp Markers ◽  
Breeding Program ◽  
Molecular Fingerprinting ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Specific Pcr ◽  
Allele Specific ◽  
Allele Specific Pcr

Optimization of a breeding program for increased genetic gain requires quality assurance (QA) and quality control (QC) at key phases of the breeding process. One vital phase in a breeding program that requires QC and QA is the choice of parents and successful hybridizations to combine parental attributes and create variations. The objective of this study was to determine parental diversity and confirm hybridity of cowpea F1 progenies using KASP (Kompetitive Allele-Specific PCR)-based single nucleotide polymorphism (SNP) markers. A total of 1,436 F1 plants were derived from crossing 220 cowpea breeding lines and landraces to 2 elite sister lines IT99K-573-1-1 and IT99K-573-2-1 as male parents, constituting 225 cross combinations. The progenies and the parents were genotyped with 17 QC SNP markers via high-throughput KASP genotyping assay. The QC markers differentiated the parents with mean efficiency of 37.90% and a range of 3.4–82.8%, revealing unique fingerprints of the parents. Neighbor-Joining cladogram divided the 222 parents into 3 clusters. Genetic distances between parents ranged from 0 to 3.74 with a mean of 2.41. Principal component analysis (PCA) depicted a considerable overlap between parents and F1 progenies with more scatters among parents than the F1s. The differentiation among parents and F1s was best contributed to by 82% of the markers. As expected, parents and F1s showed a significant contrast in proportion of heterozygous individuals, with mean values of 0.02 and 0.32, respectively. KASP markers detected true hybridity with 100% success rate in 72% of the populations. Overall, 79% of the putative F1 plants were true hybrids, 14% were selfed plants, and 7% were undetermined due to missing data and lack of marker polymorphism between parents. The study demonstrated an effective application of KASP-based SNP assay in fingerprinting, confirmation of hybridity, and early detection of false F1 plants. The results further uncovered the need to deploy markers as a QC step in a breeding program.

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 Feature Extraction And Classification On Single Nucleotide Polymorphism

2019 ◽  
Vol 1 (2) ◽  
pp. 85-90
Author(s):  
Nur Fatihah Kamarudin ◽  
Zuraini Ali Shah
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Information Gain ◽  
Principal Component ◽  
Peninsular Malaysia ◽  
Nucleotide Polymorphism ◽  
Ancestry Informative Marker ◽  
Informative Marker ◽  
Single Nucleotide ◽  
Malay Population ◽  
Information Gain Ratio

Malay in Peninsular Malaysia can be divided into eight sub-ethnics which are Malay Bugis, Malay, Malay Champa, Malay Jawa, Malay Kelantan, Malay Kedah, Malay Minang and Malay Pattani. Ancestry informative marker (AIM) can be used to represent the eight subethnic of Malay population in Peninsular Malaysia. In this research, single nucleotide polymorphism (SNP) datasets of eight sub-ethnics are analyses in order to obtain the AIM for Malays population in Peninsular Malaysia. However, the dataset may have outlier, missing data and redundancy that may impact the accuracy of the result. Pre-processing data is an important step that will remove the entire problem. Iterative pruning principal component analysis (ipPCA) is one of the techniques that usually use in analysis on genome datasets to extract the information. It can be applied on the high structured data and can improve the resolution of the data. It also used for structure a sub-population. Random Forest and Hidden Naïve Bayes is used to classify the SNP that can be used as AIM. Information Gain Ratio will rank the chosen AIM based on the value of each attribute

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