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Simulasi Metode Statistik untuk Seleksi Single Nucleotide Polymorphism pada Populasi Plasmodium
Author(s) -
Mohamad Ikhsan Nurulloh,
Yustinus Ulung Anggraito,
Hidayat Trimarsanto,
Endah Peniati,
Retno Dwi Susanti
Publication year - 2019
Publication title -
life science/life science
Language(s) - English
Resource type - Journals
eISSN - 2528-5009
pISSN - 2252-6277
DOI - 10.15294/lifesci.v8i1.29990
Subject(s) - single nucleotide polymorphism , biology , snp , genetics , linkage disequilibrium , population , tag snp , genotype , gene , medicine , environmental health
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.

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