The Global AIMs Nano set: A 31-plex SNaPshot assay of ancestry-informative SNPs

2016 ◽  
Vol 22 ◽  
pp. 81-88 ◽  
Author(s):  
M. de la Puente ◽  
C. Santos ◽  
M. Fondevila ◽  
L. Manzo ◽  
Á. Carracedo ◽  
...  
Keyword(s):  
2016 ◽  
Vol 130 (4) ◽  
pp. 897-903 ◽  
Author(s):  
Yi-Liang Wei ◽  
Qi-Fan Sun ◽  
Qing Li ◽  
Jun-Ling Yi ◽  
Lei Zhao ◽  
...  

2014 ◽  
Vol 05 (07) ◽  
pp. 669-677 ◽  
Author(s):  
Guillaume Girault ◽  
Simon Thierry ◽  
Emeline Cherchame ◽  
Sylviane Derzelle

Life Science ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 54-64
Author(s):  
Mohamad Ikhsan Nurulloh ◽  
Yustinus Ulung Anggraito ◽  
Hidayat Trimarsanto ◽  
Endah Peniati ◽  
R. Susanti

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.


2020 ◽  
Vol 32 (2) ◽  
pp. 155 ◽  
Author(s):  
D. E. Goszczynski ◽  
P. Tinetti ◽  
Y. H. Choi ◽  
K. Hinrichs ◽  
P. J. Ross

During pre-implantation development, embryos go through a critical period of embryonic genome activation (EGA). The timing of EGA is species specific, but little is known in horse embryos. Here, we aimed to characterise EGA in equine embryos produced by intracytoplasmic sperm injection. Embryos were produced by intracytoplasmic sperm injection of oocytes from 3 mares. Two embryos from each mare at each of 8 developmental stages (MII, zygote, 2-cell, 4-cell, 8-cell, 16-cell, morula, and blastocyst) were individually analysed by RNA-seq. Differential expression was evaluated using binomial Wald tests with an absolute logFC (fold change) threshold of 1 in the DESEqn 2R package. We found that EGA occurred in a two-step fashion. Minor EGA took place during the 2-cell to 4-cell transition, and featured up-regulation of 751 genes and discrete down-regulation of 60 genes in 4-cell embryos compared with 2-cell embryos. Differentially upregulated genes were enriched in gene ontology terms related to transcriptional activator activity, homeobox domains, and nucleosome assembly. Major EGA occurred during the 4-cell to 8-cell transition and included the largest number of differentially expressed genes (n=2,023) between consecutive stages. This period also featured the first massive transcript downregulation (n=816). Upregulated genes were enriched in gene ontology terms related to ribosomal assembly, translation, and RNA modification. Additionally, we observed that the number of intronic sequences was significantly higher from the 4-cell stage onward, indicating active transcription in comparison to oocytes, zygotes, and 2-cell embryos. To evaluate the timing of paternal genome activation, we used whole-genome sequencing data from the parents (average genome coverage of 19×) to quantify allele-specific expression. The average number of informative SNPs in exons, i.e. SNPs with alternative homozygous genotypes from the sire (AA mare - BB sire), was 26 128 per mare, corresponding to 7696 genes. Parental-specific transcript abundance was determined for each embryo, with an average of 1,911±865 informative SNPs detected per sample. Paternal alleles were considered expressed when they reached 10% of the maternal count. Across development, paternal transcripts became appreciable at the 4-cell stage, with 14.15±7.60% of the informative SNPs exhibiting paternal expression, and increased thereafter until reaching a maximum of 96.34% at the blastocyst stage. Overall, this work demonstrates that EGA in horse embryos starts at the 4-cell stage and achieves its main activation at the 8-cell stage. Further analysis will be performed to detail paternal vs. maternal gene expression at the different embryonic stages.


2018 ◽  
Vol 39 (1) ◽  
Author(s):  
Clizia Villano ◽  
Salvatore Esposito ◽  
Francesca Carucci ◽  
Massimo Iorizzo ◽  
Luigi Frusciante ◽  
...  

2016 ◽  
Vol 25 (21) ◽  
pp. 5527-5542 ◽  
Author(s):  
Sarah Bouchemousse ◽  
Cathy Liautard-Haag ◽  
Nicolas Bierne ◽  
Frédérique Viard
Keyword(s):  

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