DOI: 10.57760/sciencedb.11478
title: Selection increases mitonuclear DNA discordance but reconciles incompatibility in African cattle
title: Selection increases mitonuclear DNA discordance but reconciles incompatibility in African cattle

description: Deviations of ancestry for genes involved in mitonuclear crosstalk in African B. indicus. The datasets include deviations of ancestry for genes involved in mitonuclear crosstalk in African Bos indicus, analyzed using multiple approaches (FDM, FST, RFmix, and Loter). We used BCFtools v.1.8 to obtain four SNP datasets in the region of the four gene subsets, correspondingly. We then calculated Fst values of each SNP datasets based on a sliding window approach with windows of 50 kb and a step of 10 kb using VCFtools v.0.1.17. For Fdm values (degree of local introgression), we also integrated 10 Indian water buffalo (Bubalus bubalus) as outgroup to estimated local introgression for across the four gene subsets of mitonuclear, high-mito, OXPHOS, selective by Fdm (Manual: https://github.com/simonhmartin/genomics_general). We converted vcf files to Geno format parseVCF.py. We adopted ABBABABAwindows.py  to divided the whole genome into segments of 50 kb windows (10 kb sliding) and to estimate Fdm values of each window. Bedtools v.2.29.0 (https://bedtools.readthedocs.io/en/latest/) was used to intersect genome-wide level Fdm values of genome-wide level with windows spanning 500 pb upstream and downstream of genes within each of the four gene subsets. We gained four datasets of Fdm values, corresponding to the four genes subsets involved in mitonuclear crosstalk. Genotype refinement was performed using SHAPEIT v.2.904  along with phasing. Using Loter and RFmix, we identified the origin of each haplotype of African B. indicus form African B. taurus or Asian B. indicus (if the haplotype of the Asian B. indicus value is 0, otherwise, the values is 1), respectively. We then gained each haplotype value covered by each gene subset and calculated the mean ratio of B. taurus ancestry of the region of each gene subset of in 50 kb windows with a 10 kb step by custom scripts. All deviations between each SNP dataset and their genomic background were assessed using the T-test.
description: Deviations of ancestry for genes involved in mitonuclear crosstalk in African B. indicus. The datasets include deviations of ancestry for genes involved in mitonuclear crosstalk in African Bos indicus, analyzed using multiple approaches (FDM, FST, RFmix, and Loter). We used BCFtools v.1.8 to obtain four SNP datasets in the region of the four gene subsets, correspondingly. We then calculated Fst values of each SNP datasets based on a sliding window approach with windows of 50 kb and a step of 10 kb using VCFtools v.0.1.17. For Fdm values (degree of local introgression), we also integrated 10 Indian water buffalo (Bubalus bubalus) as outgroup to estimated local introgression for across the four gene subsets of mitonuclear, high-mito, OXPHOS, selective by Fdm (Manual: https://github.com/simonhmartin/genomics_general). We converted vcf files to Geno format parseVCF.py. We adopted ABBABABAwindows.py  to divided the whole genome into segments of 50 kb windows (10 kb sliding) and to estimate Fdm values of each window. Bedtools v.2.29.0 (https://bedtools.readthedocs.io/en/latest/) was used to intersect genome-wide level Fdm values of genome-wide level with windows spanning 500 pb upstream and downstream of genes within each of the four gene subsets. We gained four datasets of Fdm values, corresponding to the four genes subsets involved in mitonuclear crosstalk. Genotype refinement was performed using SHAPEIT v.2.904  along with phasing. Using Loter and RFmix, we identified the origin of each haplotype of African B. indicus form African B. taurus or Asian B. indicus (if the haplotype of the Asian B. indicus value is 0, otherwise, the values is 1), respectively. We then gained each haplotype value covered by each gene subset and calculated the mean ratio of B. taurus ancestry of the region of each gene subset of in 50 kb windows with a 10 kb step by custom scripts. All deviations between each SNP dataset and their genomic background were assessed using the T-test.