Data from: Secondary contact and genomic admixture between rhesus and long-tailed macaques in the Indochina Peninsula

Understanding the process and consequences of hybridization is one of the major challenges in evolutionary biology. A growing body of literature has reported evidence of ancient hybridization events or natural hybrid zones in primates, including humans; however, we still have relatively limited knowledge about the pattern and history of admixture because there have been little studies that simultaneously achieved genome-scale analysis and a geographically extensive sampling of wild populations. Our study applied double-digest restriction site-associated DNA sequencing to samples from the six localities in and around the provisional hybrid zone of rhesus and long-tailed macaques and evaluated population structure, phylogenetic relationships, demographic history, and geographic clines of morphology and allele frequencies. A latitudinal gradient of genetic components was observed, highlighting the transition from rhesus (north) to long-tailed macaque distribution (south) as well as the presence of one northern population of long-tailed macaques exhibiting unique genetic structure. Interspecific gene flow was estimated to have recently occurred after an isolation period, and the migration rate from rhesus to long-tailed macaques was slightly greater than in the opposite direction. Although some rhesus macaque-biased alleles have widely introgressed into long-tailed macaque-populations, the inflection points of allele frequencies have been observed as concentrated around the traditionally recognized interspecific boundary where morphology discontinuously changed; this pattern was more pronounced in the X-chromosome than in autosomes. Thus, due to geographic separation before secondary contact, reproductive isolation could have evolved, contributing to the maintenance of an interspecific boundary and species-specific morphological characteristics.,Data structure: . ├── README.txt # This file │ │ ├── fastsimcoal2 (compressed in zip format) # The data for fastsimcoal2 │ ├── setting # Estimation files (.est) and template files (.tpl) │ │ ├── default # Main analysis │ │ ├── n_her # Rhesus population size is fixed at 239704 (479408 genomes) │ │ ├── n_xue # Rhesus population size is fixed at 71000 (142000 genomes) │ │ ├── p_2fold # SFS projection size is two-hold (40, 50) │ │ └── p_half # SFS projection size if half (10, 13) │ │ │ └── sfs # Multidimensional SFS provided by easySFS.py │ ├── default_bootstrap # Main analysis. 100 bootstrap samples and the original. │ ├── p_2fold # SFS projection size is two-hold (40, 50) │ ├── p_half # SFS projection size if half (10, 13) │ ├── sub1 # Subset 1. Populations close to interspecific boundary (RH-BSS, RH-WTPMH, and LT-WHM) are excluded. │ ├── sub2 # Subset 2. Populations close to and disproportionately-far-away from interspecific boundary (RH-BSS, RH-WTPMH, LT-WHM, and LT-Sumatra) are excluded. │ └── sub3 # Subset 3. Captive populations (RH-China and LT-Sumatra) are excluded. │ │ ├── fineRADstructure (compressed in zip format) # The haplotype data used in fineRADstructure (the oupput of Stacks populations command with --radpainter option) │ ├── autosome.haps.radpainter # All the samples │ └── autosome_wild.haps.radpainter # Wild samples (RH-China and LT-Sumatra are excluded) │ │ ├── geocline (compressed in zip format) # The data and R script used in geographic cline analysis │ ├── genome.csv # Location information for SNPs data │ ├── geocline_functions.R # R script of supportive functions │ ├── mtd.csv # mtDNA data (after Figure 2 of Bunlungsup et al., 2017) │ ├── rtl.csv # Relative tail length data (after Table 1 of Hamada et al., 2015) │ └── ych.csv # Y-chromosome data (after Figure 2 of Bunlungsup et al., 2017) │ │ ├── nj (compressed in zip format) # The input and output of PAUP │ ├── nj_a.dist # Uncorrected P-distance of autosomal SNPs calculated by PAUP. This is used for Neighbor-net analysis in SplitsTree4. │ ├── nj_a.nexus # Nexus of autosome used in PAUP NJ analysis │ ├── nj_a.support.tre # NJ tree with bootstrap support value of autosome │ ├── nj_x.nexus # Nexus of X-chromosome used in PAUP NJ analysis │ ├── nj_x.support.tre # NJ tree with bootstrap support value of X-chromosome │ ├── nj_y.nexus # Nexus of Y-chromosome used in PAUP NJ analysis │ └── nj_y.support.tre # NJ tree with bootstrap support value of Ychromosome │ │ ├── sex_pop_list.txt # Tab-delimited text file of ID, sex, and population │ │ └── vcf_filtered (compressed in zip format) # Filtered vcf files │ ├── autosome.vcf # This is used in population structure analyses. This is also converted to nexus format for phylogenetic analyses using vcf2phylip.py. │ ├── autosome_sfs.vcf # This is used for making SFS (the input for easySFS.py). │ ├── x_chromosome.vcf # This is used in population structure analyses. This is also converted to nexus format for phylogenetic analyses using vcf2phylip.py. │ └── y_chromosome.vcf # This is converted to nexus format for phylogenetic analyses using vcf2phylip.py. │ │ └── vcf_raw (compressed in zip format) # Raw vcf files (the output of Stacks populations command with --vcf option) ├── autosome_raw.vcf ├── x_chromosome_raw.vcf └── y_chromosome_raw.vcf,