Human population dispersal “Out of Africa” estimated from linkage disequilibrium and allele frequencies of SNPs

Abstract

Genetic and fossil evidence supports a single, recent (<200,000 yr) origin of modern Homo sapiens in Africa, followed by later population divergence and dispersal across the globe (the ''Out of Africa'' model). However, there is less agreement on the exact nature of this migration event and dispersal of populations relative to one another. We use the empirically observed genetic correlation structure (or linkage disequilibrium) between 242,000 genome-wide single nucleotide polymorphisms (SNPs) in 17 global populations to reconstruct two key parameters of human evolution: effective population size (N e ) and population divergence times (T). A linkage disequilibrium (LD)-based approach allows changes in human population size to be traced over time and reveals a substantial reduction in N e accompanying the ''Out of Africa'' exodus as well as the dramatic re-expansion of non-Africans as they spread across the globe. Secondly, two parallel estimates of population divergence times provide clear evidence of population dispersal patterns ''Out of Africa'' and subsequent dispersal of proto-European and proto-East Asian populations. Estimates of divergence times between European-African and East Asian-African populations are inconsistent with its simplest manifestation: a single dispersal from the continent followed by a split into Western and Eastern Eurasian branches. Rather, population divergence times are consistent with substantial ancient gene flow to the proto-European population after its divergence with proto-East Asians, suggesting distinct, early dispersals of modern H. sapiens from Africa. We use simulated genetic polymorphism data to demonstrate the validity of our conclusions against alternative population demographic scenarios.

Extensive genome-wide autozygosity in the population isolates of Daghestan

“…We chose European, ND-speaking and YRI populations to trace temporal variation of N e (Supplementary Figure 9). Consistent with the earlier study 56 we found a relatively large N e for YRI, with a slight increase around 9000 years ago, and a population size expansion for Europeans for the last 10 000-12 000 years. All ND-speaking populations except the Avars show a steady decline in their effective population sizes.…”

“…r 2 values were binned into 50 genetic distance groups between 0.005 and 0.25 cM in increments of 0.005 cM, and their mean r 2 was used for further calculation of effective population size (N e ). For each population with sample size N ≥ 10 we estimated N e = 1/(4c) × ((1/r 2 ) − 2), where r 2 was adjusted for sample size: (r 2 -1/n) and c is the recombination distance between loci in Morgans 56,57 (1 cM≈1.1-1.2 Mb). The standard error and confidence intervals for N e were derived from separate analysis of each autosome.…”

“…The standard error and confidence intervals for N e were derived from separate analysis of each autosome. 56 As recombination distance between markers is approximately inversely proportional to the number of generations t≈1/(2c), 58 we estimated N e in different time intervals assuming 25 years per generation. In general, the clustering within and general relatedness between populations corresponds approximately to their relative geographical location.…”

Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods

“…Sequencing Malay Project (SSMP) 22 and 36 Indians from the Singapore Sequencing Indian Project (SSIP) 23 were used. These individuals were sequenced on the Illumina HiSeq 2000 at a target depth of 30-fold (Illumina, San Diego, CA, USA), where the alignment and variant calling were performed with CASAVA and SAMtools for the Malay data, and with CASAVA and GATK for the Indians.…”

“…16 Another class of methods infers the TMRCA from full chromosomal information, such as CoalHMM, 17 PSMC, 18 and MSMC. 19 The third class of methods essentially infers the TMRCA on the extent of linkage disequilibrium (LD), population diversity measured by the F ST parameter and population allele frequency, such as the approaches by Hayes and colleagues (abbreviated subsequently as T-LD), 20,21 by McEvoy and colleagues (abbreviated subsequently as T-FST), 22 and DADI. 23 These methods differ by the type of input data required (sequence-level information or summary statistics), and by the assumption around the presence of genetic recombination during migration.…”