Revisiting the demographic history of Central African populations from a genetic perspective

Abstract

Africa is the continent of our species’ origin and the deep history of humans is represented by African genetic variation. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter-gatherers and that the world’s deepest population divergences occur among these groups. In this review, we look back at a study published by Cavalli-Sforza and colleagues in 1969 entitled “Studies on African Pygmies. I. A pilot investigation of Babinga Pygmies in the Central African Republic (with an analysis of genetic distances)”. The study analyzed 19 classical polymorphisms and found that the deepest divergences in African populations were represented by hunter-gatherer groups such as the southern African San and the central African rainforest hunter-gatherers. We repeated the original analyses from Cavalli-Sforza et al. [1] with about 22 thousand times more genome-wide genetic markers in populations similar to those included in the original study. Our high-resolution analyses gave similar results regarding the relationships of early-diverging African populations compared to the classical polymorphism analyses. This finding, however, does not imply that research has stagnated and that developments in technology and genetic methods over the last fifty years delivered no additional information regarding African history and adaptation. We review how technology and population genetic methods have advanced to give more detailed inferences about population structure, migrations, admixture patterns, timing of admixture, sex-biased admixture, and inferences of selection and adaptive introgression in rainforest hunter-gatherers and other African populations. We also comment on how sequencing of ancient DNA has influenced findings and deliberate on the progress and development of more complex models of African history, including alternatives to tree-models and the inference of possible archaic admixture in African populations. We review the growing complexity of our picture of population history in central Africa and Africa as a whole, emerging from genomic studies and other disciplines investigating human population history and adaptation. While data and knowledge are accumulating, certain populations and areas remain underrepresented in genomic research. Their inclusion, possibly also through ancient DNA studies, together with new methods of analysis and the testing of representative models of deep population history in Africa, will help to build a more complete picture of past population history in Africa. Based on “Cavalli-Sforza LL, Zonta LA, Nuzzo F, Bernini L, de Jong WW, Meera Khan P, Ray AK, Went LN, Siniscalco M, Nijenhuis LE, van Loghem E, Modiano G. Studies on African Pygmies. I. A pilot investigation of Babinga Pygmies in the Central African Republic (with an analysis of genetic distances). Am J Hum Genet. 1969 May;21(3):252-274”.

Ancient tree-topologies and gene-flow processes among human lineages in Africa

“…Overall, Southern African Khoe-San populations exhibit the highest mean number of biallelic SNPs as well as numbers of previously unreported SNPs, followed by Central African Rainforest Hunter-Gatherer populations from the Congo Basin, and then by all other African populations in our dataset. These results show that a substantial number of previously unknown variants can still be found when investigating high-quality whole genome sequences from relatively understudied Sub-Saharan African populations, consistent with previous studies (Meyer et al, 2012;Rasmussen et al, 2014;The 1000Genomes Project Consortium et al, 2015Mallick et al, 2016;Choudhury et al, 2017;Schlebusch et al, 2020;Breton, Fortes-Lima and Schlebusch, 2021;Fan et al, 2023;Ragsdale et al, 2023). (A) Numbers of bi-allelic SNPs across individuals within populations of more than one individual, compared to the reference sequence of the human genome GCRh38 and to previously reported variants in dbSNP 156.…”

“…The processing pipeline used in the present study is adapted from the Genome Analyses Toolkit (GATK) "Germline short variant discovery (SNPs + Indels)" Best Practices workflow (McKenna et al, 2010;DePristo et al, 2011;Van Der Auwera et al, 2013) . It is described and compared to the original GATK Best Practices workflow in (Breton et al, 2021). SupplementaryFigureSF8x gives an overview of the pipelines used for the processing; all template codes with accompanying detailed explanations for all processing steps are provided below and in the corresponding GitHub repository (https://github.com/Gwennid/africa-wgs-descriptive).…”

“…Realignment around indels was performed (at the lane level) with GATK version 3.5.0 RealignerTargetCreator and IndelRealigner. We then performed a "triple mask base quality score recalibration (BQSR)", where the sample's variation is used together with dbSNP, as described in (Schlebusch et al, 2020;Breton et al, 2021). This step includes merging the reads from a given sample with SAMtools version 1.1; calling variants with GATK version 3.5.0 HaplotypeCaller with "--genotyping_mode DISCOVERY"; and (in a parallel track) standard BQSR with GATK version 3.5.0 BaseRecalibrator and PrintReads, and dbSNP version 144.…”