Genomics in Africa Coming of Age

Platform sessions are abstract driven sessions with 6 talks per session. These talks are 10 minutes in length and are cross-topical in nature to represent the broad discipline our field of genetics and genomics represent. After each talk, there will be a 5-minute Q&A with each speaker. For information on each individual session, please view the "Details" tab. 

Recorded session from the 2021 virtual meeting.

Revisiting the out of Africa event with a deep learning approach

Anatomically modern humans evolved around 300 thousand years ago in Africa. Modern humans started to appear in the fossil record outside of Africa about 100 thousand years ago though other hominins existed throughout Eurasia much earlier. Recently, several researchers argued in favourof a single out of Africa event for modern humans based on whole-genome sequences analyses. However, the single out of Africa model is in contrast with some of the findings from fossil records, which supports two out of Africa, and uniparental data, which proposes a back to Africa movement. Here, we used a deep learning approach coupled with Approximate Bayesian Computation and Sequential Monte Carlo to revisit these hypotheses from the whole genome sequence perspective. Our results support the back to Africa model over other alternatives. We estimated that there are two successive splits between Africa and out of African populations happening around 60-90 thousand years ago and separated by 13-15 thousand years. One of the populations resulting from the more recent split has to a large extent replaced the older West African population while the other one has founded the out of Africa populations.

Mayukh Mondal
Institute of Genomics, University of Tartu

An analysis of population copy number variation in sub-Saharan African genomes

Introduction Copy number variation (CNV) is responsible for a large component of normal human variation and has been implicated in the cause/genetic aetiology of several rare diseases. Population reference databases containing CNV information from all global populations is critical in disease genetics research, but current resources lack diversity, especially from the African continent. This makes such databases of limited use in studies looking at genetic diseases in African individuals. This study therefore aims to address this knowledge gap by producing a map of CNV using whole-genome data from several, previously unstudied African populations
Methods 1027 high coverage whole genome sequences obtained from individuals across west, central, southern and east Africa, were analysed using Manta and Graphtyper2. Additionally, 919 of the samples were also analysed using Genome STRiP to detect multi-allelic CNV. Quality control specific to each tool was performed in order to achieve high quality variant call sets.
Results 56 816 CNVs were detected by the Manta pipeline, consisting of 44 671 deletions and 12 145 duplications. Due the ability of Manta to detect small variants (<100bp), we are able to describe this previously less studied class of variants in an African cohort. 25% of the variants detected by Manta were <100 bp and 40% of these were common variants at >5% allele frequency. 50% of these variants are novel compared to 27% of the remaining variants >100bp. Overall, 32% of the variants identified were novel. A comparison between central, west, east and southern African regions yielded a number of variants unique to each region. We find deletions tend to have lower allele frequencies compared to duplications. The majority of variants were found in the non-coding genome, with only 8% of variants overlapping coding transcripts. An additional 5% of variants overlapped regulatory features. Genome STRiP detected 3991 multi-allelic variants with 99% having a copy number between 3-20. There were also variants with copy numbers greater than 20, some of which appear to be incidences of excessive runaway duplications not previously described.
Conclusion The amount of novel variation found demonstrates the importance of including African individuals from multiple African regions when producing reference databases and the rich genomic diversity of African genomes. Work is currently being performed to combine the full Genome STRiP and Manta call sets to produce a robust combined dataset. The variant database produced in this study will provide a valuable resource as a reference of normal CNV for the study of diseases in African populations.Emma Wiener