Tshabalala Mqondisi, Mellet Juanita, Vather Kuben, Nelson Derrick, Mohamed Fathima, Christoffels Alan, Pepper Michael S
Department of Immunology, Institute for Cellular and Molecular Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
South African Medical Research Council (SAMRC) Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Front Genet. 2022 Mar 4;13:711944. doi: 10.3389/fgene.2022.711944. eCollection 2022.
Lack of HLA data in southern African populations hampers disease association studies and our understanding of genetic diversity in these populations. We aimed to determine HLA diversity in South African populations using high resolution HLA ∼A, ∼B, ∼C, ∼DRB1, ∼DQA1 and ∼DQB1 data, from 3005 previously typed individuals. We determined allele and haplotype frequencies, deviations from Hardy-Weinberg equilibrium (HWE), linkage disequilibrium (LD) and neutrality test. South African HLA class I data was additionally compared to other global populations using non-metrical multidimensional scaling (NMDS), genetic distances and principal component analysis (PCA). All loci strongly ( < 0.0001) deviated from HWE, coupled with excessive heterozygosity in most loci. Two of the three most frequent alleles, HLA ∼DQA105:02 (0.2584) and HLA ∼C17:01 (0.1488) were previously reported in South African populations at lower frequencies. NMDS showed genetic distinctness of South African populations. Phylogenetic analysis and PCA clustered our current dataset with previous South African studies. Additionally, South Africans seem to be related to other sub-Saharan populations using HLA class I allele frequencies. Despite the retrospective nature of the study, data missingness, the imbalance of sample sizes for each locus and haplotype pairs, and induced methodological difficulties, this study provides a unique and large HLA dataset of South Africans, which might be a useful resource to support anthropological studies, disease association studies, population based vaccine development and donor recruitment programs. We additionally provide simulated high resolution HLA class I data to augment the mixed resolution typing results generated from this study.
南部非洲人群缺乏HLA数据，这阻碍了疾病关联研究以及我们对这些人群遗传多样性的理解。我们旨在利用来自3005名先前分型个体的高分辨率HLA ∼A、∼B、∼C、∼DRB1、∼DQA1和∼DQB1数据，确定南非人群中的HLA多样性。我们确定了等位基因和单倍型频率、偏离哈迪-温伯格平衡（HWE）的情况、连锁不平衡（LD）以及中性检验。还使用非度量多维标度分析（NMDS）、遗传距离和主成分分析（PCA），将南非HLA I类数据与其他全球人群进行了比较。所有位点均强烈（<0.0001）偏离HWE，且大多数位点存在过度杂合性。三个最常见的等位基因中的两个，即HLA ∼DQA105:02（0.2584）和HLA ∼C17:01（0.1488），此前在南非人群中的报道频率较低。NMDS显示出南非人群的遗传独特性。系统发育分析和PCA将我们当前的数据集与之前的南非研究聚类在一起。此外，利用HLA I类等位基因频率，南非人与其他撒哈拉以南人群似乎存在关联。尽管本研究具有回顾性、数据缺失、每个位点和单倍型对的样本量不平衡以及由此引发的方法学困难，但本研究提供了一个独特且庞大的南非人HLA数据集，这可能是支持人类学研究、疾病关联研究、基于人群的疫苗开发和供体招募计划的有用资源。我们还提供了模拟的高分辨率HLA I类数据，以增强本研究产生的混合分辨率分型结果。
