Putting RFMix and ADMIXTURE to the test in a complex admixed population

CITATION: Uren, C., Hoal, E. G. & Moller, M. 2020. Putting RFMix and ADMIXTURE to the test in a complex admixed population. BMC Genetics, 21:40, doi:10.1186/s12863-020-00845-3.The original publication is available at https://bmcinfectdis.biomedcentral.comPublication of this article was funded by the Stellenbosch University Open Access FundBackground: Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios. Results: Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses. Conclusion: This study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in worldwide complex admixture scenarios particularly when including these estimates in association studies.https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-020-00845-3Publisher's versio

The critical needs and challenges for genetic architecture studies in Africa

Human genetic studies have long been vastly Eurocentric, raising a key question about the generalizability of these study findings to other populations. Because humans originated in Africa, these populations retain more genetic diversity, and yet individuals of African descent have been tremendously underrepresented in genetic studies. The diversity in Africa affords ample opportunities to improve fine-mapping resolution for associated loci, discover novel genetic associations with phenotypes, build more generalizable genetic risk prediction models, and better understand the genetic architecture of complex traits and diseases subject to varying environmental pressures. Thus, it is both ethically and scientifically imperative that geneticists globally surmount challenges that have limited progress in African genetic studies to date. Additionally, African investigators need to be meaningfully included, as greater inclusivity and enhanced research capacity afford enormous opportunities to accelerate genomic discoveries that translate more effectively to all populations. We review the advantages, challenges, and examples of genetic architecture studies of complex traits and diseases in Africa. For example, with greater genetic diversity comes greater ancestral heterogeneity; this higher level of understudied diversity can yield novel genetic findings, but some methods that assume homogeneous population structure and work well in European populations may work less well in the presence of greater heterogeneity in African populations. Consequently, we advocate for methodological development that will accelerate studies important for all populations, especially those currently underrepresented in genetics.Peer reviewe

Genetic resistance to Mycobacterium Tuberculosis infection and disease

CITATION: Möller, M. et al. 2018. Genetic resistance to Mycobacterium tuberculosis infection and disease. Frontier in Immunology, 9:2219, 1-13. doi:10.3389/fimmu.2018.02219.The original publication is available from https://www.frontiersin.org/journals/immunology#Natural history studies of tuberculosis (TB) have revealed a spectrum of clinical outcomes after exposure to Mycobacterium tuberculosis, the cause of TB. Not all individuals exposed to the bacteriumwill become diseased and depending on the infection pressure, many will remain infection-free. Intriguingly, complete resistance to infection is observed in some individuals (termed resisters) after intense, continuing M. tuberculosis exposure. After successful infection, the majority of individuals will develop latent TB infection (LTBI). This infection state is currently (and perhaps imperfectly) defined by the presence of a positive tuberculin skin test (TST) and/or interferon gamma release assay (IGRA), but no detectable clinical disease symptoms. The majority of healthy individuals with LTBI are resistant to clinical TB, indicating that infection is remarkably well-contained in these non-progressors. The remaining 5–15% of LTBI positive individuals will progress to active TB. Epidemiological investigations have indicated that the host genetic component contributes to these infection and disease phenotypes, influencing both susceptibility and resistance. Elucidating these genetic correlates is therefore a priority as it may translate to new interventions to prevent, diagnose or treat TB. The most successful approaches in resistance/susceptibility investigation have focused on specific infection and disease phenotypes and the resister phenotype may hold the key to the discovery of actionable genetic variants in TB infection and disease. This review will not only discuss lessons from epidemiological studies, but will also focus on the contribution of epidemiology and functional genetics to human genetic resistance to M. tuberculosis infection and disease.https://www.frontiersin.org/articles/10.3389/fimmu.2018.02219/fullhttps://doi.org/10.3389/fimmu.2018.02219Published review articlePublishers versio

Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method

Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes

A Mobile Holistic Enterprise Transformation Framework

Mobile phones and tablets shipments are surpassing those of the PC category, as well as in relation to Internet usage as of 2016; all details which have made mobile adoption a priority for many enterprises and a challenge for them as well. Many enterprises have fallen into a paradox of spending on creating and updating mobile services, and gaining less than expected in return. Reasons for this include the lack of vision, and the lack of a clearly defined, well communicated mobile strategy. Enterprise Architecture ‘EA’ facilitates a successful transformation by controlling and managing the transitions in order to arrive at a clearly defined future state. It is regarded as the science of change to many. However, EA frameworks are very comprehensive and require weeks of training and resources, and are often too generic for mobile transformation. Therefore, an EA-based mobile holistic enterprise framework has been developed to support enterprises in making mobile initiatives a priority. The proposed framework ensures a clearly defined, well-communicated, holistic future state that is continually evaluated, as opposed to many of the existing frameworks. The proposed Mobile Holistic Enterprise Architecture Framework - ‘MHETF’ - is based on the realisation of the capabilities of smartphones that are aimed at individual average consumers (the backbone of the current mobile trend). The capabilities are categorised and translated into four sets of services categories for business use. They are linked to another two components of the framework which are: (i) the categorisation of goals and objectives that are incorporated into the Balanced Scorecard for evaluation at a later stage in planning, and continually referred to during transitions and (ii) the categorisation of the implementation forms (categorisation of end solutions’ functionalities). The framework is supported by EA inter-operability and maturity models to ensure continuity and alignment with the existing initiatives, the enterprise’s strategic objectives, and the change required in the scope of transformation. An evaluation for the available enterprise architecture frameworks was carried out and resulted in the selection of The Open Group Architecture Framework (TOGAF). The decision was also commended by the participants in the case study evaluation due to their familiarity with this framework, which is being adopted as the Saudi E Government Standard in contrast to the other major frameworks of Zachman and Federal Enterprise Architecture (FEA). MHETF has been applied to three case studies in the Kingdom of Saudi Arabia; two applications for a leading national outsourcing company, and the third for the outpatient clinics in a large hospital in the capital city of Riyadh. The results have shown major improvements in the four goal areas of mobile transformation; productivity, processes, satisfaction improvement and facilitating new opportunities. Eventually, the final evolution has shown that the participants are satisfied with the framework overall, and indicates that the framework changed their perspective of the power of mobile applications significantly, is relatively easy to understand, and that they are planning to adopt it for future mobile initiatives

BDNF Val66Met and DRD2 Taq1A polymorphisms interact to influence PTSD symptom severity: A preliminary investigation in a South African population

BACKGROUND: We evaluated the role that selected variants in serotonin transporter (5-HTT), dopamine receptor 2 (DRD2) and brain-derived neurotrophic factor (BDNF) genes play in PTSD symptom severity in an at-risk population. We also investigated the interaction between the genetic variants to determine whether these variables and the interactions between the variables influenced the severity of PTSD symptoms. METHODS: PTSD symptoms were quantitatively assessed using the Davidson Trauma Scale (DTS) in 150 participants from an at-risk South African population. All participants were genotyped for the 5-HTTLPR, DRD2 Taq1A and BDNF Val66Met polymorphisms. Gene–gene interactions were investigated using various linear models. All analyses were adjusted for age, gender, major depressive disorder diagnosis, level of resilience, level of social support and alcohol dependence. RESULTS: A significant interaction effect between DRD2 Taq1A and BDNF Val66Met variants on DTS score was observed. On the background of the BDNF Val66Val genotype, DTS score increased significantly with the addition of a DRD2 Taq1A A1 allele. However, on the BDNF Met66 allele background, the addition of an A1 allele was found to reduce total DTS score. CONCLUSIONS: This study provides preliminary evidence for an epistatic interaction between BDNF Val66Met and DRD2 Taq1A polymorphisms on the severity of PTSD symptoms, where both too little and too much dopamine can result in increased PTSD symptom severity.Web of Scienc

A Panel of Ancestry Informative Markers for the Complex Five-Way Admixed South African Coloured Population

Admixture is a well known confounder in genetic association studies. If genome-wide data is not available, as would be the case for candidate gene studies, ancestry informative markers (AIMs) are required in order to adjust for admixture. The predominant population group in the Western Cape, South Africa, is the admixed group known as the South African Coloured (SAC). A small set of AIMs that is optimized to distinguish between the five source populations of this population (African San, African non-San, European, South Asian, and East Asian) will enable researchers to cost-effectively reduce false-positive findings resulting from ignoring admixture in genetic association studies of the population. Using genome-wide data to find SNPs with large allele frequency differences between the source populations of the SAC, as quantified by Rosenberg et. al's -statistic, we developed a panel of AIMs by experimenting with various selection strategies. Subsets of different sizes were evaluated by measuring the correlation between ancestry proportions estimated by each AIM subset with ancestry proportions estimated using genome-wide data. We show that a panel of 96 AIMs can be used to assess ancestry proportions and to adjust for the confounding effect of the complex five-way admixture that occurred in the South African Coloured population.Department of HE and Training approved lis