Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives
Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant ge...
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| Format: | Article |
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Frontiers Media S.A.
2019-06-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2019.00601/full |
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| author | Christian Domilongo Bope Christian Domilongo Bope Emile R. Chimusa Victoria Nembaware Gaston K. Mazandu Jantina de Vries Ambroise Wonkam Ambroise Wonkam Ambroise Wonkam |
| author_facet | Christian Domilongo Bope Christian Domilongo Bope Emile R. Chimusa Victoria Nembaware Gaston K. Mazandu Jantina de Vries Ambroise Wonkam Ambroise Wonkam Ambroise Wonkam |
| author_sort | Christian Domilongo Bope |
| collection | DOAJ |
| description | Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations. In silico mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available in silico prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria. |
| first_indexed | 2024-12-20T22:29:47Z |
| format | Article |
| id | doaj.art-17e39a64c77b43da8dbd179b83979c34 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-20T22:29:47Z |
| publishDate | 2019-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-17e39a64c77b43da8dbd179b83979c342022-12-21T19:24:45ZengFrontiers Media S.A.Frontiers in Genetics1664-80212019-06-011010.3389/fgene.2019.00601457129Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and PerspectivesChristian Domilongo Bope0Christian Domilongo Bope1Emile R. Chimusa2Victoria Nembaware3Gaston K. Mazandu4Jantina de Vries5Ambroise Wonkam6Ambroise Wonkam7Ambroise Wonkam8Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartments of Mathematics and Computer Sciences, Faculty of Sciences, University of Kinshasa, Kinshasa, Democratic Republic of CongoDepartment of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartment of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartment of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartment of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartment of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaDepartment of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaInstitute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaGenomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations. In silico mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available in silico prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria.https://www.frontiersin.org/article/10.3389/fgene.2019.00601/fullAfrican genomeincidental findingsactionable variantswhole exome sequencingwhole genome sequencingprecision medicine |
| spellingShingle | Christian Domilongo Bope Christian Domilongo Bope Emile R. Chimusa Victoria Nembaware Gaston K. Mazandu Jantina de Vries Ambroise Wonkam Ambroise Wonkam Ambroise Wonkam Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives Frontiers in Genetics African genome incidental findings actionable variants whole exome sequencing whole genome sequencing precision medicine |
| title | Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives |
| title_full | Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives |
| title_fullStr | Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives |
| title_full_unstemmed | Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives |
| title_short | Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives |
| title_sort | dissecting in silico mutation prediction of variants in african genomes challenges and perspectives |
| topic | African genome incidental findings actionable variants whole exome sequencing whole genome sequencing precision medicine |
| url | https://www.frontiersin.org/article/10.3389/fgene.2019.00601/full |
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