Subject(s)
Computational Biology/education , Computational Biology/organization & administration , Universities , Africa , Computational Biology/methods , Data Interpretation, Statistical , Diffusion of Innovation , Genomics , Humans , International Cooperation , National Institutes of Health (U.S.) , Schools , Software , United StatesABSTRACT
South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.
Subject(s)
Black People/genetics , Demography , Gene Flow , Genome-Wide Association Study , Language , Chromosomes, Human, Y/genetics , Ethnicity , Female , Gene Frequency , Genetic Variation , Genetics, Population , Genomics , Geography , Haplotypes , Humans , Linguistics , Male , Phylogeny , South AfricaABSTRACT
With more microbiome studies being conducted by African-based research groups, there is an increasing demand for knowledge and skills in the design and analysis of microbiome studies and data. However, high-quality bioinformatics courses are often impeded by differences in computational environments, complicated software stacks, numerous dependencies, and versions of bioinformatics tools along with a lack of local computational infrastructure and expertise. To address this, H3ABioNet developed a 16S rRNA Microbiome Intermediate Bioinformatics Training course, extending its remote classroom model. The course was developed alongside experienced microbiome researchers, bioinformaticians, and systems administrators, who identified key topics to address. Development of containerised workflows has previously been undertaken by H3ABioNet, and Singularity containers were used here to enable the deployment of a standard replicable software stack across different hosting sites. The pilot ran successfully in 2019 across 23 sites registered in 11 African countries, with more than 200 participants formally enrolled and 106 volunteer staff for onsite support. The pulling, running, and testing of the containers, software, and analyses on various clusters were performed prior to the start of the course by hosting classrooms. The containers allowed the replication of analyses and results across all participating classrooms running a cluster and remained available posttraining ensuring analyses could be repeated on real data. Participants thus received the opportunity to analyse their own data, while local staff were trained and supported by experienced experts, increasing local capacity for ongoing research support. This provides a model for delivering topic-specific bioinformatics courses across Africa and other remote/low-resourced regions which overcomes barriers such as inadequate infrastructures, geographical distance, and access to expertise and educational materials.
Subject(s)
Computational Biology/education , Computational Biology/methods , RNA, Ribosomal, 16S , Software , Africa , Algorithms , Curriculum , Genome, Human , Geography , Humans , MicrobiotaABSTRACT
Dichapetalum cymosum produces the toxic fluorinated metabolite, fluoroacetate, presumably as a defence mechanism. Given the rarity of fluorinated metabolites in nature, the biosynthetic origin and function of fluoroacetate have been of particular interest. However, the mechanism for fluorination in D. cymosum was never elucidated. More importantly, there is a severe lack in knowledge on a genetic level for fluorometabolite-producing plants, impeding research on the subject. Here, we report on the first transcriptome for D. cymosum and investigate the wound response for insights into fluorometabolite production. Mechanical wounding studies were performed and libraries of the unwounded (control) and wounded (30 and 60 min post wounding) plant were sequenced using the Illumina HiSeq platform. A combined reference assembly generated 77,845 transcripts. Using the SwissProt, TrEMBL, GO, eggNOG, KEGG, Pfam, EC and PlantTFDB databases, a 69% annotation rate was achieved. Differential expression analysis revealed the regulation of 364 genes in response to wounding. The wound responses in D. cymosum included key mechanisms relating to signalling cascades, phytohormone regulation, transcription factors and defence-related secondary metabolites. However, the role of fluoroacetate in inducible wound responses remains unclear. Bacterial fluorinases were searched against the D. cymosum transcriptome but transcripts with homology were not detected suggesting the presence of a potentially different fluorinating enzyme in plants. Nevertheless, the transcriptome produced in this study significantly increases genetic resources available for D. cymosum and will assist with future research into fluorometabolite-producing plants.
Subject(s)
Fluoroacetates/metabolism , Magnoliopsida/genetics , Plant Leaves/genetics , Stress, Mechanical , Transcriptome/genetics , Biosynthetic Pathways/genetics , Down-Regulation/genetics , Gene Expression Regulation, Plant , Gene Ontology , Molecular Sequence Annotation , Plant Proteins/genetics , Plant Proteins/metabolism , RNA, Messenger/genetics , RNA, Messenger/metabolism , Up-Regulation/geneticsABSTRACT
The African continent is regarded as the cradle of modern humans and African genomes contain more genetic variation than those from any other continent, yet only a fraction of the genetic diversity among African individuals has been surveyed1. Here we performed whole-genome sequencing analyses of 426 individuals-comprising 50 ethnolinguistic groups, including previously unsampled populations-to explore the breadth of genomic diversity across Africa. We uncovered more than 3 million previously undescribed variants, most of which were found among individuals from newly sampled ethnolinguistic groups, as well as 62 previously unreported loci that are under strong selection, which were predominantly found in genes that are involved in viral immunity, DNA repair and metabolism. We observed complex patterns of ancestral admixture and putative-damaging and novel variation, both within and between populations, alongside evidence that Zambia was a likely intermediate site along the routes of expansion of Bantu-speaking populations. Pathogenic variants in genes that are currently characterized as medically relevant were uncommon-but in other genes, variants denoted as 'likely pathogenic' in the ClinVar database were commonly observed. Collectively, these findings refine our current understanding of continental migration, identify gene flow and the response to human disease as strong drivers of genome-level population variation, and underscore the scientific imperative for a broader characterization of the genomic diversity of African individuals to understand human ancestry and improve health.
Subject(s)
Genetic Variation , Genome, Human/genetics , Genomics , Health , Human Migration , Africa/ethnology , DNA Repair/genetics , Datasets as Topic , Female , Gene Flow , Genetics, Medical , Genetics, Population , Health/history , History, Ancient , Human Migration/history , Humans , Immunity/genetics , Language , Male , Metabolism/genetics , Selection, Genetic , Whole Genome SequencingABSTRACT
Pancreatic cancer accounts for 2.8% of new cancer cases worldwide and is projected to become the second leading cause of cancer-related deaths by 2030. Patients of African ancestry appear to be at an increased risk for pancreatic ductal adenocarcinoma (PDAC), with more severe disease and outcomes. The purpose of this study was to map the proteomic and genomic landscape of a cohort of PDAC patients of African ancestry. Thirty tissues (15 tumours and 15 normal adjacent tissues) were obtained from consenting South African PDAC patients. Optimisation of the sample preparation method allowed for the simultaneous extraction of high-purity protein and DNA for SWATH-MS and OncoArray SNV analyses. We quantified 3402 proteins with 49 upregulated and 35 downregulated proteins at a minimum 2.1 fold change and FDR adjusted p-value (q-value) ≤ 0.01 when comparing tumour to normal adjacent tissue. Many of the upregulated proteins in the tumour samples are involved in extracellular matrix formation (ECM) and related intracellular pathways. In addition, proteins such as EMIL1, KBTB2, and ZCCHV involved in the regulation of ECM proteins were observed to be dysregulated in pancreatic tumours. Downregulation of pathways involved in oxygen and carbon dioxide transport were observed. Genotype data showed missense mutations in some upregulated proteins, such as MYPN, ESTY2 and SERPINB8. Approximately 11% of the dysregulated proteins, including ISLR, BP1, PTK7 and OLFL3, were predicted to be secretory proteins. These findings help in further elucidating the biology of PDAC and may aid in identifying future plausible markers for the disease.
Subject(s)
Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Carcinoma, Pancreatic Ductal/pathology , Extracellular Matrix/metabolism , Pancreatic Neoplasms/pathology , Polymorphism, Single Nucleotide , Proteome/analysis , Aged , Aged, 80 and over , Carcinoma, Pancreatic Ductal/genetics , Carcinoma, Pancreatic Ductal/metabolism , Carcinoma, Pancreatic Ductal/surgery , Case-Control Studies , Cohort Studies , Female , Follow-Up Studies , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Humans , Male , Mass Spectrometry , Middle Aged , Pancreatic Neoplasms/genetics , Pancreatic Neoplasms/metabolism , Pancreatic Neoplasms/surgery , PrognosisABSTRACT
BACKGROUND: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. RESULTS: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. CONCLUSION: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network.
Subject(s)
Computational Biology/methods , Genomics/methods , Africa , Humans , Reproducibility of ResultsABSTRACT
Genetic variation and susceptibility to disease are shaped by human demographic history and adaptation. We can now study the genomes of extant Africans and uncover traces of population migration, admixture, assimilation and selection by applying sophisticated computational algorithms. There are four major ethnolinguistic divisions among present day Africans: Hunter-gatherer populations in southern and central Africa; Nilo-Saharan speakers from north and northeast Africa; Afro-Asiatic speakers from north and east Africa; and Niger-Congo speakers who are the predominant ethnolinguistic group spread across most of sub-Saharan Africa. The enormous ethnolinguistic diversity in sub-Saharan African populations is largely paralleled by extensive genetic diversity and until a decade ago, little was known about detailed origins and divergence of these groups. Results from large-scale population genetic studies, and more recently whole genome sequence data, are unravelling the critical role of events like migration and admixture and environmental factors including diet, infectious diseases and climatic conditions in shaping current population diversity. It is now possible to start providing quantitative estimates of divergence times, population size and dynamic processes that have affected populations and their genetic risk for disease. Finally, the availability of ancient genomes from Africa provides historical insights of unprecedented depth. In this review, we highlight some key interpretations that have emerged from recent African genome studies.
Subject(s)
Adaptation, Biological/genetics , Black People/genetics , Africa/ethnology , Biological Evolution , Ethnicity/genetics , Evolution, Molecular , Genetic Techniques , Genetic Variation/genetics , Genetics , Genetics, Population/methods , Genomics/methods , Haplotypes/genetics , Humans , Polymorphism, Single Nucleotide/genetics , Whole Genome Sequencing/methodsABSTRACT
The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous compute environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. To address this need, in 2016 H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Hackathon, with the purpose of building key genomics analysis pipelines able to run on heterogeneous computing environments and meeting the needs of H3Africa research projects. This paper describes the preparations for this hackathon and reflects upon the lessons learned about its impact on building the technical and scientific expertise of African researchers. The workflows developed were made publicly available in GitHub repositories and deposited as container images on quay.io.
ABSTRACT
The Southern African Human Genome Programme is a national initiative that aspires to unlock the unique genetic character of southern African populations for a better understanding of human genetic diversity. In this pilot study the Southern African Human Genome Programme characterizes the genomes of 24 individuals (8 Coloured and 16 black southeastern Bantu-speakers) using deep whole-genome sequencing. A total of ~16 million unique variants are identified. Despite the shallow time depth since divergence between the two main southeastern Bantu-speaking groups (Nguni and Sotho-Tswana), principal component analysis and structure analysis reveal significant (p < 10-6) differentiation, and FST analysis identifies regions with high divergence. The Coloured individuals show evidence of varying proportions of admixture with Khoesan, Bantu-speakers, Europeans, and populations from the Indian sub-continent. Whole-genome sequencing data reveal extensive genomic diversity, increasing our understanding of the complex and region-specific history of African populations and highlighting its potential impact on biomedical research and genetic susceptibility to disease.
Subject(s)
Black People/genetics , Genetic Predisposition to Disease/genetics , Genetic Variation/genetics , Genome, Human , DNA Mutational Analysis/methods , Healthy Volunteers , Humans , Male , Mutation/genetics , Pilot Projects , Principal Component Analysis , South AfricaABSTRACT
Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge "Introduction to Bioinformatics" course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery-mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online "question and discussion" forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings.
Subject(s)
Computational Biology/education , Computer-Assisted Instruction/methods , Internet , Africa , Computational Biology/organization & administration , Databases, Factual , Humans , User-Computer InterfaceABSTRACT
The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.
Subject(s)
Black People/genetics , Databases, Genetic , Genomics/methods , Database Management Systems , Developing Countries , Humans , Nigeria , South AfricaABSTRACT
BACKGROUND: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. OBJECTIVES: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. METHODS AND RESULTS: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. CONCLUSIONS: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa.
Subject(s)
Biomedical Research/methods , Computational Biology/trends , Genomics/methods , Africa , HumansABSTRACT
FOXP2 is a member of the P subfamily of FOX transcription factors, the DNA-binding domain of which is the winged helix forkhead domain (FHD). In this work we show that the FOXP2 FHD is able to bind to various DNA sequences, including a novel sequence identified in this work, with different affinities and rates as detected using surface plasmon resonance. Combining the experimental work with molecular docking, we show that high-affinity sequences remain bound to the protein for longer, form a greater number of interactions with the protein and induce a greater structural change in the protein than low-affinity sequences. We propose a binding model for the FOXP2 FHD that involves three types of binding sequence: low affinity sites which allow for rapid scanning of the genome by the protein in a partially unstructured state; moderate affinity sites which serve to locate the protein near target sites and high-affinity sites which secure the protein to the DNA and induce a conformational change necessary for functional binding and the possible initiation of downstream transcriptional events.
Subject(s)
DNA/genetics , DNA/metabolism , Forkhead Transcription Factors/chemistry , Forkhead Transcription Factors/metabolism , Base Sequence , Binding Sites , Humans , Models, Molecular , Protein Domains , Surface Plasmon ResonanceABSTRACT
We present the annotation of the draft genome sequence of Oscheius sp. TEL-2014 (Genbank accession number KM492926). This entomopathogenic nematode was isolated from grassland in Suikerbosrand Nature Reserve near Johannesburg in South Africa. Oscheius sp. Strain TEL has a genome size of 110,599,558 bp and a GC content of 42.24%. The genome sequence can be accessed at DDBJ/EMBL/GenBank under the accession number LNBV00000000.
ABSTRACT
BACKGROUND: Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. RESULTS: The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. CONCLUSIONS: Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.
Subject(s)
Genetics, Population , Genome, Human , Polymorphism, Single Nucleotide , Racial Groups/genetics , Alleles , Computational Biology , Databases, Nucleic Acid , Evolution, Molecular , Humans , Recombination, Genetic , Selection, GeneticABSTRACT
Keratolytic winter erythema (KWE), also known as Oudtshoorn skin disease, is characterised by a cyclical disruption of normal epidermal keratinisation affecting primarily the palmoplantar skin with peeling of the palms and soles, which is worse in the winter. It is a rare monogenic, autosomal dominant condition of unknown cause. However, due to a founder effect, it occurs at a prevalence of 1/7 200 among South African Afrikaans-speakers. In the mid-1980s, samples were collected from affected families for a linkage study to pinpoint the location of the KWE gene. A genome-wide linkage analysis, using microsatellite markers, identified the KWE critical region on chromosome 8p23.1-p22. Subsequent genetic studies focused on screening candidate genes in this critical region; however, no pathogenic mutations that segregated exclusively with KWE were identified. The cathepsin B (CTSB) and farnesyl-diphosphate farnesyltransferase 1 (FDFT1) genes revealed no potentially pathogenic variants, nor did they show differential gene expression in affected skin. Mutation detection in additional candidate genes also failed to identify the KWE-associated variant, suggesting that the causal variant may be in an uncharacterised functional region. Bioinformatic analysis revealed highly conserved regions within the KWE critical region and a custom tiling array was designed to cover this region and to search for copy number variation. Although the study did not identify a variant that segregates exclusively with KWE, it provided valuable insight into the complex KWE-linked region. Next-generation sequencing approaches are being used to comb the region, but the causal variant for this interesting hyperkeratotic palmoplantar phenotype still remains elusive.
Subject(s)
Erythema/genetics , Keratosis/genetics , Skin Diseases, Genetic/genetics , Computational Biology , DNA Copy Number Variations , Erythema/diagnosis , Erythema/ethnology , Genetic Association Studies , Humans , Keratosis/diagnosis , Keratosis/ethnology , Parakeratosis/pathology , Skin Diseases, Genetic/diagnosis , Skin Diseases, Genetic/ethnology , South AfricaABSTRACT
BACKGROUND: Keratolytic winter erythema (KWE) or Oudtshoorn skin disease is a rare autosomal dominant monogenic disorder of epidermal keratinisation characterized clinically by cyclical peeling of the palms and soles. Due to a founder effect many KWE families have been identified in South Africa and the gene has been localized to 8p23.1-22, but the causal gene has yet to be identified. OBJECTIVE: To examine two compelling positional and functional candidate genes within the critical region on 8p: cathepsin B (CTSB), a lysosomal cysteine protease localized to pericellular spaces between keratinocytes, possibly playing a role in cell-cell adhesion; and farnesyl-diphosphate farnesyltransferase (FDFT1), a membrane-associated enzyme in cholesterol biosynthesis which, among its many functions, plays a role in barrier permeability and integrity. METHOD: Mutation screening of the coding regions, 5'UTRs and intron/exon boundaries of CTSB and FDFT1 in genomic DNA and cDNA of patients affected with KWE. Relative gene expression profiles of CTSB and FDFT1 in palmoplantar skin biopsies were assessed by real-time RT-PCR. RESULTS: No DNA variants that segregate exclusively with KWE were identified. There was no significant difference in the CTSB expression profiles but a trend towards increased expression of FDFT1 was observed in the skin of affected individuals (p=0.063). This observation prompted analysis of the FDFT1 promoter region; however, no genetic variants segregating with the KWE phenotype were observed and it is likely that the increased expression was triggered in response to skin inflammation and peeling. CONCLUSION: CTSB and FDFT1 are excluded as candidates for KWE.
Subject(s)
Cathepsin B/biosynthesis , Erythema/genetics , Farnesyl-Diphosphate Farnesyltransferase/biosynthesis , Keratosis/genetics , Skin Diseases, Genetic/genetics , 5' Untranslated Regions , Cathepsin B/genetics , Cathepsin B/metabolism , Cell Adhesion , Chromosomes, Human, Pair 8 , DNA Mutational Analysis , Erythema/metabolism , Farnesyl-Diphosphate Farnesyltransferase/genetics , Founder Effect , Gene Expression Profiling , Genes, Dominant , Genetic Variation , Humans , Keratosis/metabolism , Models, Genetic , Mutation , Skin Diseases, Genetic/metabolism , South AfricaABSTRACT
BACKGROUND: Pseudoxanthoma elasticum (PXE) is an autosomal recessive metabolic disorder with ectopic mineralization in the skin, eyes and cardiovascular system. PXE is caused by mutations in ABCC6. OBJECTIVE: To examine 54 unrelated South African PXE patients for ABCC6 PXE causing mutations. METHODS: Patients were screened for mutations in ABCC6 using two strategies. The first involved a comprehensive screening of all the ABCC6 exons and flanking regions by dHPLC or sequencing whereas the second involved screening patients only for the common PXE mutations. The ABCC6 gene was screened in ten white and ten black healthy unrelated South Africans in order to examine the level of common non-PXE associated variation. RESULTS: The Afrikaner founder mutation, R1339C, was present in 0.41 of white ABCC6 PXE alleles, confirming the founder effect and its presence in both Afrikaans- (34/63 PXE alleles) and English-speakers (4/28). Eleven mutations were detected in the white patients (of European origin), including two nonsense mutations, 6 missense mutations, two frameshift mutations and a large deletion mutation. The five "Coloured" patients (of mixed Khoisan, Malay, European and African origin) included three compound heterozygotes with R1339C as one of the mutations. The three black patients (sub-Saharan African origin) were all apparent homozygotes for the R1314W mutation. Blacks showed a trend towards a higher degree of neurtral variation (18 variants) when compared to whites (12 variants). CONCLUSION: Delineation of the ABCC6 mutation profile in South African PXE patients will be used as a guide for molecular genetic testing in a clinical setting and for genetic counselling.