Biology subjects

Petersen, D. C.

Publications and source records attributed to Petersen, D. C..

3 recordsLinked to original sources

bioRxiv2025

Mitochondrial DNA Imputation Accuracy and Its Application in a Southern African Mitochondrial Genome-wide Association Study

Southern African populations harbor exceptional mitochondrial genetic diversity and include the earliest diverging mitochondrial haplogroups. Yet, they remain significantly underrepresented in genetic studies and reference databases. This underrepresentation raises concerns about the performance and generalizability of mitochondrial imputation tools in populations with complex demographic histories. In this study, we conducted a comprehensive evaluation of the publicly available MitoImpute reference panel to assess its accuracy and suitability for use in southern African cohorts. We examined imputation performance for mitochondrial DNA (mtDNA), the impact of imputation on haplogroup assignment, and the extent to which population-specific variants were recovered by the panel. As a proof-of-principle application, we used the MitoImpute reference panel and imputation workflow to merge five southern African tuberculosis (TB) case-control mtDNA datasets and perform a mitochondrial genome-wide association study (miWAS) of TB susceptibility. Although MitoImpute performed well in predicting mitochondrial haplogroups and accurately imputing a subset of mtDNA variants, substantial population-specific variation was not captured. No significant associations with TB susceptibility were identified, highlighting key limitations of array-based mtDNA genotyping and imputation in highly diverse populations. Together, these findings underscore the need for improved reference panels enriched for African mitochondrial diversity and provide practical guidelines for mitochondrial data harmonization and analysis in multi-ancestry cohorts.

genetics↗

bioRxiv2019

A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa

Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. We find that samples from Ghana and Nigeria cluster together, while samples from Senegal and South Africa yield distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores were also generated for each genome in the MADCaP pilot dataset, and we found that predicted risks of CaP are lower in Senegal and higher in Nigeria.\n\nSignificanceWe have developed an Africa-specific genotyping array which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.

genomics↗

bioRxiv2017

Whole genome optical mapping reveals multiple fusion events chained by large novel sequences in cancer

Genomic rearrangements are common in cancer, with demonstrated links to disease progression and treatment response. These rearrangements can be complex, resulting in fusions of multiple chromosomal fragments and generation of derivative chromosomes. While methods exist for detecting individual fusions, they are generally unable to reconstruct complex chained events. To overcome these limitations, we adopted a new optical mapping approach, allowing for megabase length DNA to be captured, and in turn rearranged genomes to be visualized without loss of integrity. Whole genome mapping (Bionano Genomics) of a well-studied highly rearranged liposarcoma cell line, resulted in 3,338 assembled haploid genome maps, including 101 fusion maps. These fusion maps represent 175 Mb of highly rearranged genomic regions, illuminating the complex architecture of chained fusions, including content, order, orientation, and size. Spanning the junction of 151 chromosomal translocations, we found a total of 32 Mb of novel interspersed sequences that were not detected from short-read sequencing. We demonstrate that optical mapping provides a powerful new approach for capturing a higher level of complex genomic architecture, creating a scaffold for renewed interpretation of sequencing data of particular relevance to human cancer.

genomics↗