Biology subjects

Brenna M Henn

Publications and source records attributed to Brenna M Henn.

4 recordsLinked to original sources

bioRxiv2016

Trends in DNA methylation with age replicate across diverse human populations

Aging is associated with widespread changes in genome-wide patterns of DNA methylation. Thousands of CpG sites whose tissue-specific methylation levels are strongly correlated with chronological age have been previously identified. However, the majority of these studies have focused primarily on cosmopolitan populations living in the developed world; it is not known if age-related patterns of DNA methylation at these loci are similar across a broad range of human genetic and ecological diversity. We investigated genome-wide methylation patterns using saliva and whole blood derived DNA from two traditionally hunting and gathering African populations: the Baka of the western Central African rainforest and the =Khomani San of the South African Kalahari Desert. We identify hundreds of CpG sites whose methylation levels are significantly associated with age, thousands that are significant in a meta-analysis, and replicate trends previously reported in populations of non-African descent. We confirm that an age-associated site in the gene ELOVL2 shows a remarkably congruent relationship with aging in humans, despite extensive genetic and environmental variation across populations. We also demonstrate that genotype state at methylation quantitative trait loci (meQTLs) can affect methylation trends at some known age-associated CpG sites. Our study explores the relationship between CpG methylation and chronological age in populations of African hunter-gatherers, who rely on different diets across diverse ecologies. While many age-related CpG sites replicate across populations, we show that considering common genetic variation at meQTLs further improves our ability to detect previously identified age associations.

Genomics↗

bioRxiv2016

False Negatives Are a Significant Feature of Next Generation Sequencing Callsets

Short-read, next-generation sequencing (NGS) is now broadly used to identify rare or de novo mutations in population samples and disease cohorts. However, NGS data is known to be error-prone and post-processing pipelines have primarily focused on the removal of spurious mutations or \"false positives\" in downstream genome datasets. Less attention has been paid to characterizing the fraction of missing mutations or \"false negatives\" (FN). We design a phylogeny-aware tool to determine false negatives [PhyloFaN] and describe how read coverage and reference bias affect the FN rate. Using thousand-fold coverage NGS data from both Illumina HiSeq and Complete Genomics platforms derived from the 1000 Genomes Project, we first characterize the false negative rate in human mtDNA genomes. The false negative rate for the publically available callsets is 17-20%, even for extremely high coverage haploid data. We demonstrate that high FN rates are not limited to mtDNA by comparing autosomal data from 28 publically available full genomes to intergenic Sanger sequenced regions for each individual. We examine both low-coverage Illumina and high-coverage Complete Genomics genomes. We show that the FN rate varies between [~]6%-18% and that false-positive rates are considerably lower (<3%). The FN rate is strongly dependent on calling pipeline parameters, as well as read coverage. Our results demonstrate that missing mutations are a significant feature of genomic datasets and imply additional fine-tuning of bioinformatics pipelines is needed. We provide a tool which can be used to quantify the FN rate for haploid genomic experiments, without additional generation of validation data.\n\nData depositionData and software are freely available on the Henn Lab website: https://ecoevo.stonybrook.edu/hennlab/data-software/\n\nSoftwareGITHUB via https://ecoevo.stonybrook.edu/hennlab/data-software/

Bioinformatics↗

bioRxiv2016

Fine-scale human population structure in southern Africa reflects ecological boundaries

Recent genetic studies have established that the KhoeSan populations of southern Africa are distinct from all other African populations and have remained largely isolated during human prehistory until about 2,000 years ago. Dozens of different KhoeSan groups exist, belonging to three different language families, but very little is known about population history within southern Africa. We examine new genome-wide polymorphism data and whole mitochondrial genomes for more than one hundred South Africans from the =Khomani San and Nama populations of the Northern Cape, analyzed in conjunction with 19 additional southern African populations. Our analyses reveal fine-scale population structure in and around the Kalahari Desert. Surprisingly, this structure does not always correspond to linguistic or subsistence categories as previously suggested, but rather reflects the role of geographic barriers and the ecology of the greater Kalahari Basin. Regardless of subsistence strategy, the indigenous Khoe-speaking Nama pastoralists and the N|u-speaking =Khomani (formerly hunter-gatherers) share recent ancestry with other Khoe-speaking forager populations that forms a rim around the Kalahari Desert. We reconstruct earlier migration patterns and estimate that the southern Kalahari populations were among the last to experience gene flow from Bantu-speakers, approximately 14 generations ago. We conclude that local adoption of pastoralism, at least by the Nama, appears to have been primarily a cultural process with limited impact from eastern African genetic diffusion.

Genetics↗

bioRxiv2015

Worldwide patterns of human epigenetic variation

DNA methylation is an epigenetic modification, influenced by both genetic and environmental variation, that can affect transcription and many organismal phenotypes. Although patterns of DNA methylation have been shown to differ between human populations, it remains to be determined whether epigenetic diversity mirrors the patterns observed for DNA polymorphisms or gene expression levels. We measured DNA methylation at 480,000 sites in 34 individuals from five diverse human populations in the Human Genome Diversity Panel, and analyzed these together with single nucleotide polymorphisms (SNPs) and gene expression data. We found greater population-specificity of DNA methylation than of mRNA levels, which may be driven by the greater genetic control of methylation. This study provides insights into gene expression and its epigenetic regulation across populations and offers a deeper understanding of worldwide patterns of epigenetic diversity in humans.

Genomics↗