Publications by authors named "S A Tishkoff"

Genome-wide association studies (GWAS) are an important tool for the study of complex disease genetics. Decisions regarding the quality control (QC) procedures employed as part of a GWAS can have important implications on the results and their biological interpretation. Many GWAS have been conducted predominantly in cohorts of European ancestry, but many initiatives aim to increase the representation of diverse ancestries in genetic studies.

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Article Synopsis
  • Researchers are studying DNA in Africa to learn more about the continent’s history, but many African scientists face challenges and are often left out of these discussions.
  • A workshop called DNAirobi was held in May 2023 to help make sure African voices are included in research about African people and their past.
  • The goal is to create a better system for DNA research in Africa over the next ten years by improving communication, building partnerships, and making science more inclusive.
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Leukocyte telomere length (LTL) varies significantly across human populations, with individuals of African ancestry having longer LTL than non-Africans. However, the genetic and environmental drivers of LTL variation in Africans remain largely unknown. We report here on the relationship between LTL, genetics, and a variety of environmental and climatic factors in ethnically diverse African adults (n = 1,818) originating from Botswana, Tanzania, Ethiopia, and Cameroon.

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Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color.

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Clinical trials for central nervous system disorders often enroll patients with unrecognized heterogeneous diseases, leading to costly trials that have high failure rates. Here, we discuss the potential of emerging technologies and datasets to elucidate disease mechanisms and identify biomarkers to improve patient stratification and monitoring of disease progression in clinical trials for neuropsychiatric disorders. Greater efforts must be centered on rigorously standardizing data collection and sharing of methods, datasets, and analytical tools across sectors.

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