The past two decades of analytical efforts have highlighted how much more remains to be learned about the human genome and, particularly, its complex involvement in promoting disease development and progression. While numerous computational tools exist for the assessment of the functional and pathogenic effects of genome variants, their precision is far from satisfactory, particularly for clinical use. Accumulating evidence also suggests that the human microbiome's interaction with the human genome plays a critical role in determining health and disease states. While numerous microbial taxonomic groups and molecular functions of the human microbiome have been associated with disease, the reproducibility of these findings is lacking. The human microbiome–genome interaction in healthy individuals is even less well understood. This review summarizes the available computational methods built to analyze the effect of variation in the human genome and microbiome. We address the applicability and precision of these methods across their possible uses. We also briefly discuss the exciting, necessary, and now possible integration of the two types of data to improve the understanding of pathogenicity mechanisms.
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Chemical Inhibition of Bromodomain Proteins in Insect-Stage African Trypanosomes Perturbs Silencing of the Variant Surface Glycoprotein Repertoire and Results in Widespread Changes in the Transcriptome
The disease African trypanosomiasis imposes a severe human and economic burden for communities in sub-Saharan Africa. The parasite that causes the disease is transmitted to the bloodstream of a human or ungulate via the tsetse fly.
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- Award ID(s):
- 2041395
- PAR ID:
- 10507579
- Editor(s):
- Mugnier, Monica
- Publisher / Repository:
- ASM
- Date Published:
- Journal Name:
- Microbiology Spectrum
- Volume:
- 11
- Issue:
- 3
- ISSN:
- 2165-0497
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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