Bigham, A. | bioRxiv Science

bioRxiv2025

Adaptive Increase of Amylase Gene Copy Number in Peruvians Driven by Potato-rich Diets

Summary/AbstractThe salivary amylase gene (AMY1) exhibits remarkable copy number variation linked to dietary shifts in human evolution. While global studies highlight its structural complexity and association with starch-rich diets, localized selection patterns remain under explored. Here, we analyzed AMY1 copy number in 3,723 individuals from 85 populations, revealing that Indigenous Peruvian Andean populations possess the highest AMY1 copy number globally. A genome-wide analysis showed significantly higher amylase copy numbers in Peruvian Andean genomes compared to closely related populations. Further, we identified positive selection (selection coefficient of 0.0124, log likelihood ratio of 11.1543) at the nucleotide level on a haplotype harboring at least five haploid AMY1 copies, with a Peruvian Andean-specific expansion coinciding with potato domestication ([~]6-10 kya). Using ultra-long-read sequencing, we demonstrated that previously described recombination-based mutational mechanisms drive the formation of high-copy AMY1 haplotypes observed in Andean population. Our study provides a framework for investigating structurally complex loci and their role in human dietary adaptation.

genetics↗

bioRxiv2020

Hypothetical Human Immune Genome Complex Gradient May Help To Explain The Congenital Zika Symdrome Catastrophe In Brazil: A New Theory

There are few data considering human genetics as an important risk factor for birth abnormalities related to ZIKV infection during pregnancy, even though sub-Saharan African populations are apparently more resistant to CZS as compared to populations in the Americas. We hypothesized that single nucleotide variants (SNVs), especially in innate immune genes, could make some populations more susceptible to Zika congenital complications than others. Differences in the SNV frequencies among continental populations provide great potential for Machine Learning techniques. We explored a key immune genomic gradient between individuals from Africa, Asia and Latin America, working with complex signatures, using 297 SNVs. We employed a two-step approach. In the first step, decision trees (DTs) were used to extract the most discriminating SNVs among populations. In the second step, machine learning algorithms were used to evaluate the quality of the SNV pool identified in step one for discriminating between individuals from sub-Saharan African and Latin-American populations. Our results suggest that 10 SNVs from 10 genes (CLEC4M, CD58, OAS2, CD80, VEPH1, CTLA4, CD274, CD209, PLAAT4, CREB3L1) were able to discriminate sub-Saharan Africans from Latin American populations using only immune genome data, with an accuracy close to 100%. Moreover, we found that these SNVs form a genome gradient across the three main continental populations. These SNVs are important elements of the innate immune system and in the response against viruses. Our data support the Human Immune Genome Complex Gradient hypothesis as a new theory that may help to explain the CZS catastrophe in Brazil.

genetics↗