Biology subjects

Kasianov, A.

Publications and source records attributed to Kasianov, A..

4 recordsLinked to original sources

bioRxiv2026

From Genes to Brains: Molecular Evolution and Mammalian Brain Cellular Diversity

Mammalian brains exhibit extensive diversity in size, cellular composition, and organization, yet the molecular evolutionary changes associated with this phenotypic diversification remain incompletely understood. Here, we investigated whether protein-sequence evolution covaries with quantitative differences in brain phenotypes across mammals. We integrated 29 brain and body traits with orthologous protein sequences from 18 mammalian species and obtained gene-specific molecular evolutionary measures for 10,395 genes. To reduce redundancy among strongly correlated phenotypes, we selected five representative traits that explained 88.12% of the standardized trait variance under linear reconstruction. Using RERconverge, we tested for associations between gene-specific relative evolutionary rates and evolutionary changes in these five representative traits. The primary analysis, based on log-transformed phenotypes, identified 25 significant gene--trait associations involving 23 genes, 19 of which were also recovered using untransformed phenotypes, indicating that a substantial subset of the associations was robust to phenotype transformation. Expression profiling of these shared candidate genes across adult human GTEx brain tissues revealed heterogeneous patterns ranging from broad expression across the examined tissues to low adult brain expression. Functional enrichment analysis further showed that the gene set retained for comparative analysis was enriched for diverse biological processes, including metabolic, cellular, and neural pathways. These results identify gene-specific evolutionary-rate associations with quantitative mammalian phenotypes and provide functional context for the genes represented in the comparative analysis. Our study provides a comparative framework linking relative evolutionary rates of protein-coding genes to quantitative variation in mammalian brain cellular architecture while accounting for shared evolutionary history.

evolutionary biology↗

bioRxiv2025

Assessing the feasibility of machine learning for ancient DNA age prediction: limitations and insights

We investigated the possibility of estimating the age of ancient biological samples directly from their DNA damage profiles using supervised machine learning. Traditional dating methods such as radiocarbon dating, dendrochronology rely on either material context or isotope composition, while our approach exploits intrinsic molecular degradation signatures. Using damage statistics obtained from ancient DNA sequencing data, we trained several regression models to predict sample age over a temporal range of up to 10,000 years. Despite initial correlations between specific damage features and age, cross-validation and external testing revealed no statistically significant predictive signal beyond mean-based baselines. These findings indicate that, in the current formulation, DNA damage information alone is insufficient for reliable age estimation. However, this negative result provides important methodological insight: environmental and biochemical factors appear to dominate damage variation, effectively masking chronological signal. We suggest that integrating contextual data, expanding labeled datasets, and incorporating physical models of DNA decay may improve future attempts. Our study thus contributes to a transparent assessment of the limitations and prospects of DNA-based fossil dating.

bioinformatics↗

bioRxiv2025

Post-admixture selection favours Duffy negativity in the Lower Okavango Basin

The FY*BES allele in the human Duffy blood group is nearly fixed across much of sub-Saharan Africa. Individuals homozygous for this allele (Duffy-negative) were considered resistant to red blood cell invasion by the malaria parasite Plasmodium vivax, restricting its distribution across the continent. However, as recent studies have demonstrated that P. vivax can infect Duffy-negative individuals and is widespread among African populations where FY*BES predominates, long-standing assumptions about the evolutionary relationship between Duffy negativity and parasite resistance should be re-evaluated across diverse geographic, ecological and epidemiological settings. Previous research investigating the role of natural selection in increasing the frequency of the FY*BES allele has primarily centered on admixed populations with African and non-African ancestries from regions with long-documented P. vivax transmission. Here, we focus on the Khwe foragers from the lower Okavango River Basin, where the parasite has only recently been reported. Using locus-specific statistics, simulations of neutral scenarios, and local ancestry inference, we found strong evidence for post-admixture selection promoting FY*BES introgression from Bantu-speaking populations into the Khwe. If P. vivax resistance indeed drove the rise in FY*BES allele frequency, our findings suggest that the parasite has been present in the region at least 500 to 1,000 years ago.

genetics↗

bioRxiv2017

Coat color allele and mtDNA haplotype distributions in Russian cat populations: a citizen-science research

This work has started as a project for the summer school in molecular and theoretical biology. Efficient teaching and learning modern methods of molecular biology and population genetics in a two-week study course for high school students needs an attractive subject. We chose phylogeography of the domestic cat as the subject of our project because 1) everybody likes cats; 2) cats are polymorphic for several coat color mutations, which can be easily detected by street survey or in the photographs; 3) samples for DNA extraction are easy to collect without posing ethical and biosafety problems; 4) rich background information of geographical distribution of coat color alleles and variation in mtDNA is available; 5) phylogeography of cat population in Russia is poorly studied and therefore new data collected in this large territory may shed a light on the global cat distribution and on the origin of the fancy breeds.\n\nDuring the project students studied coat color and mitotype distribution across Russian random bred cats. The basics of field (observations of natural cat populations, hair collection), formal (inheritance of coat colors), mathematical population (allele frequency distributions and their comparisons, building phylogenetic trees, multidimensional scaling), and molecular (DNA extraction and amplification, quality control of DNA sequencing data) genetics were covered.\n\nWe scored coat color phenotypes in 1182 cats and sequenced mtDNA control region from hair samples of 38 cats from 18 geographical sites. Analysis of coat color alleles frequencies and mitotype distribution confirmed relative homogeneity of gene pools of Russian cat populations, indicating their recent origin. We found several unique mitotypes and demonstrated that OL1 mitotype, previously found only in Siberian fancy breed, was present in random bred cats from several Russian cities. This contributes to the discussion on the origin of the Siberian breed of cats, and supports the view that Siberians is a recent breed created in the 1980s by breeding of selected representatives of the random bred population.

genetics↗