bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2023.02.08.527617

Genetic investigation of honeybee populations in Kazakhstan

Gritsenko, D.·Temirbayeva, K.·Taskuzhina, A.·Kostyukova, V.·Pozharskiy, A.·Khusnitdinova, M.·Krupskiy, O.·Mayer, A.·Nuralieva, U.·Bienefeld, K.
View original source ↗Export metadata ↓

Abstract

Beekeeping as a staple of agriculture in Kazakhstan is believed to have emerged when external bee specimens were introduced into the country. The Central Russian bee (Apis mellifera mellifera) has been present throughout Kazakhstanian apiaries for a long time since its import into Eastern Kazakhstan at the end of the 18th century. To date, six subspecies have been distributed across the country (A.m. sossimai, A.m. carpatica, A.m. mellifera, A.m. ligustica, [A].m. caucasica, and A.m. carnica). According to mitochondrial haplotype analysis based on DraI mtDNA COI-COII (DmCC) test, local samples were represented by C2 (316), C1 (99), and M4 (7) haplotypes. The results of simple sequence repeats (SSR) genotyping revealed a large polymorphism at nine microsatellite loci, with the number of alleles amounting to 35 (AP55), 32 (AP43), 25 (A124), 18 (A113), 13 (A88), 12 (A43), 11 (A007), 7 (A28), and 5 (A24). Relative to the expected heterozygosity (He), the observed heterozygosity (Ho) was slightly higher for most markers considering both the overall samples and individual populations. The inbreeding coefficient confirmed the excess outbreeding for the geographical populations of car-Shym-T (-0,105), car-zham-A (-0,114), Zhet-Alakol (-0,008), and Zhet-Ushbulak (-0,028). The admixture of honeybee local populations was confirmed by the research presented here.The differentiation of populations was only possible by geographical location according to clustering analysis. A considerable degree of genetic admixtures among subspecies was identified in every population. The subspecies were not separated from each other. None of the groups formed by the neighbor-joining tree based on Neis genetic distance included a precise subspecies or population. All groups represented an admixture of subspecies from different populations. Unregulated cross-breeding for the past 50 years has laid the foundation for the promiscuous genetic nature of honeybee populations in Kazakhstan. It could be concluded that some samples were the result of cross-breeding with endemic bee Apis mellifera pomonella since most apiaries were located in areas of endemic bee distribution.

Explore related subjects

geneticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gritsenko, D., Temirbayeva, K., Taskuzhina, A., Kostyukova, V., Pozharskiy, A., Khusnitdinova, M., Krupskiy, O., Mayer, A., Nuralieva, U., Bienefeld, K.. 2023-02-08. Genetic investigation of honeybee populations in Kazakhstan. https://doi.org/10.1101/2023.02.08.527617

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Utilizing single-cell data for per-cell type eQTL mapping in the human pancreas

Aims/hypothesis The human pancreas is a central organ for metabolic regulation that is comprised of diverse cell types that uniquely contribute to its function. Previous studies have performed expression quantitative trail loci (eQTL) discovery in either whole pancreas or in pancreatic islets, but due to differences between pancreatic cell types, this approach does not reveal cell type-specific effects. In this study, we sought to either implicate the cell type of action for known eQTLs or identify new eQTLs that may have been masked in bulk studies by performing eQTL discovery in individual pancreatic cell types. Methods We clustered 153,018 single-cell RNA sequencing (scRNA-seq) data from 71 pancreatic islet donors from the Human Pancreas Analysis Program (HPAP). We performed eQTL discovery in six pancreatic cell types using this resource directly. We further utilized this single cell resource as a reference to deconvolute bulk pancreatic RNA sequencing data from 305 Genotype Tissue Expression (GTEx) project donors and performed eQTL discovery in four pancreatic cell types. Finally, we performed fine-mapping and co-localization of pancreatic cell type eQTLs with metabolic GWAS to connect our findings to metabolic disease risk. Results From analyzing 71 individuals with single cell profiles, we identified 112 unique eGenes across six pancreatic cell types, 99 of which had been identified previously and 13 unique to this study. From the deconvoluted eQTLs, we identified 3,134 unique eGenes across four pancreatic cell types, 116 of which were unique to our study. Fine-mapping and co-localization of eQTLs with metabolic GWAS yielded key leads that warrant further investigation, such as the association of rs2168101 with LMO1 expression in alpha cells. Conclusions/interpretation We identified new signals that were previously not found in bulk pancreatic eQTL studies and potential cell type of action for several signals that were identified previously. Although there are limitations to the power, and therefore, discoverability of this study, it provides insights into how individual pancreatic cells differently contribute to metabolic disease.

genetics↗
bioRxiv2026

MOD-scTWAS: Leveraging gene co-expression for single-cell transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) provide an effective framework for identifying genes associated with complex traits. Population-scale single-cell transcriptomic data enable genetically regulated expression (GReX) prediction and TWAS analyses at cell-type resolution, but the predictive performance of existing single-cell TWAS methods remains limited. Here, we develop MOD-scTWAS, a module-based method that jointly models GReX for genes within co-expression modules to borrow information across genes. Starting from a generative model for single-cell gene expression, MOD-scTWAS accounts for the heteroscedasticity and cross-gene correlation of individual-level pseudobulk expression in joint GReX prediction. In cross-validation analyses of the OneK1K dataset, MOD-scTWAS achieved higher mean GReX prediction accuracy than scTWAS across all 14 cell types and increased the number of imputable genes. When applied to TWAS analyses of UK Biobank quantitative hematological traits, MOD-scTWAS identified more significant cell type-gene-trait associations than scTWAS. These results demonstrate the potential of leveraging gene co-expression through joint modeling to improve cell-type-specific GReX prediction and TWAS discovery.

genetics↗
bioRxiv2026

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗