Biology subjects

Estonba, A.

Publications and source records attributed to Estonba, A..

3 recordsLinked to original sources

bioRxiv2024

A SNP-based honey bee paternity assignment test for evaluating the effectiveness of mating stations and its application to the Ataun valley, Basque Country, Spain

Geographically isolated mating stations are deployed across Europe to facilitate controlled mating with selected drone-producing colonies. To assess the reliability of these stations, we developed a paternity assignment test using a custom Illumina genotyping chip with 6457 SNPs based on two metrics (number of mismatch alleles and kinship). The method demonstrated remarkable accuracy during validation with an independent dataset of known parent-offspring pairs, with an accuracy rate of 97.7%. We then applied the developed paternity assignment test to the Apis mellifera iberiensis mating station in the Ataun valley, Basque Country, Spain, in 2021. Drone-producing colonies in the valley were sampled and genotyped, as well as 156 worker offspring of queens mated at the station, and 56 drones collected in the drone congregation area. Out of the 156 worker samples, we could assign paternity of 120 (76.9%) to one of the drone-producing colonies in the valley, while 23.1% were of unknown patriline. Out of the 56 drones collected in the air, 52 (92.9%) were assigned to drone-producing colonies. We were also able to determine the colonies and apiaries that made the most significant contributions to the matings. This information aids in effective apiary management, including the selection of suitable mating station locations and the positioning of drone-producing colonies therein. Overall, our SNP-based paternity assignment test offers a valuable tool for evaluating mating station effectiveness across Europe, crucial for advancing breeding objectives in honey bee populations.

genetics↗

bioRxiv2021

Recovering high-quality host genomes from gut metagenomic data through genotype imputation

Metagenomic data sets of host-associated microbial communities often contain host DNA that is usually discarded because the amount of data is too low for accurate host genetic analyses. However, if a reference panel is available, genotype imputation can be employed to reconstruct host genotypes and maximise the use of such a priori useless data. We tested the performance of a two-step strategy to input genotypes from four types of reference panels, comprised of deeply sequenced chickens to low-depth host genome (~2x coverage) data recovered from metagenomic samples of chicken intestines. The target chicken population was formed by two broiler breeds and the four reference panels employed were (i) an internal panel formed by population-specific individuals, (ii) an external panel created from a public database, (iii) a combined panel of the previous two, and (iv) a diverse panel including more distant populations. Imputation accuracy was high for all tested panels (concordance >0.90), although samples with coverage under 0.28x consistently showed the lowest accuracies. The best imputation performance was achieved by the combined panel due to the high number of imputed variants, including low-frequency ones. However, common population genetics parameters measured to characterise the chicken populations, including observed heterozygosity, nucleotide diversity, pairwise distances and kinship, were only minimally affected by panel choice, with all four panels yielding suitable results for host population characterization and comparison. Likewise, genome scans between the two studied broiler breeds using imputed data with each panel consistently identified the same sweep regions. In conclusion, we show that the applied imputation strategy enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitate the implementation of hologenomic approaches that jointly analyse host genomic and microbial metagenomic data. Author summaryWe introduce and assess a methodological approach that enables recovering animal genomes from complex mixtures of metagenomic data, and thus expand the portfolio of analyses that can be conducted from samples such as faeces and gut contents. Metagenomic data sets of host-associated microbial communities often contain DNA of the host organism. The principal drawback to use this data for host genomic characterisation is the low percentage and quality of the host DNA. In order to leverage this data, we propose a two-step imputation method, to recover high-density of variants. We tested the pipeline in a chicken metagenomic dataset, validated imputation accuracy statistics, and studied common population genetics parameters to assess how these are affected by genotype imputation and choice of reference panel. Being able to analyse both domains from the same data set could considerably reduce sampling and laboratory efforts and resources, thereby yielding more sustainable practices for future studies that embrace a hologenomic approach that jointly analyses animal genomic and microbial metagenomic features.

genomics↗

bioRxiv2018

Hygroregulation, a key ability for eusocial insects: Native Western European bees as a case study

Sociality has brought many advantages to various hymenoptera species, including their ability of regulating physical factors in their nest (e.g., temperature). Although less studied, humidity is known to be important for egg, larval and pupal development. Two subspecies of Apis mellifera of the M branch, also called black bees, were used as models to test the \"hygroregulation hypothesis\", by means of monitoring hygrometry in hives during one year in four conservation centers: two in France (A. m. mellifera) and two in Portugal (A. m. iberiensis). We investigated the ability of both subspecies to regulate the hygrometry daily, but also during the seasons and one complete year. Our data and statistical analysis probed the capacity of the bees to regulate humidity in their hive, regardless of the day, season or subspecies. Furthermore, the study showed that humidity in beehives is very stable even during winter, when brood is absent, and when temperature is known to be less stable in the beehives. These results would support that hygrometry could prevail over temperature in maintaining nest homeostasis, maybe because of a bigger importance of hygrometry for all the population during a year, or because of the imprint of the evolutionary history of this hymenopteran lineage.

ecology↗