Using genomic information to conserve genetic diversity in livestock

Concern about the status of livestock breeds and their conservation has increased as selection and small population sizes caused loss of genetic diversity. Meanwhile, dense SNP chips and whole genome sequences (WGS) became available, providing opportunities to accurately quantify the impact of selection on genetic diversity and develop tools to better preserve such genetic diversity for long-term perspectives. This thesis aimed to infer the impact of selection and mitigate its effects on genetic diversity using genomic information. One of the advantages of WGS information, compared to pedigree and SNP chip information, is that it provides information on all variants, including rare ones, and ‘true’ relationships between individuals may be estimated thus being useful for evaluating genetic diversity. Taking into account rare variants had significant effects on estimated relationships. Moreover, optimal contribution (OC) strategy was used to perform selection either in a breeding program, maximising genetic merit while minimising loss of genetic diversity, or to build a gene bank, only maximising the conserved genetic diversity, with the aim to quantify loss of genetic diversity due to selection decisions. More genetic diversity was conserved when genomic information was used for selection decisions instead of pedigree and WGS information revealed a high loss of genetic diversity due to losing rare variants. Ways to reduce the loss of genetic diversity during a genomic selection program were investigated. The choice of individuals to update the reference population was proposed as a promising way to better conserve genetic diversity in a breeding population. In fact, changes in the reference population will lead to changes in prediction equations and thus ultimately to a shift in long-term selection decisions. Differences between reference population design using either random, truncation or OC selection of individuals, on the breeding population were modest but OC achieved conservation of more genetic diversity in the breeding population with only a small reduction in long-term genetic gain. Finally the potential of gene bank material as additional source of genetic diversity in the breeding population was examined, using the Dutch MRY cattle breed as a case study. Including old bulls, containing more genetic diversity than recent bulls, in the population of fathers for the next generation, selected with OC, resulted in both a slightly higher genetic merit and more genetic diversity conserved. The impact of selection on genetic diversity can be monitored by estimating the loss of rare variants over time. For the long-term perspectives of populations it is important to use specialised methods and genomic information to balance between selection response and conservation of genetic diversity. </p

Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid drones:Sequencing haploid honey bee drones

International audienceHoney bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environment and mate naturally with queens from the local subspecies. The resulting admixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to subspecies, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP-chip or by low-pass sequencing, or (iii) selecting SNPs compatible with the requirements of genotyping chips

Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid drones

Honey bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environment and mate naturally with queens from the local subspecies. The resulting admixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to subspecies, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP-chip or by low-pass sequencing, or (iii) selecting SNPs compatible with the requirements of genotyping chips.This work was performed in collaboration with the GeT platform, Toulouse (France), a partner of the National Infrastructure France Génomique, thanks to support by the Commissariat aux Grands Invetissements (ANR-10-INBS-0009). Bioinformatics analyses were performed on the GenoToul Bioinfo computer cluster. This work was funded by a grant from the INRA Département de Génétique Animale (INRA Animal Genetics division) and by the SeqApiPop programme, funded by the FranceAgriMer grant 14-21-AT. We thank John Kefuss for helpful discussions. We thank Andrew Abrahams for providing honey bee samples from Colonsay (Scotland), the Association Conservatoire de l'Abeille Noire Bretonne (ACANB) for samples from Ouessant (France), CETA de Savoie for sample from Savoie, ADAPI for samples from Porquerolles and all beekeepers and bee breeders who kindly participated in this study by providing samples from their colonies.info:eu-repo/semantics/publishedVersio

Descriptive Analysis of the Varroa Non-Reproduction Trait in Honey Bee Colonies and Association with Other Traits Related to Varroa Resistance

In the current context of worldwide honey bee colony losses, among which the varroa mite plays a major role, the hope to improve honey bee health lies in part in the breeding of varroa resistant colonies. To do so, methods used to evaluate varroa resistance need better understanding. Repeatability and correlations between traits such as mite non-reproduction (MNR), varroa sensitive hygiene (VSH), and hygienic behavior are poorly known, due to practical limitations and to their underlying complexity. We investigate (i) the variability, (ii) the repeatability of the MNR score, and (iii) its correlation with other resistance traits. To reduce the inherent variability of MNR scores, we propose to apply an empirical Bayes correction. In the short-term (ten days), MNR had a modest repeatability of 0.4, whereas in the long-term (a month), it had a low repeatability of 0.2, similar to other resistance traits. Within our dataset, there was no correlation between MNR and VSH. Although MNR is amongst the most popular varroa resistance estimates in field studies, its underlying complex mechanism is not fully understood. Its lack of correlation with better described resistance traits and low repeatability suggest that MNR needs to be interpreted cautiously, especially when used for selection

Whole-genome sequence data uncover loss of genetic diversity due to selection

Background: Whole-genome sequence (WGS) data give access to more complete structural genetic information of individuals, including rare variants, not fully covered by single nucleotide polymorphism chips. We used WGS to investigate the amount of genetic diversity remaining after selection using optimal contribution (OC), considering different methods to estimate the relationships used in OC. OC was applied to minimise average relatedness of the selection candidates and thus miminise the loss of genetic diversity in a conservation strategy, e.g. for establishment of gene bank collections. Furthermore, OC was used to maximise average genetic merit of the selection candidates at a given level of relatedness, similar to a genetic improvement strategy. In this study, we used data from 277 bulls from the 1000 bull genomes project. We measured genetic diversity as the number of variants still segregating after selection using WGS data, and compared strategies that targeted conservation of rare (minor allele frequenc

The impact of using old germplasm on genetic merit and diversity - A cattle breed case study

Artificial selection and high genetic gains in livestock breeds led to a loss of genetic diversity. Current genetic diversity conservation actions focus on long-term maintenance of breeds under selection. Gene banks play a role in such actions by storing genetic materials for future use and the recent development of genomic information is facilitating characterization of gene bank material for better use. Using the Meuse-Rhine-Issel Dutch cattle breed as a case study, we inferred the potential role of germplasm of old individuals for genetic diversity conservation of the current population. First, we described the evolution of genetic merit and diversity over time and then we applied the optimal contribution (OC) strategy to select individuals for maximizing genetic diversity, or maximizing genetic merit while constraining loss of genetic diversity. In the past decades, genetic merit increased while genetic diversity decreased. Genetic merit and diversity were both higher in an OC scenario restricting the rate of inbreeding when old individuals were considered for selection, compared to considering only animals from the current population. Thus, our study shows that gene bank material, in the form of old individuals, has the potential to support long-term maintenance and selection of breeds.</p