Phenotypic and genetic characterization of Africanized Apis mellifera colonies with natural tolerance to Varroa destructor and contrasting defensive behavior.

Africanized Apis mellifera colonies with promising characteristics for beekeeping have been detected in northern Argentina (subtropical climate) and are considered of interest for breeding programs. Integral evaluation of this feral material revealed high colony strength and resistance/tolerance to brood diseases. However, these Africanized honeybees (AHB) also showed variable negative behavioral traits for beekeeping, such as defensiveness, tendency to swarm and avoidance behavior. We developed a protocol for the selection of AHB stocks based on defensive behavior and characterized contrasting colonies for this trait using NGS technologies. For this purpose, population and behavioral parameters were surveyed throughout a beekeeping season in nine daughter colonies obtained from a mother colony (A1 mitochondrial haplotype) with valuable characteristics (tolerance to the mite Varroa destructor, high colony strength and low defensiveness). A Defensive Behavior Index was developed and tested in the colonies under study. Mother and two daughter colonies displaying contrasting defensive behavior were analyzed by ddRADseq. High-quality DNA samples were obtained from 16 workers of each colony. Six pooled samples, including two replicates of each of the three colonies, were processed. A total of 12,971 SNPs were detected against the reference genome of A. mellifera, 142 of which showed significant differences between colonies. We detected SNPs in coding regions, lncRNA, miRNA, rRNA, tRNA, among others. From the original data set, we also identified 647 SNPs located in protein-coding regions, 128 of which are related to 21 genes previously associated with defensive behavior, such as dop3 and dopR2, CaMKII and ADAR, obp9 and obp10, and members of the 5-HT family. We discuss the obtained results by considering the influence of polyandry and paternal lineages on the defensive behavior in AHB and provide baseline information to use this innovative molecular approach, ddRADseq, to assist in the selection and evaluation of honey bee stocks showing low defensive behavior for commercial uses.

Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices.

Genomic selection based on the single-step genomic best linear unbiased prediction (ssGBLUP) approach is becoming an important tool in forest tree breeding. The quality of the variance components and the predictive ability of the estimated breeding values (GEBV) depends on how well marker-based genomic relationships describe the actual genetic relationships at unobserved causal loci. We investigated the performance of GEBV obtained when fitting models with genomic covariance matrices based on two identity-by-descent (IBD) and two identity-by-state (IBS) relationship measures. Multiple-trait multiple-site ssGBLUP models were fitted to diameter and stem straightness in five open-pollinated progeny trials of Eucalyptus dunnii, genotyped using the EUChip60K. We also fitted the conventional ABLUP model with a pedigree-based covariance matrix. Estimated relationships from the IBD estimators displayed consistently lower standard deviations than those from the IBS approaches. Although ssGBLUP based in IBS estimators resulted in higher trait-site heritabilities, the gain in accuracy of the relationships using IBD estimators has resulted in higher predictive ability and lower bias of GEBV, especially for low-heritability trait-site. ssGBLUP based on IBS and IBD approaches performed considerably better than the traditional ABLUP. In summary, our results advocate the use of the ssGBLUP approach jointly with the IBD relationship matrix in open-pollinated forest tree evaluation.

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections.

Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A mixed genotyping strategy was implemented, by combining proprietary genotyping-by-sequencing data with public whole-genome-sequencing data, to generate an integrative 11,834-common single nucleotide polymorphism matrix including the three breeding collections. In general, the GD estimates obtained were moderate. An analysis of molecular variance provided evidence of population structure between breeding collections. However, the optimal number of subpopulations, studied via discriminant analysis of principal components (K = 12), the bayesian STRUCTURE algorithm (K = 6) and distance-based methods (K = 9) remains unclear, since no single unifying characteristic is apparent for any of the inferred groups. Different overall patterns of linkage disequilibrium (LD) were observed across chromosomes, with Chr10, Chr17, Chr5, and Chr2 showing the highest LD. This work represents the largest and most comprehensive inter-breeding collection analysis of genomic diversity for cultivated sunflower conducted to date.