Humans have had a major influence on the dissemination of crops beyond their native range, thereby offering new hybridization opportunities. Characterizing admixed genomes with mosaic origins generates valuable insight into the adaptive history of crops and the impact on current varietal diversity. We applied the ELAI tool—an efficient local ancestry inference method based on a two-layer hidden Markov model to track segments of wild origin in cultivated accessions in the case of multiway admixtures. Source populations—which may actually be limited and partially admixed—must be generally specified when using such inference models. We thus developed a framework to identify local ancestry with admixed source populations. Using sequencing data for wild and cultivated Coffea canephora (commonly called Robusta), our approach was found to be highly efficient and accurate on simulated hybrids. Application of the method to assess elite Robusta varieties from Vietnam led to the identification of an accession derived from a likely backcross between two genetic groups from the Congo Basin and the western coastal region of Central Africa. Admixtures resulting from crop hybridization and diffusion could thus lead to the generation of elite high-yielding varieties. Our methods should be widely applicable to gain insight into the role of hybridization during plant and animal evolutionary history.

Nanodiamond (ND) has recently emerged as a potential nanomaterial for nanovaccine development. Here, a plant-based haemagglutinin protein (H5.c2) of A/H5N1 virus was conjugated with detonation NDs (DND) of 3.7 nm in diameter (ND4), and high-pressure and high-temperature (HPHT) oxidative NDs of ~40–70 nm (ND40) and ~100–250 nm (ND100) in diameter. Our results revealed that the surface charge, but not the size of NDs, is crucial to the protein conjugation, as well as the in vitro and in vivo behaviors of H5.c2:ND conjugates. Positively charged ND4 does not effectively form stable conjugates with H5.c2, and has no impact on the immunogenicity of the protein both in vitro and in vivo. In contrast, the negatively oxidized NDs (ND40 and ND100) are excellent protein antigen carriers. When compared to free H5.c2, H5.c2:ND40, and H5.c2:ND100 conjugates are highly immunogenic with hemagglutination titers that are both 16 times higher than that of the free H5.c2 protein. Notably, H5.c2:ND40 and H5.c2:ND100 conjugates induce over 3-folds stronger production of both H5.c2-specific-IgG and neutralizing antibodies against A/H5N1 than free H5.c2 in mice. These findings support the innovative strategy of using negatively oxidized ND particles as novel antigen carriers for vaccine development, while also highlighting the importance of particle characterization before use.

Background Using long reads provide higher contiguity and better genome assemblies. However, producing such high quality sequences from raw reads requires to chain a growing set of tools, and determining the best workflow is a complex task. Results To tackle this challenge, we developed CulebrONT, an open-source, scalable, modular and traceable Snakemake pipeline for assembling long reads data. CulebrONT enables to test on multiple samples multiple long reads assemblers in parallel, and can optionally perform, downstream assembly, circularization and polishing. It further provides a range of assembly quality metrics summarized in a final user-friendly report. Conclusions CulebrONT leverages the difficulties of assembly pipelines development, and allow even basic users to obtain high-quality assemblies.

Low‐coverage sequencing (LCS) followed by genotype imputation has become a cost‐efficient approach for obtaining whole‐genome SNPs. Several imputation methods for LCS data have been developed over the last decade. However, comparisons of their accuracy in inferring missing genotypes and their effectiveness for downstream analysis such as population genetics have not been comprehensively studied. In the present study, we assessed the imputation performance of five different tools: GLIMPSE2, GeneImp, QUILT2, STITCH and Beagle5.4, using populations simulated by SLiM4 that represent different levels of genetic relatedness and inbreeding. Imputation accuracy was calculated at the level of variant, haplotype and sample. The effectiveness of using imputed genotypes in recovering genetic structure, relatedness, inbreeding coefficients and demographic history was subsequently evaluated. The imputation accuracy of different methods was further tested in a real population of 283 hihi (stitchbird) samples. Our results suggest a high accuracy of all the tested methods on populations with high levels of genetic relatedness. However, in populations with low relatedness, the imputation accuracy differed across different tools and impacted the results of some downstream analyses. The simulation and imputation pipeline presented here can help determine the most suitable imputation method for different population scenarios.

Vietnam is the main producer of Robusta (Coffea canephora) coffee, but faces several future agronomic challenges. These may be addressed through breeding for improved cultivars and more sustainable cropping systems. For such efforts to be successful and efficient, locally available genetic resources must be understood. Indeed, while C. canephora exhibits high genetic diversity in its native tropical African forests, only a part of it contributed to the worldwide diffusion of Robusta. Here we traced the African origins of Robusta accessions cultivated in the Central Highlands of Vietnam. A total of 126 Robusta accessions from the Vietnam coffee germplasm collection were characterized, including historical, elite and local cultivated clones. Their genetic diversity and origins were inferred through comparisons with wild reference samples using a new set of 261 genome-wide SNPs. A core set of 45 accessions that maximize the genetic distance and allelic richness were identified for conservation and breeding priorities. Full genome sequencing of these individuals helped to closely trace the origins of chromosomal segments back to different, geographically-structured wild African genetic groups. All Vietnamese Robusta accessions displayed Congo Basin (ER group) origins, albeit to various extents. However, we also uncovered contribution from several other genetic groups, variously from the Guinean region (D), the central African Atlantic coast (AG), and Eastern CAR/Uganda (OB), in 31 hybrid individuals. These source groups have been widely used in crossbreeding to develop elite clones. In addition, using whole-genome sequencing data, we also identified various admixture patterns at the chromosome level among the hybrids, which might provide valuable information for selecting breeding materials.

Genotype imputation, the inference of missing genotypes using a reference set of population haplotypes, is a cost‐effective tool for improving the quality and quantity of genetic datasets. Imputation is usually applied to large and well‐characterised datasets of humans and livestock, even though it could also benefit smaller natural populations. This study aims to understand the best practices and effectiveness of imputation with a small reference panel for species with low genetic diversity, using a case study of a population of the hihi/stitchbird ( Notiomystis cincta ). We used a leave‐one‐out method to test imputation on 30 high‐coverage hihi individuals where SNPs were masked before being imputed with Beagle v5.4. Imputation accuracy was measured using r ² , the correlation between imputed and ground truth genotype dosages. We tested combinations of five imputation parameters, the inclusion of two linkage maps, reference panels of different sizes and compositions and targets of various SNP densities and sporadic missingness. We achieved mean r ² exceeding 0.95 in most tests from a small reference panel of high‐fecundity individuals. Imputation accuracy was not improved by including a linkage map and decreased at very low SNP densities. Imputed SNPs were filtered using r ² to assess downstream heterozygosity calculations, the site frequency spectrum (SFS) and inference of runs of homozygosity (ROHs). We found that filtering and SNP density greatly affected heterozygosity and SFS at low SNP densities but that ROH inference was relatively robust to both. We provide a template for testing and optimising imputation in other wild populations.