CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons

Cultivated cottons are the most important economic crop, which produce natural fiber for the textile industry. In recent years, the genetic basis of several essential traits for cultivated cottons has been gradually elucidated by decoding their genomic variations. Although an abundance of resequencing data is available in public, there is still a lack of a comprehensive tool to exhibit the results of genomic variations and genome-wide association study (GWAS). To assist cotton researchers in utilizing these data efficiently and conveniently, we constructed the cotton genomic variation database (CottonGVD; http://120.78.174.209/ or http://db.cngb.org/cottonGVD). This database contains the published genomic information of three cultivated cotton species, the corresponding population variations (SNP and InDel markers), and the visualized results of GWAS for major traits. Various built-in genomic tools help users retrieve, browse, and query the variations conveniently. The database also provides interactive maps (e.g., Manhattan map, scatter plot, heatmap, and linkage disequilibrium block) to exhibit GWAS and expression GWAS results. Cotton researchers could easily focus on phenotype-associated loci visualization, and they are interested in and screen for candidate genes. Moreover, CottonGVD will continue to update by adding more data and functions.

panModule: detecting conserved modules in the variable regions of a pangenome graph

The recent years have seen the rise of pangenomes as comparative genomic tools to better understand the evolution of gene content among microbial genomes in close phylogenetic groups such as species. While the core or persistent genome is often well-known as it includes essential or ubiquitous genes, the variable genome is usually less characterized and includes many genes with unknown functions even among the most studied organisms. It gathers important genes for strain adaptation that are acquired by horizontal gene transfer. Here, we introduce panModule, an original method to identify conserved modules in pangenome graphs built from thousands of microbial genomes. These modules correspond to synteny blocks composed of consecutive genes that are conserved in a subset of the compared strains. Identifying conserved modules can provide insights on genes involved in the same functional processes, and as such is a very helpful tool to facilitate the understanding of genomic regions with complex evolutionary histories. The panModule method was benchmarked on a curated dataset of conserved modules in Escherichia coli genomes. Its use was illustrated through a study of a high pathogenicity island in Klebsiella pneumoniae that allowed a better understanding of this region. panModule is freely available and accessible through the PPanGGOLiN software suite (https://github.com/labgem/PPanGGOLiN).

Genetic architecture and genomic prediction accuracy of apple quantitative traits across environments

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. The apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic prediction accuracy, and studying genotype by environment interactions (GxE). Here we show contrasting genetic architecture and genomic prediction accuracies for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic prediction accuracies of 0.18-0.88 were estimated using single-environment univariate, single-environment multivariate, multi-environment univariate, and multi-environment multivariate models. The GxE accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.

Unraveling Cuticle Formation, Structure, and Properties by Using Tomato Genetic Diversity

The tomato (Solanum lycopersicum) fruit has a thick, astomatous cuticle that has become a model for the study of cuticle formation, structure, and properties in plants. Tomato is also a major horticultural crop and a long-standing model for research in genetics, fruit development, and disease resistance. As a result, a wealth of genetic resources and genomic tools have been established, including collections of natural and artificially induced genetic diversity, introgression lines of genome fragments from wild relatives, high-quality genome sequences, phenotype and gene expression databases, and efficient methods for genetic transformation and editing of target genes. This mini-review reports the considerable progresses made in recent years in our understanding of cuticle by using and generating genetic diversity for cuticle-associated traits in tomato. These include the synthesis of the main cuticle components (cutin and waxes), their role in the structure and properties of the cuticle, their interaction with other cell wall polymers as well as the regulation of cuticle formation. It also addresses the opportunities offered by the untapped germplasm diversity available in tomato and the current strategies available to exploit them.

Genetics of Thoroughbred Racehorse Performance

Thoroughbred horses have been selected for racing performance for more than 400 years. Despite continued selection, race times have not improved significantly during the past 60 years, raising the question of whether genetic variation for racing performance still exists. Studies using phenotypes such as race time, money earned, and handicapping, however, demonstrate that there is extensive variation within these traits and that they are heritable. Even so, these are poor measures of racing success since Thoroughbreds race at different ages and distances and on different types of tracks, and some may not race at all. With the advent of genomic tools, DNA variants are being identified that contribute to racing success. Aside from strong associations for myostatin variants with best racing distance, weak to modest associations with racing phenotypes are reported for other genomic regions. These data suggest that diverse genetic strategies have contributed to producing a successful racehorse, and genetic variation contributing to athleticism remains important. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Regeneration in the Segmented Annelid Capitella teleta

The segmented worms, or annelids, are a clade within the Lophotrochozoa, one of the three bilaterian superclades. Annelids have long been models for regeneration studies due to their impressive regenerative abilities. Furthermore, the group exhibits variation in adult regeneration abilities with some species able to replace anterior segments, posterior segments, both or neither. Successful regeneration includes regrowth of complex organ systems, including the centralized nervous system, gut, musculature, nephridia and gonads. Here, regenerative capabilities of the annelid Capitella teleta are reviewed. C. teleta exhibits robust posterior regeneration and benefits from having an available sequenced genome and functional genomic tools available to study the molecular and cellular control of the regeneration response. The highly stereotypic developmental program of C. teleta provides opportunities to study adult regeneration and generate robust comparisons between development and regeneration.

Making Genomic Surveillance Deliver: A Lineage Classification and Nomenclature System to Inform Rabies Virus Elimination

The availability of pathogen sequence data and use of genomic surveillance is rapidly increasing. Genomic tools and classification systems need updating to reflect this. Here, rabies virus is used as an example to showcase the potential value of updated genomic tools to enhance surveillance to better understand epidemiological dynamics and improve disease control. Previous studies have described the evolutionary history of rabies virus, however the resulting taxonomy lacks the definition necessary to identify incursions, lineage turnover and transmission routes at high resolution. Here we propose a lineage classification system based on the dynamic nomenclature used for SARS-CoV-2, defining a lineage by phylogenetic methods for tracking virus spread and comparing sequences across geographic areas. We demonstrate this system through application to the globally distributed Cosmopolitan clade of rabies virus, defining 73 total lineages within the clade, beyond the 22 previously reported. We further show how integration of this tool with a new rabies virus sequence data resource (RABV-GLUE) enables rapid application, for example, highlighting lineage dynamics relevant to control and elimination programmes, such as identifying importations and their sources, and areas of persistence and transmission, including transboundary incursions. This system and the tools developed should be useful for coordinating and targeting control programmes and monitoring progress as we work towards eliminating dog-mediated rabies, as well as having potential for broad application to the surveillance of other viruses.

168 Use of Genomic Tools to Improve Production Efficiency, Health Resilience and Carbon Footprint of Beef Production

The aim is to present validation studies that demonstrate the benefits of genomic retained heterozygosity, genomic enhanced expected progeny differences (gEPDs) for feed efficiency and carcass traits, as well as DNA pooling technologies, to the beef industry. Team members of Livestock Gentec are global leaders in beef genomics research as evidenced by their leadership roles on the Canadian Cattle Genome Project, 1,000 Bull Genomes Project, gEPDs for Commercial Cattle Project and the Functional Annotation of ANimal Genomes initiative. These large-scale projects have created databases of 380 whole bovine sequence genomes, >24,000 cattle genotypes imputed to sequence variants using Run 6 genotypes from 1000 Bull Genomes project, and >20,000 cattle with associated phenotypes for feed efficiency, carcass quality, cow fertility and methane emissions. The use of admixture analysis, genome wide association studies, and genomic prediction have resulted in new genomic tools that aid in mate selection, improve herd heterosis, female fertility, lifetime productivity and health resilience, and improve accuracy (acc. >0.36) of gEPDs for 18 traits in crossbred cattle. Genomic retained heterozygosity has a benefit of $161/female over five parities while decreasing morbidity of calves and improving the carbon intensity of beef production. Multi-trait selection studies using gEPDs for residual feed intake (acc. > 0.35) have demonstrated annual rates of genetic progress of 0.7%. Validation studies have reported that sires with superior gEPDs for increased marbling, decreased grade fat, increased ribeye and increased carcass weight (acc. > 0.45) produced progeny with improved AAA retail cut yield (59.9 vs 56.7%). DNA pooling shows potential for cheaper genotyping while providing information on pooled records related to sire contribution, heterosis and performance as influenced by genetics. The application of these genomic tools has potential to improve calf crop percentage, health resilience, and retail cut yield while decreasing the carbon footprint of beef production.

PSX-B-19 Behaviour of cows while being tested for methane emissions using the greenfeed system

Increased focus on sustainability is driving a need for environmental efficiency traits in dairy cattle breeding. Breeding for reduced emission of methane, an inevitable product of fermentation in ruminants, is increasingly being explored. Methods to measure methane emissions vary but can be impacted by cow behaviour. As part of an on-going project to develop genomic tools for breeding resilient dairy cows, we explored changes in cow behaviour over time during methane emission measurements. First lactation heifers (n = 49) were tested in tie-stall housing at a research herd in Ontario, Canada. Animals were tested over 5 consecutive days at 08:00h, 12:00h, and 16:00h each day for a 10-min period using the GreenFeed system (C-Lock Inc., Rapid City, SD, USA). The frequency of movement (body shifts and leg lifts) and the number of seconds the cow removed her head from the machine were recorded. The effect of day on the average frequency of movements or time the cow’s head was outside of the machine was assessed using a repeated measures model. In general, cows moved their legs the most on day 1 of testing (76 ± 5.0 movements per 10 min), after which it numerically decreased (e.g., day 5: 68 ± 5.0 movements per 10 min, P = 0.1110). A similar effect was observed for seconds the cow had her head out of the machine (P = 0.0650). Cows spent an average of 39 ± 5.7 sec with their head outside of the machine on day 1 versus 25 ± 3.6 sec on day 5 (P = 0.0499). These preliminary results suggest that cows adapt to the testing conditions; however, changes in their behaviour were minor and do not intervene with recording of methane emissions using the GreenFeed system.