The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license.

Ensembl (http://www.ensembl.org) is a genomic interpretation system providing the most up-to-date annotations, querying tools and access methods for chordates and key model organisms. This year we released updated annotation (gene models, comparative genomics, regulatory regions and variation) on the new human assembly, GRCh38, although we continue to support researchers using the GRCh37.p13 assembly through a dedicated site (http://grch37.ensembl.org). Our Regulatory Build has been revamped to identify regulatory regions of interest and to efficiently highlight their activity across disparate epigenetic data sets. A number of new interfaces allow users to perform large-scale comparisons of their data against our annotations. The REST server (http://rest.ensembl.org), which allows programs written in any language to query our databases, has moved to a full service alongside our upgraded website tools. Our online Variant Effect Predictor tool has been updated to process more variants and calculate summary statistics. Lastly, the WiggleTools package enables users to summarize large collections of data sets and view them as single tracks in Ensembl. The Ensembl code base itself is more accessible: it is now hosted on our GitHub organization page (https://github.com/Ensembl) under an Apache 2.0 open source license.

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Understanding the mechanisms driving lineage-specific evolution in both primates and rodents has been hindered by the lack of sister clades with a similar phylogenetic structure having high-quality genome assemblies. Here, we have created chromosome-level assemblies of the Mus caroli and Mus pahari genomes. Together with the Mus musculus and Rattus norvegicus genomes, this set of rodent genomes is similar in divergence times to the Hominidae (human-chimpanzee-gorilla-orangutan). By comparing the evolutionary dynamics between the Muridae and Hominidae, we identified punctate events of chromosome reshuffling that shaped the ancestral karyotype of Mus musculus and Mus caroli between 3 and 6 million yr ago, but that are absent in the Hominidae. Hominidae show between four- and sevenfold lower rates of nucleotide change and feature turnover in both neutral and functional sequences, suggesting an underlying coherence to the Muridae acceleration. Our system of matched, high-quality genome assemblies revealed how specific classes of repeats can play lineage-specific roles in related species. Recent LINE activity has remodeled protein-coding loci to a greater extent across the Muridae than the Hominidae, with functional consequences at the species level such as reproductive isolation. Furthermore, we charted a Muridae-specific retrotransposon expansion at unprecedented resolution, revealing how a single nucleotide mutation transformed a specific SINE element into an active CTCF binding site carrier specifically in Mus caroli, which resulted in thousands of novel, species-specific CTCF binding sites. Our results show that the comparison of matched phylogenetic sets of genomes will be an increasingly powerful strategy for understanding mammalian biology.

Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license.

The Ensembl project (http://www.ensembl.org) seeks to enable genomic science by providing high quality, integrated annotation on chordate and selected eukaryotic genomes within a consistent and accessible infrastructure. All supported species include comprehensive, evidence-based gene annotations and a selected set of genomes includes additional data focused on variation, comparative, evolutionary, functional and regulatory annotation. The most advanced resources are provided for key species including human, mouse, rat and zebrafish reflecting the popularity and importance of these species in biomedical research. As of Ensembl release 59 (August 2010), 56 species are supported of which 5 have been added in the past year. Since our previous report, we have substantially improved the presentation and integration of both data of disease relevance and the regulatory state of different cell types.

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

Facial eczema (FE) is a significant metabolic disease that affects New Zealand ruminants. Ingestion of the mycotoxin sporidesmin leads to liver and bile duct damage, which can result in photosensitisation, reduced productivity and death. Strategies used to manage the incidence and severity of the disease include breeding. In sheep, there is considerable genetic variation in the response to FE. A commercial testing program is available for ram breeders who aim to increase tolerance, determined by the concentration of the serum enzyme, gamma-glutamyltransferase 21 days after a measured sporidesmin challenge (GGT21). Genome-wide association studies were carried out to determine regions of the genome associated with GGT21. Two regions on chromosomes 15 and 24 are reported, which explain 5% and 1% of the phenotypic variance in the response to FE, respectively. The region on chromosome 15 contains the β-globin locus. Of the significant SNPs in the region, one is a missense variant within the haemoglobin subunit β (HBB) gene. Mass spectrometry of haemoglobin from animals with differing genotypes at this locus indicated that genotypes are associated with different forms of adult β-globin. Haemoglobin haplotypes have previously been associated with variation in several health-related traits in sheep and warrant further investigation regarding their role in tolerance to FE in sheep. We show a strategic approach to the identification of regions of importance for commercial breeding programs with a combination of discovery, statistical and biological validation. This study highlights the power of using increased density genotyping for the identification of influential genomic regions, combined with subsequent inclusion on lower density genotyping platforms.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic will be remembered as one of the defining events of the 21st century. The rapid global outbreak has had significant impacts on human society and is already responsible for millions of deaths. Understanding and tackling the impact of the virus has required a worldwide mobilisation and coordination of scientific research. The COVID-19 Data Portal (https://www.covid19dataportal.org/) was first released as part of the European COVID-19 Data Platform, on April 20th 2020 to facilitate rapid and open data sharing and analysis, to accelerate global SARS-CoV-2 and COVID-19 research. The COVID-19 Data Portal has fortnightly feature releases to continue to add new data types, search options, visualisations and improvements based on user feedback and research. The open datasets and intuitive suite of search, identification and download services, represent a truly FAIR (Findable, Accessible, Interoperable and Reusable) resource that enables researchers to easily identify and quickly obtain the key datasets needed for their COVID-19 research.

An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set.

To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.

The Ensembl project (http://www.ensembl.org) provides genome resources for chordate genomes with a particular focus on human genome data as well as data for key model organisms such as mouse, rat and zebrafish. Five additional species were added in the last year including gibbon (Nomascus leucogenys) and Tasmanian devil (Sarcophilus harrisii) bringing the total number of supported species to 61 as of Ensembl release 64 (September 2011). Of these, 55 species appear on the main Ensembl website and six species are provided on the Ensembl preview site (Pre!Ensembl; http://pre.ensembl.org) with preliminary support. The past year has also seen improvements across the project.

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds.

The evolution of the amniotic egg was one of the great evolutionary innovations in the history of life, freeing vertebrates from an obligatory connection to water and thus permitting the conquest of terrestrial environments. Among amniotes, genome sequences are available for mammals and birds, but not for non-avian reptiles. Here we report the genome sequence of the North American green anole lizard, Anolis carolinensis. We find that A. carolinensis microchromosomes are highly syntenic with chicken microchromosomes, yet do not exhibit the high GC and low repeat content that are characteristic of avian microchromosomes. Also, A. carolinensis mobile elements are very young and diverse-more so than in any other sequenced amniote genome. The GC content of this lizard genome is also unusual in its homogeneity, unlike the regionally variable GC content found in mammals and birds. We describe and assign sequence to the previously unknown A. carolinensis X chromosome. Comparative gene analysis shows that amniote egg proteins have evolved significantly more rapidly than other proteins. An anole phylogeny resolves basal branches to illuminate the history of their repeated adaptive radiations.

The potent greenhouse gas methane (CH4) is produced in the rumens of ruminant animals from hydrogen produced during microbial degradation of ingested feed. The natural animal-to-animal variation in the amount of CH4 emitted and the heritability of this trait offer a means for reducing CH4 emissions by selecting low-CH4 emitting animals for breeding. We demonstrate that differences in rumen microbial community structure are linked to high and low CH4 emissions in sheep. Bacterial community structures in 236 rumen samples from 118 high- and low-CH4 emitting sheep formed gradual transitions between three ruminotypes. Two of these (Q and S) were linked to significantly lower CH4 yields (14.4 and 13.6 g CH4/kg dry matter intake [DMI], respectively) than the third type (H; 15.9 g CH4/kg DMI; p<0.001). Low-CH4 ruminotype Q was associated with a significantly lower ruminal acetate to propionate ratio (3.7±0.4) than S (4.4±0.7; p<0.001) and H (4.3±0.5; p<0.001), and harbored high relative abundances of the propionate-producing Quinella ovalis. Low-CH4 ruminotype S was characterized by lactate- and succinate-producing Fibrobacter spp., Kandleria vitulina, Olsenella spp., Prevotella bryantii, and Sharpea azabuensis. High-CH4 ruminotype H had higher relative abundances of species belonging to Ruminococcus, other Ruminococcaceae, Lachnospiraceae, Catabacteriaceae, Coprococcus, other Clostridiales, Prevotella, other Bacteroidales, and Alphaproteobacteria, many of which are known to form significant amounts of hydrogen. We hypothesize that lower CH4 yields are the result of bacterial communities that ferment ingested feed to relatively less hydrogen, which results in less CH4 being formed.

Cattle and other ruminants have evolved the ability to derive most of their metabolic energy requirement from otherwise indigestible plant matter through a symbiotic relationship with plant fibre degrading microbes within a specialised fermentation chamber, the rumen. The genetic changes underlying the evolution of the ruminant lifestyle are poorly understood. The BPI-like locus encodes several putative innate immune proteins, expressed predominantly in the oral cavity and airways, which are structurally related to Bactericidal/Permeability Increasing protein (BPI). We have previously reported the expression of variant BPI-like proteins in cattle (Biochim Biophys Acta 2002, 1579, 92-100). Characterisation of the BPI-like locus in cattle would lead to a better understanding of the role of the BPI-like proteins in cattle physiology

Ruminants obtain nutrients from microbial fermentation of plant material, primarily in their rumen, a multilayered forestomach. How the different layers of the rumen wall respond to diet and influence microbial fermentation, and how these process are regulated, is not well understood. Gene expression correlation networks were constructed from full thickness rumen wall transcriptomes of 24 sheep fed two different amounts and qualities of a forage and measured for methane production. The network contained two major negatively correlated gene sub-networks predominantly representing the epithelial and muscle layers of the rumen wall. Within the epithelium sub-network gene clusters representing lipid/oxo-acid metabolism, general metabolism and proliferating and differentiating cells were identified. The expression of cell cycle and metabolic genes was positively correlated with dry matter intake, ruminal short chain fatty acid concentrations and methane production. A weak correlation between lipid/oxo-acid metabolism genes and methane yield was observed. Feed consumption level explained the majority of gene expression variation, particularly for the cell cycle genes. Many known stratified epithelium transcription factors had significantly enriched targets in the epithelial gene clusters. The expression patterns of the transcription factors and their targets in proliferating and differentiating skin is mirrored in the rumen, suggesting conservation of regulatory systems.

Over the past 40 years New Zealand (NZ) aquaculture has grown into a significant primary industry. Tonnage is small on a global scale, but the industry has built an international reputation for the supply of high quality seafood to many overseas markets. Since the early 1990s the industry has recognized the potential gains from selective breeding and the challenge has been to develop programs that can overcome biological obstacles (such as larval rearing and mortality) and operate cost-effectively on a relatively small scale while still providing significant gains in multiple traits of economic value. This paper provides an overview of the current status, and a perspective on genomic technology implementation, for the family based genetic improvement programs established for the two main species farmed in NZ: Chinook (king) salmon (Oncorhynchus tshawytscha) and GreenshellTM mussel (Perna canaliculus). These programs have provided significant benefit to the industry in which we are now developing genomic resources based on genotyping-by-sequencing to complement the breeding programs, enable evaluation of the genetic diversity and identify the potential benefits of genomic selection. This represents an opportunity to increase genetic gain and more effectively utilize the potential for within family selection.

Black-billed gulls (Larus bulleri) are endemic to New Zealand and are suspected to be undergoing substantial population declines. They primarily breed on open gravel beds in braided rivers of the South Island-a habitat that is diminishing and becoming increasingly modified. Although management of this species is increasing, little has been published on their movements and demographics. In this study, both mitochondrial DNA (mtDNA) control region domain I and nuclear single nucleotide polymorphisms (SNPs) were examined to help understand the connectivity and population structure of black-billed gulls across the country and to help inform management decisions. Mitochondrial DNA showed no population structure, with high haplotype and low nucleotide diversity, and analyses highlighted mitochondrial introgression with the closely related red-billed gulls (Larus novaehollandiae scopulinus). Nuclear DNA analyses, however, identified two groups, with Rotorua birds in the North Island being distinct from the rest of New Zealand, and isolation-by-distance evident across the South Island populations. Gene flow primarily occurs between nearby colonies with a stepwise movement across the landscape. The importance from a genetic perspective of the more isolated North Island birds (1.6% of total population) needs to be further evaluated. From our results, we infer that the South Island black-billed gull management should focus on maintaining several populations within each region rather than focusing on single specific colonies or river catchments. Future study is needed to investigate the genetic structure of populations at the northern limit of the species' range, and identify the mechanisms behind, and extent of, the hybridisation between red-billed and black-billed gulls.