scholarly journals Bovine Genome Database: new annotation tools for a new reference genome

2019 ◽  
Author(s):  
Md Shamimuzzaman ◽  
Justin J Le Tourneau ◽  
Deepak R Unni ◽  
Colin M Diesh ◽  
Deborah A Triant ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Genome Annotation ◽  
Reference Genome ◽  
Gene Annotation ◽  
Bovine Genome ◽  
Data Retrieval ◽  
Genome Database ◽  
Ruminant Species ◽  
Search Tool ◽  
Efficient Data

Abstract The Bovine Genome Database (BGD) (http://bovinegenome.org) has been the key community bovine genomics database for more than a decade. To accommodate the increasing amount and complexity of bovine genomics data, BGD continues to advance its practices in data acquisition, curation, integration and efficient data retrieval. BGD provides tools for genome browsing (JBrowse), genome annotation (Apollo), data mining (BovineMine) and sequence database searching (BLAST). To augment the BGD genome annotation capabilities, we have developed a new Apollo plug-in, called the Locus-Specific Alternate Assembly (LSAA) tool, which enables users to identify and report potential genome assembly errors and structural variants. BGD now hosts both the newest bovine reference genome assembly, ARS-UCD1.2, as well as the previous reference genome, UMD3.1.1, with cross-genome navigation and queries supported in JBrowse and BovineMine, respectively. Other notable enhancements to BovineMine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species (goat and sheep), support for multiple assemblies per organism in the Regions Search tool, integration of additional ontologies and development of many new template queries. To better serve the research community, we continue to focus on improving existing tools, developing new tools, adding new datasets and encouraging researchers to use these resources.

scholarly journals Bovine Genome Database: integrated tools for genome annotation and discovery

2010 ◽  
Vol 39 (suppl_1) ◽  
pp. D830-D834 ◽  
Author(s):  
Christopher P. Childers ◽  
Justin T. Reese ◽  
Jaideep P. Sundaram ◽  
Donald C. Vile ◽  
C. Michael Dickens ◽  
...  
Keyword(s):  
Genome Annotation ◽  
Bovine Genome ◽  
Genome Database

scholarly journals Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

2020 ◽  
Author(s):  
Isis da Costa Hermisdorff ◽  
Raphael Bermal Costa ◽  
Lucia Galvão de Albuquerque ◽  
Hubert Pausch ◽  
Naveen Kumar Kadri
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
Bovine Genome ◽  
Imputation Accuracy ◽  
Quality Score ◽  
Reference Panel ◽  
Marker Density ◽  
Model Based ◽  
Reference Genome Assembly ◽  
Nellore Cattle

AbstractBackgroundImputation accuracy among other things depends on the size of the reference panel, the marker’s minor allele frequency (MAF), and the correct placement of variants on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50K to 777K SNP density, using map positions determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing-based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to empirical imputation accuracy.ResultsThe overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R2dose) was virtually identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R2dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy and the marker density in the imputed data increased from 0.903 to 0.913 and from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals, respectively. The model-based imputation quality scores from Minimac3 (Rsq) were highly correlated to but systematically higher than empirically estimated accuracies. The correlation between these metrics increased with the size of the reference panel and MAF of imputed variants.ConclusionsAccurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel used and MAF of the imputed variants.

scholarly journals Using online tools at the Bovine Genome Database to manually annotate genes in the new reference genome

2020 ◽  
Vol 51 (5) ◽  
pp. 675-682
Author(s):  
D. A. Triant ◽  
J. J. Le Tourneau ◽  
C. M. Diesh ◽  
D. R. Unni ◽  
M. Shamimuzzaman ◽  
...  
Keyword(s):  
Reference Genome ◽  
Bovine Genome ◽  
Genome Database ◽  
Online Tools

scholarly journals Canfam_GSD: De novo chromosome-length genome assembly of the German Shepherd Dog (Canis lupus familiaris) using a combination of long reads, optical mapping, and Hi-C

GigaScience ◽  
2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Matt A Field ◽  
Benjamin D Rosen ◽  
Olga Dudchenko ◽  
Eva K F Chan ◽  
Andre E Minoche ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Gene Annotation ◽  
Draft Genome ◽  
Single Copy ◽  
Canis Lupus Familiaris ◽  
German Shepherd ◽  
German Shepherd Dog ◽  
First Choice

Abstract Background The German Shepherd Dog (GSD) is one of the most common breeds on earth and has been bred for its utility and intelligence. It is often first choice for police and military work, as well as protection, disability assistance, and search-and-rescue. Yet, GSDs are well known to be susceptible to a range of genetic diseases that can interfere with their training. Such diseases are of particular concern when they occur later in life, and fully trained animals are not able to continue their duties. Findings Here, we provide the draft genome sequence of a healthy German Shepherd female as a reference for future disease and evolutionary studies. We generated this improved canid reference genome (CanFam_GSD) utilizing a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. The GSD assembly is ∼80 times as contiguous as the current canid reference genome (20.9 vs 0.267 Mb contig N50), containing far fewer gaps (306 vs 23,876) and fewer scaffolds (429 vs 3,310) than the current canid reference genome CanFamv3.1. Two chromosomes (4 and 35) are assembled into single scaffolds with no gaps. BUSCO analyses of the genome assembly results show that 93.0% of the conserved single-copy genes are complete in the GSD assembly compared with 92.2% for CanFam v3.1. Homology-based gene annotation increases this value to ∼99%. Detailed examination of the evolutionarily important pancreatic amylase region reveals that there are most likely 7 copies of the gene, indicative of a duplication of 4 ancestral copies and the disruption of 1 copy. Conclusions GSD genome assembly and annotation were produced with major improvement in completeness, continuity, and quality over the existing canid reference. This resource will enable further research related to canine diseases, the evolutionary relationships of canids, and other aspects of canid biology.

scholarly journals Investigating the accuracy of imputing autosomal variants in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Isis da Costa Hermisdorff ◽  
Raphael Bermal Costa ◽  
Lucia Galvão de Albuquerque ◽  
Hubert Pausch ◽  
Naveen Kumar Kadri
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
Bovine Genome ◽  
Imputation Accuracy ◽  
Quality Score ◽  
Reference Panel ◽  
Marker Density ◽  
Model Based ◽  
Reference Genome Assembly ◽  
Nellore Cattle

Abstract Background Imputation accuracy among other things depends on the size of the reference panel, the marker’s minor allele frequency (MAF), and the correct placement of single nucleotide polymorphism (SNP) on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50 K to 777 K SNP density using Minimac3, when map positions were determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to the empirical imputation accuracy. Results The overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R2dose) was almost identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R2dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy increased from 0.903 to 0.913, and the marker density in the imputed data increased from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals. The model-based imputation quality scores from Minimac3 (Rsq) were systematically higher than empirically estimated accuracies. However, both metrics were positively correlated and the correlation increased with the size of the reference panel and MAF of imputed variants. Conclusions Accurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel and MAF of the imputed variants.

scholarly journals Uncovering transcriptional dark matter via gene annotation independent single-cell RNA sequencing analysis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael F. Z. Wang ◽  
Madhav Mantri ◽  
Shao-Pei Chou ◽  
Gaetano J. Scuderi ◽  
David W. McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Annotation ◽  
Gene Annotation ◽  
Active Regions ◽  
Sequencing Analysis ◽  
Biologically Relevant ◽  
Mole Rat ◽  
Genome Annotations ◽  
Cell Expression ◽  
High Quality Genome

AbstractConventional scRNA-seq expression analyses rely on the availability of a high quality genome annotation. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, genome annotations are often incomplete, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant transcriptional activity beyond the scope of the best available genome annotation by performing scRNA-seq analysis on any region in the genome for which transcriptional products are detected. Our tool generates a single-cell expression matrix for all transcriptionally active regions (TARs), performs single-cell TAR expression analysis to identify biologically significant TARs, and then annotates TARs using gene homology analysis. This procedure uses single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

scholarly journals Whole-genome assembly of Ganoderma leucocontextum (Ganodermataceae, Fungi) discovered from the Tibetan Plateau of China

2021 ◽  
Author(s):  
Yuanchao Liu ◽  
Longhua Huang ◽  
Huiping Hu ◽  
Manjun Cai ◽  
Xiaowei Liang ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Southwest China ◽  
Reference Genome ◽  
Biological Activities ◽  
Single Copy ◽  
The Tibetan Plateau ◽  
Whole Genome ◽  
High Quality ◽  
Pharmacological Activities ◽  
Genetic Studies

Abstract Ganoderma leucocontextum, a newly discovered species of Ganodermataceae in China, has diverse pharmacological activities. G. leucocontextum was widely cultivated in southwest China, but the systematic genetic study has been impeded by the lack of a reference genome. Herein, we present the first whole-genome assembly of G. leucocontextum based on the Illumina and Nanopore platform from high-quality DNA extracted from a monokaryon strain (DH-8). The generated genome was 50.05 Mb in size with a N50 scaffold size of 3.06 Mb, 78,206 coding sequences and 13,390 putative genes. Genome completeness was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) tool, which identified 96.55% of the 280 Fungi BUSCO genes. Furthermore, differences in functional genes of secondary metabolites (terpenoids) were analyzed between G. leucocontextum and G. lucidum. G. leucocontextum has more genes related to terpenoids synthesis compared to G. lucidum, which may be one of the reasons why they exhibit different biological activities. This is the first genome assembly and annotation for G. leucocontextum, which would enrich the toolbox for biological and genetic studies in G. leucocontextum.

scholarly journals The genome sequence of the European peacock butterfly, Aglais io (Linnaeus, 1758)

2021 ◽  
Vol 6 ◽  
pp. 258
Author(s):  
Konrad Lohse ◽  
Alexander Mackintosh ◽  
Roger Vila ◽  
◽  
◽  
...  
Keyword(s):  
Genome Sequence ◽  
Genome Assembly ◽  
Sex Chromosome ◽  
Gene Annotation ◽  
Protein Coding ◽  
Individual Male ◽  
Protein Coding Genes ◽  
A Genome ◽  
Inachis Io

We present a genome assembly from an individual male Aglais io (also known as Inachis io and Nymphalis io) (the European peacock; Arthropoda; Insecta; Lepidoptera; Nymphalidae). The genome sequence is 384 megabases in span. The majority (99.91%) of the assembly is scaffolded into 31 chromosomal pseudomolecules, with the Z sex chromosome assembled. Gene annotation of this assembly on Ensembl has identified 11,420 protein coding genes.

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