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133 results for “gene annotation”
Great hammerhead and shortfin mako gene annotation files
<p>These preliminary annotation gff files of great hammerhead and shortfin mako chromosome-level genomes are presented here, in hopes of being an asset to the shark genomics community. These annotations were not used for analysis in our associated paper which focused on conservation genomic analyses involving levels of heterozygosity and demographic history of these two species. These annotations should be regarded as preliminary because of the paucity of quality tissue samples that were available to us, from these endangered species, to acquire multiple sets of transcriptomic data. As a result, this hammerhead annotation identifies genes using ab initio predictions from the Maker2 pipeline (employing Augustus and EvidenceModeler) combined with a single tissue transcriptome for training the Augustus gene model (see Stanhope et al. for further details), and evidence-based predictions for mako, using Stringtie2, employing the limited RNA-seq available. The majority of the genes reported here could nonetheless prove beneficial for a variety of comparative analyses, however, the genomes should not be considered thoroughly annotated and the full gene structure should be validated prior to use for targeted analyses. The entire mako annotation is presented (27,804 protein coding genes). A subset of the hammerhead ab initio gene prediction pipeline is presented, representing a total of 26,110 protein coding genes, that were supported by blast evidence in the hammerhead heart transcriptome sequences. Additionally, the gff file contains repeats that were soft masked using RepeatMasker prior to annotation per the methods in Stanhope et al.</p>
Data to run analyses present in the paper: Cell specificity of human regulatory annotations and their genetic effects on gene expression
<p>Data for the manuscript:</p> <p>Varshney A., H. VanRenterghem, P. Orchard, A. P. Boyle, M. L. Stitzel, <em>et al.</em>, 2019 Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression. Genetics 211: 549–562. <a href="https://doi.org/10.1534/genetics.118.301525">https://doi.org/10.1534/genetics.118.301525</a></p> <p>The code to generate these data are at GitHub: https://github.com/ParkerLab/regulatoryAnnotations_comparisons</p> <p>Also see processed data available in this previous Zenodo record: https://zenodo.org/record/1413623</p>
Gene annotation for TAMU_BisBis3 in GTF format and biallelic population SNV in VCF format
<p class="MsoNormal"><span>We developed a highly contiguous chromosome-level reference genome for North American bison to provide a platform to evaluate the conservation, ecological, evolutionary, and population genomics of this species. Generated from an F1 hybrid between a North American bison dam and a domestic cattle bull, completeness and contiguity exceed that of other published bison genome assemblies</span><span>. To </span><span>demonstrate the utility for genome-wide variant frequency estimation, we compiled a genomic variant database consisting of three true albino bison and 45 wild-type pelage color bison. Through the examination of genomic </span>variants fixed in the albino cohort and absent in the controls<span>, we identified a nonsynonymous</span> single nucleotide polymorphism (SNP) <span>mutation on chromosome 29 </span>in exon 3 of the tyrosinase gene (c.1114C>T). A TaqMan SNP Genotyping Assay was developed to genotype this SNP in a total of 283 animals across 29 herds. This assay confirmed the absence of homozygous variants in all animals except 7 true albino bison included in this study. In addition, the only heterozygous animals identified were 2 wild-type pelage color dams of albino offspring. Therefore, we propose that this new high-quality bison genome assembly and incipient variant database provide a highly robust and informative resource for <span>genomics </span>investigations for this iconic North American species.</p>
Gene Ontology Annotations for Homo Sapiens Gene Products
<p><strong>ABSTRACT:</strong></p> <p>This dataset displays the utilization of Gene Ontology (GO) and the web application AmiGO for gene annotation across multiple species, including Homo sapiens (humans). The study involves the analysis of diverse gene types such as complexes, RNAs, proteins, and isoforms which are all gene products found specifically in humans. The provided dataset encompasses comprehensive information regarding these genes, including data source companies, gene names, descriptions, and Gene Ontology IDs. By leveraging Gene Ontology and AmiGO, this research aims to provide valuable insights into the functional characteristics and annotations of different gene types, contributing to a deeper understanding of gene function in the context of human biology.</p> <p><strong>Instructions:</strong></p> <p>Data was collected as 4 separate sets with 4 different types of genes and the duplicated genes, organism type, references, and dates were removed. Links to the specific gene descriptions were added to the dataset as a new column. All four data sets are appended to one another because all of the columns are identical. Isoforms have a different link location going to UniProt.</p> <p><strong>Inspiration:</strong></p> <p>This dataset uploaded to U-BRITE for "DRG_DEPOT" summer 2023 team project.</p> <p><strong>Acknowledgements:</strong></p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/?term=Carbon+S&cauthor_id=19033274">Seth Carbon</a><sup> <a href="https://pubmed.ncbi.nlm.nih.gov/19033274/#full-view-affiliation-1">1</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Ireland+A&cauthor_id=19033274">Amelia Ireland</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Mungall+CJ&cauthor_id=19033274">Christopher J Mungall</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Shu+S&cauthor_id=19033274">ShengQiang Shu</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Marshall+B&cauthor_id=19033274">Brad Marshall</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Lewis+S&cauthor_id=19033274">Suzanna Lewis</a>; <a href="https://pubmed.ncbi.nlm.nih.gov/?term=AmiGO+Hub%5BCorporate+Author%5D">AmiGO Hub</a>; <a href="https://pubmed.ncbi.nlm.nih.gov/?term=Web+Presence+Working+Group%5BCorporate+Author%5D">Web Presence Working Group</a></p> <p>Collaborators, Affiliations expand PMID: <strong>19033274</strong> PMCID: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/pmc2639003/">PMC2639003</a> DOI: <a href="https://doi.org/10.1093/bioinformatics/btn615">10.1093/bioinformatics/btn615</a></p> <p><strong>AmiGO online access to ontology and annotation data- </strong> https://amigo.geneontology.org/amigo/search/annotation</p> <p><strong>U-BRITE last update data: </strong>06/27/2023</p>
Chromosome assembly and preliminary gene and repeat annotations for Myzomela tristrami reference genome
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Data from: SNP discovery and gene annotation in the surf clam Mesodesma donacium
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Gene annotation for TAMU_BisBis3 in GTF format and biallelic population SNV in VCF format
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Data from: A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa
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Great hammerhead and shortfin mako gene annotation files
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Nucleotide diversity of functionally different groups of immune response genes in Old World camels based on newly annotated and reference-guided assemblies
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Gene annotation of the Fhb1 locus on the assembly of bread wheat variety Norin 61
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Gibbon genome (Nleu3.0) custom gene annotation file
<p>Co-option of transposable elements (TEs) to become part of existing or new enhancers is an important mechanism for evolution of gene regulation. However, contributions of lineage-specific TE insertions to recent regulatory adaptations remain poorly understood. Gibbons present a suitable model to study these contributions as they have evolved a lineage-specific TE called <i>LAVA, </i>which is still active in the gibbon genome. The LAVA retrotransposon is thought to have played a role in the emergence of the highly rearranged structure of the gibbon genome by disrupting transcription of cell cycle genes. In this study, we investigated whether LAVA may have also contributed to the evolution of gene regulation by adopting enhancer function. We characterized fixed and polymorphic LAVA insertions across multiple gibbons and found 96 LAVA elements overlapping enhancer chromatin states. Moreover, LAVA was enriched in multiple transcription factor binding motifs, was bound by an important transcription factor (PU.1), and was associated with higher levels of gene expression in <i>cis</i>. We found gibbon-specific signatures of purifying/positive selection at 27 LAVA insertions. Two of these insertions were fixed in the gibbon lineage and overlapped with enhancer chromatin states, representing putative co-opted LAVA enhancers. These putative enhancers were located within genes encoding SETD2 and RAD9A,<i> </i>two proteins that facilitate accurate repair of DNA double-strand breaks and prevent chromosomal rearrangement mutations. Co-option of LAVA in these genes may have influenced regulation of processes that preserve genome integrity. Our findings highlight the importance of considering lineage-specific TEs in studying evolution of novel gene regulatory elements.</p>
Data from: Repertoire-wide gene structure analyses: a case study comparing automatically predicted and manually annotated gene models
The location and modular structure of eukaryotic protein-coding genes in genomic sequences can be automatically predicted by gene annotation algorithms. These predictions are often used for comparative studies on gene structure, gene repertoires, and genome evolution. However, automatic annotation algorithms do not yet correctly identify all genes within a genome, and manual annotation is often necessary to obtain accurate gene models and gene sets. As manual annotation is time-consuming, only a fraction of the gene models in a genome is typically manually annotated, and this fraction often differs between species. To assess the impact of manual annotation efforts on genome-wide analyses of gene structural properties, we compared the structural properties of protein-coding genes in seven diverse insect species sequenced by the i5k initiative. Our results show that the subset of genes chosen for manual annotation by a research community (3.5-7% of gene models) may have structural properties (e.g., lengths and exon counts) that are not necessarily representative for a species' gene set as a whole. Nonetheless, the structural properties of automatically generated gene models are only altered marginally (if at all) through manual annotation. Major correlative trends, for example a negative correlation between genome size and exonic proportion, can be inferred from either the automatically predicted or manually annotated gene models alike. Vice versa, some previously reported trends did not appear in either the automatic or manually annotated gene sets, pointing towards insect-specific gene structural peculiarities. In our analysis of gene structural properties, automatically predicted gene models proved to be sufficiently reliable to recover the same gene-repertoire-wide correlative trends that we found when focusing on manually annotated gene models only. We acknowledge that analyses on the individual gene level clearly benefit from manual curation. However, as genome sequencing and annotation projects often differ in the extent of their manual annotation and curation efforts, our results indicate that comparative studies analyzing gene structural properties in these genomes can nonetheless be justifiable and informative.
Data from: De novo genome assembly and annotation of rice sheath rot fungus Sarocladium oryzae reveals genes involved in Helvolic acid and Cerulenin biosynthesis pathways
Background: Sheath rot disease caused by Sarocladium oryzae is an emerging threat for rice cultivation at global level. However, limited information with respect to genomic resources and pathogenesis is a major setback to develop disease management strategies. Considering this fact, we sequenced the whole genome of highly virulent Sarocladium oryzae field isolate, Saro-13 with 82x sequence depth. Results: The genome size of S. oryzae was 32.78 Mb with contig N50 18.07 Kb and 10526 protein coding genes. The functional annotation of protein coding genes revealed that S. oryzae genome has evolved with many expanded gene families of major super family, proteinases, zinc finger proteins, sugar transporters, dehydrogenases/reductases, cytochrome P450, WD domain G-beta repeat and FAD-binding proteins. Gene orthology analysis showed that around 79.80 % of S. oryzae genes were orthologous to other Ascomycetes fungi. The polyketide synthase dehydratase, ATP-binding cassette (ABC) transporters, amine oxidases, and aldehyde dehydrogenase family proteins were duplicated in larger proportion specifying the adaptive gene duplications to varying environmental conditions. Thirty-nine secondary metabolite gene clusters encoded for polyketide synthases, nonribosomal peptide synthase, and terpene cyclases. Protein homology based analysis indicated that nine putative candidate genes were found to be involved in helvolic acid biosynthesis pathway. The genes were arranged in cluster and structural organization of gene cluster was similar to helvolic acid biosynthesis cluster in Metarhizium anisophilae. Around 9.37 % of S. oryzae genes were identified as pathogenicity genes, which are experimentally proven in other phytopathogenic fungi and enlisted in pathogen-host interaction database. In addition, we also report 13212 simple sequences repeats (SSRs) which can be deployed in pathogen identification and population dynamic studies in near future. Conclusions: Large set of pathogenicity determinants and putative genes involved in helvolic acid and cerulenin biosynthesis will have broader implications with respect to Sarocladium disease biology. This is the first genome sequencing report globally and the genomic resources developed from this study will have wider impact worldwide to understand Rice-Sarocladium interaction.
Domain scanning results for a selected set of high-quality-annotation protein isoforms produced by human transcription factor genes
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Wikipedia Gene Ontology Annotations (WikiGOA)
<p>Gene Ontology Annotation gene sets obtained via Wikidata. </p> <p>Gene Ontology terms with English Wikipedia pages were obtained from Wikidata using the SPARQL query language via the Wikidata Query Service: <a href="https://w.wiki/5DsS">https://w.wiki/5DsS</a> </p> <p>Gene Ontology Annotations were obtained indirectly from the UniProt-GoA database (<a href="https://www.ebi.ac.uk/GOA/publications">https://www.ebi.ac.uk/GOA/publications</a>) via mappings on Wikidata done by the ProteinBoxBot (<a href="https://elifesciences.org/articles/52614">https://elifesciences.org/articles/52614</a>) <br> <br> T.L. is funded by grant #2019/26284-1 from the São Paulo Research Foundation (FAPESP). T.L.D. is funded by grant from VSV-EBOPLUS Consortium. </p>
Toumeyella liriodendri helixer gene annotation
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Relevant loci from genomic assembly, gene model, and interproscan annotation, for PKZILLA-B1 from B-type P. parvum strain RCC3426
<h2><strong>Version 1.0 of the <em>Prymnesium parvum</em> RCC3426 PKZILLA-B1 gene annotation (PKZILLA-B1.gff)</strong></h2> <p>Version 1.0 of the <em>P. parvum</em> RCC3426 gene annotation (PKZILLA-B1.gff), consisting of expert guided <em>ab initio</em> gene prediction of just the PKZILLA-B1 gene model on its selected loci from the draft RCC3426 genome assembly. Interproscan annotations of PKS domains are also included (see <code>interproscan-parallel.zip</code>)</p> <p>See the manuscript "Materials and Methods" section for full details.</p> <p><strong>seqkit stat statistics:</strong></p> <p>file format type num_seqs sum_len min_len avg_len max_len<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.gene.fa.gz FASTA DNA 1 <strong>118,049 </strong> 118,049 118,049 118,049<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.mRNA.fa.gz FASTA DNA 1 <strong>116,940</strong> 116,940 116,940 116,940<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.pep.fa.gz FASTA Protein 1 <strong>38,980</strong> 38,980 38,980 38,980<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.CDS.fa.gz FASTA DNA 1 116,940 116,940 116,940 116,940<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSnt.fa.gz FASTA DNA 16 116,940 1,140 7,308.8 14,895<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSpep.fa.gz FASTA Protein 16 38,980 380 2,436.3 4,965<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indExon.fa.gz FASTA DNA 16 116,940 1,140 7,308.8 14,895<br>./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indIntron.fa.gz FASTA DNA 30 2,218 63 73.9 101</p> <p><strong>seqkit sum checksums:</strong></p> <p>seqkit.v0.1_DLS_k0_48447ccbb39a48a389fc726e3647a9a4 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.CDS.fa.gz<br>seqkit.v0.1_DLS_k0_1366665c674b96f4e302f8afab53fa4e ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.gene.fa.gz<br>seqkit.v0.1_DLS_k0_101122a59afec1b41ca7f9d1a4186b52 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSnt.fa.gz<br>seqkit.v0.1_PLS_k0_404d6657b58d22da550585c3bfa06f8d ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSpep.fa.gz<br>seqkit.v0.1_DLS_k0_101122a59afec1b41ca7f9d1a4186b52 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indExon.fa.gz<br>seqkit.v0.1_DLS_k0_af7f0b217bd14bf6dff5dbca157c5cbb ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indIntron.fa.gz<br>seqkit.v0.1_DLS_k0_48447ccbb39a48a389fc726e3647a9a4 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.mRNA.fa.gz<br>seqkit.v0.1_PLS_k0_9f280bb95c4ee9afe7a1f28975de338d ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.pep.fa.gz</p> <p><strong>seqkit sum -g checksums:</strong></p> <p>seqkit.v0.1_DLS_k0_48447ccbb39a48a389fc726e3647a9a4 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.CDS.fa.gz<br>seqkit.v0.1_DLS_k0_1366665c674b96f4e302f8afab53fa4e ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.gene.fa.gz<br>seqkit.v0.1_DLS_k0_101122a59afec1b41ca7f9d1a4186b52 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSnt.fa.gz<br>seqkit.v0.1_PLS_k0_fced14c2e2e98c5464f20ac91aab1bde ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSpep.fa.gz<br>seqkit.v0.1_DLS_k0_101122a59afec1b41ca7f9d1a4186b52 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indExon.fa.gz<br>seqkit.v0.1_DLS_k0_af7f0b217bd14bf6dff5dbca157c5cbb ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indIntron.fa.gz<br>seqkit.v0.1_DLS_k0_48447ccbb39a48a389fc726e3647a9a4 ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.mRNA.fa.gz<br>seqkit.v0.1_PLS_k0_8eb393988e68fdfa1fe5a435eefe353b ./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.pep.fa.gz</p> <p><strong>openssl md5 checksums:</strong></p> <p>MD5(./PKZILLA-B1.gff)= b7389f45965e2b078597ceeaa2ad4d67<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.CDS.fa.gz)= 7f576dbd61bd60ba1955ce46b5077e85<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.gene.fa.gz)= 7dcae701dea30fbfa4508c0f01438168<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSnt.fa.gz)= 0fae261356f4a20629d20fccaad00d1c<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indCDSpep.fa.gz)= d0081800e314b9f99c0fa759d4e80187<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indExon.fa.gz)= 79b6b942b61fcab1f14682f38e80cf41<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.indIntron.fa.gz)= c2055a64ebcf332c7c6bb28c57762c94<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.mRNA.fa.gz)= 7f576dbd61bd60ba1955ce46b5077e85<br>MD5(./PKZILLA-B1.gff__PKZILLA-1-on-B.loci.nt.rename.consensus.fa.pep.fa.gz)= 2f01d8cf130b343076e1d9197e6041ab</p> <p>MD5(./interproscan-parallel.zip)= 595ec69a0d77e8c96c7aa29ea913532b</p>
Table S3_Gene annotations
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Data from: De novo genome assembly and annotation of rice sheath rot fungus Sarocladium oryzae reveals genes involved in Helvolic acid and Cerulenin biosynthesis pathways
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.