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http://www.projects.roslin.ac.uk/cdiv/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The objective of the project is the standardization of micro-satellite markers used within participating laboratories, use of DNA markers to define genetic diversity and to enable monitoring of breeds to promote conservation programs where required, and the determination of diversity present in rare and local breeds across Europe. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project (See BovMaP). Work with micro-satellite markers has shown that they are valuable tools for examining genetic diversity and phylogeny in many species. However, for work carried out in different laboratories to be comparable, it is essential that the same markers are used. To maintain the compatibility of data generated by the various typing labs, it is essential that all laboratories adopt the same markers and typing protocols. It is therefore of paramount importance that the blood typing laboratories and research labs that are examining the genetic structure of the cattle populations adopt a common panel of the best micro-satellite markers available. Some pilot comparative work has been undertaken through the International Society for Animal Genetics, but so far this has only involved the blood typing laboratories. One objective of this project is to facilitate the comparison of the micro-satellite markers currently in use in the different types of laboratory and determine the efficiency of the markers available in revealing genetic differences within and among breeds. It will also be important to compare the use of markers in different laboratories to determine how robust they are and how easily results can be compared. From comparison of the markers, those that are most suitable will be selected to form a panel which will be recommended for pedigree validation and genetic surveys. Cattle are an important source of food in Europe, and intense selection has resulted in the development of specialized breeds. Selection for high-producing dairy cattle has been successful, but one associated drawback is that the cattle population, both in Europe and North America, has been skewed dramatically towards one breed, the Holstein/Friesian. So there has been a decline in the number of individuals of other breeds, and hence a general erosion of the genetic base of the cattle population. The progressive move towards the North American-type Holstein animals has also resulted in the requirement for high input/high output farming and intensive management schemes. The impact of this on the environment has been significant, e.g. pollution problems arising from the need for high nitrogen fertilizers to produce sufficient high quality fodder, and disposal problems associated with slurry waste. Poorer areas of the community have been unable to compete with such farming systems, and are more suited to low input/low output farming using traditional stock. It is however the future perspective that is of greatest concern. It is impossible to predict requirements for cattle production - quality, production type, management systems, etc. The ability to switch rapidly to alternative production will be dependent on the genetic base of the population available to selection programs. It is therefore essential to maintain the greatest genetic diversity possible in the cattle population. Whilst current farming practices are perceived to be both efficient and acceptable, the breeds less favored by commercial farmers will dwindle. It is therefore important that on an European scale efficient management of these breeds maintains the widest genetic base possible. This project aims to carry out a survey of the current genetic base of the European cattle population and to provide the tools to assist breeding programs to maintain a broad base. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project. Early work to measure genetic diversity used blood groups to show differences between breeds and the diversity present. Unfortunately, the number of loci available are limited, with only the B system being sufficiently polymorphic to be really useful. However, since there is a wealth of information available from such typing, this information can be used to estimate changes in the genetic structure of cattle populations across Europe over the past twenty years. More recently mini-satellite probes have been used to generate ''genetic fingerprints'' which have been used to show differences between individuals. Such fingerprints have been used to estimate genetic diversity - the greater the number of bands revealed by the fingerprint being equated with greater diversity. This is valid within limits. The main disadvantage of the fingerprint approach is that the chromosomal location and number of loci being sampled, and so the proportion of the genome examined, is unknown. The allelic bands on the gel cannot be easily identified, so allele inheritance cannot be addressed making it impossible to trace ancestry. Through the EC funded BovMaP project, large numbers of highly polymorphic micro-satellite markers have become available, which are being mapped on the bovine genome. These markers are particularly suited to measuring genetic diversity, and markers can be selected to cover the entire genome.

Proper citation: CaDBase: Genetic diversity in cattle (RRID:SCR_008146) Copy   

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http://locus.jouy.inra.fr/cgi-bin/bovmap/intro.pl

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database containing information on the cattle genome comprising loci list, phenes list, homology query, cattle maps, gene list, and chromosome homology. The objective of BovMap is to develop a set of anchored loci for the cattle genome map. In total, 58 clones were hybridized with chromosomes and identified loci on 22 of the 31 different bovine chromosomes. Three clones contained satellite DNA. Two or more markers were placed on 12 chromosomes. Sequencing of the microsatellites and flanking regions was performed directly from 43 cosmids, as previously reported. Primers were developed for 39 markers and used to describe the polymorphism associated with the corresponding loci. Users are also allowed to summit their own data for Bovmap. An integrated cytogenetic and meiotic map of the bovine genome has also been developed around the Bovmap database. One objective that Bovmap uses as the mapping strategy for the bovine genome uses large insert clones as a tool for physical mapping and as a source of highly polymorphic microsatellites for genetic typing.

Proper citation: BovMap Database (RRID:SCR_008145) Copy   

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http://www.genome.wisc.edu/

The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments.

Proper citation: E. coli Genome project (RRID:SCR_008139) Copy   

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http://mitores.ba.itb.cnr.it

MitoRes, is a comprehensive and reliable resource for massive extraction of sequences and sub-sequences of nuclear genes and encoded products targeting mitochondria in metazoa. It has been developed for supporting high-throughput in-silico analyses aimed to studies of functional genomics related to mitochondrial biogenesis, metabolism and to their pathological dysfunctions. It integrates information from the most accredited world-wide databases to bring together gene, transcript and encoded protein sequences associated to annotations on species name and taxonomic classification, gene name, functional product, organelle localization, protein tissue specificity, Enzyme Classification (EC), Gene Ontology (GO) classification and links to other related public databases. The section Cluster, has been dedicated to the collection of data on protein clustering of the entire catalogue of MitoRes protein sequences based on all versus all global pair-wise alignments for assessing putative intra- and inter-species functional relationships. The current version of MitoRes is based on the UniProt release 4 and contains 64 different metazoan species. The incredible explosion of knowledge production in Biology in the past two decades has created a critical need for bioinformatic instruments able to manage data and facilitate their retrieval and analysis. Hundreds of biological databases have been produced and the integration of biological data from these different resources is very important when we want to focus our efforts towards the study of a particular layer of biological knowledge. MitoRes is a completely rebuilt edition of MitoNuc database, which has been extensively modified to deal successfully with the challenges of the post genomic era. Its goal is to represent a comprehensive and reliable resource supporting high-quality in-silico analyses aimed to the functional characterization of gene, transcript and amino acid sequences, encoded by the nuclear genome and involved in mitochondrial biogenesis, metabolism and pathological dysfunctions in metazoa. The central features of MitoRes are: # an integrated catalogue of protein, transcript and gene sequences and sub-sequences # a Web-based application composed of a wide spectrum of search/retrieval facilities # a sequence export manager allowing massive extraction of bio-sequences (genes, introns, exons, gene flanking regions, transcripts, UTRs, CDS, proteins and signal peptides) in FASTA, EMBL and GenBank formats. It is an interconnected knowledge management system based on a MySQL relational database, which ensures data consistency and integrity, and on a Web Graphical User Interface (GUI), built in Seagull PHP Framework, offering a wide range of search and sequence extraction facilities. The database is compiled extracting and integrating information from public resources and data generated by the MitoRes team. The MitoRes database consists of comprehensive sequence entries whose core data are protein, transcript and gene sequences and taxonomic information describing the biological source of the protein. Additional information include: bio-sequences structure and location, biological function of protein product and dynamic links to both, external public databases used as data resources and public databases reporting complementary information. The core entity of the MitoRes database is represented by the protein so that each MitoRes entry is generated for each protein reported in the UniProt database as a nuclear encoded protein involved in mitochondrial biogenesis and function. Sponsors: MitoRes has been supported by Ministero Universit e Ricerca Scientifica, Italy (PRIN, Programma Biotecnologie legge 95/95-MURST 5, Proiect MURST Cluster C03/2000, CEGBA). Currently it is supported by operating grants from the Ministero dellIstruzione, dellUniversit e della Ricerca (MIUR), Italy (PNR 2001-2003 (FIRB art.8) D.M. 199, Strategic Program: Post-genome, grant 31-063933 and Project n.2, Cluster C03 L. 488/929).

Proper citation: MitoRes (RRID:SCR_008208) Copy   

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http://www.ebi.ac.uk/parasites/parasite-genome.html

This website contains information about the genomic sequence of parasites. It also contains multiple search engines to search six frame translations of parasite nucleotide databases for motifs, parasite protein databases for motifs, and parasite protein databases for keywords and text terms. * Guide to Internet Access to Parasite Genome Information * Guide to web-based analysis tools * Parasite Genome BLAST Server: Search a range of parasite specific nucleotide sequence databases with your own sequence. * Parasite Proteome Keyword Search Facility: Search parasite protein databases for keywords and text terms * Parasite Proteome Motif Search Facility: Search parasite protein databases for motifs * Parasite Six Frame Translation Motif Search Facility: Search six frame translations of parasite nucleotide databases for motifs * Genome computing resources: A list of ftp and gopher sites where genome computing applications and other resources can be found.

Proper citation: Parasite genome databases and genome research resources (RRID:SCR_008150) Copy   

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http://www.broad.mit.edu/mammals/dog

The genome of the domesticated dog, a close evolutionary relation to human, is a powerful new tool for understanding the human genome. Comparison of the dog with human and other mammals reveals key information about the structure and evolution of genes and genomes. The unique breeding history of dogs, with their extraordinary behavioral and physical diversity, offers the opportunity to find important genes underlying diseases shared between dogs and humans, such as cancer, diabetes, and epilepsy. The Canine Genome Sequencing Project produced a high-quality draft sequence of a female boxer named Tasha. By comparing Tasha with many other breeds, the project also compiled a comprehensive set of SNPs (single nucleotide polymorphisms) useful in all dog breeds. These closely spaced genomic landmarks are critical for disease mapping. By comparing the dog, rodent, and human lineages, researchers at the Broad Institute uncovered exciting new information about human genes, their evolution, and the regulatory mechanisms governing their expression. Using SNPs, researchers describe the strikingly different haplotype structure in dog breeds compared with the entire dog population. In addition, they show that by understanding the patterns of variation in dog breeds, scientists can design powerful gene mapping experiments for complex diseases that are difficult to map in human populations. Contribute Although the astounding generosity of Eli and Edythe L. Broad and several other venture philanthropists empowers our scientists to tackle many of the most important problems at the cutting edge of genomic medicine, there are many other critical challenges that they cannot yet pursue because of limited resources. We need additional visionary partners to join the Broads and the Broad Institute in transforming medicine with the power of genomics.

Proper citation: Dog Genome Project (RRID:SCR_008486) Copy   

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http://www.hgsc.bcm.tmc.edu/content/bovine-genome-project

Downloadable files of the bos taurus genome. Draft assemblies available for download as contigs or linearized scaffolds of the genomic sequence of cow, Bos taurus, including the final draft assembly (7.1 coverage) and the two previous assemblies. The genome is sequenced to 6- to 8-fold sequence depth, with high-quality finished sequence in some areas. Accompanying EST and SNP analyses is also included. The bovine genome assembly and analysis and the study of cattle genetic history were published in April 24, 2009 issue of Science. The Human Genome Sequencing Center provides BLAST searches of the genome assemblies, either as contigs or as linearized chromosome sequences. The WGS sequence enriched BAC assemblies and the unassembled reads (sequencing reads that did not end up in the genome assembly) can also be searched by BLAST. Traces are available from the NCBI Trace Archive by using the link in the sidebar or by using NCBI MegaBLAST with a same species or cross species query.

Proper citation: Bovine Genome Project (RRID:SCR_008370) Copy   

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http://roadmapepigenomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 11, 2022. Project for human epigenomic data from experimental pipelines built around next-generation sequencing technologies to map DNA methylation, histone modifications, chromatin accessibility and small RNA transcripts in stem cells and primary ex vivo tissues selected to represent normal counterparts of tissues and organ systems frequently involved in human disease. Consortium expects to deliver collection of normal epigenomes that will provide framework or reference for comparison and integration within broad array of future studies. Consortium is also committed to development, standardization and dissemination of protocols, reagents and analytical tools to enable research community to utilize, integrate and expand upon this body of data.

Proper citation: Roadmap Epigenomics Project (RRID:SCR_008924) Copy   

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http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

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http://www.maizegdb.org

Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.

Proper citation: MaizeGDB (RRID:SCR_006600) Copy   

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http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

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http://www.gigasciencejournal.com/

An online open-access open-data journal, publishing ''big-data'' studies from the entire spectrum of life and biomedical sciences whose publication format links standard manuscript publication with its affiliated database, GigaDB, that hosts all associated data, provides data analysis tools, cloud-computing resources, and a DOI assignment to every dataset. GigaScience covers not just ''omic'' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data. Supporting the open-data movement, they require that all supporting data and source code be publicly available in a suitable public repository and/or under a public domain CC0 license in the BGI GigaScience database. Using the BGI cloud as a test environment, they also consider open-source software tools / methods for the analysis or handling of large-scale data. When submitting a manuscript, please contact them if you have datasets or cloud applications you would like them to host. To maximize data usability submitters are encouraged to follow best practice for metadata reporting and are given the opportunity to submit in ISA-Tab format.

Proper citation: GigaScience (RRID:SCR_006565) Copy   

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http://flybase.org/

Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.

Proper citation: FlyBase (RRID:SCR_006549) Copy   

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http://www.ebi.ac.uk/interpro

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

Proper citation: InterPro (RRID:SCR_006695) Copy   

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http://pre.ensembl.org/index.html

Database of genomes that are in the process of being annotated are provided as an early access site for users. Genomes are here when the initial BLAST analysis on a new assembly has been done but the gene build has not been completed. Owing to the preliminary nature of the data, Pre-Ensembl provides views of the assembly, BLAST against the assembly and download of portions of the assembly - and little else. A number of ready-made tools for processing your data are also available. In general a full Ensembl release takes months depending on how complex the data are and the time constraints of people in the team. Occasionally a more complete gene build will be released on this site, but without any comparative genomics, variation or other additional data. Many other species with fully annotated genomic data, more website features and documentation are available at www.ensembl.org

Proper citation: Pre Ensembl (RRID:SCR_006766) Copy   

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http://159.149.160.51/cscan/

Data resource that includes a large collection of genome-wide ChIP-Seq experiments performed on transcription factors (TFs), histone modifications, RNA polymerases and others. Enriched peak regions from the ChIP-Seq experiments are crossed with the genomic coordinates of a set of input genes, to identify which of the experiments present a statistically significant number of peaks within the input genes' loci. The input can be a cluster of co-expressed genes, or any other set of genes sharing a common regulatory profile. Users can thus single out which TFs are likely to be common regulators of the genes, and their respective correlations. Also, by examining results on promoter activation, transcription, histone modifications, polymerase binding and so on, users can investigate the effect of the TFs (activation or repression of transcription) as well as of the cell or tissue specificity of the genes' regulation and expression.

Proper citation: Cscan (RRID:SCR_006756) Copy   

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http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://www.funnet.info/

Functional Analysis of Transcriptional Networks (FunNet) is designed as an integrative tool for analyzing gene co-expression networks built from microarray expression data. The analytical model implemented in this tool involves two abstraction layers: transcriptional (i.e. gene expression profiles) and functional (i.e. biological themes indicating the roles of the analyzed transcripts). A functional analysis technique, which relies on Gene Ontology and KEGG annotations, is applied to extract a list of relevant biological themes from microarray gene expression data. Afterwards multiple-instance representations are built to relate relevant biological themes to their annotated transcripts. An original non-linear dynamical model is used to quantify the contextual proximity of relevant genomic themes based on their patterns of propagation in the gene co-expression network (i.e. capturing the similarity of the expression profiles of the transcriptional instances of annotating themes). In the end an unsupervised multiple-instance spectral clustering procedure is used to explore the modular architecture of the co-expression network by grouping together biological themes demonstrating a significant relationship in the co-expression network. Functional and transcriptional representations of the co-expression network are provided, together with detailed information on the contextual centrality of related transcripts and genomic themes. FunNet is provided both as a web-based tool and as a standalone R package. The standalone R implementation can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix) and can be downloaded from the FunNet website, or from the worldwide mirrors of CRAN. Both implementations of the FunNet tool are provided freely under the GNU General Public License 2.0. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FunNet - Transcriptional Networks Analysis (RRID:SCR_006968) Copy   

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http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   

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