Bases and spaces: resources on the web for accessing the draft human genome

Much is expected of the draft human genome sequence, and yet there is no central resource to host the plethora of sequence and mapping information available. Consequently, finding the most useful and reliable human genome data and resources currently available on the web can be challenging, but is not impossible.     

Plant genome resources at the national center for biotechnology information

The National Center for Biotechnology Information (NCBI) integrates data from more than 20 biological databases through a flexible search and retrieval system called Entrez. A core Entrez database, Entrez Nucleotide, includes GenBank and is tightly linked to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMed. A suite of more specialized databases for genomes, genes, gene families, gene expression, gene variation, and protein domains dovetails with the core databases to make Entrez a powerful system for genomic research. Linked to the full range of Entrez databases is the NCBI Map Viewer, which displays aligned genetic, physical, and sequence maps for eukaryotic genomes including those of many plants. A specialized plant query page allow maps from all plant genomes covered by the Map Viewer to be searched in tandem to produce a display of aligned maps from several species. PlantBLAST searches against the sequences shown in the Map Viewer allow BLAST alignments to be viewed within a genomic context. In addition, precomputed sequence similarities, such as those for proteins offered by BLAST Link, enable fluid navigation from unannotated to annotated sequences, quickening the pace of discovery. NCBI Web pages for plants, such as Plant Genome Central, complete the system by providing centralized access to NCBI's genomic resources as well as links to organism-specific Web pages beyond NCBI.     

MitoCore: a curated constraint-based model for simulating human central metabolism

Background

The complexity of metabolic networks can make the origin and impact of changes in central metabolism occurring during diseases difficult to understand. Computer simulations can help unravel this complexity, and progress has advanced in genome-scale metabolic models. However, many models produce unrealistic results when challenged to simulate abnormal metabolism as they include incorrect specification and localisation of reactions and transport steps, incorrect reaction parameters, and confounding of prosthetic groups and free metabolites in reactions. Other common drawbacks are due to their scale, making them difficult to parameterise and simulation results hard to interpret. Therefore, it remains important to develop smaller, manually curated models.

Results

We present MitoCore, a manually curated constraint-based computer model of human metabolism that incorporates the complexity of central metabolism and simulates this metabolism successfully under normal and abnormal physiological conditions, including hypoxia and mitochondrial diseases. MitoCore describes 324 metabolic reactions, 83 transport steps between mitochondrion and cytosol, and 74 metabolite inputs and outputs through the plasma membrane, to produce a model of manageable scale for easy interpretation of results. Its key innovations include a more accurate partitioning of metabolism between cytosol and mitochondrial matrix; better modelling of connecting transport steps; differentiation of prosthetic groups and free co-factors in reactions; and a new representation of the respiratory chain and the proton motive force. MitoCore’s default parameters simulate normal cardiomyocyte metabolism, and to improve usability and allow comparison with other models and types of analysis, its reactions and metabolites have extensive annotation, and cross-reference identifiers from Virtual Metabolic Human database and KEGG. These innovations—including over 100 reactions absent or modified from Recon 2—are necessary to model central metabolism more accurately.

Conclusion

We anticipate MitoCore as a research tool for scientists, from experimentalists looking to interpret their data and test hypotheses, to experienced modellers predicting the consequences of disease or using computationally intensive methods that are infeasible with larger models, as well as a teaching tool for those new to modelling and needing a small, manageable model on which to learn and experiment.

     

Introducing defined chromosomal rearrangements into the mouse genome

Chromosomal rearrangements have been instrumental in genetic studies in Drosophila. Visibly marked deficiencies (deletions) are used in mapping studies and region-specific mutagenesis screens by providing segmental haploidy required to uncover recessive mutations. Marked recessive lethal inversions are used as balancer chromosomes to maintain recessive lethal mutations and to maintain the integrity of mutagenized chromosomes. In mice, studies on series of radiation-induced deletions that surround several visible mutations have yielded invaluable functional genomic information in the regions analyzed. However, most regions of the mouse genome are not accessible to such analyses due to a lack of marked chromosomal rearrangements. Here we describe a method to generate defined chromosomal rearrangements using the Cre--loxP recombination system based on a published strategy [R. Ramirez-Solis, P. Liu, and A. Bradley, (1995) Nature 378, 720--724]. Various types of rearrangements, such as deletions, duplications, inversions, and translocations, can be engineered using this strategy. Furthermore, the rearrangements can be visibly marked with coat color genes, providing essential reagents for large-scale recessive genetic screens in the mouse. The ability to generate marked chromosomal rearrangements will help to elevate the level of manipulative mouse genetics to that of Drosophila genetics.     

dbSNP: the NCBI database of genetic variation

In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Center for Biotechnology Information (NCBI) has established the dbSNP database [S.T.Sherry, M.Ward and K. Sirotkin (1999) Genome Res., 9, 677-679]. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. The complete contents of dbSNP can also be downloaded in multiple formats via anonymous FTP at ftp://ncbi.nlm.nih.gov/snp/.     

Telomere-related sequences at interstitial sites in the human genome

The ends (telomeres) of eukaryotic chromosomes are protected from degradation and from loss during DNA replication by buffers of simple tandem repetitive sequence. The nucleotide sequence of these telomeric arrays is fundamental to telomere function as a site for protein and ribonucleoprotein binding and varies only slightly in a wide range of organisms. We present evidence that arrays of this human telomeric sequence, TTAGGG, are present not only at the ends of human chromosomes but also at numerous interstitial sites. These interstitial loci share nucleotide sequence similarity outside the repetitive array, suggesting that they are related functionally or have evolved from a common progenitor locus.     

TaxonKit: A practical and efficient NCBI taxonomy toolkit

The National Center for Biotechnology Information (NCBI) Taxonomy is widely applied in biomedical and ecological studies. Typical demands include querying taxonomy identifier (TaxIds) by taxonomy names, querying complete taxonomic lineages by TaxIds, listing descendants of given TaxIds, and others. However, existed tools are either limited in functionalities or inefficient in terms of runtime. In this work, we present TaxonKit, a command-line toolkit for comprehensive and efficient manipulation of NCBI Taxonomy data. TaxonKit comprises seven core subcommands providing functions, including TaxIds querying, listing, filtering, lineage retrieving and reformatting, lowest common ancestor computation, and TaxIds change tracking. The practical functions, competitive processing performance, scalability with different scales of datasets and good accessibility can facilitate taxonomy data manipulations. TaxonKit provides free access under the permissive MIT license on GitHub, Brewsci, and Bioconda. The documents are also available at https://bioinf.shenwei.me/taxonkit/.     

Visualizing the genome: techniques for presenting human genome data and annotations

Background  

In order to take full advantage of the newly available public human genome sequence data and associated annotations, biologists require visualization tools ("genome browsers") that can accommodate the high frequency of alternative splicing in human genes and other complexities.     

The TIGR rice genome annotation resource: annotating the rice genome and creating resources for plant biologists

Rice is not only a major food staple for the world's population but it also is a model species for a major group of flowering plants, the monocotyledonous plants. Draft genomic sequence of two subspecies of rice, Oryza sativa spp. japonica and indica ssp. are publicly available. To provide the community with a resource to data-mine the rice genome, we have constructed an annotation resource for rice (http://www.tigr.org/tdb/e2k1/osa1/). In this resource, we have annotated the rice genome for gene content, identified motifs/domains within the predicted genes, constructed a rice repeat database, identified related sequences in other plant species, and identified syntenic sequences between rice and maize. All of the data is available through web-based interfaces, FTP downloads, and a Distributed Annotation System.     

NCBI Reference Sequence project: update and current status

The goal of the NCBI Reference Sequence (RefSeq) project is to provide the single best non-redundant and comprehensive collection of naturally occurring biological molecules, representing the central dogma. Nucleotide and protein sequences are explicitly linked on a residue-by-residue basis in this collection. Ideally all molecule types will be available for each well-studied organism, but the initial database collection pragmatically includes only those molecules and organisms that are most readily identified. Thus different amounts of information are available for different organisms at any given time. Furthermore, for some organisms additional intermediate records are provided when the genome sequence is not yet finished. The collection is supplied by NCBI through three distinct pipelines in addition to collaborations with community groups. The collection is curated on an ongoing basis. Additional information about the NCBI RefSeq project is available at http://www.ncbi.nih.gov/RefSeq/.