Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets.

To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the data is easily discoverable and usable by the biological research community. To address these challenges, the National Center for Biotechnology Information (NCBI) has created NCBI Datasets. This resource provides straightforward, comprehensive, and scalable access to biological sequences, annotations, and metadata for a wide range of taxa. Following the FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles, NCBI Datasets offers user-friendly web interfaces, command-line tools, and documented APIs, empowering researchers to access NCBI data seamlessly. The data is delivered as packages of sequences and metadata, thus facilitating improved data retrieval, sharing, and usability in research. Moreover, this data delivery method fosters effective data attribution and promotes its further reuse. This paper outlines the current scope of data accessible through NCBI Datasets and explains various options for exploring and downloading the data.

The NCBI Comparative Genome Viewer (CGV) is an interactive visualization tool for the analysis of whole-genome eukaryotic alignments.

We report a new visualization tool for analysis of whole-genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.gov/genome/cgv/). CGV visualizes pairwise same-species and cross-species alignments provided by National Center for Biotechnology Information (NCBI) using assembly alignment algorithms developed by us and others. Researchers can examine large structural differences spanning chromosomes, such as inversions or translocations. Users can also navigate to regions of interest, where they can detect and analyze smaller-scale deletions and rearrangements within specific chromosome or gene regions. RefSeq or user-provided gene annotation is displayed where available. CGV currently provides approximately 800 alignments from over 350 animal, plant, and fungal species. CGV and related NCBI viewers are undergoing active development to further meet needs of the research community in comparative genome visualization.

Rapid and sensitive detection of genome contamination at scale with FCS-GX.

Assembled genome sequences are being generated at an exponential rate. Here we present FCS-GX, part of NCBI's Foreign Contamination Screen (FCS) tool suite, optimized to identify and remove contaminant sequences in new genomes. FCS-GX screens most genomes in 0.1-10 min. Testing FCS-GX on artificially fragmented genomes demonstrates high sensitivity and specificity for diverse contaminant species. We used FCS-GX to screen 1.6 million GenBank assemblies and identified 36.8 Gbp of contamination, comprising 0.16% of total bases, with half from 161 assemblies. We updated assemblies in NCBI RefSeq to reduce detected contamination to 0.01% of bases. FCS-GX is available at https://github.com/ncbi/fcs/ or https://doi.org/10.5281/zenodo.10651084 .

Database resources of the National Center for Biotechnology Information.

The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. NCBI provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for most of these databases. Resources receiving significant updates in the past year include PubMed, PMC, Bookshelf, SciENcv, the NIH Comparative Genomics Resource (CGR), NCBI Virus, SRA, RefSeq, foreign contamination screening tools, Taxonomy, iCn3D, ClinVar, GTR, MedGen, dbSNP, ALFA, ClinicalTrials.gov, Pathogen Detection, antimicrobial resistance resources, and PubChem. These resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.

Interactive visualization of whole eukaryote genome alignments using NCBI's Comparative Genome Viewer (CGV).

We report a new visualization tool for analysis of whole genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.gov/genome/cgv/). CGV visualizes pairwise same-species and cross-species alignments provided by NCBI using assembly alignment algorithms developed by us and others. Researchers can examine the alignments between the two assemblies using two alternate views: a chromosome ideogram-based view or a 2D genome dotplot. Whole genome alignment views expose large structural differences spanning chromosomes, such as inversions or translocations. Users can also navigate to regions of interest, where they can detect and analyze smaller-scale deletions and rearrangements within specific chromosome or gene regions. RefSeq or user-provided gene annotation is displayed in the ideogram view where available. CGV currently provides approximately 700 alignments from over 300 animal, plant, and fungal species. CGV and related NCBI viewers are undergoing active development to further meet needs of the research community in comparative genome visualization.

The NIH Comparative Genomics Resource: addressing the promises and challenges of comparative genomics on human health.

Comparative genomics is the comparison of genetic information within and across organisms to understand the evolution, structure, and function of genes, proteins, and non-coding regions (Sivashankari and Shanmughavel, Bioinformation 1:376-8, 2007). Advances in sequencing technology and assembly algorithms have resulted in the ability to sequence large genomes and provided a wealth of data that are being used in comparative genomic analyses. Comparative analysis can be leveraged to systematically explore and evaluate the biological relationships and evolution between species, aid in understanding the structure and function of genes, and gain a better understanding of disease and potential drug targets. As our knowledge of genetics expands, comparative genomics can help identify emerging model organisms among a broader span of the tree of life, positively impacting human health. This impact includes, but is not limited to, zoonotic disease research, therapeutics development, microbiome research, xenotransplantation, oncology, and toxicology. Despite advancements in comparative genomics, new challenges have arisen around the quantity, quality assurance, annotation, and interoperability of genomic data and metadata. New tools and approaches are required to meet these challenges and fulfill the needs of researchers. This paper focuses on how the National Institutes of Health (NIH) Comparative Genomics Resource (CGR) can address both the opportunities for comparative genomics to further impact human health and confront an increasingly complex set of challenges facing researchers.

Rapid and sensitive detection of genome contamination at scale with FCS-GX.

Assembled genome sequences are being generated at an exponential rate. Here we present FCS-GX, part of NCBI's Foreign Contamination Screen (FCS) tool suite, optimized to identify and remove contaminant sequences in new genomes. FCS-GX screens most genomes in 0.1-10 minutes. Testing FCS-GX on artificially fragmented genomes demonstrates sensitivity >95% for diverse contaminant species and specificity >99.93%. We used FCS-GX to screen 1.6 million GenBank assemblies and identified 36.8 Gbp of contamination (0.16% of total bases), with half from 161 assemblies. We updated assemblies in NCBI RefSeq to reduce detected contamination to 0.01% of bases. FCS-GX is available at https://github.com/ncbi/fcs/.

Database resources of the National Center for Biotechnology Information in 2023.

The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. NCBI provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for most of these databases. New resources include the Comparative Genome Resource (CGR) and the BLAST ClusteredNR database. Resources receiving significant updates in the past year include PubMed, PMC, Bookshelf, IgBLAST, GDV, RefSeq, NCBI Virus, GenBank type assemblies, iCn3D, ClinVar, GTR, dbGaP, ALFA, ClinicalTrials.gov, Pathogen Detection, antimicrobial resistance resources, and PubChem. These resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.

Personalized genome assembly for accurate cancer somatic mutation discovery using tumor-normal paired reference samples.

BACKGROUND: The use of a personalized haplotype-specific genome assembly, rather than an unrelated, mosaic genome like GRCh38, as a reference for detecting the full spectrum of somatic events from cancers has long been advocated but has never been explored in tumor-normal paired samples. Here, we provide the first demonstrated use of de novo assembled personalized genome as a reference for cancer mutation detection and quantifying the effects of the reference genomes on the accuracy of somatic mutation detection. RESULTS: We generate de novo assemblies of the first tumor-normal paired genomes, both nuclear and mitochondrial, derived from the same individual with triple negative breast cancer. The personalized genome was chromosomal scale, haplotype phased, and annotated. We demonstrate that it provides individual specific haplotypes for complex regions and medically relevant genes. We illustrate that the personalized genome reference not only improves read alignments for both short-read and long-read sequencing data but also ameliorates the detection accuracy of somatic SNVs and SVs. We identify the equivalent somatic mutation calls between two genome references and uncover novel somatic mutations only when personalized genome assembly is used as a reference. CONCLUSIONS: Our findings demonstrate that use of a personalized genome with individual-specific haplotypes is essential for accurate detection of the full spectrum of somatic mutations in the paired tumor-normal samples. The unique resource and methodology established in this study will be beneficial to the development of precision oncology medicine not only for breast cancer, but also for other cancers.

Evaluation of Lou et al.: Proposed benefits of a population-specific genome reference.

One snapshot of the peer review process for "Haplo-type-resolved de novo assembly of a Tujia genome suggests the necessity for high-quality population-specific genome references" (Lou et al., 2022).

The Human Pangenome Project: a global resource to map genomic diversity.

The human reference genome is the most widely used resource in human genetics and is due for a major update. Its current structure is a linear composite of merged haplotypes from more than 20 people, with a single individual comprising most of the sequence. It contains biases and errors within a framework that does not represent global human genomic variation. A high-quality reference with global representation of common variants, including single-nucleotide variants, structural variants and functional elements, is needed. The Human Pangenome Reference Consortium aims to create a more sophisticated and complete human reference genome with a graph-based, telomere-to-telomere representation of global genomic diversity. Here we leverage innovations in technology, study design and global partnerships with the goal of constructing the highest-possible quality human pangenome reference. Our goal is to improve data representation and streamline analyses to enable routine assembly of complete diploid genomes. With attention to ethical frameworks, the human pangenome reference will contain a more accurate and diverse representation of global genomic variation, improve gene-disease association studies across populations, expand the scope of genomics research to the most repetitive and polymorphic regions of the genome, and serve as the ultimate genetic resource for future biomedical research and precision medicine.

Accessing NCBI data using the NCBI Sequence Viewer and Genome Data Viewer (GDV).

The National Center for Biotechnology Information (NCBI) is an archive providing free access to a wide range and large volume of biological sequence data and literature. Staff scientists at NCBI analyze user-submitted data in the archive, producing gene and SNP annotation and generating sequence alignment tools. NCBI's flagship genome browser, Genome Data Viewer (GDV), displays our in-house RefSeq annotation; is integrated with other NCBI resources such as Gene, dbGaP, and BLAST; and provides a platform for customized analysis and visualization. Here, we describe how members of the biomedical research community can use GDV and the related NCBI Sequence Viewer (SV) to access, analyze, and disseminate NCBI and custom biomedical sequence data. In addition, we report how users can add SV to their own web pages to create a custom graphical sequence display without the need for infrastructure investments or back-end deployments.

Database resources of the National Center for Biotechnology Information.

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. The Entrez system provides search and retrieval operations for most of these data from 34 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Custom implementations of the BLAST program provide sequence-based searching of many specialized datasets. New resources released in the past year include a new PubMed interface and NCBI datasets. Additional resources that were updated in the past year include PMC, Bookshelf, Genome Data Viewer, SRA, ClinVar, dbSNP, dbVar, Pathogen Detection, BLAST, Primer-BLAST, IgBLAST, iCn3D and PubChem. All of these resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.

[The disability adviser, an important member of the training team]. / Le référent handicap, un interlocuteur privilégié de la formation.

Disability advisers work in companies and training centres. They are real resource people for learners with a disability. They are there to answer all their questions, favour their integration and ensure their training is a success.

Telomere-to-telomere assembly of a complete human X chromosome.

After two decades of improvements, the current human reference genome (GRCh38) is the most accurate and complete vertebrate genome ever produced. However, no single chromosome has been finished end to end, and hundreds of unresolved gaps persist1,2. Here we present a human genome assembly that surpasses the continuity of GRCh382, along with a gapless, telomere-to-telomere assembly of a human chromosome. This was enabled by high-coverage, ultra-long-read nanopore sequencing of the complete hydatidiform mole CHM13 genome, combined with complementary technologies for quality improvement and validation. Focusing our efforts on the human X chromosome3, we reconstructed the centromeric satellite DNA array (approximately 3.1 Mb) and closed the 29 remaining gaps in the current reference, including new sequences from the human pseudoautosomal regions and from cancer-testis ampliconic gene families (CT-X and GAGE). These sequences will be integrated into future human reference genome releases. In addition, the complete chromosome X, combined with the ultra-long nanopore data, allowed us to map methylation patterns across complex tandem repeats and satellite arrays. Our results demonstrate that finishing the entire human genome is now within reach, and the data presented here will facilitate ongoing efforts to complete the other human chromosomes.

ClinVar: improvements to accessing data.

ClinVar is a freely available, public archive of human genetic variants and interpretations of their relationships to diseases and other conditions, maintained at the National Institutes of Health (NIH). Submitted interpretations of variants are aggregated and made available on the ClinVar website (https://www.ncbi.nlm.nih.gov/clinvar/), and as downloadable files via FTP and through programmatic tools such as NCBI's E-utilities. The default view on the ClinVar website, the Variation page, was recently redesigned. The new layout includes several new sections that make it easier to find submitted data as well as summary data such as all diseases and citations reported for the variant. The new design also better represents more complex data such as haplotypes and genotypes, as well as variants that are in ClinVar as part of a haplotype or genotype but have no interpretation for the single variant. ClinVar's variant-centric XML had its production release in April 2019. The ClinVar website and E-utilities both have been updated to support the VCV (variation in ClinVar) accession numbers found in the variant-centric XML file. ClinVar's search engine has been fine-tuned for improved retrieval of search results.

Database resources of the National Center for Biotechnology Information.

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts published in life science journals. The Entrez system provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Custom implementations of the BLAST program provide sequence-based searching of many specialized datasets. New resources released in the past year include a new PubMed interface, a sequence database search and a gene orthologs page. Additional resources that were updated in the past year include PMC, Bookshelf, My Bibliography, Assembly, RefSeq, viral genomes, the prokaryotic genome annotation pipeline, Genome Workbench, dbSNP, BLAST, Primer-BLAST, IgBLAST and PubChem. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

The Genome of C57BL/6J "Eve", the Mother of the Laboratory Mouse Genome Reference Strain.

Isogenic laboratory mouse strains enhance reproducibility because individual animals are genetically identical. For the most widely used isogenic strain, C57BL/6, there exists a wealth of genetic, phenotypic, and genomic data, including a high-quality reference genome (GRCm38.p6). Now 20 years after the first release of the mouse reference genome, C57BL/6J mice are at least 26 inbreeding generations removed from GRCm38 and the strain is now maintained with periodic reintroduction of cryorecovered mice derived from a single breeder pair, aptly named Adam and Eve. To provide an update to the mouse reference genome that more accurately represents the genome of today's C57BL/6J mice, we took advantage of long read, short read, and optical mapping technologies to generate a de novo assembly of the C57BL/6J Eve genome (B6Eve). Using these data, we have addressed recurring variants observed in previous mouse genomic studies. We have also identified structural variations, closed gaps in the mouse reference assembly, and revealed previously unannotated coding sequences. This B6Eve assembly explains discrepant observations that have been associated with GRCm38-based analyses, and will inform a reference genome that is more representative of the C57BL/6J mice that are in use today.

A strategy for building and using a human reference pangenome.

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.