Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences.

While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.

Toward building a comprehensive human pan-genome: The SEN-GENOME project.

The human reference genome (GRCh38), primarily sourced from individuals of European descent, falls short in capturing the vast genetic diversity across global populations. Efforts to diversify the reference genome face challenges in accessibility and representation, exacerbating the scarcity of African genomic data crucial for studying diseases prevalent in these populations. Sherman et al. proposed constructing reference genomes tailored to distinct human sub-populations. Their African Pan-Genome initiative highlighted substantial genetic variation missing from the GRCh38 human reference genome, emphasizing the necessity for population-specific genomes. In response, local initiatives like the Senegalese Genome project (SEN-GENOME) have emerged to document the genomes of historically overlooked populations. SEN-GENOME embodies community-driven decentralized research. With meticulous recruitment criteria and ethical practices, it aims to sequence 1,000 genomes from 31 ethnolinguistic groups, in the fourteen administrative regions of Senegal, fostering local genomic research tailored to the region. The key to SEN-GENOME's success is its commitment to local governance of data, capacity building, and integration with broader pan-genome projects in Africa. Despite the complexities of data harmonization and sharing, our collaborative efforts are aligned with common goals, ensuring steady progress toward a comprehensive human pan-genome. We invite and welcome collaboration with other research entities to achieve this shared vision. In summary, local initiatives such as SEN-GENOME are pivotal in bridging genomic disparities, offering pathways to equitable and inclusive genomic research. Collaborative endeavors guided by a collective vision for human health will propel us toward a more encompassing understanding of the human genome and better health through genomic medicine.

Local Ancestry Inference Based on Population-Specific Single-Nucleotide Polymorphisms-A Study of Admixed Populations in the 1000 Genomes Project.

Human populations have interacted throughout history, and a considerable portion of modern human populations show evidence of admixture. Local ancestry inference (LAI) is focused on detecting the genetic ancestry of chromosomal segments in admixed individuals and has wide applications. In this work, we proposed a new LAI method based on population-specific single-nucleotide polymorphisms (SNPs) and applied it in the analysis of admixed populations in the 1000 Genomes Project (1KGP). Based on population-specific SNPs in a sliding window, we computed local ancestry information vectors, which are moment estimators of local ancestral proportions, for two haplotypes of an admixed individual and inferred the local ancestral origins. Then we used African (AFR), East Asian (EAS), European (EUR) and South Asian (SAS) populations from the 1KGP and indigenous American (AMR) populations from the Human Genome Diversity Project (HGDP) as reference populations and conducted the proposed LAI analysis on African American populations and American populations in the 1KGP. The results were compared with those obtained by RFMix, G-Nomix and FLARE. We demonstrated that the existence of alleles in a chromosomal region that are specific to a particular reference population and the absence of alleles specific to the other reference populations provide reasonable evidence for determining the ancestral origin of the region. Contemporary AFR, AMR and EUR populations approximate ancestral populations of the admixed populations well, and the results from RFMix, G-Nomix and FLARE largely agree with those from the Ancestral Spectrum Analyzer (ASA), in which the proposed method was implemented. When admixtures are ancient and contemporary reference populations do not satisfactorily approximate ancestral populations, the performances of RFMix, G-Nomix and FLARE deteriorate with increased error rates and fragmented chromosomal segments. In contrast, our method provides fair results.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

Massive RNA sequencing effort proposed.

U.S. plan would harness the "RNome" for medicine and more-but funding is uncertain.

The interplay of ethics and genetic technologies in balancing the social valuation of the human genome in UNESCO declarations.

This study investigates changes in the social valuation of the human genome over the more than 30 years since the establishment of the Human Genome Project. It offers a descriptive sociological analysis of the three waves of this valuation, mainly by considering three key UNESCO declarations and a relevant report. These waves represent a shifting balance between collectivism and individualism, starting with a broadly constructed valuation of the human genome as common human heritage and moving toward a valuation of dynamic applications within various social and medical contexts (e.g., personalized genomic medicine and genome editing). We seek to broaden the analytical perspective by examining how the declarations' ethical foci are framed within the context of rapidly evolving genetic technologies and their social applications. We conclude by discussing continuity and change in value balancing vis-à-vis changing genomic technologies.

NIH megastudy analyzes first 250,000 genomes.

All of Us finds new DNA variants and refines genetic risk scores in diverse groups.

Did the human genome project affect research on Schizophrenia?

The Human Genome Project was undertaken primarily to discover genetic causes and better treatments for human diseases. Schizophrenia was targeted since three of the project`s principal architects had a personal interest and also because, based on family, adoption, and twin studies, schizophrenia was widely believed to be a genetic disorder. Extensive studies using linkage analysis, candidate genes, genome wide association studies [GWAS], copy number variants, exome sequencing and other approaches have failed to identify causal genes. Instead, they identified almost 300 single nucleotide polymorphisms [SNPs] associated with altered risks of developing schizophrenia as well as some rare variants associated with increased risk in a small number of individuals. Risk genes play a role in the clinical expression of most diseases but do not cause the disease in the absence of other factors. Increasingly, observers question whether schizophrenia is strictly a genetic disorder. Beginning in 1996 NIMH began shifting its research resources from clinical studies to basic research based on the promise of the Human Genome Project. Consequently, three decades later NIMH's genetics investment has yielded almost nothing clinically useful for individuals currently affected. It is time to review NIMH`s schizophrenia research portfolio.

The Human Genome Organisation (HUGO) and a vision for Ecogenomics: the Ecological Genome Project.

BACKGROUND: The following outlines ethical reasons for widening the Human Genome Organisation's (HUGO) mandate to include ecological genomics. MAIN: The environment influences an organism's genome through ambient factors in the biosphere (e.g. climate and UV radiation), as well as the agents it comes into contact with, i.e. the epigenetic and mutagenic effects of inanimate chemicals and pollution, and pathogenic organisms. Emerging scientific consensus is that social determinants of health, environmental conditions and genetic factors work together to influence the risk of many complex illnesses. That paradigm can also explain the environmental and ecological determinants of health as factors that underlie the (un)healthy ecosystems on which communities rely. We suggest that The Ecological Genome Project is an aspirational opportunity to explore connections between the human genome and nature. We propose consolidating a view of Ecogenomics to provide a blueprint to respond to the environmental challenges that societies face. This can only be achieved by interdisciplinary engagement between genomics and the broad field of ecology and related practice of conservation. In this respect, the One Health approach is a model for environmental orientated work. The idea of Ecogenomics-a term that has been used to relate to a scientific field of ecological genomics-becomes the conceptual study of genomes within the social and natural environment. CONCLUSION: The HUGO Committee on Ethics, Law and Society (CELS) recommends that an interdisciplinary One Health approach should be adopted in genomic sciences to promote ethical environmentalism. This perspective has been reviewed and endorsed by the HUGO CELS and the HUGO Executive Board.

The status of the human gene catalogue.

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

Methods for Assessing Population Relationships and History Using Genomic Data.

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

"Love is a microbe too": Microbiome dialectics.

Whereas the Human Genome Project was an anthropocentric research endeavour, microbiome research entails a much more interactive and symbiotic view of human existence, seeing human beings as holobionts, a term coined by Lynn Margulis to emphasise the interconnectedness and multiplicity of organisms. In this paper, building on previous authors, a dialectical perspective on microbiome research will be adopted, striving to supersede the ontological divide between self and other, humans and microbes, and to incorporate the microbiome as a crucial dimension of human existence, not only corporally, but also in terms of mood and cognition. On the practical level, microbiome insights promise to offer opportunities for self-care and self-management, allowing us to consciously interact with our microbiome to foster wellness and health. How to distinguish realistic scenarios from hype? Here again, an interactive (dialectical) approach is adopted, arguing that practices of the self should result from mutual learning between laboratory research and life-world experience.

Short arms of human acrocentric chromosomes and the completion of the human genome sequence.

The complete, ungapped sequence of the short arms of human acrocentric chromosomes (SAACs) is still unknown almost 20 years after the near completion of the Human Genome Project. Yet these short arms of Chromosomes 13, 14, 15, 21, and 22 contain the ribosomal DNA (rDNA) genes, which are of paramount importance for human biology. The sequences of SAACs show an extensive variation in the copy number of the various repetitive elements, the full extent of which is currently unknown. In addition, the full spectrum of repeated sequences, their organization, and the low copy number functional elements are also unknown. The Telomere-to-Telomere (T2T) Project using mainly long-read sequence technology has recently completed the assembly of the genome from a hydatidiform mole, CHM13, and has thus established a baseline reference for further studies on the organization, variation, functional annotation, and impact in human disorders of all the previously unknown genomic segments, including the SAACs. The publication of the initial results of the T2T Project will update and improve the reference genome for a better understanding of the evolution and function of the human genome.

The complete sequence of a human genome.

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

Don Lindberg and the Creation of the National Center for Biotechnology Information.

The highest priority new initiative resulting from the 1985-86 National Library of Medicine Long Range Planning exercise initiated by NLM Director Dr. Donald A.B. Lindberg was the creation of new information resources and services related to molecular biology and genetics, termed "biotechnology information". Beginning with existing NLM resources and research projects associated with molecular data, and with Lindberg's enthusiastic support, the institution launched a Congressionally-mandated Center that has become an essential part of 21st century biomedical science.