Showing papers on "Genomics published in 2015"

A global reference for human genetic variation.

Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

An integrated map of structural variation in 2,504 human genomes

Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

The re-emergence of natural products for drug discovery in the genomics era

Abstract: Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.

Analysis of protein-coding genetic variation in 60,706 humans

Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities. The resulting catalogue of human genetic diversity has unprecedented resolution, with an average of one variant every eight bases of coding sequence and the presence of widespread mutational recurrence. The deep catalogue of variation provided by the Exome Aggregation Consortium (ExAC) can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 79% of which have no currently established human disease phenotype. Finally, we show that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human knockout variants in protein-coding genes.

Sambamba: fast processing of NGS alignment formats

Abstract: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically reduces processing time. Sambamba is being adopted at sequencing centers, not only because of its speed, but also because of additional functionality, including coverage analysis and powerful filtering capability. AVAILABILITY AND IMPLEMENTATION: Sambamba is free and open source software, available under a GPLv2 license. Sambamba can be downloaded and installed from http://www.open-bio.org/wiki/Sambamba. Sambamba v0.5.0 was released with doi:10.5281/zenodo.13200. CONTACT: j.c.p.prins@umcutrecht.nl.

High-throughput functional genomics using CRISPR–Cas9

Abstract: CRISPR–Cas9 has been adopted as a powerful genome-editing technology in various species. By generating libraries of thousands of guide RNAs — which direct the Cas9 nuclease to chosen genomic loci — high-throughput genetic perturbations are now possible. This Review discusses the latest applications of CRISPR–Cas9 in mammalian functional genomics screens. It covers related genome-scale applications of Cas9 for either gene knockout or transcriptional modulation, and provides comparisons with complementary RNA interference (RNAi)-based approaches.

The UK10K project identifies rare variants in health and disease

Abstract: The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.

Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells

Abstract: Although RNA-guided genome editing via the CRISPR-Cas9 system is now widely used in biomedical research, genome-wide target specificities of Cas9 nucleases remain controversial. Here we present Digenome-seq, in vitro Cas9-digested whole-genome sequencing, to profile genome-wide Cas9 off-target effects in human cells. This in vitro digest yields sequence reads with the same 5' ends at cleavage sites that can be computationally identified. We validated off-target sites at which insertions or deletions were induced with frequencies below 0.1%, near the detection limit of targeted deep sequencing. We also showed that Cas9 nucleases can be highly specific, inducing off-target mutations at merely several, rather than thousands of, sites in the entire genome and that Cas9 off-target effects can be avoided by replacing 'promiscuous' single guide RNAs (sgRNAs) with modified sgRNAs. Digenome-seq is a robust, sensitive, unbiased and cost-effective method for profiling genome-wide off-target effects of programmable nucleases including Cas9.

High-throughput sequencing of DNA G-quadruplex structures in the human genome

Abstract: G-quadruplexes (G4s) are nucleic acid secondary structures that form within guanine-rich DNA or RNA sequences. G4 formation can affect chromatin architecture and gene regulation and has been associated with genomic instability, genetic diseases and cancer progression. Here we present a high-resolution sequencing-based method to detect G4s in the human genome. We identified 716,310 distinct G4 structures, 451,646 of which were not predicted by computational methods. These included previously uncharacterized noncanonical long loop and bulged structures. We observed a high G4 density in functional regions, such as 5' untranslated regions and splicing sites, as well as in genes previously not predicted to contain these structures (such as BRCA2). G4 formation was significantly associated with oncogenes, tumor suppressors and somatic copy number alterations related to cancer development. The G4s identified in this study may therefore represent promising targets for cancer intervention.

Resolving the complexity of the human genome using single-molecule sequencing

Abstract: The human genome is arguably the most complete mammalian reference assembly, yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. To identify missing sequence and genetic variation, here we sequence and analyse a haploid human genome (CHM1) using single-molecule, real-time DNA sequencing. We close or extend 55% of the remaining interstitial gaps in the human GRCh37 reference genome--78% of which carried long runs of degenerate short tandem repeats, often several kilobases in length, embedded within (G+C)-rich genomic regions. We resolve the complete sequence of 26,079 euchromatic structural variants at the base-pair level, including inversions, complex insertions and long tracts of tandem repeats. Most have not been previously reported, with the greatest increases in sensitivity occurring for events less than 5 kilobases in size. Compared to the human reference, we find a significant insertional bias (3:1) in regions corresponding to complex insertions and long short tandem repeats. Our results suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.

G&T-seq: parallel sequencing of single-cell genomes and transcriptomes

Abstract: G&T-seq offers robust full-length transcript and whole-genome sequencing simultaneously from a single cell.

Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways. Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium.

Abstract: Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Insights from 20 years of bacterial genome sequencing

Abstract: Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

Microbial species delineation using whole genome sequences

Abstract: Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. We introduce an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, we observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. Our results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. We propose that this precise and objective AF,gANI-based species definition: the MiSI (Microbial Species Identifier) method, be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach, as required.

A practical guide to environmental association analysis in landscape genomics

Abstract: Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies.

Assembly and diploid architecture of an individual human genome via single-molecule technologies

Abstract: We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality.

SpeedSeq: ultra-fast personal genome analysis and interpretation

Abstract: SpeedSeq is an open-source genome analysis platform that accomplishes alignment, variant detection and functional annotation of a 50× human genome in 13 h on a low-cost server and alleviates a bioinformatics bottleneck that typically demands weeks of computation with extensive hands-on expert involvement. SpeedSeq offers performance competitive with or superior to current methods for detecting germline and somatic single-nucleotide variants, structural variants, insertions and deletions, and it includes novel functionality for streamlined interpretation.

Integrated genome and transcriptome sequencing of the same cell

Abstract: Single-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transcriptome heterogeneity. We describe a quasilinear amplification strategy to quantify genomic DNA and mRNA from the same cell without physically separating the nucleic acids before amplification. We show that the efficiency of our integrated approach is similar to existing methods for single-cell sequencing of either genomic DNA or mRNA. Further, we find that genes with high cell-to-cell variability in transcript numbers generally have lower genomic copy numbers, and vice versa, suggesting that copy number variations may drive variability in gene expression among individual cells. Applications of our integrated sequencing approach could range from gaining insights into cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissues.

DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation

Abstract: Epigenome modulation potentially provides a mechanism for organisms to adapt, within and between generations. However, neither the extent to which this occurs, nor the mechanisms involved are known. Here we investigate DNA methylation variation in Swedish Arabidopsis thaliana accessions grown at two different temperatures. Environmental effects were limited to transposons, where CHH methylation was found to increase with temperature. Genome-wide association studies (GWAS) revealed that the extensive CHH methylation variation was strongly associated with genetic variants in both cis and trans, including a major trans-association close to the DNA methyltransferase CMT2. Unlike CHH methylation, CpG gene body methylation (GBM) was not affected by growth temperature, but was instead correlated with the latitude of origin. Accessions from colder regions had higher levels of GBM for a significant fraction of the genome, and this was associated with increased transcription for the genes affected. GWAS revealed that this effect was largely due to trans-acting loci, many of which showed evidence of local adaptation.

Chromosome-scale shotgun assembly using an in vitro method for long-range linkage

Abstract: Long-range and highly accurate de novo assembly from short-read data is one of the most pressing challenges in genomics. Recently, it has been shown that read pairs generated by proximity ligation of DNA in chromatin of living tissue can address this problem. These data dramatically increase the scaffold contiguity of assemblies and provide haplotype phasing information. Here, we describe a simpler approach ("Chicago") based on in vitro reconstituted chromatin. We generated two Chicago datasets with human DNA and used a new software pipeline ("HiRise") to construct a highly accurate de novo assembly and scaffolding of a human genome with scaffold N50 of 30 Mb. We also demonstrated the utility of Chicago for improving existing assemblies by re-assembling and scaffolding the genome of the American alligator. With a single library and one lane of Illumina HiSeq sequencing, we increased the scaffold N50 of the American alligator from 508 kb to 10 Mb. Our method uses established molecular biology procedures and can be used to analyze any genome, as it requires only about 5 micrograms of DNA as the starting material.

FlyBase: introduction of the Drosophila melanogaster Release 6 reference genome assembly and large-scale migration of genome annotations

Abstract: Release 6, the latest reference genome assembly of the fruit fly Drosophila melanogaster, was released by the Berkeley Drosophila Genome Project in 2014; it replaces their previous Release 5 genome assembly, which had been the reference genome assembly for over 7 years. With the enormous amount of information now attached to the D. melanogaster genome in public repositories and individual laboratories, the replacement of the previous assembly by the new one is a major event requiring careful migration of annotations and genome-anchored data to the new, improved assembly. In this report, we describe the attributes of the new Release 6 reference genome assembly, the migration of FlyBase genome annotations to this new assembly, how genome features on this new assembly can be viewed in FlyBase (http://flybase.org) and how users can convert coordinates for their own data to the corresponding Release 6 coordinates.

The bioenergetic costs of a gene

Abstract: An enduring mystery of evolutionary genomics concerns the mechanisms responsible for lineage-specific expansions of genome size in eukaryotes, especially in multicellular species. One idea is that all excess DNA is mutationally hazardous, but weakly enough so that genome-size expansion passively emerges in species experiencing relatively low efficiency of selection owing to small effective population sizes. Another idea is that substantial gene additions were impossible without the energetic boost provided by the colonizing mitochondrion in the eukaryotic lineage. Contrary to this latter view, analysis of cellular energetics and genomics data from a wide variety of species indicates that, relative to the lifetime ATP requirements of a cell, the costs of a gene at the DNA, RNA, and protein levels decline with cell volume in both bacteria and eukaryotes. Moreover, these costs are usually sufficiently large to be perceived by natural selection in bacterial populations, but not in eukaryotes experiencing high levels of random genetic drift. Thus, for scaling reasons that are not yet understood, by virtue of their large size alone, eukaryotic cells are subject to a broader set of opportunities for the colonization of novel genes manifesting weakly advantageous or even transiently disadvantageous phenotypic effects. These results indicate that the origin of the mitochondrion was not a prerequisite for genome-size expansion.

Viral dark matter and virus-host interactions resolved from publicly available microbial genomes

Abstract: Viruses are infectious particles that can only multiply inside the cells of microbes and other organisms. Little is known about the genetic differences between virus particles (so-called ‘genetic diversity’), especially compared to what we know about the diversity of bacteria, archaea, and other single-celled microbes. This lack of knowledge hampers our understanding of the role viruses play in the evolution of microbial communities and their associated ecosystems. Studying the genetics of the viruses in these communities is challenging. There is no single ‘marker’ gene that can be used to identify all viruses in environmental samples. Also, many of the fragments of viral genomes that have been identified have not yet been linked to their host microbes. Many viruses integrate their genome into the DNA of their host cell, and there are computational tools available that exploit this ability to identify viruses and link them to their host. However, other viruses can live and multiply inside cells without integrating their genome into the host's DNA. Earlier in 2015, researchers developed a new computational tool called VirSorter that can predict virus genome sequences within the DNA extracted from microbes. VirSorter identifies viral genome sequences based on the presence of ‘hallmark’ genes that encode for components found in many virus particles, together with a reference database of genomes from many viruses. Now, Roux et al.—including some of the researchers from the earlier work—use VirSorter to predict viral DNA from publicly available bacteria and archaea genome data. The study identifies over 12,000 viral genomes and links them to their microbial hosts. These data increase the number of viral genome sequences that are publically available by a factor of ten and identify the first viruses associated with 13 new types of bacteria, which include species that are abundant in particular environments. It is possible for several different viruses to infect a single cell at the same time. Some viruses are known to be able to exchange DNA, and if this happens frequently in other viruses, it could have a big impact on how viruses evolve. Roux et al.'s findings suggest that although it is common for several different viruses to infect the same cell, it is relatively rare for these viruses to exchange genetic material. Roux et al.'s findings demonstrate the value of searching publicly available microbial genome data for fragments of viral genomes. These new viral genomes will serve as a useful resource for researchers as they explore the communities of viruses and microbes in natural environments, the human body and in industrial processes.

Large multiallelic copy number variations in humans

Abstract: Thousands of genome segments appear to be present in widely varying copy number in different human genomes. We developed ways to use increasingly abundant whole genome sequence data to identify the copy numbers, alleles and haplotypes present at most large, multi-allelic CNVs (mCNVs). We analyzed 849 genomes sequenced by the 1000 Genomes Project to identify most large (>5 kb) mCNVs, including 3,878 duplications, of which 1,356 appear to have three or more segregating alleles. We find that mCNVs give rise to most human gene-dosage variation – exceeding sevenfold the contribution of deletions and biallelic duplications – and that this variation in gene dosage generates abundant variation in gene expression. We describe “runaway duplication haplotypes” in which genes, including HPR and ORM1, have mutated to high copy number on specific haplotypes. We describe partially successful initial strategies for analyzing mCNVs via imputation and provide an initial data resource to support such analyses.

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Abstract: We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders

Abstract: Genetic and genomic approaches have implicated hundreds of genetic loci in neurodevelopmental disorders and neurodegeneration, but mechanistic understanding continues to lag behind the pace of gene discovery. Understanding the role of specific genetic variants in the brain involves dissecting a functional hierarchy that encompasses molecular pathways, diverse cell types, neural circuits and, ultimately, cognition and behaviour. With a focus on transcriptomics, this Review discusses how high-throughput molecular, integrative and network approaches inform disease biology by placing human genetics in a molecular systems and neurobiological context. We provide a framework for interpreting network biology studies and leveraging big genomics data sets in neurobiology.

Computational approaches to natural product discovery.

Abstract: Starting with the earliest Streptomyces genome sequences, the promise of natural product genome mining has been captivating: genomics and bioinformatics would transform compound discovery from an ad hoc pursuit to a high-throughput endeavor Until recently, however, genome mining has advanced natural product discovery only modestly Here, we argue that the development of algorithms to mine the continuously increasing amounts of (meta)genomic data will enable the promise of genome mining to be realized We review computational strategies that have been developed to identify biosynthetic gene clusters in genome sequences and predict the chemical structures of their products We then discuss networking strategies that can systematize large volumes of genetic and chemical data and connect genomic information to metabolomic and phenotypic data Finally, we provide a vision of what natural product discovery might look like in the future, specifically considering longstanding questions in microbial ecology regarding the roles of metabolites in interspecies interactions

Genetic variation and the de novo assembly of human genomes.

Abstract: The discovery of genetic variation and the assembly of genome sequences are both inextricably linked to advances in DNA-sequencing technology. Short-read massively parallel sequencing has revolutionized our ability to discover genetic variation but is insufficient to generate high-quality genome assemblies or resolve most structural variation. Full resolution of variation is only guaranteed by complete de novo assembly of a genome. Here, we review approaches to genome assembly, the nature of gaps or missing sequences, and biases in the assembly process. We describe the challenges of generating a complete de novo genome assembly using current technologies and the impact that being able to perfectly sequence the genome would have on understanding human disease and evolution. Finally, we summarize recent technological advances that improve both contiguity and accuracy and emphasize the importance of complete de novo assembly as opposed to read mapping as the primary means to understanding the full range of human genetic variation.