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Schatz, M. C.

Publications and source records attributed to Schatz, M. C..

At least 37 records · Page 2Linked to original sources

Complete sequence of a 641-kb insertion of mitochondrial DNA in the Arabidopsis thaliana nuclear genome

Intracellular transfers of mitochondrial DNA continue to shape nuclear genomes. Chromosome 2 of the model plant Arabidopsis thaliana contains one of the largest known nuclear insertions of mitochondrial DNA (numts). Estimated at over 600 kb in size, this numt is larger than the entire Arabidopsis mitochondrial genome. The primary Arabidopsis nuclear reference genome contains less than half of the numt because of its structural complexity and repetitiveness. Recent datasets generated with improved long-read sequencing technologies (PacBio HiFi) provide an opportunity to finally determine the accurate sequence and structure of this numt. We performed a de novo assembly using sequencing data from recent initiatives to span the Arabidopsis centromeres, producing a gap-free sequence of the Chromosome 2 numt, which is 641-kb in length and has 99.933% nucleotide sequence identity with the actual mitochondrial genome. The numt assembly is consistent with the repetitive structure previously predicted from fiber-based fluorescent in situ hybridization. Nanopore sequencing data indicate that the numt has high levels of cytosine methylation, helping to explain its biased spectrum of nucleotide sequence divergence and supporting previous inferences that it is transcriptionally inactive. The original numt insertion appears to have involved multiple mitochondrial DNA copies with alternative structures that subsequently underwent an additional duplication event within the nuclear genome. This work provides insights into numt evolution, addresses one of the last unresolved regions of the Arabidopsis reference genome, and represents a resource for distinguishing between highly similar numt and mitochondrial sequences in studies of transcription, epigenetic modifications, and de novo mutations. Significance statementNuclear genomes are riddled with insertions of mitochondrial DNA. The model plant Arabidopsis has one of largest of these insertions ever identified, which at over 600-kb in size represents one of the last unresolved regions in the Arabidopsis genome more than 20 years after the insertion was first identified. This study reports the complete sequence of this region, providing insights into the origins and subsequent evolution of the mitochondrial DNA insertion and a resource for distinguishing between the actual mitochondrial genome and this nuclear copy in functional studies.

genomics↗

Automated assembly scaffolding elevates a new tomato system for high-throughput genome editing

Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a rapid-cycling genotype that we developed to accelerate functional genomics and genome editing. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

plant biology↗

Sketching and sampling approaches for fast and accurate long read classification

BackgroundIn modern sequencing experiments, quickly and accurately identifying the sources of the reads is a crucial need. In metagenomics, where each read comes from one of potentially many members of a community, it can be important to identify the exact species the read is from. In other settings, it is important to distinguish which reads are from the targeted sample and which are from potential contaminants. In both cases, identification of the correct source of a read enables further investigation of relevant reads, while minimizing wasted work. This task is particularly challenging for long reads, which can have a substantial error rate that obscures the origins of each read. ResultsExisting tools for the read classification problem are often alignment or index-based, but such methods can have large time and/or space overheads. In this work, we investigate the effectiveness of several sampling and sketching-based approaches for read classification. In these approaches, a chosen sampling or sketching algorithm is used to generate a reduced representation (a "screen") of potential source genomes for a query readset before reads are streamed in and compared against this screen. Using a query reads similarity to the elements of the screen, the methods predict the source of the read. Such an approach requires limited pre-processing, stores and works with only a subset of the input data, and is able to perform classification with a high degree of accuracy. ConclusionsThe sampling and sketching approaches investigated include uniform sampling, methods based on MinHash and its weighted and order variants, a minimizer-based technique, and a novel clustering-based sketching approach. We demonstrate the effectiveness of these techniques both in identifying the source microbial genomes for reads from a metagenomic long read sequencing experiment, and in distinguishing between long reads from organisms of interest and potential contaminant reads. We then compare these approaches to existing alignment, index and sketching-based tools for read classification, and demonstrate how such a method is a viable alternative for determining the source of query reads. Finally, we present a reference implementation of these approaches at https://github.com/arun96/sketching.

bioinformatics↗

A complete reference genome improves analysis of human genetic variation

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 Mbp of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome to clinical and functional study. Here we demonstrate how the new reference universally improves read mapping and variant calling for 3,202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of novel variants per sample--a new frontier for evolutionary and biomedical discovery. Simultaneously, the new reference eliminates tens of thousands of spurious variants per sample, including up to 12-fold reduction of false positives in 269 medically relevant genes. The vast improvement in variant discovery coupled with population and functional genomic resources position T2T-CHM13 to replace GRCh38 as the prevailing reference for human genetics. One Sentence SummaryThe T2T-CHM13 reference genome universally improves the analysis of human genetic variation.

genomics↗

The genetic and epigenetic landscape of the Arabidopsis centromeres

Centromeres attach chromosomes to spindle microtubules during cell division and, despite this conserved role, show paradoxically rapid evolution and are typified by complex repeats. We used ultra-long-read sequencing to generate the Col-CEN Arabidopsis thaliana genome assembly that resolves all five centromeres. The centromeres consist of megabase-scale tandemly repeated satellite arrays, which support high CENH3 occupancy and are densely DNA methylated, with satellite variants private to each chromosome. CENH3 preferentially occupies satellites with least divergence and greatest higher-order repetition. The centromeres are invaded by ATHILA retrotransposons, which disrupt genetic and epigenetic organization of the centromeres. Crossover recombination is suppressed within the centromeres, yet low levels of meiotic DSBs occur that are regulated by DNA methylation. We propose that Arabidopsis centromeres are evolving via cycles of satellite homogenization and retrotransposon-driven diversification. One-sentence summaryLong read sequencing and assembly of the Arabidopsis centromeres reveals their genetic and epigenetic topography.

genomics↗

Jasmine: Population-scale structural variant comparison and analysis

The increasing availability of long-reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine (https://github.com/mkirsche/Jasmine), a fast and accurate method for SV refinement, comparison, and population analysis. Using an SV proximity graph, Jasmine outperforms five widely-used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than five-fold, and reveals a set of high confidence de novo SVs confirmed by multiple long-read technologies. We also present a harmonized callset of 205,192 SVs from 31 samples of diverse ancestry sequenced with long reads. We genotype these SVs in 444 short read samples from the 1000 Genomes Project with both DNA and RNA sequencing data and assess their widespread impact on gene expression, including within several medically relevant genes.

genomics↗

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

The traditional model of genomic data analysis - downloading data from centralized warehouses for analysis with local computing resources - is increasingly unsustainable. Not only are transfers slow and cost prohibitive, but this approach also leads to redundant and siloed compute infrastructure that makes it difficult to ensure security and compliance of protected data. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) inverts this model, providing a unified cloud computing environment for data storage, management, and analysis. AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides scalable, shared computing resources that can be acquired by researchers as needed. This presents many new opportunities for collaboration and data sharing that will ultimately lead to scientific discoveries at scales not previously possible.

bioinformatics↗

Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy

Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models. Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2s non-structural protein 3 (Nsp3). We also produced models of SARS-CoV2s spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor (MOG) and dipeptidyl peptidase-4 (DPP4). The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org and usegalaxy.eu.

genomics↗

Local adaptation and archaic introgression shape global diversity at human structural variant loci

Large genomic insertions, deletions, and inversions are a potent source of functional and fitness-altering variation, but are challenging to resolve with short-read DNA sequencing alone. While recent long-read sequencing technologies have greatly expanded the catalog of structural variants (SVs), their costs have so far precluded their application at population scales. Given these limitations, the role of SVs in human adaptation remains poorly characterized. Here, we used a graph-based approach to genotype 107,866 long-read-discovered SVs in short-read sequencing data from diverse human populations. We then applied an admixture-aware method to scan these SVs for patterns of population-specific frequency differentiation--a signature of local adaptation. We identified 220 SVs exhibiting extreme frequency differentiation, including several SVs that were among the lead variants at their corresponding loci. The top two signatures traced to separate insertion and deletion polymorphisms at the immunoglobulin heavy chain locus, together tagging a 325 Kbp haplotype that swept to high frequency and was subsequently fragmented by recombination. Alleles defining this haplotype are nearly fixed (60-95%) in certain Southeast Asian populations, but are rare or absent from other global populations composing the 1000 Genomes Project. Further investigation revealed that the haplotype closely matches with sequences observed in two of three high-coverage Neanderthal genomes, providing strong evidence of a Neanderthal-introgressed origin. This extraordinary episode of positive selection, which we infer to have occurred between 1700 and 8400 years ago, corroborates the role of immune-related genes as prominent targets of adaptive archaic introgression. Our study demonstrates how combining recent advances in genome sequencing, genotyping algorithms, and population genetic methods can reveal signatures of key evolutionary events that remained hidden within poorly resolved regions of the genome.

evolutionary biology↗

High resolution copy number inference in cancer using short-molecule nanopore sequencing

Genome copy number is an important source of genetic variation in health and disease. In cancer, clinically actionable Copy Number Alterations (CNAs) can be inferred from short-read sequencing data, enabling genomics-based precision oncology. Emerging Nanopore sequencing technologies offer the potential for broader clinical utility, for example in smaller hospitals, due to lower instrument cost, higher portability, and ease of use. Nonetheless, Nanopore sequencing devices are limited in terms of the number of retrievable sequencing reads/molecules compared to short-read sequencing platforms. This represents a challenge for applications that require high read counts such as CNA inference. To address this limitation, we targeted the sequencing of short-length DNA molecules loaded at optimized concentration in an effort to increase sequence read/molecule yield from a single nanopore run. We show that sequencing short DNA molecules reproducibly returns high read counts and allows high quality CNA inference. We demonstrate the clinical relevance of this approach by accurately inferring CNAs in acute myeloid leukemia samples. The data shows that, compared to traditional approaches such as chromosome analysis/cytogenetics, short molecule nanopore sequencing returns more sensitive, accurate copy number information in a cost effective and expeditious manner, including for multiplex samples. Our results provide a framework for the sequencing of relatively short DNA molecules on nanopore devices with applications in research and medicine, that include but are not limited to, CNAs.

genomics↗

LongTron: Automated Analysis of Long Read Spliced Alignment Accuracy

MotivationLong read sequencing has increased the accuracy and completeness of assemblies of various organisms genomes in recent months. Similarly, spliced alignments of long read RNA sequencing hold the promise of delivering much longer transcripts of existing and novel isoforms in known genes without the need for error-prone transcript assemblies from short reads. However, low coverage and high-error rates potentially hamper the widespread adoption of long-read spliced alignments in annotation updates and isoform-level expression quantifications. ResultsAddressing these issues, we first develop a simulation of error modes for both Oxford Nanopore and PacBio CCS spliced-alignments. Based on this we train a Random Forest classifier to assign new long-read alignments to one of two error categories, a novel category, or label them as non-error. We use this classifier to label reads from the spliced-alignments of the popular aligner minimap2, run on three long read sequencing datasets, including NA12878 from Oxford Nanopore and PacBio CCS, as well as a PacBio SKBR3 cancer cell line. Finally, we compare the intron chains of the three long read alignments against individual splice sites, short read assemblies, and the output from the FLAIR pipeline on the same samples. Our results demonstrate a substantial lack of precision in determining exact splice sites for long reads during alignment on both platforms while showing some benefit from postprocessing. This work motivates the need for both better aligners and additional post-alignment processing to adjust incorrectly called putative splice-sites and clarify novel transcripts support. Availability and implementationSource code for the random forest implemented in python is available at https://github.com/schatzlab/LongTron under the MIT license. The modified version of GffCompare used to construct Table 3 and related is here: https://github.com/ChristopherWilks/gffcompare/releases/tag/0.11.2LT O_TBL View this table: org.highwire.dtl.DTLVardef@117255borg.highwire.dtl.DTLVardef@95a815org.highwire.dtl.DTLVardef@14e21faorg.highwire.dtl.DTLVardef@98e040org.highwire.dtl.DTLVardef@aab93e_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 3.C_FLOATNO O_TABLECAPTIONIsoform comparison table, using gene models from Gencode V29, plus the isoforms from all the union of annotations; both exact and fuzz comparisons of the set of long-read derived isoforms which 1) match in number of introns or 2) are contained or contain a reference isoform. Percentages use the "Total Intron Chains" as the denominator for the row. C_TABLECAPTION C_TBL Supplementary InformationSupplementary notes and figures are available online.

bioinformatics↗

Unraveling molecular mechanisms of immunity and cancer-resistance using the genomes of the Neotropical bats Artibeus jamaicensis and Pteronotus mesoamericanus

Bats are exceptional among mammals for their powered flight, extended lifespans, and robust immune systems. To investigate the genomic underpinnings of unique bat adaptations, we sequenced the genomes of the Jamaican fruit bat (Artibeus jamaicensis) and the Mesoamerican mustached bat (Pteronotus mesoamericanus) and compared them to a diverse collection of 13 additional bat species together with other mammals. We used the Oxford Nanopore Technologies long-read platform to generate highly complete assemblies (N50: 28-29Mb) and facilitate analysis of complex genomic regions containing duplicated genes. Using gene family size analysis, we found that the type I interferon locus was contracted by eight genes in the most recent common ancestor (MRCA) of bats, shifting the proportion of interferon-{omega} to interferon- and making interferon-{omega} the most common type I interferon in bats. Antiviral genes stimulated by type I interferons were also rapidly evolving, with interferon-induced transmembrane genes experiencing a lineage-specific duplication and strong positive selection in the gene IFIT2. Moreover, the lineage of phyllostomid bats showed an unprecedented expansion of PRDM9, a recombination-related gene also involved in infection responses, raising the possibility that this gene contributes to bat antiviral defenses. These modifications in the bat innate immune system may be important adaptations allowing them to harbor viruses asymptomatically. We additionally found evidence of positive selection on the branch leading to the MRCA of bats acting on 33 tumor suppressors and six DNA repair genes, which may contribute to the low cancer rates and longevity observed across bats. These new genomic resources enable insights into the extraordinary adaptations of bats, with implications for mammalian evolutionary studies and public health.

genomics↗

SNPC-1.3 is a sex-specific transcription factor that drives male piRNA expression in C. elegans

Piwi-interacting RNAs (piRNAs) play essential roles in silencing repetitive elements to promote fertility in metazoans. Studies in worms, flies, and mammals reveal that piRNAs are expressed in a sex-specific manner. However, the mechanisms underlying this sex-specific regulation are unknown. Here we identify SNPC-1.3, a variant of a conserved subunit of the snRNA activating protein complex, as a male-specific piRNA transcription factor in C. elegans. Binding of SNPC-1.3 at male piRNA loci drives spermatogenic piRNA transcription and requires the core piRNA transcription factor SNPC-4. Loss of snpc-1.3 leads to depletion of male piRNAs and defects in male-dependent fertility. Furthermore, TRA-1, a master regulator of sex determination, binds to the snpc-1.3 promoter and represses its expression during oogenesis. Loss of TRA-1 targeting causes ectopic expression of snpc-1.3 and male piRNAs during oogenesis. Thus, sexual dimorphic regulation of snpc-1.3 coordinates male and female piRNA expression during germline development.

developmental biology↗

The human Origin Recognition Complex is essential for pre-RC assembly, mitosis and maintenance of nuclear structure.

The Origin Recognition Complex (ORC) cooperates with CDC6, MCM2-7, and CDT1 to form pre- RC complexes at origins of DNA replication. Here we report tiling-sgRNA CRISPR screens that show that each subunit of ORC and CDC6 are essential in human cells. Using an auxin-inducible degradation system, stable cell lines were created that ablate ORC2 rapidly, revealing multiple cell division cycle phenotypes. The primary defect in the absence of ORC2 was cells encountering difficulty in initiating DNA replication or progressing through the cell division cycle due to reduced MCM2-7 loading onto chromatin in G1 phase. The nuclei of ORC2 deficient cells were also large, with decompacted heterochromatin. Some ORC2 deficient cells that completed DNA replication entered into, but never exited mitosis. ORC1 knockout cells also demonstrated extremely slow cell proliferation and abnormal cell and nuclear morphology. Thus, ORC proteins and CDC6 are indispensable for normal cellular proliferation and contribute to nuclear organization.

molecular biology↗

SVCollector: Optimized sample selection for cost-efficient long-read population sequencing

An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g. microarrays, exome capture, short-read WGS), from which a few individuals are selected for resequencing using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically been focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. To address this goal, SVCollector (https://github.com/fritzsedlazeck/SVCollector) identifies the optimal subset of individuals for resequencing. SVCollector analyzes a population-level VCF file from a low resolution genotyping study. It then computes a ranked list of samples that maximizes the total number of variants present from a subset of a given size. To solve this optimization problem, SVCollector implements a fast greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3K Rice Genomes Project and show the rankings it computes are more representative than widely used naive strategies. Notably, we show that when selecting an optimal subset of 100 samples in these two cohorts, SV-Collector identifies individuals from every subpopulation while naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts of different sizes selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.

bioinformatics↗

A plasmid locus associated with Klebsiella clinical infections encodes a microbiome-dependent gut fitness factor

Introductory paragraphGut colonization by the pathogen Klebsiella pneumoniae (Kp) is consistently associated with subsequent Kp disease1-5, and patients are predominantly infected with their colonizing strain1,2. However, colonizing strains likely vary in their potential to cause infection. We previously identified the plasmid-encoded tellurium resistance (ter) operon as highly associated with infection when compared to asymptomatic colonization in hospitalized patients1. The ter operon bestows resistance to the toxic compound tellurite oxide (TeO3-2), but this is unlikely to be its physiological function, as tellurium and TeO3-2 are exceedingly rare. Here we show that terC is necessary and terZABCDEF is sufficient for phenotypic TeO3-2 resistance. Next, we demonstrate that ter is encoded on a diverse group of plasmids without known plasmid-encoded virulence genes, suggesting an independent role in infection. Finally, our studies indicate that ter is a gut fitness factor, and its fitness advantage is conferred only when specific gut microbiota constituents are present. Collectively, these data reveal the Kp ter operon that is highly associated with human infection likely acts early in pathogenesis as a horizontally-transferrable fitness factor promoting robust gut colonization in the presence of the indigenous microbiota.

microbiology↗

iGenomics: Comprehensive DNA Sequence Analysis on your Smartphone

Following the miniaturization of integrated circuitry and other computer hardware over the past several decades, DNA sequencing is following a similar path. Leading this trend is the Oxford Nanopore sequencing platform, which currently offers the hand-held MinION instrument and even smaller instruments on the near horizon. This technology has been used in several important applications, including the analysis of genomes of major pathogens in remote stations around the world. However, despite the simplicity of the sequencer, an equally simple and portable analysis platform is not yet available. iGenomics is the first comprehensive mobile genome analysis application, with capabilities to align reads, call variants, and visualize the results entirely on an iOS device. Implemented in Objective-C using the FM-index, banded dynamic programming, and other high-performance bioinformatics techniques, iGenomics is optimized to run in a mobile environment. We benchmark iGenomics using a variety of real and simulated Nanopore sequencing datasets and show that iGenomics has performance comparable to the popular BWA-MEM/Samtools/IGV suite, without needing a laptop or server cluster. iGenomics is available open-source (https://github.com/stuckinaboot/iGenomics) and for free on Apples App Store (https://apps.apple.com/us/app/igenomics-mobile-dna-analysis/id1495719841).

bioinformatics↗

Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED

ReadUntil sequencing allows nanopore devices to selectively eject individual reads from the pore in real-time. This could enable purely computational targeted sequencing, however most mapping methods require basecalling, which is computationally intensive. Here we present UNCALLED (github.com/skovaka/UNCALLED), an open-source mapper that rapidly matches streaming nanopore current signals to a reference sequence. UNCALLED probabilistically considers k-mers that the signal could represent, and then prunes the candidates based on the reference encoded within an FM-index. We used UNCALLED to deplete sequencing of known bacterial genomes within a metagenomics community, enriching the remaining species by 4.46 fold. UNCALLED also enriched 148 human genes associated with hereditary cancers to 29.6x coverage using one MinION flowcell, enabling accurate detection of SNPs, indels, structural variants (SVs), and methylation in these genes. Twice as many SVs were detected compared to 50x coverage Illumina sequencing, all verified by whole-genome nanopore and PacBio HiFi sequencing.

genomics↗