Biology subjects

Quinlan, A. R.

Publications and source records attributed to Quinlan, A. R..

35 records · Page 2Linked to original sources

bioRxiv2020

Poxviruses capture host genes by LINE-1 retrotransposition

Horizontal gene transfer (HGT) provides a major source of genetic variation. Many viruses, including poxviruses, encode genes with crucial functions directly gained by gene transfer from hosts. The mechanism of transfer to poxvirus genomes is unknown. Using genome analysis and experimental screens of infected cells, we discovered a central role for Long Interspersed Nuclear Element-1 (LINE-1) retrotransposition in HGT to virus genomes. The process recapitulates processed pseudogene generation, but with host messenger RNA directed into virus genomes. Intriguingly, hallmark features of retrotransposition appear to favor virus adaption through rapid duplication of captured host genes on arrival. Our study reveals a previously unrecognized conduit of genetic traffic with fundamental implications for the evolution of many virus classes and their hosts. SummaryActive selfish genetic elements in infected cells aid virus adaptation by catalyzing transfer of host genes to virus genomes.

evolutionary biology↗

bioRxiv2020

CaBagE: a Cas9-based Background Elimination strategy for targeted, long-read DNA sequencing

A substantial fraction of the human genome is difficult to interrogate with short-read DNA sequencing technologies due to paralogy, complex haplotype structures, or tandem repeats. Long-read sequencing technologies, such as Oxford Nanopores MinION, enable direct measurement of complex loci without introducing many of the biases inherent to short-read methods, though they suffer from relatively lower throughput. This limitation has motivated recent efforts to develop amplification-free strategies to target and enrich loci of interest for subsequent sequencing with long reads. Here, we present CaBagE, a novel method for target enrichment that is efficient and useful for sequencing large, structurally complex targets. The CaBagE method leverages the stable binding of Cas9 to its DNA target to protect desired fragments from digestion with exonuclease. Enriched DNA fragments are then sequenced with Oxford Nanopores MinION long-read sequencing technology. Enrichment with CaBagE resulted in up to 416X coverage of target loci when tested on five genomic targets ranging from 4-20kb in length using healthy donor DNA. Four cancer gene targets were enriched in a single reaction and multiplexed on a single MinION flow cell. We further demonstrate the utility of CaBagE in two ALS patients with C9orf72 short tandem repeat expansions to produce genotype estimates commensurate with genotypes derived from repeat-primed PCR for each individual. With CaBagE there is a physical enrichment of on-target DNA in a given sample prior to sequencing. This feature allows adaptability across sequencing platforms and potential use as an enrichment strategy for applications beyond sequencing. CaBagE is a rapid enrichment method that can illuminate regions of the hidden genome underlying human disease.

genetics↗

bioRxiv2020

De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. The germline mutation rate for single nucleotide variants and factors that significantly influence this rate, such as parental age, are now well established. However, far less is known about the frequency, distribution, and features that impact de novo structural mutations. We report a large, family-based study of germline mutations, excluding aneuploidy, that affect genome structure among 572 genomes from 33 families in a multigenerational CEPH-Utah cohort and 2,363 cases of non-familial autism spectrum disorder (ASD), 1,938 unaffected siblings, and both parents (9,599 genomes in total). We find that de novo structural mutations detected by alignment-based, short-read WGS occurred at an overall rate of at least 0.160 events per genome in unaffected individuals and was significantly higher (0.206 per genome) in ASD cases. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations, and that these mechanisms likely have markedly different rates and selective pressures than those leading to point mutations.

genomics↗

bioRxiv2020

Effective variant filtering and expected candidate variant yield in studies of rare human disease

In studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we derive effective guidelines for variant filtering and report the expected number of candidates for de novo dominant and recessive modes of inheritance. The filters are applied to common attributes, including genotype quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield approximately 10 candidate SNP and INDEL variants per exome, and 19 per genome. For whole genomes, this includes an average of three de novo, ten compound-heterozygotes, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

bioinformatics↗

bioRxiv2020

Regulatory Sharing Between Estrogen Receptor α Bound Enhancers

The human genome encodes an order of magnitude more gene expression enhancers than promoters, suggesting that most genes are regulated by the combined action of multiple enhancers. We have previously shown that neighboring estrogen-responsive enhancers, which are approximately 5,000 basepairs apart, exhibit complex synergistic contributions to the production of an estrogenic transcriptional response. Here we sought to determine the molecular underpinnings of the observed enhancer cooperativity. We generated genetic deletions of individual estrogen receptor (ER) bound enhancers and found that enhancers containing full estrogen response element (ERE) motifs control ER binding at neighboring sites, while enhancers with pre-existing histone acetylation/accessibility confer a permissible chromatin environment to the neighboring enhancers. Genome engineering revealed that a cluster of two enhancers with half EREs could not compensate for the lack of a full ERE site within the cluster. In contrast, two enhancers with full EREs produced a transcriptional response greater than the wild-type locus. By swapping genomic sequences between enhancers, we found that the genomic location in which a full ERE resides strongly influences enhancer activity. Our results lead to a model in which a full ERE is required for ER recruitment, but the presence of a pre-existing active chromatin environment within an enhancer cluster is also needed in order for estrogen-driven gene regulation to occur.

genetics↗

bioRxiv2019

Somalier: rapid relatedness estimation for cancer and germline studies using efficient genome sketches

When interpreting sequencing data from multiple spatial or longitudinal biopsies, detecting sample mix-ups is essential yet more difficult than in studies of germline variation. In most genomic studies of tumors, genetic variation is frequently detected through pairwise comparisons of the tumor and a matched normal tissue from the sample donor, and in many cases, only somatic variants are reported. The disjoint genotype information that results hinders the use of existing tools that detect sample swaps solely based on genotypes of germline variants. To address this problem, we have developed somalier, which can operate directly on the alignments, so as not to require jointly-called germline variants. Instead, somalier extracts a small sketch of informative genetic variation for each sample. Sketches from hundreds of biopsies and normal tissues can then be compared in under a second. This speed also makes it useful for checking relatedness in large cohorts of germline samples. Somalier produces both text output and an interactive visual report that facilitates the detection and correction of sample swaps using multiple relatedness metrics. We introduce the tool and demonstrate its utility on a cohort of five glioma samples each with a normal, tumor, and cell-free DNA sample. Applying somalier to high-coverage sequence data from the 1000 Genomes Project also identifies several related samples. Somalier can be applied to diverse sequencing data types and genome builds, and is freely available for academic use at github.com/brentp/somalier.

bioinformatics↗

bioRxiv2019

XPRESSyourself: Enhancing and Automating the Ribosome Profiling and RNA-Seq Analysis Toolkit

Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools for these data is bleak. We introduce XPRESSyourself, an analytical toolkit that eliminates barriers and bottlenecks associated with this specialized data type by filling gaps in the computational toolset for both experts and non-experts of ribosome profiling. XPRESSyourself automates and standardizes analysis procedures, decreasing time-to-discovery and increasing reproducibility. This toolkit acts as a reference implementation of current best practices in ribosome profiling analysis. We demonstrate this toolkits performance on publicly available ribosome profiling data by rapidly identifying hypothetical mechanisms related to neurodegenerative phenotypes and neuroprotective mechanisms of the small-molecule ISRIB during acute cellular stress. XPRESSyourself brings robust, rapid analysis of ribosome-profiling data to a broad and ever-expanding audience and will lead to more reproducible and accessible measurements of translation regulation. XPRESSyourself software is perpetually open-source under the GPL-3.0 license and is hosted at https://github.com/XPRESSyourself, where users can access additional documentation and report software issues.

bioinformatics↗

bioRxiv2019

Endless Conflicts: Detecting Molecular Arms Races in Mammalian Genomes

Recurrent positive selection at the codon level is often a sign that a gene is engaged in a molecular arms race - a conflict between the genome of its host and the genome of another species over mutually exclusive access to a resource that has a direct effect on the fitness of both individuals. Detecting molecular arms races has led to a better understanding of how evolution changes the molecular interfaces of proteins when organisms compete over time, especially in the realm of host-pathogen interactions. Here, we present a method for detection of gene-level recurrent positive selection across entire genomes for a given phylogenetic group. We deploy this method on five mammalian clades - primates, mice, deer mice, dogs, and bats - to both detect novel instances of recurrent positive selection and to compare the prevalence of recurrent positive selection between clades. We analyze the frequency at which individual genes are targets of recurrent positive selection in multiple clades. We find that coincidence of selection occurs far more frequently than expected by chance, indicating that all clades experience shared selective pressures. Additionally, we highlight Polymeric Immunoglobulin Receptor (PIGR) as a gene which shares specific amino acids under recurrent positive selection in multiple clades, indicating that it has been locked in a molecular arms race for [~]100My. These data provide an in-depth comparison of recurrent positive selection across the mammalian phylogeny, and highlights of the power of comparative evolutionary approaches to generate specific hypotheses about the molecular interactions of rapidly evolving genes.

evolutionary biology↗

bioRxiv2019

Large, three-generation CEPH families reveal post-zygotic mosaicism and variability in germline mutation accumulation

The number of de novo mutations (DNMs) found in an offsprings genome is known to increase with both paternal and maternal age. But does the rate of mutation accumulation in parental gametes differ across families? To answer this question, we analyzed DNMs in 33 large, three-generation families collected in Utah by the Centre dEtude du Polymorphisme Humain (CEPH) consortium. We observed significant variability in parental age effects on DNM counts across families, ranging from 0.24 to 3.33 additional DNMs per year. Using up to 14 grandchildren in these families, we find that 3% of DNMs originated following primordial germ cell specification (PGCS) in a parent, and differ from non-mosaic germline DNMs in their mutational spectra. We also identify a median of 3 gonosomal mutations per sample in the F1 generation, which, along with post-PGCS DNMs, occur at equivalent frequencies on the paternal and maternal haplotypes. These results demonstrate that the rate of germline mutation accumulation varies among families with similar ancestry, and confirm that parental mosaicism is a substantial source of de novo mutations in children. Data and code availabilityCode used for statistical analysis and figure generation has been deposited on GitHub as a collection of annotated Jupyter Notebooks: https://github.com/quinlan-lab/ceph-dnm-manuscript. Data files containing germline de novo mutations, as well as the gonosomal and post-primordial germ cell specification (PGCS) mosaic mutations, are included with these Notebooks. To mitigate compatibility/version issues, we have also made all notebooks available in a Binder environment, accessible at the above GitHub repository.

genetics↗

bioRxiv2018

duphold: scalalable, depth-based annotation and curation of high-confidence structural variant calls.

Most structural variant detection tools use clusters of discordant read-pair and split-read alignments to identify variants, yet do not integrate depth of sequence coverage as an additional means to support or refute putative events. Here, we present duphold, as a new method to efficiently annotate structural variant calls with sequence depth information that can add (or remove) confidence to SV predicted to affect copy number. It indicates not only the change in depth across the event, but also the presence of a rapid change in depth relative to the regions surrounding the breakpoints. It uses a unique algorithm that allows the run time to be nearly independent of the number of variants. This performance is important for large, jointly-called projects with many samples, each of which must be evaluated at thousands of sites. We show that filtering on duphold annotations can greatly improve the specificity of deletion calls and that its annotations match visual inspection. Duphold can annotate structural variant predictions made from both short-read and long-read data. It is available under the MIT license at: https://github.com/brentp/duphold.

bioinformatics↗

bioRxiv2018

Co-expression patterns define epigenetic regulators associated with neurological dysfunction

Coding variants in genes encoding for epigenetic regulators are an emerging cause of neurological dysfunction and cancer. However, a systematic effort to identify disease candidates within the human epigenetic machinery (EM) has not been performed, and it is unclear whether features exist that distinguish between variation-intolerant and variation-tolerant EM genes, and between EM genes associated with neurological dysfunction versus cancer. Here, we rigorously define a set of 295 human genes with a direct role in epigenetic regulation (writers, erasers, remodelers, readers). Systematic exploration of these genes reveals that while individual enzymatic functions are always mutually exclusive, readers often also exhibit enzymatic activity as well (dual function EM genes). We find that the majority of EM genes are very intolerant to loss-of-function variation, even when compared to the dosage sensitive group of transcription factors. Using this strategy, we identify 103 novel EM disease candidates. We show that the intolerance to loss-of-function variation is driven by the protein domains encoding the epigenetic function, strongly suggesting that disease is caused by a perturbed chromatin state. Unexpectedly, we also describe a large subset of EM genes that are co-expressed within multiple tissues. This subset is almost exclusively populated by extremely variation-intolerant EM genes, and shows enrichment for dual function EM genes. It is also highly enriched for genes associated with neurological dysfunction, even when accounting for dosage sensitivity, but not for cancer-associated EM genes. These findings prioritize novel disease candidate EM genes, and suggest that the co-expression itself may play a functional role in normal neurological homeostasis.

genomics↗

bioRxiv2018

SV-plaudit: A cloud-based framework for manually curating thousands of structural variants

SV-plaudit is a framework for rapidly curating structural variant (SVs) predictions. For each SV, we generate an image that visualizes the coverage and alignment signals from a set of samples. Images are uploaded to our cloud framework where users assess the quality of each image using a client-side web application. Reports can then be generated as a tab-delimited file or annotated VCF. As a proof of principle, nine researchers collaborated for one hour to evaluate 1,350 SVs each. We anticipate that SV-plaudit will become a standard step in variant calling pipelines and the crowd-sourced curation of other biological results.\n\nCode available at https://github.com/jbelyeu/SV-plaudit\n\nDemonstration video available at https://www.youtube.com/watch?v=ono8kHMKxDs

bioinformatics↗

bioRxiv2018

hts-nim: scripting high-performance genomic analyses

MotivationExtracting biological insight from genomic data inevitably requires custom software. In many cases, this is accomplished with scripting languages, owing to their accessibility and brevity. Unfortunately, the ease of scripting languages typically comes at a substantial performance cost that is especially acute with the scale of modern genomics datasets.\n\nResultsWe present hts-nim, a high-performance library written in the Nim programming language that provides a simple, scripting-like syntax without sacrificing performance.\n\nAvailabilityhts-nim is available at https://github.com/brentp/hts-nim and the example tools are at https://github.com/brentp/hts-nim-tools both under the MIT license.\n\nContactbpederse@gmail.com\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2018

Long read sequencing reveals poxvirus evolution through rapid homogenization of gene arrays

Large DNA viruses rapidly evolve to defeat host defenses. Poxvirus adaptation can involve combinations of recombination-driven gene copy number variation and beneficial single nucleotide variants (SNVs) at the same locus, yet how these distinct mechanisms of genetic diversification might simultaneously facilitate adaptation to immune blocks is unknown. We performed experimental evolution with a vaccinia virus population harboring a SNV in a gene actively undergoing copy number amplification. Comparisons of virus genomes using the Oxford Nanopore Technologies sequencing platform allowed us to phase SNVs within large gene copy arrays for the first time, and uncovered a mechanism of adaptive SNV homogenization reminiscent of gene conversion, which is actively driven by selection. Our work reveals a new mechanism for the fluid gain of beneficial mutations in genetic regions undergoing active recombination in viruses, and illustrates the value of long read sequencing technologies for investigating complex genome dynamics in diverse biological systems.

evolutionary biology↗

bioRxiv2017

A map of constrained coding regions in the human genome.

Deep catalogs of genetic variation collected from many thousands of humans enable the detection of intraspecies constraint by revealing coding regions with a scarcity of variation. While existing techniques summarize constraint for entire genes, single metrics cannot capture the fine-scale variability in constraint within each protein-coding gene. To provide greater resolution, we have created a detailed map of constrained coding regions (CCRs) in the human genome by leveraging coding variation observed among 123,136 humans from the Genome Aggregation Database (gnomAD). The most constrained coding regions in our map are enriched for both pathogenic variants in ClinVar and de novo mutations underlying developmental disorders. CCRs also reveal protein domain families under high constraint, suggest unannotated or incomplete protein domains, and facilitate the prioritization of previously unseen variation in studies of disease. Finally, a subset of CCRs with the highest constraint likely exist within genes that cause yet unobserved human phenotypes owing to strong purifying selection.

genomics↗

bioRxiv2017

GIGGLE: a search engine for large-scale integrated genome analysis

GIGGLE is a genomics search engine that identifies and ranks the significance of shared genomic loci between query features and thousands of genome interval files. GIGGLE scales to billions of intervals, is faster (+1,000X) than existing methods, and its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEX by facilitating data integration and hypothesis generation. GIGGLE is available at https://github.com/ryanlayer/giggle.

bioinformatics↗

bioRxiv2017

Indexcov: fast coverage quality control for whole-genome sequencing

The BAM1 and CRAM2 formats provide a supplementary linear index that facilitates rapid access to sequence alignments in arbitrary genomic regions. Comparing consecutive entries in a BAM or CRAM index allows one to infer the number of alignment records per genomic region for use as an effective proxy of sequence depth in each genomic region. Based on these properties, we have developed indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at: https://github.com/brentp/goleft under the MIT license.

genomics↗