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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 757 records · Page 42Linked to original sources
bioRxiv2018

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.

genomics↗
bioRxiv2018

DNA barcodes for rapid, whole genome, single-molecule analyses

We report an approach for visualizing DNA sequence and using these DNA barcodes to search complex mixtures of genomic material for DNA molecules of interest. We demonstrate three applications of this methodology; by identifying specific molecules of interest from a dataset containing gigabasepairs of genome; by straightforward strain-typing of bacteria from such a dataset and, finally, by locating infecting virus molecules in a background of human genomic material. DNA barcodes enable quantitative understanding of complex genome mixtures, on a large scale. As a result of the dense fluorescent labelling of the DNA, individual barcodes of the order 40 kilobase pairs in length can be reliably identified. This means DNA can be prepared for imaging using standard handling and purification techniques. The recorded dataset provides stable physical and electronic records of the total genomic content of a sample that can be readily searched for a molecule or region of interest.

genomics↗
bioRxiv2014

Efficient synergistic single-cell genome assembly

As the vast majority of all microbes are unculturable, single-cell sequencing has become a significant method to gain insight into microbial physiology. Single-cell sequencing methods, currently powered by multiple displacement genome amplification (MDA), have passed important milestones such as finishing and closing the genome of a prokaryote. However, the quality and reliability of genome assemblies from single cells are still unsatisfactory due to uneven coverage depth and the absence of scattered chunks of the genome in the final collection of reads caused by MDA bias. In this work, our new algorithm Hybrid De novo Assembler (HyDA) demonstrates the power of co-assembly of multiple single-cell genomic data sets through significant improvement of the assembly quality in terms of predicted functional elements and length statistics. Co-assemblies contain significantly more base pairs and protein coding genes, cover more subsystems, and consist of longer contigs compared to individual assemblies by the same algorithm as well as state-of-the-art single-cell assemblers SPAdes and IDBA-UD. Hybrid De novo Assembler (HyDA) is also able to avoid chimeric assemblies by detecting and separating shared and exclusive pieces of sequence for input data sets. By replacing one deep single-cell sequencing experiment with a few single-cell sequencing experiments of lower depth, the co-assembly method can hedge against the risk of failure and loss of the sample, without significantly increasing sequencing cost. Application of the single-cell coassembler HyDA to the study of three uncultured members of an alkane-degrading methanogenic community validated the usefulness of the co-assembly concept.

Bioinformatics↗
bioRxiv2014

HGTector: An automated method facilitating genome-wide discovery of putative horizontal gene transfers

A new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has low requirements for computational resources, and is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

Bioinformatics↗
bioRxiv2014

Background selection as baseline for nucleotide variation across the Drosophila genome

The constant removal of deleterious mutations by natural selection causes a reduction in neutral diversity and efficacy of selection at genetically linked sites (a process called Background Selection, BGS). Population genetic studies, however, often ignore BGS effects when investigating demographic events or the presence of other types of selection. To obtain a more realistic evolutionary expectation that incorporates the unavoidable consequences of deleterious mutations, we generated high-resolution landscapes of variation across the Drosophila melanogaster genome under a BGS scenario independent of polymorphism data. We find that BGS plays a significant role in shaping levels of variation across the entire genome, including long introns and intergenic regions distant from annotated genes. We also find that a very large percentage of the observed variation in diversity across autosomes can be explained by BGS alone, up to 70% across individual chromosome arms, thus indicating that BGS predictions can be used as baseline to infer additional types of selection and demographic events. This approach allows detecting several outlier regions with signal of recent adaptive events and selective sweeps. The use of a BGS baseline, however, is particularly appropriate to investigate the presence of balancing selection and our study exposes numerous genomic regions with the predicted signature of higher polymorphism than expected when a BGS context is taken into account. Importantly, we show that these conclusions are robust to the mutation and selection parameters of the BGS model. Finally, analyses of protein evolution together with previous comparisons of genetic maps between Drosophila species, suggest temporally variable recombination landscapes and thus, local BGS effects that may differ between extant and past phases. Because genome-wide BGS and temporal changes in linkage effects can skew approaches to estimate demographic and selective events, future analyses should incorporate BGS predictions and capture local recombination variation across genomes and along lineages.

Evolutionary Biology↗
bioRxiv2014

High-throughput functional annotation of influenza A virus genome at single-nucleotide resolution

A novel genome-wide genetics platform is presented in this study, which permits functional interrogation of all point mutations across a viral genome in parallel. Here we generated the first fitness profile of individual point mutations across the influenza virus genome. Critical residues on the viral genome were systematically identified, which provided a collection of subdomain data informative for structure-function studies and for effective rational drug and vaccine design. Our data was consistent with known, well-characterized structural features. In addition, we have achieved a validation rate of 68% for severely attenuated mutations and 94% for neutral mutations. The approach described in this study is applicable to other viral or microbial genomes where a means of genetic manipulation is available.

Systems Biology↗
bioRxiv2014

Establishment of regions of genomic activity during the Drosophila maternal to zygotic transition

A conspicuous feature of early animal development is the lack of transcription from the embryonic genome, and it typically takes several hours to several days (depending on the species) until widespread transcription of the embryonic genome begins. Although this transition is ubiquitous, relatively little is known about how the shift from a transcriptionally quiescent to transcriptionally active genome is controlled. We describe here the genome-wide distributions and temporal dynamics of nucleosomes and post-translational histone modifications through the maternal-to-zygotic transition in embryos of the pomace fly Drosophila melanogaster. At mitotic cycle 8, when few zygotic genes are being transcribed, embryonic chromatin is in a relatively simple state: there are few nucleosome free regions, undetectable levels of the histone methylation marks characteristic of mature chromatin, and low levels of histone acetylation at a relatively small number of loci. Histone acetylation increases by cycle 11, but it is not until cycle 13 that nucleosome free regions and domains of histone methylation become widespread. Early histone acetylation is strongly associated with regions that we have previously shown are bound in early embryos by the maternally deposited transcription factor Zelda. Most of these Zelda-bound regions are destined to be enhancers or promoters active during mitotic cycle 14, and our data demonstrate that they are biochemically distinct long before they become active, raising the possibility that Zelda triggers a cascade of events, including the accumulation of specific histone modifications, that plays a role in the subsequent activation of these sequences. Many of these Zelda-associated active regions occur in larger domains that we find strongly enriched for histone marks characteristic of Polycomb-mediated repression, suggesting a dynamic balance between Zelda activation and Polycomb repression. Collectively, these data paint a complex picture of a genome in transition from a quiescent to an active state, and highlight the role of Zelda in mediating this transition.

Developmental Biology↗
bioRxiv2014

Population genomic analysis uncovers African and European admixture in Drosophila melanogaster populations from the southeastern United States and Caribbean Islands

Genome sequences from North American Drosophila melanogaster populations have become available to the scientific community. Deciphering the underlying population structure of these resources is crucial to make the most of these population genomic resources. Accepted models of North American colonization generally purport that several hundred years ago, flies from Africa and Europe were transported to the east coast United States and the Caribbean Islands respectively and thus current east coast US and Caribbean populations are an admixture of African and European ancestry. Theses models have been constructed based on phenotypes and limited genetic data. In our study, we have sequenced individual whole genomes of flies from populations in the southeast US and Caribbean Islands and examined these populations in conjunction with population sequences from Winters, CA, (USA); Raleigh, NC (USA); Cameroon (Africa); and Montpellier (France) to uncover the underlying population structure of North American populations. We find that west coast US populations are most like European populations likely reflecting a rapid westward expansion upon first settlements into North America. We also find genomic evidence of African and European admixture in east coast US and Caribbean populations, with a clinal pattern of decreasing proportions of African ancestry with higher latitude further supporting the proposed demographic model of Caribbean flies being established by African ancestors. Our genomic analysis of Caribbean flies is the first study that exposes the source of previously reported novel African alleles found in east coast US populations.

Evolutionary Biology↗
bioRxiv2014

Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations

Recent cancer genome studies have identified numerous genomic alterations in cancer genomes. It is hypothesized that only a fraction of these genomic alterations drive the progression of cancer - often called driver mutations. Current sample sizes for cancer studies, often in the hundreds, are sufficient to detect pivotal drivers solely based on their high frequency of alterations. In cases where the alterations for a single function are distributed among multiple genes of a common pathway, however, single gene alteration frequencies might not be statistically significant. In such cases, we expect to observe that most samples are altered in only one of those alternative genes because additional alterations would not convey an additional selective advantage to the tumor. This leads to a mutual exclusion pattern of alterations, that can be exploited to identify these groups.\n\nWe developed a novel method for the identification of sets of mutually exclusive gene alterations in a signaling network. We scan the groups of genes with a common downstream effect, using a mutual exclusivity criterion that makes sure that each gene in the group significantly contributes to the mutual exclusivity pattern. We have tested the method on all available TCGA cancer genomics datasets, and detected multiple previously unreported alterations that show significant mutual exclusivity and are likely to be driver events.

Cancer Biology↗
bioRxiv2014

Quantification of GC-biased gene conversion in the human genome

Many lines of evidence indicate GC-biased gene conversion (gBGC) has a major impact on the evolution of mammalian genomes. However, up to now, this process had not been properly quantified. In principle, the strength of gBGC can be measured from the analysis of derived allele frequency spectra. However, this approach is sensitive to a number of confounding factors. In particular, we show by simulations that the inference is pervasively affected by polymorphism polarization errors, especially at hypermutable sites, and spatial heterogeneity in gBGC strength. Here we propose a new method to quantify gBGC from DAF spectra, incorporating polarization errors and taking spatial heterogeneity into account. This method is very general in that it does not require any prior knowledge about the source of polarization errors and also provides information about mutation patterns. We apply this approach to human polymorphism data from the 1000 genomes project. We show that the strength of gBGC does not differ between hypermutable CpG sites and non-CpG sites, suggesting that in humans gBGC is not caused by the base-excision repair machinery. We further find that the impact of gBGC is concentrated primarily within recombination hotspots: genome-wide, the strength of gBGC is in the nearly neutral area, but 2% of the human genome is subject to strong gBGC, with population-scaled gBGC coefficients above 5. Given that the location of recombination hotspots evolves very rapidly, our analysis predicts that in the long term, a large fraction of the genome is affected by short episodes of strong gBGC.

Evolutionary Biology↗
bioRxiv2014

Analyses of Eurasian wild and domestic pig genomes reveals long-term gene-flow during domestication

Traditionally, the process of domestication is assumed to be initiated by people, involve few individuals and rely on reproductive isolation between wild and domestic forms. However, an emerging zooarcheological consensus depicts animal domestication as a long-term process without reproductive isolation or strong intentional selection. Here, we ask whether pig domestication followed a traditional linear model, or a complex, reticulate model as predicted by zooarcheologists. To do so, we fit models of domestication to whole genome data from over 100 wild and domestic pigs. We found that the assumptions of traditional models, such as reproductive isolation and strong domestication bottlenecks, are incompatible with the genetic data and provide support for the zooarcheological theory of a complex domestication process. In particular, gene-flow from wild to domestic pigs was a ubiquitous feature of the domestication of pigs. In addition, we show that despite gene-flow, the genomes of domestic pigs show strong signatures of selection at loci that affect behaviour and morphology. Specifically, our results are consistent with independent parallel sweeps in two independent domestication areas (China and Anatolia) at loci linked to morphological traits. We argue that recurrent selection for domestic traits likely counteracted the homogenising effect of gene-flow from wild boars and created \"islands of domestication\" in the genome. Overall, our results suggest that genomic approaches that allow for more complex models of domestication to be embraced should be employed. The results from these studies will have significant ramifications for studies that attempt to infer the origin of domesticated animals.\n\nSignificance StatementThough animal domestication has traditionally been viewed as a human-directed process involving small populations of domestic animals and limited interbreeding between wild and domestic forms, but recent zooarcheological insights have questioned this model. By studying domestication in pigs, we demonstrate that complex models of domestication incorporating long-term gene-flow from multiple wild boar populations fit genomic data from modern wild and domestic pigs significantly better than models based on the traditional perspective. In addition, we demonstrate that selection at genes associated with domestic traits countered the effects of the gene flow, thus allowing morphological and behavioural differentiation between wild and domestic populations to be maintained.

Evolutionary Biology↗
bioRxiv2014

The genetic architecture of local adaptation I: The genomic landscape of foxtail pine (Pinus balfouriana Grev. & Balf.) as revealed from a high-density linkage map

Explaining the origin and evolutionary dynamics of the genetic architecture of adaptation is a major research goal of evolutionary genetics. Despite controversy surrounding success of the attempts to accomplish this goal, a full understanding of adaptive genetic variation necessitates knowledge about the genomic location and patterns of dispersion for the genetic components affecting fitness-related phenotypic traits. Even with advances in next generation sequencing technologies, the production of full genome sequences for non-model species is often cost prohibitive, especially for tree species such as pines where genome size often exceeds 20 to 30 Gbp. We address this need by constructing a dense linkage map for foxtail pine (Pinus balfouriana Grev. & Balf.), with the ultimate goal of uncovering and explaining the origin and evolutionary dynamics of adaptive genetic variation in natural populations of this forest tree species. We utilized megagametophyte arrays (n = 76-95 megagametophytes/tree) from four maternal trees in combination with double-digestion restriction site associated DNA sequencing (ddRADseq) to produce a consensus linkage map covering 98.58% of the foxtail pine genome, which was estimated to be 1276 cM in length (95% CI: 1174 cM to 1378 cM). A novel bioinformatic approach using iterative rounds of marker ordering and imputation was employed to produce single-tree linkage maps (507-17 066 contigs/map; lengths: 1037.40- 1572.80 cM). These linkage maps were collinear across maternal trees, with highly correlated marker orderings (Spearmans{rho} > 0.95). A consensus linkage map derived from these single-tree linkage maps contained 12 linkage groups along which 20 655 contigs were non-randomly distributed across 901 unique positions (n = 23 contigs/position), with an average spacing of 1.34 cM between adjacent positions. Of the 20 655 contigs positioned on the consensus linkage map, 5627 had enough sequence similarity to contigs contained within the most recent build of the loblolly pine (P. taeda L.) genome to identify them as putative homologs containing both genic and non-genic loci. Importantly, all 901 unique positions on the consensus linkage map had at least one contig with putative homology to loblolly pine. When combined with the other biological signals that predominate in our data (e.g., correlations of recombination fractions across single trees), we show that dense linkage maps for non-model forest tree species can be efficiently constructed using next generation sequencing technologies. We subsequently discuss the usefulness of these maps as community-wide resources and as tools with which to test hypotheses about the genetic architecture of adaptation.

Evolutionary Biology↗
bioRxiv2014

SpeedSeq: Ultra-fast personal genome analysis and interpretation

Comprehensive interpretation of human genome sequencing data is a challenging bioinformatic problem that typically requires weeks of analysis, with extensive hands-on expert involvement. This informatics bottleneck inflates genome sequencing costs, poses a computational burden for large-scale projects, and impedes the adoption of time-critical clinical applications such as personalized cancer profiling and newborn disease diagnosis, where the actionable timeframe can measure in hours or days. We developed SpeedSeq, an open-source genome analysis platform that vastly reduces computing time. SpeedSeq accomplishes read alignment, duplicate removal, variant detection and functional annotation of a 50X human genome in <24 hours, even using one low-cost server. SpeedSeq offers competitive or superior performance to current methods for detecting germline and somatic single nucleotide variants (SNVs), indels, and structural variants (SVs) and includes novel functionality for SV genotyping, SV annotation, fusion gene detection, and rapid identification of actionable mutations. SpeedSeq will help bring timely genome analysis into the clinical realm.\n\nAvailability: SpeedSeq is available at https://github.com/cc2qe/speedseq.

Bioinformatics↗
bioRxiv2015

Discovery of large genomic inversions using pooled clone sequencing

MotivationThere are many different forms of genomic structural variation that can be broadly classified into two groups as copy number variation (CNV) and balanced rearrangements. Although many algorithms are now available in the literature that aim to characterize CNVs, discovery of balanced rearrangements (inversions and translocations) remains an open problem. This is mainly because the breakpoints of such events typically lie within segmental duplications and common repeats, which reduce the mappability of short reads. The 1000 Genomes Project spearheaded the development of several methods to identify inversions, however, they are limited to relatively short inversions, and there are currently no available algorithms to discover large inversions using high throughput sequencing technologies (HTS).\n\nResultsHere we propose to use a sequencing method (Kitzman et al., 2011) originally developed to improve haplotype phasing to characterize large genomic inversions. This method, called pooled clone sequencing, merges the advantages of clone based sequencing approaches with the speed and cost efficiency of HTS technologies. Using data generated with pooled clone sequencing method, we developed a novel algorithm, dipSeq, to discover large inversions (>500 Kbp). We show the power of dipSeq first on simulated data, and then apply it to the genome of a HapMap individual (NA12878). We were able to accurately discover all previously known and experimentally validated large inversions in the same genome. We also identified a novel inversion, and confirmed using fluorescent in situ hybridization.\n\nAvailabilityImplementation of the dipSeq algorithm is available at https://github.com/BilkentCompGen/dipseq\n\nContactcalkan@cs.bilkent.edu.tr, francesca.antonacci@uniba.it

Bioinformatics↗
bioRxiv2015

Flaw or discovery? Calculating exact p-values for genome-wide association studies in inbred populations

MotivationGenome-wide association studies have been conducted in inbred populations where the sample size is small. The ordinary association p-values and multiple testing correction therefore become questionable, as the detected genetic effect may or may not be due to chance, depending on the minor allele frequency distribution across the genome. Instead of permutation testing, marker-specific false positive rate can be analytically calculated in inbred populations without heterozygotes.\n\nResultsSolutions of exact p-values for genome-wide association studies in inbred populations were derived and implemented. An example is presented to illustrate that the marker-specific experiment-wise p-value varies as the genome-wide minor allele frequency distribution changes. A simulation using real Arabidopsis thaliana genome indicates that the use of exact p-values improves detection power and reduces inflation due to population structure. An analysis of a defense-related case-control phenotype using the exact p-values revealed the causal locus, where markers with higher MAFs had smaller p-values than the top variants with lower MAFs in ordinary genome-wide association analysis.\n\nAvailability and ImplementationProject URL: https://r-forge.r-project.org/projects/statomics/. The R package p.exact: https://r-forge.r-project.org/R/?group_id=2030.\n\nContactxia.shen@ki.se

Bioinformatics↗
bioRxiv2015

The Spatial Mixing of Genomes in Secondary Contact Zones

Recent genomic studies have highlighted the important role of admixture in shaping genome-wide patterns of diversity. Past admixture leaves a population genomic signature of linkage disequilibrium (LD), reflecting the mixing of parental chromosomes by segregation and recombination. The extent of this LD can be used to infer the timing of admixture. However, the results of inference can depend strongly on the assumed demographic model. Here, we introduce a theoretical framework for modeling patterns of LD in a geographic contact zone where two differentiated populations are diffusing back together. We derive expressions for the expected LD and admixture tract lengths across geographic space as a function of the age of the contact zone and the dispersal distance of individuals. We develop an approach to infer age of contact zones using population genomic data from multiple spatially sampled populations by fitting our model to the decay of LD with recombination distance. We use our approach to explore the fit of a geographic contact zone model to three human population genomic datasets from populations along the Indonesian archipelago, populations in Central Asia and populations in India.

Evolutionary Biology↗
bioRxiv2015

Variation in linked selection and recombination drive genomic divergence during allopatric speciation of European and American aspens

Despite the global economic and ecological importance of forest trees, the genomic basis of differential adaptation and speciation in tree species is still poorly understood. Populus tremula and P. tremuloides are two of the most widespread tree species in the Northern Hemisphere. Using whole-genome re-sequencing data of 24 P. tremula and 22 P. tremuloides individuals, we find that the two species diverged [~]2.2-3.1 million years ago, coinciding with the severing of the Bering land bridge and the onset of dramatic climatic oscillations during the Pleistocene. Both species have experienced substantial population expansions following long-term declines after species divergence. We detect widespread and heterogeneous genomic differentiation between species, and in accordance with the expectation of allopatric speciation, coalescent simulations suggest that neutral evolutionary processes can account for most of the observed patterns of genomic differentiation. However, there is an excess of regions exhibiting extreme differentiation relative to those expected under demographic simulations, which is indicative of the action of natural selection. Overall genetic differentiation is negatively associated with recombination rate in both species, providing strong support for a role of linked selection in generating the heterogeneous genomic landscape of differentiation between species. Finally, we identify a number of candidate regions and genes that may have been subject to positive and/or balancing selection during the speciation process.

Evolutionary Biology↗
bioRxiv2015

Neptune: A Tool for Rapid Microbial Genomic Signature Discovery

The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using \"big data\" approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptunes loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real data sets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci.

Bioinformatics↗