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Results for “Genomics”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries

A fundamental question in microbiology is whether there is a continuum of genetic diversity among genomes or clear species boundaries prevail instead. Answering this question requires robust measurement of whole-genome relatedness among thousands of genomes and from diverge phylogenetic lineages. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) can provide the resolution needed for this task, overcoming several limitations of traditional techniques used for the same purposes. Although the number of genomes currently available may be adequate, the associated bioinformatics tools for analysis are lagging behind these developments and cannot scale to large datasets. Here, we present a new method, FastANI, to compute ANI using alignment-free approximate sequence mapping. Our analyses demonstrate that FastANI produces an accurate ANI estimate and is up to three orders of magnitude faster when compared to an alignment (e.g., BLAST)-based approach. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal a clear genetic discontinuity among the database genomes, with 99.8% of the total 8 billion genome pairs analyzed showing either >95% intra-species ANI or <83% inter-species ANI values. We further show that this discontinuity is recovered with or without the most frequently represented species in the database and is robust to historic additions in the public genome databases. Therefore, 95% ANI represents an accurate threshold for demarcating almost all currently named prokaryotic species, and wide species boundaries may exist for prokaryotes.

bioinformatics↗

bioRxiv2017

The asexual genome of Drosophila

The rate of recombination affects the mode of molecular evolution. In high-recombining sequence, the targets of selection are individual genetic loci; under low recombination, selection collectively acts on large, genetically linked genomic segments. Selection under linkage can induce clonal interference, a specific mode of evolution by competition of genetic clades within a population. This mode is well known in asexually evolving microbes, but has not been traced systematically in an obligate sexual organism. Here we show that the Drosophila genome is partitioned into two modes of evolution: a local interference regime with limited effects of genetic linkage, and an interference condensate with clonal competition. We map these modes by differences in mutation frequency spectra, and we show that the transition between them occurs at a threshold recombination rate that is predictable from genomic summary statistics. We find the interference condensate in segments of low-recombining sequence that are located primarily in chromosomal regions flanking the centromeres and cover about 20% of the Drosophila genome. Condensate regions have characteristics of asexual evolution that impact gene function: the efficacy of selection and the speed of evolution are lower and the genetic load is higher than in regions of local interference. Our results suggest that multicellular eukaryotes can harbor heterogeneous modes and tempi of evolution within one genome. We argue that this variation generates selection on genome architecture.\n\nAuthor SummaryThe Drosophila genome is an ideal system to study how the rate of recombination affects molecular evolution. It harbors a wide range of local recombination rates, and its high-recombining parts show broad signatures of adaptive evolution. The low-recombining parts, however, have remained dark genomic matter that has been omitted from most studies on the inference of selection. Here we show that these genomic regions evolve in a different way, which involves clonal competition and is akin to the evolution of asexual systems. This regime shows a lower efficacy of selection, a lower speed of evolution, and a higher genetic load than high-recombining regions. We argue these evolutionary differences have functional consequences: protein stability and protein expression are gene traits likely to be partially compromised by low recombination rates.

genetics↗

bioRxiv2018

Genomic SEM Provides Insights into the Multivariate Genetic Architecture of Complex Traits

Methods for using GWAS to estimate genetic correlations between pairwise combinations of traits have produced \"atlases\" of genetic architecture. Genetic atlases reveal pervasive pleiotropy, and genome-wide significant loci are often shared across different phenotypes. We introduce genomic structural equation modeling (Genomic SEM), a multivariate method for analyzing the joint genetic architectures of complex traits. Using formal methods for modeling covariance structure, Genomic SEM synthesizes genetic correlations and SNP-heritabilities inferred from GWAS summary statistics of individual traits from samples with varying and unknown degrees of overlap. Genomic SEM can be used to identify variants with effects on general dimensions of cross-trait liability, boost power for discovery, and calculate more predictive polygenic scores. Finally, Genomic SEM can be used to identify loci that cause divergence between traits, aiding the search for what uniquely differentiates highly correlated phenotypes. We demonstrate several applications of Genomic SEM, including a joint analysis of GWAS summary statistics from five genetically correlated psychiatric traits. We identify 27 independent SNPs not previously identified in the univariate GWASs, 5 of which have been reported in other published GWASs of the included traits. Polygenic scores derived from Genomic SEM consistently outperform polygenic scores derived from GWASs of the individual traits. Genomic SEM is flexible, open ended, and allows for continuous innovations in how multivariate genetic architecture is modeled.

genetics↗

bioRxiv2018

Efficient Merging of Genome Profile Alignments

MotivationWhole-genome alignment methods show insufficient scalability towards the generation of large-scale whole-genome alignments (WGAs). Profile alignment-based approaches revolutionized the fields of multiple sequence alignment construction methods by significantly reducing computational complexity and runtime. However, WGAs need to consider genomic rearrangements between genomes, which makes the profile-based extension of several whole-genomes challenging. Currently, none of the available methods offer the possibility to align or extend WGA profiles. ResultsHere, we present GPA, an approach that aligns the profiles of WGAs and is capable of producing large-scale WGAs many times faster than conventional methods. Our concept relies on already available whole-genome aligners, which are used to compute several smaller sets of aligned genomes that are combined to a full WGA with a divide and conquer approach. To align or extend WGA profiles, we make use of the SuperGenome data structure, which features a bidirectional mapping between individual sequence and alignment coordinates. This data structure is used to efficiently transfer different coordinate systems into a common one based on the principles of profiles alignments. The approach allows the computation of a WGA where alignments are subsequently merged along a guide tree. The current implementation uses progressiveMauve (Darling et al., 2010) and offers the possibility for parallel computation of independent genome alignments. Our results based on various bacterial data sets up to several hundred genomes show that we can reduce the runtime from months to hours with a quality that is negligibly worse than the WGA computed with the conventional progressiveMauve tool. AvailabilityGPA is freely available at https://lambda.informatik.uni-tuebingen.de/gitlab/ahennig/GPA. GPA is implemented in Java, uses progressiveMauve and offers a parallel computation of WGAs. Contactandre.hennig@uni-tuebingen.de

bioinformatics↗

bioRxiv2018

Designing Genomes using Design-Simulate-Test Cycles

In the future, entire genomes tailored to specific functions and environments could be designed using computational tools. However, computational tools for genome design are currently scarce. Here we present algorithms that enable the use of design-simulate-test cycles for genome design, using genome minimisation as a proof-of-concept. Minimal genomes are ideal for this purpose as they have a very simple functional assay, the cell can either replicate or not. We used the first (and currently only published) whole-cell model, for the bacterium Mycoplasma genitalium 1. Our computational design-simulate-test cycles discovered novel in-silico minimal genomes smaller than JCVI-Syn3.0 2, a bacterial cell with the currently known smallest genome that can be grown in pure culture. In the process, we identified 10 low essentiality genes, 18 high essentiality genes 3, and produced evidence for at least two minimal genomes for Mycoplasma genitalium in-silico. This work brings combined computational and laboratory genome design and construction a step closer.

synthetic biology↗

bioRxiv2018

Nanopore sequence-based genome assembly of the basmati rice

BACKGROUNDThe circum-basmati group of cultivated Asian rice (Oryza sativa) contains many iconic varieties and is widespread in the Indian subcontinent. Despite its economic and cultural importance, a high-quality reference genome is currently lacking, and the groups evolutionary history is not fully resolved. To address these gaps, we used long-read nanopore sequencing and assembled the genomes of two circum-basmati rice varieties, Basmati 334 and Dom Sufid.\n\nRESULTSWe generated two high-quality, chromosome-level reference genomes that represented the 12 chromosomes of Oryza. The assemblies showed a contig N50 of 6.32Mb and 10.53Mb for Basmati 334 and Dom Sufid, respectively. Using our highly contiguous assemblies we characterized structural variations segregating across circum-basmati genomes. We discovered repeat expansions not observed in japonica--the rice group most closely related to circum- basmati--as well as presence/absence variants of over 20Mb, one of which was a circum- basmati-specific deletion of a gene regulating awn length. We further detected strong evidence of admixture between the circum-basmati and circum-aus groups. This gene flow had its greatest effect on chromosome 10, causing both structural variation and single nucleotide polymorphism to deviate from genome-wide history. Lastly, population genomic analysis of 78 circum-basmati varieties showed three major geographically structured genetic groups: (1) Bhutan/Nepal group, (2) India/Bangladesh/Myanmar group, and (3) Iran/Pakistan group.\n\nCONCLUSIONAvailability of high-quality reference genomes from nanopore sequencing allowed functional and evolutionary genomic analyses, providing genome-wide evidence for gene flow between circum-aus and circum-basmati, the nature of circum-basmati structural variation, and the presence/absence of genes in this important and iconic rice variety group.

evolutionary biology↗

bioRxiv2018

Whole genome sequencing for drug resistance profile prediction in Mycobacterium tuberculosis

Whole genome sequencing allows rapid detection of drug-resistant M. tuberculosis isolates. However, high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been lacking.\n\nWe determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared phenotypic drug susceptibility results with predicted drug resistance profiles inferred by whole genome sequencing.\n\nBoth phenotypic DST methods identically classified the strains into resistant/susceptible in 73-99% of the cases, depending on the drug. Changes in minimal inhibitory concentrations were readily explained by mutations identified by whole genome sequencing. Using the whole genome sequences we were able to predict quantitative drug resistance levels where wild type and mutant MIC distributions did not overlap. The utility of genome sequences to predict quantitative levels of drug resistance was partially limited due to incompletely understood mechanisms influencing the expression of phenotypic drug resistance. The overall sensitivity and specificity of whole genome-based DST were 86.8% and 94.5%, respectively.\n\nDespite some limitations, whole genome sequencing has high predictive power to infer resistance profiles without the need for time-consuming phenotypic methods.\n\nOne sentence summaryWhole genome sequencing of clinical M. tuberculosis isolates accurately predicts drug resistance profiles and may replace culture-based drug susceptibility testing in the future.

microbiology↗

bioRxiv2018

Impact of transposable elements on genome structure and evolution in bread wheat

BackgroundTransposable elements (TEs) are ubiquitous components of genomes and they are the main contributors to genome evolution. The reference sequence of the hexaploid bread wheat (Triticum aestivum L.) genome enabled for the first time a comprehensive genome-wide view of the dynamics of TEs that have massively proliferated in the A, B, and D subgenomes.\n\nResultsTEs represent 85% of the genome. We traced back TE amplification dynamics in the evolutionary history of wheat and did not find large bursts in the wake of either the tetra- or the hexaploidization. Despite the massive turnover of TEs since A, B, and D diverged, 76% of TE families are present in similar proportions in the three subgenomes. Moreover, spacing between homeologous genes was also conserved. TE content around genes is very different from the TE space comprising large intergenic regions and families that are enriched or depleted from gene promoters are the same in the three subgenomes.\n\nConclusionsThe chromosome-scale assembly of the wheat genome provided an unprecedented genome-wide view of the organization and impact of TEs in such a complex genome. Our results suggest that TEs play a role at the structural level and that the overall chromatin structure is likely under selection pressure.

genomics↗

bioRxiv2014

Chromothripsis-like patterns are recurring but heterogeneously distributed features in a survey of 22,347 cancer genome screens

BackgroundChromothripsis is a recently discovered phenomenon of genomic rearrangement, possibly arising during a single genome-shattering event. This could provide an alternative paradigm in cancer development, replacing the gradual accumulation of genomic changes with a \"one-off\" catastrophic event. However, the term has been used with varying operational definitions, with the minimal consensus being a large number of locally clustered copy number aberrations. The mechanisms underlying these chromothripsis-like patterns (CTLP) and their specific impact on tumorigenesis are still poorly understood.\n\nResultsHere, we identified CTLP in 918 cancer samples, from a dataset of more than 22,000 oncogenomic arrays covering 132 cancer types. Fragmentation hotspots were found to be located on chromosome 8, 11, 12 and 17. Among the various cancer types, soft-tissue tumors exhibited particularly high CTLP frequencies. Genomic context analysis revealed that CTLP rearrangements frequently occurred in genomes that additionally harbored multiple copy number aberrations (CNAs). An investigation into the affected chromosomal regions showed a large proportion of arm-level pulverization and telomere related events, which would be compatible to a number of underlying mechanisms. We also report evidence that these genomic events may be correlated with patient age, stage and survival rate.\n\nConclusionsThrough a large-scale analysis of oncogenomic array data sets, this study characterized features associated with genomic aberrations patterns, compatible to the spectrum of \"chromothripsis\"-definitions as previously used. While quantifying clustered genomic copy number aberrations in cancer samples, our data indicates an underlying biological heterogeneity behind these chromothripsis-like patterns, beyond a well defined \"chromthripsis\" phenomenon.

Genomics↗

bioRxiv2014

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the \"pan-genome\" of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Genomics↗

bioRxiv2014

The genomic landscape of polymorphic human nuclear mitochondrial insertions

The transfer of mitochondrial genetic material into the nuclear genomes of eukaryotes is a well-established phenomenon. Many studies over the past decade have utilized reference genome sequences of numerous species to characterize the prevalence and contribution of nuclear mitochondrial insertions to human diseases. The recent advancement of high throughput sequencing technologies has enabled the interrogation of genomic variation at a much finer scale, and now allows for an exploration into the diversity of polymorphic nuclear mitochondrial insertions (NumtS) in human populations. We have developed an approach to discover and genotype previously undiscovered Numt insertions using whole genome, paired-end sequencing data. We have applied this method to almost a thousand individuals in twenty populations from the 1000 Genomes Project and other data sets and identified 138 novel sites of Numt insertions, extending our current knowledge of existing Numt locations in the human genome by almost 20%. Most of the newly identified NumtS were found in less than 1% of the samples we examined, suggesting that they occur infrequently in nature or have been rapidly removed by purifying selection. We find that recent Numt insertions are derived from throughout the mitochondrial genome, including the D-loop, and have integration biases consistent with previous studies on older, fixed NumtS in the reference genome. We have further determined the complete inserted sequence for a subset of these events to define their age and origin of insertion as well as their potential impact on studies of mitochondrial heteroplasmy.

Genomics↗

bioRxiv2016

Recurrent selection explains parallel evolution of genomic regions of high relative but low absolute differentiation in greenish warblers

Recent technological developments allow investigation of the repeatability of evolution at the genomic level. Such investigation is particularly powerful when applied to a ring species, in which spatial variation represents changes during the evolution of two species from one. We examined genomic variation among three subspecies of the greenish warbler ring species, using genotypes at 13,013,950 nucleotide sites along a new greenish warbler consensus genome assembly. Genomic regions of low within-group variation are remarkably consistent between the three populations. These regions show high relative differentiation but low absolute differentiation between populations. Comparisons with outgroup species show the locations of these peaks of relative differentiation are not well explained by phylogenetically-conserved variation in recombination rates or selection. These patterns are consistent with a model in which selection in an ancestral form has reduced variation at some parts of the genome, and those same regions experience recurrent selection that subsequently reduces variation within each subspecies. The degree of heterogeneity in nucleotide diversity is greater than explained by models background selection, but are consistent with selective sweeps. Given the evidence that greenish warblers have had both population differentiation for a long period of time and periods of gene flow between those populations, we propose that some genomic regions underwent selective sweeps over a broad geographic area followed by within-population selection-induced reductions in variation. An important implication of this \"sweep-before-differentiation\" model is that genomic regions of high relative differentiation may have moved among populations more recently than other genomic regions.

Genomics↗

bioRxiv2016

Optimizing multiplex CRISPR/Cas9-based genome editing for wheat

BackgroundCRISPR/Cas9-based genome editing holds great promise to accelerate the development of new crop varieties by providing a powerful tool to modify the genomic regions controlling major agronomic traits. To diversify the set of tools available for wheat genome engineering, we have established a tRNA-based multiplex gene editing strategy for hexaploid wheat.\n\nResultsThe functionality of the various CRISPR/Cas9 components was assessed using the transient expression in the wheat protoplasts followed by next-generation sequencing (NGS) of the targeted genomic regions. The efficiency of wheat codon-optimized Cas9 for targeted gene editing in wheat was validated. Multiple single guide RNAs (gRNAs) were evaluated for the ability to edit the homoeologous copies of four genes affecting some important agronomic traits in wheat. Low correspondence was found between the gRNA efficiency predicted bioinformatically and that assessed in the transient expression assay. A multiplex gene editing construct with several gRNA-tRNA units under the control of a single promoter for the RNA polymerase III generated indels at the targets sites with the efficiency comparable to that obtained for a single gRNA construct.\n\nConclusionsBy integrating the protoplast transformation assay with multiplexed NGS, it is possible to perform fast functional screens for a large number of gRNAs and to optimize constructs for effective editing of multiple independent targets in the wheat genome. The multiplexing capacity of the tandemly arrayed tRNA-gRNA construct is well suited for the simultaneous editing of the redundant gene copies in the allopolyploid genomes or genomic regions beneficially affecting multiple agronomic traits. A polycistronic gene construct that can be quickly assembled using the Golden Gate reaction along with the wheat codon optimized Cas9 will further expand the set of tools available for engineering the wheat genome.

Genomics↗

bioRxiv2016

Direct determination of diploid genome sequences

Determining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses and, in general, failing to capture sequences novel to a given genome.\n\nSome de novo assemblies have been constructed, free of reference bias, but nearly all were constructed by merging homologous loci into single consensus sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploid de novo assemblies have been made, at great expense. One was generated using Sanger sequencing and one using thousands of clone pools.\n\nHere we demonstrate a straightforward and low-cost method for creating true diploid de novo assemblies. We make a single library from ~1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new pushbutton algorithm, Supernova. Each computation took two days on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.

Genomics↗

bioRxiv2017

Trichoderma reesei Complete Genome Sequence, Repeat-Induced Point Mutation And Partitioning Of CAZyme Gene Clusters

Trichoderma reesei (Ascomycota, Pezizomycotina) QM6a is a model fungus for a broad spectrum of physiological phenomena, including plant cell wall degradation, industrial production of enzymes, light responses, conidiation, sexual development, polyketide biosynthesis and plant-fungal interactions. The genomes of QM6a and its high-enzyme producing mutants have been sequenced by second-generation-sequencing methods and are publicly available from the Joint Genome Institute (JGI). While these genome sequences have offered useful information for genomic and transcriptomic studies, their limitations and especially their short read lengths make them poorly suited for some particular biological problems, including assembly, genome-wide determination of chromosome architecture and genetic modification or engineering. We integrated Pacific Biosciences and Illumina sequencing platforms for the highest-quality genome assembly yet achieved, revealing seven telomere-to-telomere chromosomes (34,922,528 bp; 10877 genes) with 1630 newly-predicted genes and >1.5 Mb of new sequences. Most new sequences are located on AT-rich blocks, including 7 centromeres, 14 subtelomeres and 2329 interspersed AT-rich blocks. The seven QM6a centromeres separately consist of 24 conserved repeats and 37 putative centromere-encoded genes. These findings open up a new perspective for future centromere and chromosome architecture studies. Next, we demonstrate that sexual crossing readily induced cytosine-to-thymine point mutations on both tandem and unlinked duplicated sequences. We also show by bioinformatic analysis that Trichoderma reesei has evolved a robust repeat-induced point mutation (RIP) system to accumulate AT-rich sequences, with longer AT-rich blocks having more RIP mutations. The widespread distribution of AT-rich blocks correlates genome-wide partitions with gene clusters, explaining why clustering of genes has been reported to not influence gene expression in Trichoderma reesei. Compartmentation of ancestral gene clusters by AT-rich blocks might promote flexibilities that are evolutionarily advantageous in this fungus soil habitats and other natural environments. Our analyses, together with the complete genome sequence, provide a better blueprint for biotechnological and industrial applications.

genomics↗

bioRxiv2017

Classifying cancer genome aberrations by their mutually exclusive effects on transcription

BackgroundMalignant tumors are typically caused by a conglomeration of genomic aberrations--including point mutations, small insertions, small deletions, and large copy-number variations. In some cases, specific chemotherapies and targeted drug treatments are effective against tumors that harbor certain genomic aberrations. However, predictive aberrations (biomarkers) have not been identified for many tumors. One way to address this problem is to examine the downstream, transcriptional effects of genomic aberrations and to identify characteristic patterns. Even though two tumors harbor different genomic aberrations, the transcriptional effects of those aberrations may be similar. These patterns could be used to inform treatment choices.\n\nResultsWe hypothesized that by grouping genomic aberrations according to their downstream transcriptional effects, we could identify drug-repurposing candidates that coincide with prior knowledge. To evaluate this hypothesis, we developed a computational pipeline that uses supervised machine learning to identify similarities among mutually exclusive genomic aberrations based on their transcriptional effects. We used data from 9300 tumors across 25 cancer types from The Cancer Genome Atlas to evaluate our approach. Our pipeline recapitulates known relationships in cancer pathways, and it identifies gene pairs known to predict responses to the same treatments.\n\nConclusionWe show that transcriptional data offer promise as a way to group genomic aberrations according to their downstream effects, and these groupings recapitulate known relationships. Our approach shows potential to help pharmacologists and clinical trialists narrow the search space for candidate gene/drug associations, including for rare mutations, and for identifying potential drug-repurposing opportunities.

genomics↗

bioRxiv2017

Long-read assembly of the Aedes aegypti genome reveals the nature of heritable adaptive immunity sequences

The Aedes aegypti mosquito is a major vector for arboviruses including dengue, chikungunya and Zika virus. Combating the spread of these viruses requires a more complete understanding of the mosquito immune system. Recent studies have implicated genomic endogenous viral elements (EVEs) derived from non-retroviral RNA viruses in insect immunity. Because these elements are inserted into repetitive regions of the mosquito genome, their large-scale structure and organization with respect to other genomic elements has been difficult to resolve with short-read sequencing. To better define the origin, diversity and biological role of EVEs, we employed single-molecule, real-time sequencing technology to generate a high quality, long-read assembly of the Ae. aegypti-derived Aag2 cell line genome. We leverage the quality and contiguity of this assembly to characterize the diversity and genomic context of EVEs in the genome of this important model system. We find that EVEs in the Aag2 genome are acquired through recombination by LTR retrotransposons, and organize into larger loci (>50kbp) characterized by high LTR density. These EVE containing loci are associated with increased transcription factor binding sight density and increased production of anti-genomic piRNAs. We also detected piRNA processing corresponding to on-going viral infection. This global view of EVEs and piRNA responses demonstrates the ubiquity and diversity of these heritable elements that define small-RNA mediated antiviral immunity in mosquitoes.

genomics↗

bioRxiv2017

Precision Medicine Screening Using Whole Genome Sequencing And Advanced Imaging To Identify Disease Risk In Adults

BACKGROUNDProgress in science and technology have created the capabilities and alternatives to symptom-driven medical care. Reducing premature mortality associated with age-related chronic diseases, such as cancer and cardiovascular disease, is an urgent priority we address using advanced screening detection.\n\nMETHODSWe enrolled active adults for early detection of risk for age-related chronic disease associated with premature mortality. Whole genome sequencing together with: global metabolomics, 3D/4D imaging using non-contrast whole body magnetic resonance imaging and echocardiography, and 2-week cardiac monitoring were employed to detect age-related chronic diseases and risk for diseases.\n\nRESULTSWe detected previously unrecognized age-related chronic diseases requiring prompt (<30 days) medical attention in 17 (8%, 1:12) of 209 study participants, including 4 participants with early stage neoplasms (2%, 1:50). Likely mechanistic genomic findings correlating with clinical data were identified in 52 participants (25%. 1:4). More than three-quarters of participants (n=164, 78%, 3:4) had evidence of age-related chronic diseases or associated risk factors.\n\nCONCLUSIONSPrecision medicine screening using genomics with other advanced clinical data among active adults identified unsuspected disease risks for age-related chronic diseases associated with premature mortality. This technology-driven phenotype screening approach has the potential to extend healthy life among active adults through improved early detection and prevention of age-related chronic diseases. Our success provides a scalable strategy to move medical practice and discovery toward risk detection and disease modification thus achieving healthier extension of life.\n\nSIGNIFICANCE STATEMENTAdvances in science and technology have enabled scientists to analyze the human genome cost-effectively and to combine genome sequencing with noninvasive imaging technologies for alternatives to symptom-driven medical care. Using whole genome sequencing and noninvasive 3D/4D imaging technologies we screened 209 adults to detect age-related chronic diseases, such as cancer and cardiovascular disease. We found unrecognized age-related chronic diseases requiring prompt (<30 days) medical attention in 1:12 study participants, likely genomic findings correlating with clinical data in 1:4 participants, and evidence of age-related chronic diseases or associated risk factors in more than 3 of 4 participants. These results demonstrate that genome sequencing with clinical imaging data can be used for screening and early detection of diseases associated with premature mortality.

genomics↗