Biology subjects

Li, Q.

Publications and source records attributed to Li, Q..

At least 757 records · Page 42Linked to original sources

bioRxiv2018

powerTCR: a model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire

Sequencing of the T cell receptor repertoire is a powerful tool for deeper study of immune response, but the unique structure of this type of data makes its meaningful quantification challenging. We introduce a new method, the Gamma-GPD spliced threshold model, to address this difficulty. This biologically interpretable model captures the distribution of the TCR repertoire, demonstrates stability across varying sequencing depths, and permits comparative analysis across any number of sampled individuals. We apply our method to several datasets and obtain insights regarding the differentiating features in the T cell receptor repertoire among sampled individuals across conditions. We have implemented our method in the open-source R package powerTCR.\n\nAuthor summaryA more detailed understanding of the immune response can unlock critical information concerning diagnosis and treatment of disease. Here, in particular, we study T cells through T cell receptor sequencing, as T cells play a vital role in immune response. One important feature of T cell receptor sequencing data is the frequencies of each receptor in a given sample. These frequencies harbor global information about the landscape of the immune response. We introduce a flexible method that extracts this information by modeling the distribution of these frequencies, and show that it can be used to quantify differences in samples from individuals of different biological conditions.

immunology↗

bioRxiv2018

Condition-adaptive fused graphical lasso (CFGL): an adaptive procedure for inferring condition-specific gene co-expression network

Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis.\n\nOne possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.\n\nAuthor summaryGene co-expression networks provide insights into the mechanism of cellular activity and gene regulation. Condition-specific mechanisms may be identified by constructing and comparing co-expression networks of multiple conditions. We propose a novel statistical method to jointly construct co-expression networks for gene expression profiles from multiple conditions. By using a data-driven approach to capture condition-specific co-expression patterns, this method is effective in identifying both co-expression patterns that are specific to a condition and that are common across conditions. The application of this method on real datasets reveals interesting biological insights.

bioinformatics↗

bioRxiv2018

Small effect size leads to reproducibility failure in resting-state fMRI studies

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinsons disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

neuroscience↗

bioRxiv2018

A conserved nuclear export complex coordinates transcripts for dopaminergic synaptogenesis and neuronal surviva

Synaptic vesicle and active zone proteins are required for synaptogenesis. The molecular mechanisms for coordinated synthesis of these proteins are not understood. Using forward genetic screens, we identified the conserved THO nuclear export Complex (THOC) as master regulator of presynapse development in C.elegans dopaminergic neurons. In THOC mutants, synaptic messenger RNAs are trapped in the nucleus, resulting in dramatic decrease of synaptic protein expression, near complete loss of synapses and compromised dopamine function. cAMP-responsive element binding protein (CREB) interacts with THOC to mark activity-dependent transcripts for efficient nuclear export. Deletion of the THOC subunit Thoc5 in mouse dopaminergic neurons causes severe defects in synapse maintenance and subsequent neuronal death in the Substantia Nigra compacta (SNc). These cellular defects lead to abrogated dopamine release, ataxia and animal death. Together, our results argue that nuclear export mechanisms can select specific mRNAs and be a rate-limiting step for synapse development and neuronal survival.\n\nHighlightsO_LIDopaminergic presynapses are severely impaired in thoc mutant worms and mice\nC_LIO_LITHOC specifically controls the nuclear export of synaptic transcripts\nC_LIO_LICREB recruits THOC onto activity-dependent synaptic transcripts for efficient export\nC_LIO_LIDopamine neurons in the SNc degenerate upon conditional knock-out of thoc5\nC_LI

neuroscience↗

bioRxiv2018

The tumor suppressor BRCA1/BARD1 complex localizes to the synaptonemal complex and regulates recombination under meiotic dysfunction in Caenorhabditis elegans

Breast cancer susceptibility gene 1(BRCA1) and binding partner BRCA1-associated RING domain protein 1 (BARD1) form an essential E3 ubiquitin ligase important for DNA damage repair and homologous recombination. In Caenorhabditis elegans BRCA1/BRC-1 and BARD1/BRD-1 orthologs are not essential, but function in DNA damage repair and homologous recombination, as well as in meiosis. In proliferating germ cells and in early meiotic prophase, BRC-1 and BRD-1 are nucleoplasmic, with enrichment at foci that partially overlap with the recombinase RAD-51. In mid-pachytene, BRC-1 and BRD-1 are observed on tracks, before concentrating to the short arms of bivalents, co-localizing with a central region component of the synaptonemal complex. We found that BRD-1 is essential for BRC-1 to associate with chromatin and the synaptonemal complex, but BRC-1 is not required for BRD-1 localization; the complex fails to properly localize in the absence of either meiotic recombination or chromosome synapsis. Inactivation of BRC-1/BRD-1 enhances the embryonic lethality of mutants that perturb chromosome synapsis and crossover recombination, suggesting that BRC-1/BRD-1 plays an important role in monitoring recombination in the context of the synaptonemal complex. We discovered that BRC-1/BRD-1 stabilizes the RAD51 filament when the formation of a crossover-intermediate is disrupted. Further, in the absence of BRC-1/BRD-1 crossover distribution is altered, and under meiotic dysfunction, crossover numbers are perturbed. Together, our studies indicate that BRC-1/BRD-1 localizes to the synaptonemal complex where it serves a checkpoint function to monitor and modulate meiotic recombination.\n\nProject SummaryOur genomes are passed down from one generation to the next through the specialized cell division program of meiosis. Meiosis is highly regulated to coordinate both the large scale chromosomal and fine scale DNA events to ensure fidelity. We analyzed the role of the tumor suppressor BRCA1/BARD1 complex in meiosis in the worm, Caenorhabditis elegans. We find that BRCA1/BARD1 localizes dynamically to the proteinaeous structure that aligns maternal and paternal chromosomes, where it regulates crossover recombination. Although BRCA1/BARD1 mutants have only subtle meiotic defects, we show that this complex plays a critical role in meiotic recombination when meiosis is perturbed. These results highlight the complexity of ensuring accurate transmission of the genome and uncover the requirement for this conserved complex in meiosis. As women carrying BRCA1 mutations with no indication of cancer have fertility defects, our results provide insight into why BRCA1 mutations impact reproductive success.

genetics↗

bioRxiv2018

A learning-based framework for miRNA-disease association prediction using neural networks

MotivationA microRNA (miRNA) is a type of non-coding RNA, which plays important roles in many bio-logical processes. Lots of studies have shown that miRNAs were implicated in human diseases, indicating that miRNAs might be potential biomarkers for various types of diseases. Therefore, it is important to reveal the relationships between miRNAs and diseases/phenotypes.\n\nResultsWe proposed a novel learning-based framework, MDA-CNN, for miRNA-disease association identification. The model first captures richer interaction features between diseases and miRNAs based on a three-layer network with an additional gene layer. An auto-encoder is then employed to identify the essential feature combination for each pair of miRNA and disease automatically. A final label is given by a convolutional neural network taking the reduced feature representation as input. The evaluation results showed that the proposed framework outperformed some state-of-the-art approaches in a large margin on both tasks of miRNA-disease associations prediction and miRNA-phenotype associations prediction.\n\nAvailabilityThe software will be available after the manuscript is accepted.\n\nContactjiajiepeng@nwpu.edu.cn;zywei@fudan.edu.cn;shang@nwpu.edu.cn\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2018

Cell atlas of human uterus

The human uterus is a highly dynamic tissue that undergoes repeated damage repair and regeneration during the menstrual cycle, which make it ideal model to study tissue regeneration and pathological process. Stem/progenitors were speculated to be involved in the regeneration of endometrial epithelial and pathogenesis of endometriosis. But the identity, microenvironment and regulatory mechanisms of the uterus epithelial stem/progenitors in vivo remain unclear. Here, we dissected the cell heterogeneities of the full-thickness human uterus epithelial cells (11 clusters), stroma cells (6 clusters), endothelial cells (5 clusters), smooth muscle cells (2 clusters), myofibroblasts (2 clusters) and immune cells (6 clusters) from 2735 single cell by single cell RNA-seq. Further analysis identified a unique ciliated epithelial cell cluster showing characteristics of stem/progenitors with properties of epithelial-mesenchymal transition (EMT) that mainly localized in the upper functionalis of the endometrium. Ordering the cell subpopulations along the pseudo-space revealed cell clusters possess cellular states of stress, inflammation and apoptosis in the upper functionalis cellular ecosystem of the endometrium. Connectivity map between the human uterus subpopulations revealed potential inflammatory (cytokines and chemokines) and developmental (WNT, FGF, VEGF) signals within the upper functionalis cellular ecosystem of the endometrium, especially from other epithelial clusters, regulating cell plasticity of the EMT-epithelial clusters. This study reconstructed the heterogeneities, space-specific distribution and connectivity map of human uterus atlas, which would provide insight in the regeneration of uterus endometria and reference for the pathogenesis of uterus.

cell biology↗

bioRxiv2018

The plasma miR-122 basal levels respond to circulating catecholamine in rats

miR-122 in circulation is a promising non-invasive biomarker as a replacement or supplement of current serum biomarkers for liver injuries. But the concept was questioned by recent studies, mainly due to its release from hepatocytes in absence of overt cellular injuries. In this study, we reported that the hepatic metabolism of circulating catecholamines resulted in the release of hepatocyte-specific miR-122. Acute stress-induced hepatocellular deformation was histopathologically different from drug-induced liver injury with significant increases of plasma miR-122 levels. The basal levels of human plasma miR-122 could be significantly altered by emotional responses. Interday variances of plasma miR-122 measurements were reduced effectively by stress-relief measures. The metabolism of basal circulating norepinephrine and epinephrine in liver might contribute to the basal levels of plasma miRNAs expressed in hepatocytes.

molecular biology↗

bioRxiv2018

Targeted epigenomic changes to the maize methylome resulting from tissue culture

DNA methylation can contribute to the maintenance of genome integrity and regulation of gene expression. In most situations, DNA methylation patterns are inherited quite stably. However, changes in DNA methylation can occur at some loci as a result of tissue culture resulting in somaclonal variation. A sequence-capture bisulfite sequencing approach was implemented to monitor context-specific DNA methylation patterns in ~15Mb of the maize genome for a population of plants that had been regenerated from tissue culture. Plants that have been regenerated from tissue culture exhibit gains and losses of DNA methylation at a subset of genomic regions. There was evidence for a high rate of homozygous changes to DNA methylation levels that occur consistently in multiple independent tissue culture lines suggesting the existence of a targeted process for altering epigenetic state during tissue culture. The consistent changes induced by tissue culture include both gains and losses of DNA methylation and can affect CG, CHG or both contexts within a region. The majority of changes in DNA methylation exhibit stable inheritance although there is some evidence for stochastic reacquisition of the initial epigenetic state in some individuals. This study provides insights into the susceptibility of some loci and potential mechanisms that could contribute to altered DNA methylation and epigenetic state that occur during tissue culture in plant species.

plant biology↗

bioRxiv2017

Subtle perturbations of the maize methylome reveal genes and transposons silenced by DNA methylation

DNA methylation is a chromatin modification that can provide epigenetic regulation of gene and transposon expression. Plants utilize several pathways to establish and maintain DNA methylation in specific sequence contexts. The chromomethylase (CMT) genes maintain CHG (where H = A, C or T) methylation. The RNA-directed DNA methylation (RdDM) pathway is important for CHH methylation. Transcriptome analysis was performed in a collection of Zea mays lines carrying mutant alleles for CMT or RdDM-associated genes. While the majority of the transcriptome was not affected, we identified sets of genes and transposon families sensitive to context-specific decreases in DNA methylation in mutant lines. Many of the genes that are up-regulated in CMT mutant lines have high levels of CHG methylation, while genes that are differentially expressed in RdDM mutants are enriched for having nearby mCHH islands, providing evidence that context-specific DNA methylation directly regulates expression of a small number of genes. The analysis of a diverse set of inbred lines revealed that many genes regulated by CMTs exhibit natural variation for DNA methylation and gene expression. Transposon families with differential expression in the mutant genotypes show few defining features, though several families up-regulated in RdDM mutants show enriched expression in endosperm, highlighting the importance for this pathway during reproduction. Taken together, our findings suggest that while the number of genes and transposon families whose expression is reproducibly affected by mild perturbations in context-specific methylation is small, there are distinct patterns for loci impacted by RdDM and CMT mutants.

plant biology↗

bioRxiv2017

Measuring the reproducibility and quality of Hi-C data

Hi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established (e.g., ratio of intra to interchromosomal interactions) and novel (e.g., QuASAR-QC) measures to identify low quality experiments. In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

genomics↗

bioRxiv2017

The effect of sonic hedgehog on motor neuron positioning in the spinal cord during chicken embryo development

Sonic hedgehog (Shh) is a vertebrate homologue of the secreted Drosophila protein hedgehog, and is expressed by the notochord and the floor plate in the developing spinal cord. Shh provides signals relevant for positional information, cell proliferation, and possibly cell survival depending on the time and location of the expression. Although the role of Shh in providing positional information in the neural tube has been experimentally proven, the exact underlying mechanism still remains unclear. In this study, we report that overexpression of Shh affects motor neuron positioning in the spinal cord during chicken embryo development by inducing abnormalities in the structure of the motor column and motor neuron integration. In addition, Shh overexpression inhibits the expression of dorsal transcription factors and commissural axon projections. Our results indicate that correct location of Shh expression is the key to the formation of the motor column. In conclusion, the overexpression of Shh in the spinal cord not only affects the positioning of motor neurons, but also induces abnormalities in the structure of the motor column.

developmental biology↗

bioRxiv2017

Genetics and epigenetic alterations of hexaploid early generation derived from hybrid between Brassica napus and B. oleracea

Good fertility was observed previously in hexaploid derived from hybrid (ACC) between calona Zhongshuang 9(Brassica napus, 2n = 38, AACC) and kale SWU01 (B. oleracea var. acephala, 2n = 18, CC). However, the mechanism to underlying the character is unknown. In the present study, genetic and epigenetic alterations of S0, 6 S1, and 18 of their S2 progenies with hexaploid chromosome conformation (20A + 36C) were selected to compare with ACC and their parental species. 13.08% and 26.45% polymorphism alleles different from two parental species were identified in ACC via 58 SSR (simple sequence repeats) and 14 MSAP (methylation sensitive amplified polymorphism), respectively. 33.74% new alleles in DNA methylation, but not in DNA sequence were detected in S0 after chromosome doubling of ACC. DNA profilling revealed a little genetic but much epigenetic differences among S0, S1 and S2 generations. Genetic alteration was relatively stable, because only 8.09% and 3.21% alleles inheriated from ACC were changed in S2 and S1, respectively. While on average of 52.44 {+/-} 5.32% DNA methylation site inherited from ACC were detected in S1, and 41.52 {+/-} 9.04% in S2 due to dramatic epigenetic variance among early generations. New DNA methylation sites occurred in S0 would inheritated into the successive generations, but the frequency was decreased because some new site might be recovered. It demonstrated that much DNA methylation but a little DNA sequence variance was occurred in hexaploid early generation.

genetics↗

bioRxiv2017

Decoding the orientation of contrast edges from MEG evoked and induced responses

1Visual gamma oscillations have been proposed to subserve perceptual binding, but their strong modulation by diverse stimulus features confounds interpretations of their precise functional role. Overcoming this challenge necessitates a comprehensive account of the relationship between gamma responses and stimulus features. Here we used multivariate pattern analyses on human MEG data to characterize the relationships between gamma responses and one basic stimulus feature, the orientation of contrast edges. Our findings confirmed we could decode orientation information from induced responses in two dominant frequency bands at 24-32 Hz and 50-58 Hz. Decoding was higher for cardinal than oblique orientations, with similar results also obtained for evoked MEG responses. In contrast to multivariate analyses, orientation information was mostly absent in univariate signals: evoked and induced responses in early visual cortex were similar in all orientations, with only exception an inverse oblique effect observed in induced responses, such that cardinal orientations produced weaker oscillatory signals than oblique orientations. Taken together, our results showed multivariate methods are well suited for the analysis of gamma oscillations, with multivariate patterns robustly encoding orientation information and predominantly discriminating cardinal from oblique stimuli.

neuroscience↗

bioRxiv2017

The Structure Of Small Beta Barrels

0.The small {beta}-barrel is an ancient protein structural domain characterized by extremes: It features an extremely broad range of structural varieties, a deeply intricate evolutionary history, and it is associated with a bewildering array of biomolecular pathways and physiological functions. These and related features of this domain are described and analyzed herein. Specifically, we present a comprehensive, survey-based analysis of the structural properties of small {beta}-barrels (SBBs). We first consider the defining characteristics of the SBB fold, as well as the various systems of nomenclature used to describe it. In order to begin elucidating how such vast functional diversity is achieved by a relatively simple protein domain, we then explore the anatomy of the SBB fold and some of its representative structural variants. Many types of SBB proteins assemble into cyclic oligomers that act as the biologically-functional entity. These oligomers exhibit a great deal of plasticity even at the quaternary structural level--including homomeric and heteromeric assemblies, rings of variable subunit stoichiometries (pentamer, hexamer, etc.), as well as higher-order oligomers (e.g., double-rings) and fibrillar polymers. We conclude with three themes that emerge from the SBBs unique structure{leftrightarrow}function versatility.

bioinformatics↗

bioRxiv2017

Conserved properties of Drosophila Insomniac link sleep regulation and synaptic function

Sleep is an ancient animal behavior that is regulated similarly in species ranging from flies to mammals. Various genes that regulate sleep have been identified in invertebrates, but whether the functions of these genes are conserved in mammals remains poorly explored. Drosophila insomniac (inc) mutants exhibit severely shortened and fragmented sleep. Inc protein physically associates with the Cullin-3 (Cul3) ubiquitin ligase, and neuronal depletion of Inc or Cul3 strongly curtails sleep, suggesting that Inc is a Cul3 adaptor that directs the ubiquitination of neuronal substrates that regulate sleep. Three proteins similar to Inc exist in vertebrates--KCTD2, KCTD5, and KCTD17--but are uncharacterized within the nervous system and their functional conservation with Inc has not been addressed. Here we show that Inc and its mouse orthologs exhibit striking biochemical and functional interchangeability within Cul3 complexes. Remarkably, KCTD2 and KCTD5 restore sleep to inc mutants, indicating that they can substitute for Inc in vivo and engage its neuronal targets that impact sleep. Inc and its orthologs traffic similarly within fly and mammalian neurons and are present at synapses, suggesting that their substrates include synaptic proteins. Consistent with such a mechanism, inc mutants exhibit defects in synaptic structure and physiology, indicating that Inc is vital for both synaptic function and sleep. Our findings reveal that molecular functions of Inc are conserved through ~600 million years of evolution and support the hypothesis that Inc and its orthologs participate in an evolutionarily conserved ubiquitination pathway that links synaptic function and sleep regulation.\n\nAuthor summarySleep is ubiquitous among animals and is regulated in a similar manner across phylogeny, but whether conserved molecular mechanisms govern sleep is poorly defined. The Insomniac protein is vital for sleep in Drosophila and is a putative adaptor for the Cul3 ubiquitin ligase. We show that two mammalian orthologs of Insomniac can restore sleep to flies lacking Insomniac, indicating that the molecular functions of these proteins are conserved through evolution. Our comparative analysis reveals that Insomniac and its mammalian orthologs localize to neuronal synapses and that Insomniac impacts synaptic structure and physiology. Our findings suggest that Insomniac and its mammalian orthologs are components of an evolutionarily conserved ubiquitination pathway that links synaptic function and the regulation of sleep.

neuroscience↗

bioRxiv2017

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient

Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach.

bioinformatics↗

bioRxiv2017

The 3D genome organization of Drosophila melanogaster through data integration

Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of 3D genome structural models, it is important to integrate all available sources of experimental information about a genomes organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete 3D genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our 3D geome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about the genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of differnet chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. To our knowledge our approach is the first that allows systematic integration of Hi-C and lamina DamID data for complete 3D genome structure calculation, while also explicitly considering genome structural variability.

bioinformatics↗