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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

A transcriptome and literature guided algorithm for reconstruction of pathways to assess activity of telomere maintenance mechanisms

Activation of telomere maintenance mechanisms (TMMs) is a crucial factor for indefinite proliferation of cancer cells. The most common TMM is based on the action of telomerase, but in some cancers telomeres are elongated via homologous recombination based alternative mechanism (ALT). Despite their importance, little is known about TMM regulation and factors responsible for TMM phenotype choice in different cells. Currently, many studies address the involvement of few genes in TMMs, but a consensus unified picture of the full process is missing.\n\nWe have developed a computational biology framework combining knowledge- and data-driven approaches to aid in understanding of TMMs. It is based on a greedy algorithm with three core modules: (1) knowledge-based construction/modification of molecular pathways for telomerase-dependent and alternative TMMs, (2) coupled with gene expression data-based validation with an in-house pathway signal flow (PSF) algorithm, and (3) iteration of these two coupled steps until converging at pathway topologies that best reflect state of the art knowledge and are in maximum accordance with the data. We have used gene expression data derived from cell lines and tumor tissues and have performed extensive literature search and multiple cycles of greedy iterations until reaching TMM assessment accuracy of 100% and 77%, respectively.\n\nAvailability of TMM pathways that best reflect recent knowledge and data will facilitate better understanding of TMM processes. As novel experimental findings in TMM biology emerge, and new datasets are generated, our approach may be used to further expand/improve the pathways, possibly allowing for making distinctions not only between telomerase-dependent and ALT TMMs, but also among their different subtypes. Moreover, this method may be used for assessment of TMM phenotypes from gene expression data, which is crucial for studies where experimental detection of TMM states is missing. Furthermore, it can also be used to assess TMM activities in proliferating healthy cells.

bioinformatics↗
bioRxiv2017

Gene regulatory network rewiring by an adaptively evolving microRNA cluster in Drosophila

New miRNAs are evolutionarily important but their impact on existing biological networks remains unclear. We report the evolution of a microRNA cluster, mir-972C, that arose de novo and the subsequently rewired gene regulatory networks in Drosophila. Molecular evolution analyses revealed that mir-972C originated in the common ancestor of Drosophila where it comprises five old miRNAs. It subsequently recruited five new members in the melanogaster subgroup after conservative evolution for at least 50 million years. Population genetics analyses reveal that young and old mir-972C miRNAs evolved rapidly under positive selection in both seed and non-seed regions. Combining target prediction and cell transfection experiments, we find that sequence changes in individual mir-972C members resulted in extensive gene regulatory network divergence among D. melanogaster, D. simulans, and D. virilis, whereas the target pool of the cluster as a whole remains relatively conserved. Our results suggest that clustering of young and old miRNAs at the same locus broadens target repertoires, resulting in the gain of new targets without losing many old ones. This may facilitate the establishment of new miRNAs within existing regulatory networks.

evolutionary biology↗
bioRxiv2015

Digit evolution in gymnophthalmid lizards

BackgroundThe tetrapod limb is a highly diverse structure, and reduction of the limbs accounts for much of the phenotypes observed within species. Squamate reptiles represent one of the many lineages in which the limbs have been greatly modified from the pentadactyl generalized pattern; within the group, limb-reduced morphologies can vary from minor reductions in size of elements to complete limblessness, with several intermediate forms in between. Even though limb reduction is widespread, it is not clear what are the evolutionary and developmental mechanisms involved in the formation of reduced limb morphologies.\n\nMethodsIn this study, we present an overview of limb morphology within the microteiid lizard group Gymnophthalmidae, focusing on digit number.\n\nResultsWe show that there are two major groups of limb-reduced gymnophthalmids. The first group is formed by lizard-like - and frequently pentadactyl - species, in which minor reductions (such as the loss of 1-2 phalanges mainly in digits I and V) are the rule; these morphologies generally correspond to those seen in other squamates. The second group is formed by species showing more drastic losses, which can include the absence of an externally distinct limb in adults. We also show the expression patterns of Sonic Hedgehog (Shh) in the greatly reduced fore and hindlimb of a serpentiform gymnophthalmid.\n\nConclusionsOur discussion focus on identifying shared patterns of limb reduction among tetrapods, and explaining these patterns and the morphological variation within the gymnophthalmids based on the current knowledge of the molecular signaling pathways that coordinate limb development.

Developmental Biology↗
bioRxiv2016

Do aye-ayes echolocate? Studying convergent genomic evolution in a primate auditory specialist

Several taxonomically distinct mammalian groups - certain microbats and cetaceans (e.g. dolphins) - share both morphological adaptations related to echolocation behavior and strong signatures of convergent evolution at the amino acid level across seven genes related to auditory processing. Aye-ayes (Daubentonia madagascariensis) are nocturnal lemurs with a derived auditory processing system. Aye-ayes tap rapidly along the surfaces of dead trees, listening to reverberations to identify the mines of wood-boring insect larvae; this behavior has been hypothesized to functionally mimic echolocation. Here we investigated whether there are signals of genomic convergence between aye-ayes and known mammalian echolocators. We developed a computational pipeline (BEAT: Basic Exon Assembly Tool) that produces consensus sequences for regions of interest from shotgun genomic sequencing data for non-model organisms without requiring de novo genome assembly. We reconstructed complete coding region sequences for the seven convergent echolocating bat-dolphin genes for aye-ayes and another lemur. Sequences were compared in a phylogenetic framework to those of bat and dolphin echolocators and appropriate non-echolocating outgroups. Our analysis reaffirms the existence of amino acid convergence at these loci among echolocating bats and dolphins; we also detected unexpected signals of convergence between echolocating bats and both mice and elephants. However, we observed no significant signal of amino acid convergence between aye-ayes and echolocating bats and dolphins; our results thus suggest that aye-aye tap-foraging auditory adaptations represent distinct evolutionary innovations. These results are also consistent with a developing consensus that convergent behavioral ecology is not necessarily a reliable guide to convergent molecular evolution.

Evolutionary Biology↗
bioRxiv2016

Separating spandrels from phenotypic targets of selection in adaptive molecular evolution

There are many examples of adaptive molecular evolution in natural populations, but there is no existing method to verify which phenotypic changes were directly targeted by selection. The problem is that correlations between traits make it difficult to distinguish between direct and indirect selection. A phenotype is a direct target of selection when that trait in particular was shaped by selection to better perform a function. An indirect target of selection, also known as an evolutionary spandrel, is a phenotype that changes only because it is correlated with another trait under direct selection. Studies that mutate genes and examine the phenotypic consequences are increasingly common, and these experiments could estimate the mutational accessibility of the phenotypic changes that arise during an instance of adaptive molecular evolution. Under indirect selection, we expect phenotypes to evolve toward states that are more accessible by mutation. Deviation from this null expectation (evolution toward a phenotypic state rarely produced by mutation) would be compelling evidence of adaptation, and could be used to distinguish direct selection from indirect selection on correlated traits. To be practical, this molecular test of adaptation requires phenotypic differences that are caused by changes in a small number of genes. These kinds of genetically simple traits have been observed in many empirical studies of adaptive evolution. Here we describe how to use mutational accessibility to separate spandrels from direct targets of selection and thus verify adaptive hypotheses for phenotypes that evolve by adaptive molecular changes at one or a few genes.

Evolutionary Biology↗
bioRxiv2017

Genomics of cellular proliferation under periodic stress

Living systems control cell growth dynamically by processing information from their environment. Although responses to one environmental change have been intensively studied, little is known about how cells react to fluctuating conditions. Here we address this question at the genomic scale by measuring the relative proliferation rate (fitness) of 3,568 yeast gene deletion mutants in out-of-equilibrium conditions: periodic oscillations between two salinity conditions. Fitness and its genetic variance largely depended on the stress period. Surprisingly, dozens of mutants displayed pronounced hyperproliferation at short periods, identifying unexpected controllers of growth under fast dynamics. We validated the implication of the high-affinity cAMP phosphodiesterase and of a regulator of protein translocation to mitochondria in this control. The results illustrate how natural selection acts on mutations in a fluctuating environment, highlighting unsuspected genetic vulnerabilities to periodic stress in molecular processes that are conserved across all eukaryotes.

systems biology↗
bioRxiv2017

An efficient experiment design helps to identify differential expressed genes (DEGs) in RNA-seq data in studies of plant qualitative traits

In this study, we conducted comparative transcriptome analysis between homozygous dominant parent and heterozygous F1 hybrid with homozygous recessive parent in qualitative trait study of common wheat (Triticum aestivum L.). Two sets of near-isogenic lines (NILs) were used: one set of NILs carrying powdery mildew resistance and susceptible Pm2 alleles, the other set of NILs carrying different awn inhibition gene B1 alleles. The results demonstrated that 2,932 DEGs were identified between L031 (Pm2Pm2) and Chancellor (pm2pm2), while 1,494 DEGs presented between F1 hybrid (Pm2pm2) and Chancellor, the co-regulated DEGs were 1,028. For the wheat awn inhibition gene B1 test, 720 DEGs were identified between SN051-2 (B1B1) and SN051-1 (b1b1), and 231 DEGs were identified between F1 hybrid (B1b1) and SN051-1, the co-regulated DEGs were 180. Hierarchical clustering analysis of co-regulated DEGs showed that dominant parent and F1 hybrid were clustered as the nearest neighbors, while recessive parent showed an apparent departure. The results showed that the overlapping DEGs between dominant parent and F1 hybrid with recessive parent reduced the number of interested DEGs to only one-quarter (or one-third) of that between dominant and recessive parent, these overlapping loci could provide insights into molecular mechanisms that are affected by causal mutations.

plant biology↗
bioRxiv2017

RelTime relaxes the strict molecular clock throughout the phylogeny

The RelTime method estimates divergence times when evolutionary rates vary among lineages. Theoretical analyses show that RelTime relaxes the strict molecular clock throughout a molecular phylogeny, and it performs well in the analysis of empirical and computer simulated datasets in which evolutionary rates are variable. Lozano-Fernandez et al. (2017) found that the application of RelTime to one metazoan dataset (Erwin et al. 2011) produced equal rates for several ancient lineages, which led them to speculate that RelTime imposes a strict molecular clock for deep animal divergences. RelTime does not impose a strict molecular clock. The pattern observed by Lozano-Fernandez et al. (2017) was a result of the use of an option to assign the same rate to lineages in RelTime when the rates are not statistically significantly different. The median rate difference was 5% for many deep metazoan lineages for Erwin et al. (2011) dataset, so the rate equality was not rejected. In fact, RelTime analysis with and without the option to test rate differences produced very similar time estimates. We found that the Bayesian time estimates vary widely depending on the root priors assigned, and that the use of less restrictive priors produce Bayesian divergence times that are concordant with those from RelTime for Erwin et al. (2011) dataset. Therefore, it is prudent to discuss Bayesian estimates obtained under a range of priors in any discourse about molecular dating, including method comparisons.

evolutionary biology↗
bioRxiv2018

Improvements in the fossil record may largely resolve the conflict between morphological and molecular estimates of mammal phylogeny

Morphological phylogenies of mammals continue to show major conflicts with the robust molecular consensus view of their relationships. This raises doubts as to whether current morphological character sets are able to accurately resolve mammal relationships, particularly for fossil taxa for which, in most cases, molecular data is unlikely to ever become available. We tested this under a hypothetical \"best case scenario\" by using ancestral state reconstruction (under both maximum parsimony and maximum likelihood) to infer the morphologies of fossil ancestors for all clades present in a recent comprehensive molecular phylogeny of mammals, and then seeing what effect inclusion of these predicted ancestors had on unconstrained analyses of morphological data. We found that this resulted in topologies that are highly congruent with the molecular consensus, even when simulating the effect of incomplete fossilisation. Most strikingly, several analyses recovered monophyly of clades that have never been found in previous morphology-only studies, such as Afrotheria and Laurasiatheria. Our results suggest that, at least in principle, improvements in the fossil record may be sufficient to largely reconcile morphological and molecular phylogenies of mammals, even with current morphological character sets.

evolutionary biology↗
bioRxiv2018

Electron Cryo-Tomography Provides Insight into Procentriole Architecture and Assembly Mechanism

Centriole is an essential structure with multiple functions in cellular processes. Centriole biogenesis and homeostasis is tightly regulated. Using electron cryo-tomography (cryoET) we present the structure of procentrioles from Chlamydomonas reinhardtii. We identified a set of non-tubulin components attached to the triplet microtubule (MT), many are at the junctions of tubules likely to reinforce the triplet. We describe structure of the A-C linker that bridges neighboring triplets. We find that POC1 is an integral component of the A-C linker. Its conserved WD40 {beta}-propeller domain provides sites for attachment to other A-C linker components. The twist of A-C linker results in an iris diaphragm-like motion of the triplets in the longitudinal direction of procentriole. Finally, we identified two assembly intermediates at the growing ends of procentriole allowing us to propose a model for the procentriole assembly. Our results provide a comprehensive structural framework for understanding the molecular mechanisms underpinning procentriole biogenesis and assembly.

cell biology↗
bioRxiv2018

Rate variation in conserved noncoding DNA reveals regulatory pathways associated with social evolution

The evolutionary origins of eusociality represent increases in complexity from individual to caste-based, group reproduction. These behavioral transitions have been hypothesized to go hand-in-hand with an increased ability to regulate when and where genes are expressed. Bees have convergently evolved eusociality up to five times, providing a framework to test this hypothesis. To examine potential links between putative gene regulatory elements and social evolution, we compare alignable, non-coding sequences in eleven diverse bee species, encompassing three independent origins of reproductive division of labor and two elaborations of eusocial complexity. We find that rates of evolution in a number of non-coding sequences correlate with key social transitions in bees. Interestingly, while we find little evidence for convergent rate changes associated with independent origins of social behavior, a number of molecular pathways exhibit convergent rate changes in conjunction with subsequent elaborations of social organization. We also present evidence that many novel non-coding regions may have been recruited alongside the origin of sociality in corbiculate bees; these loci could represent gene regulatory elements associated with division of labor within this group. Thus, our findings are consistent with the hypothesis that gene regulatory innovations are associated with the evolution of eusociality and illustrate how a thorough examination of both coding and non-coding sequence can provide a more complete understanding of the molecular mechanisms underlying behavioral evolution.

evolutionary biology↗
bioRxiv2018

Antiviral Functions of ARGONAUTE Proteins During Turnip Crinkle Virus Infection Revealed by Image-based Trait Analysis in Arabidopsis

RNA-based silencing functions as an important antiviral immunity mechanism in plants. Plant viruses evolved to encode viral suppressors of RNA silencing (VSRs) that interfere with the function of key components in the silencing pathway. As effectors in the RNA silencing pathway, ARGONAUTE (AGO) proteins are targeted of by some VSRs, such as that encoded by Turnip crinkle virus (TCV). A VSR-deficient TCV mutant was used to identify AGO proteins with antiviral activities during infection. A quantitative phenotyping protocol using an image-based color trait analysis pipeline on the PlantCV platform, with temporal red, green and blue (RGB) imaging and a computational segmentation algorithm, was used to measure plant disease after TCV inoculation. This process captured and analyzed growth and leaf color of Arabidopsis plants in response to virus infection over time. By combining this quantitative phenotypic data with molecular assays to detect local and systemic virus accumulation, AGO2, AGO3, and AGO7 were shown to play antiviral roles during TCV infection. In leaves, AGO2 and AGO7 functioned as prominent non-additive, anti-TCV effectors, while AGO3 played a minor role. Other AGOs were required to protect inflorescence tissues against TCV. Overall, these results indicate that distinct AGO proteins have specialized, modular roles in antiviral defense across different tissues, and demonstrate the effectiveness of image-based phenotyping to quantify disease progression.\n\nAuthor SummaryPlant viruses caused substantial losses in crop production and quality worldwide. Precisely measuring plant health is critical for better understanding the mechanisms underlying plant virus and host interactions. Advances in high-resolution imaging technologies and deep-learning tools have made acquiring and analyzing \"big data\" of disease traits possible. In this study, we have developed a high-throughput, image-based trait phenotyping pipeline to quantify disease severity in Arabidopsis thaliana infected by Turnip Crinkle Virus (TCV). Our aim is to understand how the antiviral RNA silencing machinery is tuned to protect the host from invading virus infection. We focused on ARGONAUTE proteins, which are the effectors in the RNA silencing pathway. A mutant line of TCV with a dysfunctional silencing suppressor (P38) was used to investigate which ago mutation could compensate for the dysfunctional silencing suppressor and facilitate the development of disease symptoms. We demonstrated that specific AGO proteins contribute to protecting leaves from TCV infection in a non-additive manner. Our results also implied that distinct AGOs are required to function collectively to silence TCV in inflorescence tissues. More evidence is still needed to further understand how these antiviral AGOs interact with suppressor proteins molecularly during TCV infection.

plant biology↗
bioRxiv2015

On the identifiability of transmission dynamic models for infectious diseases

Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models causes two challenges: Firstly, the likelihood function of the models is generally not computable and computationally intensive simulation-based inference methods need to be employed. Secondly, the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences which are more driven by the prior assumptions than the data themselves. We here consider a popular and relatively simple, yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, presenting also some methodological advances regarding the inference. Using likelihood approximations, it is shown that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size which has generally been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision.

Bioinformatics↗
bioRxiv2017

Paleocene origin of the Neotropical lineage of cleptoparasitc bees Ericrocidini-Rhathymini (Hymenoptera, Apidae)

Cleptoparasitic bees abandoned the pollen collecting for their offspring and lay their eggs on other bees provisioned nests. Also known as cuckoo bees they belong to several lineages, especially diverse in Apinae. We focused on a lineage of Apinae cleptoparasitic bees, the clade Ericrocidini+Rhathymini, which attack nests of the oil-collecting bees. We sequenced five genes for a broad sampling in this clade plus a large outgroup and reconstruct phylogeny and divergence times. We confirmed the monophyly of the clade Ericrocidini+Rhathymini and its position inside the ericrocidine line, together with the tribes Protepeolini, Isepeolini and Coelioxoidini. Our results corroborate the current taxonomic classification. Ericrocis is the basal most lineage in Ericrocidini and the position of Acanthopus and the most diverse genus Mesoplia were inconclusive. Ericrocidini+Rhathymini diverged from Parepeolus aterrimus 74 mya in the Cretaceous. Considering the robust molecular evidence of their sister relationships, the striking differences on the first instar larvae morphology of the two groups are probably adaptations to the distinct nesting biology of their hosts. As other parasites in the ericrocidine line, both groups possess larvae adapted to kill the immature host and to feed on floral oil provisioned by the host female. The evolution of host specialization in the line Ericrocidini+Rhathymini retroced to the Eocene when they arose synchronously with their hosts, Centris and Epicharis.

evolutionary biology↗
bioRxiv2018

Systematic Elucidation and Validation of OncoProtein-Centric Molecular Interaction Maps

The largely incomplete and tissue-independent nature of cancer pathways represents a key limitation to the ability to elucidate mechanistic determinants of cancer phenotypes and to predict adaptive response to targeted therapy. To address these challenges, we propose replacing canonical cancer pathways with a more accurate, comprehensive, and context-specific architecture - dubbed a Protein-Centric molecular interaction Map (PC-Map) - representing modulators, effectors, and cognate binding-partners of any oncoprotein of interest. To reconstruct these complex molecular architectures de novo, we introduce a novel OncoSig algorithm. Validation of a lung adenocarcinoma specific (LUAD) KRAS-centric PC-Map recapitulated known KRAS biology and, more critically, identified a novel repertoire of proteins eliciting synthetic lethality in KRASG12D LUAD organoid cultures. Showing the generalizable nature of the algorithm, we elucidated PC-Maps for ten recurrently mutated oncoproteins, including KRAS, in distinct tumor contexts. This revealed a highly context-specific nature of cancers regulatory and signaling architectures to an unprecedented degree of resolution.

systems biology↗
bioRxiv2018

Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map.

Progress in olfactory research is currently hampered by incomplete knowledge about chemical receptive ranges of primary receptors. Moreover, the chemical logic underlying the arrangement of computational units in the olfactory bulb has still not been resolved. We undertook a large-scale approach at characterising molecular receptive ranges (MRRs) of glomeruli innervated by the MOR18-2 olfactory receptor in the dorsal olfactory bulb (dOB). Guided by an iterative approach that combined biological screening and machine learning, we selected 214 odorants to characterise the response of MOR18-2 and its neighbouring glomeruli. We discovered several previously unknown odorants activating MOR18-2 glomeruli, and we obtained detailed MRRs of MOR18-2 glomeruli and their neighbours. Physico-chemical MRR descriptions revealed that the spatial layout of glomeruli followed a chemical logic. Our results confirm earlier findings that demonstrate a partial chemical map underlying glomerular arrangement in the dOB. Moreover, our novel methodology that combines machine learning and physiological measurements lights the way towards future high-throughput studies to deorphanise and characterise structure-activity relationships in olfaction.

neuroscience↗
bioRxiv2014

Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli

A widely studied problem in systems biology is to predict bacterial phenotype from growth conditions, using mechanistic models such as flux balance analysis (FBA). However, the inverse prediction of growth conditions from phenotype is rarely considered. Here we develop a computational framework to carry out this inverse prediction on a computational model of bacterial metabolism. We use FBA to calculate bacterial phenotypes from growth conditions in E. coli, and then we assess how accurately we can predict the original growth conditions from the phenotypes. Prediction is carried out via regularized multinomial regression. Our analysis provides several important physiological and statistical insights. First, we show that by analyzing metabolic end products we can consistently predict growth conditions. Second, prediction is reliable even in the presence of small amounts of impurities. Third, flux through a relatively small number of reactions per growth source (~10) is sufficient for accurate prediction. Fourth, combining the predictions from two separate models, one trained only on carbon sources and one only on nitrogen sources, performs better than models trained to perform joint prediction. Finally, that separate predictions perform better than a more sophisticated joint prediction scheme suggests that carbon and nitrogen utilization pathways, despite jointly affecting cellular growth, may be fairly decoupled in terms of their dependence on specific assortments of molecular precursors.

Systems Biology↗