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bioRxiv2018

Non-linear phenotypic variation uncovers the emergence of heterosis in Arabidopsis thaliana

Heterosis describes the phenotypic superiority of hybrids over their parents in traits related to fitness. Understanding and predicting non-additive inheritance such as heterosis is crucial for evolutionary biology, as well as for plant and animal breeding. However, the physiological bases of heterosis remain debated. Moreover, empirical data in various species have shown that diverse genetic and molecular mechanisms are likely to explain heterosis, making it difficult to predict its emergence and amplitude from parental genotypes alone. In this study, we evaluated a model of physiological dominance proposed by Sewall Wright to explain the non-additive inheritance of metabolic fluxes at the cellular level. We used 450 hybrids derived from crosses among natural inbred accessions of Arabidopsis thaliana to test Wrights model for two fitness-related traits at the whole-plant level: growth rate and fruit number. We found that allometric relationships between traits constrain phenotypic variation in hybrids and inbreds to a similar extent. These allometric relationships behave predictably, in a non-linear manner, explaining up to 75% of heterosis amplitude, while genetic distance among parents at best explains 7%. Thus, our findings are consistent with Wrights model of physiological dominance on plant performance, and suggest that the emergence of heterosis is an intrinsic property of non-linear relationships between traits. Furthermore, our study highlights the potential of a geometric approach of phenotypic relationships for predicting heterosis of two major components of crop productivity and yield.

evolutionary biology↗

bioRxiv2015

A targeted subgenomic approach for phylogenomics based on microfluidic PCR and high throughput sequencing

Advances in high-throughput sequencing (HTS) have allowed researchers to obtain large amounts of biological sequence information at speeds and costs unimaginable only a decade ago. Phylogenetics, and the study of evolution in general, is quickly migrating towards using HTS to generate larger and more complex molecular datasets. In this paper, we present a method that utilizes microfluidic PCR and HTS to generate large amounts of sequence data suitable for phylogenetic analyses. The approach uses a Fluidigm microfluidic PCR array and two sets of PCR primers to simultaneously amplify 48 target regions across 48 samples, incorporating sample-specific barcodes and HTS adapters (2,304 unique amplicons per microfluidic array). The final product is a pooled set of amplicons ready to be sequenced, and thus, there is no need to construct separate, costly genomic libraries for each sample. Further, we present a bioinformatics pipeline to process the raw HTS reads to either generate consensus sequences (with or without ambiguities) for every locus in every sample or--more importantly--recover the separate alleles from heterozygous target regions in each sample. This is important because it adds allelic information that is well suited for coalescent-based phylogenetic analyses that are becoming very common in conservation and evolutionary biology. To test our subgenomic method and bioinformatics pipeline, we sequenced 576 samples across 96 target regions belonging to the South American clade of the genus Bartsia L. in the plant family Orobanchaceae. After sequencing cleanup and alignment, the experiment resulted in [~]25,300bp across 486 samples for a set of 48 primer pairs targeting the plastome, and [~]13,500bp for 363 samples for a set of primers targeting regions in the nuclear genome. Finally, we constructed a combined concatenated matrix from all 96 primer combinations, resulting in a combined aligned length of [~]40,500bp for 349 samples.

Evolutionary Biology↗

bioRxiv2017

A Spatially Localized Architecture for Fast and Modular Computation at the Molecular Scale

Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signaling networks. Here we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations, and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbors, identical DNA hairpins can be reused across circuits. Colocalization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate that our approach will motivate the use of spatial constraints in molecular engineering more broadly, bringing embedded molecular control circuits closer to applications.

synthetic biology↗

bioRxiv2017

A Systematic Analysis Of Atomic Protein-Ligand Interactions In The PDB

As the protein databank (PDB) recently passed the cap of 123,456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biological systems, but also to study the prevalence of structural patterns observed in a large body of unrelated structures, that may reflect rules governing protein folding or molecular recognition. Here, we compiled a list of 11,016 unique structures of small-molecule ligands bound to proteins - 6,444 of which have experimental binding affinity - representing 750,873 protein-ligand atomic interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extracted from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high number of C-H ...O hydrogen bonds or the relatively frequent amide-{pi} stacking between the backbone amide of proteins and aromatic rings of ligands, uncover underused ligand design strategies.

biophysics↗

bioRxiv2017

Single-Cell Reprogramming Of Mouse Embryo Development Through A Critical Transition State

Our work dealing with the temporal development of the genome-expression profile in single-cell mouse early embryo indicated that reprogramming occurs via a critical transition state, where the critical-regulation pattern of the zygote state disappears. In this report, we unveil the detailed mechanism of how the dynamic interaction of thermodynamic states (critical states) enables the genome system to pass through the critical transition state to achieve genome reprogramming.\n\nSelf-organized criticality (SOC) control of overall expression provides a snapshot of self-organization and explains the coexistence of critical states at a certain experimental time point. The time-development of self-organization is dynamically modulated by exchanges in expression flux between critical states through the cell nucleus milieu, where sequential global perturbations involving activation-inhibition of multiple critical states occur from the early state to the late 2-cell state. Two cyclic fluxes act as feedback flow and generate critical-state coherent oscillatory dynamics. Dynamic perturbation of these cyclic flows due to vivid activation of the ensemble of low-variance expression (sub-critical state) genes allows the genome system to overcome a transition state during reprogramming.\n\nOur findings imply that a universal mechanism of long-term global RNA oscillation underlies autonomous SOC control, and the critical gene ensemble at a critical point (CP) drives genome reprogramming. Unveiling the corresponding molecular players will be essential to understand single-cell reprogramming.

developmental biology↗

bioRxiv2018

A framework for large-scale dynamic metabolome drug profiling in mammalian cells: a case study analysis of the anti-cancer drug dichloroacetate

Metabolic profiling of cell line collections have become an invaluable tool to study disease etiology, drug modes of action and personalized medicine. However, large-scale in vitro dynamic metabolic profiling is limited by time-consuming sampling and complex measurement procedures. By adapting an MS-based metabolomics workflow for high-throughput profiling of diverse adherent mammalian cells, we establish a technique for the rapid measurement and analysis of drug-induced dynamic changes in intracellular metabolites. This methodology is scalable to large compound libraries and is here applied to study the mechanism underlying the toxic effect of dichloroacetate in ovarian cancer cell lines. System-level analysis of the metabolic responses revealed a key and unexpected role of CoA imbalance in dichloroacetate toxicity. The herein proposed strategy for large-scale drug metabolic profiling is complementary to other molecular profiling techniques, opening new scientific and drug-discovery opportunities.

systems biology↗

bioRxiv2018

The soft explosive model of placental mammal evolution

Recent molecular dating estimates for placental mammals echo fossil inferences for an explosive interordinal diversification, but typically place this event some 10-20 million years earlier than the Paleocene fossils, among apparently more \"primitive\" mammal faunas. However, current models of molecular evolution do not adequately account for parallel rate changes, and result in dramatic divergence underestimates for large, long-lived mammals such as whales and hominids. Calibrating among these taxa shifts the rate model errors deeper in the tree, inflating interordinal divergence estimates. We employ simulations based on empirical rate variation, which show that this \"error-shift inflation\" can explain previous molecular dating overestimates relative to fossil inferences. Molecular dating accuracy is substantially improved in the simulations by focusing on calibrations for taxa that retain plesiomorphic life-history characteristics. Applying this strategy to the empirical data favours the soft explosive model of placental evolution, in line with traditional palaeontological interpretations - a few Cretaceous placental lineages give rise to a rapid interordinal diversification following the 66 Ma Cretaceous-Paleogene boundary mass extinction. Our soft explosive model for the diversification of placental mammals brings into agreement previously incongruous molecular, fossil, and ancestral life history estimates, and closely aligns with a growing consensus for a similar model for bird evolution. We show that recent criticism of the soft explosive model relies on ignoring both experimental controls and statistical confidence, as well as misrepresentation, and inconsistent interpretations of morphological phylogeny. More generally, we suggest that the evolutionary properties of adaptive radiations may leave current molecular dating methods susceptible to overestimating the timing of major diversification events.

evolutionary biology↗

bioRxiv2018

Survival of the simplest: the cost of complexity in microbial evolution

The evolution of microbial and viral organisms often generates clonal interference, a mode of competition between genetic clades within a population. In this paper, we show that interference strongly constrains the genetic and phenotypic complexity of evolving systems. Our analysis uses biophysically grounded evolutionary models for an organisms quantitative molecular phenotypes, such as fold stability and enzymatic activity of genes. We find a generic mode of asexual evolution called phenotypic interference with strong implications for systems biology: it couples the stability and function of individual genes to the populations global speed of evolution. This mode occurs over a wide range of evolutionary parameters appropriate for microbial populations. It generates selection against genome complexity, because the fitness cost of mutations increases faster than linearly with the number of genes. Recombination can generate a distinct mode of sexual evolution that eliminates the superlinear cost. We show that positive selection can drive a transition from asexual to facultative sexual evolution, providing a specific, biophysically grounded scenario for the evolution of sex. In a broader context, our analysis suggests that the systems biology of microbial organisms is strongly intertwined with their mode of evolution.

evolutionary biology↗

bioRxiv2018

Diagnosis of Human Leptospirosis: High Resolution Melting Analysis for Direct Detection of Leptospira in the Early Stage of the Disease in a Clinical Setting

Currently, the direct detection of Leptospira infection can be done in clinical laboratories by a conventional nested polymerase chain reaction method (nested PCR), which is labourious and time-consuming. To overcome these drawbacks, we tested a set of paired samples of serum and urine from 202 patients presenting at a hospital located in an area endemic for leptospirosis using high resolution melting (HRM). The results were compared with those obtained by nested PCR for direct detection of the pathogen in both specimens and with the gold standard test used for indirect detection of anti-Leptospira antibodies in serum (the microscopic agglutination test, MAT). The HRM assay results were positive for 46/202 (22.7%) samples, whereas 47/202 (23.3%) samples were positive by nested PCR. As expected in recently infected febrile patients, MAT results were positive in only 3/46 (6.5%) HRM-positive samples. We did a unique comparative analysis using a robust biobank of paired samples of serum and urine from the same patient to validate the HRM assay for molecular diagnosis of human leptospirosis in a clinical setting. This assay fills a void unmet by serologic assays as it can detect the presence of Leptospira in biological samples even before development of antibody takes place.

microbiology↗

bioRxiv2018

Genome analysis of the unicellular eukaryote Euplotes vannus provides insights into mating type determination and tolerance to environmental stresses

As a model organism in studies of cell and environmental biology, the free-living and cosmopolitan ciliated protist Euplotes vannus has more than ten mating types (sexes) and shows strong resistance to environmental stresses. However, the molecular basis of its sex determination mechanism and how the cell responds to stress remain largely unknown. Here we report a combined analysis of de novo assembled high-quality macronucleus (MAC; i.e. somatic) genome and partial micronucleus (MIC; i.e. germline) genome of Euplotes vannus. Furthermore, MAC genomic and transcriptomic data from several mating types of E. vannus were investigated and gene expression levels were profiled under different environmental stresses, including nutrient scarcity, extreme temperature, salinity and the presence of free ammonia. We found that E. vannus, which possesses gene-sized nanochromosomes in its MAC, shares a similar pattern on frameshifting and stop codon usage as Euplotes octocarinatus and may be undergoing incipient sympatric speciation with Euplotes crassus. Somatic pheromone loci of E. vannus are generated from programmed DNA rearrangements of multiple germline macronuclear destined sequences (MDS) and the mating types of E. vannus are distinguished by the different combinations of pheromone loci instead of possessing mating type-specific genes. Lastly, we linked the resilience to environmental temperature change to the evolved loss of temperature stress-sensitive regulatory regions of HSP70 gene in E. vannus. Together, the genome resources generated in this study, which are available online at Euplotes vannus DB (http://evan.ciliate.org), provide new evidence for sex determination mechanism in eukaryotes and common pheromone-mediated cell-cell signaling and cross-mating.

genomics↗

bioRxiv2018

Transcriptome-wide association supplements genome-wide association in Zea mays

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The potential of using endophenotypes for dissecting traits of interest remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299 genotype and 7 tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation for agronomic and seed quality (carotenoid, tocochromanol) traits is regulatory. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits, beating the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This improves not only the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.\n\nAuthor summaryWe examined the ability to associate variability in gene expression directly with terminal phenotypes of interest, as a supplement linking genotype to phenotype. We found that transcriptome-wide association studies (TWAS) are a useful accessory to genome-wide association studies (GWAS). In a combined test with GWAS results, TWAS improves the capacity to re-detect genes known to underlie quantitative trait loci for kernel and agronomic phenotypes. This improves not only the capacity to link genes to phenotypes, but also illustrates the widespread importance of regulation for phenotype.

genetics↗

bioRxiv2018

Inducible formation of leading cells driven by CD44 switching gives rise to collective invasion

Collective invasion into adjacent tissue is a hallmark of luminal breast cancer, with about 20% of cases that eventually undergo metastasis. It remained unclear how less aggressive luminal-like breast cancer transit to invasive cancer. Our study revealed that CD44hi cancer cells are the leading subpopulation in collective invading cancer cells, which could efficiently lead the collective invasion of CD44lo/follower cells. CD44hi/leading subpopulation showed specific gene signature of a cohort of hybrid epithelial/mesenchymal state genes and key functional co-regulators of collective invasion, which was distinct from CD44lo/follower cells. However, the CD44hi/leading cells, in partial-EMT state, were readily switching to CD44lo phenotype along with collective movements and vice versa, which is spontaneous and sensitive to tumor microenvironment. The CD44lo-to-CD44hi conversion is accompanied with a shift of CD44s-to-CD44v, but not corresponding to the conversion of non-CSC-to-CSC. Therefore, the CD44hi leader cells are not a stable subpopulation in breast tumors. This plasticity and ability to generate CD44hi carcinoma cells with enhanced invasion-initiating powers might be responsible for the transition from in situ to invasive behavior of luminal-type breast cancer.\n\nSignificanceNow, the mechanisms involved in local invasion and distant metastasis are still unclear. We identified a switch of CD44 that drives leader cell formation during collective invasion in luminal breast cancer. We provided evidence that interconversions between low and high CD44 states occur frequently during collective invasion. Furthermore, these findings demonstrated that the CD44hi/leader cells featuring partial EMT are inducible and attainable in response to tumor microenvironment. The CD44lo cancer cells are plastic that readily shift to CD44hi state, accompanied with shifts of CD44s-to-CD44v, thereby increasing tumorigenic and malignant potential. There are many \"non-invasiveness\" epithelial/follower cells with reversible invasive potential within an individual tumor, that casting some challenges on molecular targeting therapy.

cancer biology↗

bioRxiv2018

Cadherin-7 mediates proper neural crest cell-placodal neuron interactions during trigeminal ganglia assembly

The cranial trigeminal ganglia play a vital role in the peripheral nervous system through their relay of sensory information from the vertebrate head to the brain. These ganglia are generated from the intermixing and coalescence of two distinct cell populations: cranial neural crest cells and placodal neurons. Trigeminal ganglia assembly requires the formation of cadherin-based adherens junctions within the neural crest cell and placodal neuron populations; however, the molecular composition of these adherens junctions is still unknown. Herein, we aimed to define the spatio-temporal expression pattern and function of Cadherin-7 during early chick trigeminal ganglia formation. Our data reveal that Cadherin-7 is expressed exclusively in migratory cranial neural crest cells and is absent from trigeminal neurons. Using molecular perturbation experiments, we demonstrate that modulation of Cadherin-7 in neural crest cells influences trigeminal ganglia assembly, including the organization of neural crest cells and placodal neurons within the ganglionic anlage. Moreover, alterations in Cadherin-7 levels lead to changes in the morphology of trigeminal neurons. Taken together, these findings provide additional insight into the role of cadherin-based adhesion in trigeminal ganglia formation, and, more broadly, the molecular mechanisms that orchestrate the cellular interactions essential for cranial gangliogenesis.

developmental biology↗

bioRxiv2018

Structure and function of a bacterial gap junction analog

Multicellular lifestyle requires cell-cell connections. In multicellular cyanobacteria, septal junctions enable molecular exchange between sister cells and are required for cellular differentiation. The structure of septal junctions is poorly understood and it is unknown whether they regulate intercellular communication.\n\nHere we resolved the in situ architecture of septal junctions by electron cryotomography of cryo-focused ion beam-milled cyanobacteria. Septal junctions consisted of a tube traversing the septal peptidoglycan. Each tube end comprised a plug that was covered by a cytoplasmic cap. Fluorescence recovery after photobleaching showed that intercellular communication was blocked upon stress. This gating was accompanied by a conformational change of the septal junctions, mediated by the proteins FraC/D.\n\nWe provide the mechanistic framework for a cell junction that predates eukaryotic gap junctions by a billion years. The conservation of a gated dynamic mechanism across different domains of life emphasizes the importance of controlling molecular exchange, e.g. upon injury.

cell biology↗

bioRxiv2018

Cell growth dilutes the cell cycle inhibitor Rb to trigger cell division

Cell size is fundamental to function in different cell types across the human body because it sets the scale of organelle structures, biosynthesis, and surface transport1,2. Tiny erythrocytes squeeze through capillaries to transport oxygen, while the million-fold larger oocyte divides without growth to form the ~100 cell pre-implantation embryo. Despite the vast size range across cell types, cells of a given type are typically uniform in size likely because cells are able to accurately couple cell growth to division3-6. While some genes whose disruption in mammalian cells affects cell size have been identified, the molecular mechanisms through which cell growth drives cell division have remained elusive7-12. Here, we show that cell growth acts to dilute the cell cycle inhibitor Rb to drive cell cycle progression from G1 to S phase in human cells. In contrast, other G1/S regulators remained at nearly constant concentration. Rb is a stable protein that is synthesized during S and G2 phases in an amount that is independent of cell size. Equal partitioning to daughter cells of chromatin bound Rb then ensures that all cells at birth inherit a similar amount of Rb protein. RB overexpression increased cell size in tissue culture and a mouse cancer model, while RB deletion decreased cell size and removed the inverse correlation between cell size at birth and the duration of G1 phase. Thus, Rb-dilution by cell growth in G1 provides a long-sought cell autonomous molecular mechanism for cell size homeostasis.

cell biology↗

bioRxiv2019

APC2 is Critical for Ovarian WNT Signalling Control, Fertility and Tumour Suppression

Canonical WNT signalling plays a critical role in the regulation of ovarian development; mis-regulation of this key pathway in the adult ovary is associated with subfertility and tumourigenesis. The roles of Adenomatous polyposis coli 2 (APC2), a little-studied WNT signalling pathway regulator, in ovarian homeostasis, fertility and tumourigenesis have not previously been explored. Here, we demonstrate for the first time using constitutive APC2-knockout (Apc2-/-) mice, essential roles of APC2 in regulating ovarian WNT signalling and ovarian homeostasis. APC2-deficiency resulted in activation of ovarian WNT signalling and sub-fertility driven by intra-ovarian defects. Follicular growth was perturbed, resulting in a reduced rate of ovulation and corpora lutea formation, which could not be rescued by administration of gonadotrophins. Defects in steroidogenesis and follicular vascularity contributed to the subfertility phenotype. Tumour incidence was assessed in aged APC2-deficient mice, which also carried a hypomorphic Apc allele. APC2-deficiency in these mice resulted in predisposition to granulosa cell tumour (GCT) formation, accompanied by acute tumour-associated WNT-signalling activation and a histologic pattern and molecular signature seen in human adult GCTs. Hence, APC2 has an important tumour-suppressor activity within ovarian granulosa cells, most likely due to its role in regulating WNT-signalling. Importantly, given that the APC2-deficient tumours recapitulate the molecular signature and histological features of human adult GCTs, this APC2-deficient mouse has excellent potential as a pre-clinical model to study ovarian tumour biology and for therapeutic testing.

cancer biology↗

bioRxiv2017

TreeTime: maximum likelihood phylodynamic analysis

Mutations that accumulate in the genome of replicating biological organisms can be used to infer their evolutionary history. In the case of measurably evolving organisms genomes often reveal their detailed spatiotemporal spread. Such phylodynamic analyses are particularly useful to understand the epidemiology of rapidly evolving viral pathogens. The number of genome sequences available for different pathogens, however, has increased dramatically over the last couple of years and traditional methods for phylodynamic analysis scale poorly with growing data sets. Here, we present TreeTime, a Python based framework for phylodynamic analysis using an approximate Maximum Likelihood approach. TreeTime can estimate ancestral states, infer evolution models, reroot trees to maximize temporal signals, estimate molecular clock phylogenies and population size histories. The run time of TreeTime scales linearly with data set size.

evolutionary biology↗

bioRxiv2016

Systems Biomedicine of Rabies Delineates the Affected Signaling Pathways

The prototypical neurotropic virus, rabies, is a member of the Rhabdoviridae family that causes lethal encephalomyelitis. Although there have been a plethora of studies investigating the etiological mechanism of the rabies virus and many precautionary methods have been implemented to avert the disease outbreak over the last century, the disease has surprisingly no definite remedy at its late stages. The psychological symptoms and the underlying etiology, as well as the rare survival rate from rabies encephalitis, has still remained a mystery. We, therefore, undertook a systems biomedicine approach to identify the network of gene products implicated in rabies. This was done by meta-analyzing whole-transcriptome microarray datasets of the CNS infected by strain CVS-11, and integrating them with interactome data using computational and statistical methods. We first determined the differentially expressed genes (DEGs) in each study and horizontally integrated the results at the mRNA and microRNA levels separately. A total of 61 seed genes involved in signal propagation system were obtained by means of unifying mRNA and microRNA detected integrated DEGs. We then reconstructed a refined protein-protein interaction network (PPIN) of infected cells to elucidate biological signaling transduction pathways affected by rabies virus. To validate our findings, we confirmed differential expression of randomly selected genes in the network using Real-time PCR. In conclusion, the identification of seed genes and their network neighborhood within the refined PPIN can be useful for demonstrating signaling pathways including interferon circumvent, toward proliferation and survival, and neuropathological clue, explaining the intricate underlying molecular neuropathology of rabies infection and thus rendered a molecular framework for predicting potential drug targets.

Systems Biology↗