Higher fitness yeast genotypes are less robust to deleterious mutations, bioRxiv, 2019-06-20
AbstractNatural selection drives populations towards higher fitness, but second-order selection for adaptability and mutational robustness can also influence the dynamics of adaptation. In many microbial systems, diminishing returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust they have distributions of fitness effects (DFEs) with lower mean and higher variance. These shifts in the DFE arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.
biorxiv evolutionary-biology 0-100-users 2019Motility induced fracture reveals a ductile to brittle crossover in the epithelial tissues of a simple animal, bioRxiv, 2019-06-20
ABSTRACTAnimals are characterized by their movement, and their tissues are continuously subjected to dynamic force loading while they crawl, walk, run or swim1. Tissue mechanics fundamentally determine the ecological niches that can be endured by a living organism2. While epithelial tissues provide an important barrier function in animals, they are subjected to extreme strains during day to day physiological activities, such as breathing1, feeding3, and defense response4. How-ever, failure or inability to withstand to these extreme strains can result in epithelial fractures5, 6 and associated diseases7, 8. From a materials science perspective, how properties of living cells and their interactions prescribe larger scale tissue rheology and adaptive response in dynamic force landscapes remains an important frontier9. Motivated by pushing tissues to the limits of their integrity, we carry out a multi-modal study of a simple yet highly dynamic organism, the Trichoplax Adhaerens10–12, across four orders of magnitude in length (1 µm to 10 mm), and six orders in time (0.1 sec to 10 hours). We report the discovery of abrupt, bulk epithelial tissue fractures (∼10 sec) induced by the organism’s own motility. Coupled with rapid healing (∼10 min), this discovery accounts for dramatic shape change and physiological asexual division in this early-divergent metazoan. We generalize our understanding of this phenomena by codifying it in a heuristic model, highlighting the fundamental questions underlying the debondingbonding criterion in a soft-active-living material by evoking the concept of an ‘epithelial alloy’. Using a suite of quantitative experimental and numerical techniques, we demonstrate a force-driven ductile to brittle material transition governing the morphodynamics of tissues pushed to the edge of rupture. This work contributes to an important discussion at the core of developmental biology13–17, with important applications to an emerging paradigm in materials and tissue engineering5, 18–20, wound healing and medicine8, 21, 22.
biorxiv biophysics 200-500-users 2019A neuronal signature for monogamous reunion, bioRxiv, 2019-06-19
AbstractPair bond formation depends vitally on neuromodulatory signaling within the nucleus accumbens, but the neuronal dynamics underlying this behavior remain unclear. Using in vivo Ca2+ imaging in monogamous prairie voles, we found that pair bonding does not elicit differences in overall nucleus accumbens Ca2+ activity. Instead, we identified distinct neuronal ensembles in this region recruited during approach to either a partner or novel vole. The partner-approach neuronal ensemble increased in size following bond formation, representing a substrate linked to bond formation and maturation.
biorxiv neuroscience 100-200-users 2019Compensatory sequence variation between trans-species small RNAs and their target sites, bioRxiv, 2019-06-19
AbstractTrans-species small regulatory RNAs (sRNAs) are delivered to host plants from diverse pathogens and parasites and can target host mRNAs. How trans-species sRNAs can be effective on diverse hosts has been unclear. Multiple species of the parasitic plant Cuscuta produce trans-species sRNAs that collectively target many host mRNAs. Confirmed target sites are nearly always in highly conserved, protein-coding regions of host mRNAs. Cuscuta trans-species sRNAs can be grouped into superfamilies that have variation in a three-nucleotide period. These variants compensate for synonymous-site variation in host mRNAs. By targeting host mRNAs at highly conserved protein-coding sites, and simultaneously expressing multiple variants to cover synonymous-site variation, Cuscuta trans-species sRNAs may be able to successfully target homologous mRNAs from diverse hosts.One Sentence SummaryThe parasitic plant Cuscuta produces a diverse set of sRNAs that compensate for sequence variation in mRNA targets in diverse hosts.
biorxiv plant-biology 0-100-users 2019Passenger Hotspot Mutations in Cancer, bioRxiv, 2019-06-19
AbstractHotspots, or mutations that recur at the same genomic site across multiple tumors, have been conventionally interpreted as strong universal evidence of somatic positive selection, unequivocally pinpointing genes driving tumorigenesis. Here, we demonstrate that this convention is falsely premised on an inaccurate statistical model of background mutagenesis. Many hotspots are in fact passenger events, recurring at sites that are simply inherently more mutable rather than under positive selection, which current background models do not account for. We thus detail a log-normal-Poisson (LNP) background model that accounts for variation in site-specific mutability in a manner consistent with models of mutagenesis, use this model to show that the tendency to generate passenger hotspots pervades all common mutational processes, and apply it to a ~10, 000 patient cohort from The Cancer Genome Atlas to nominate driver hotspots with far fewer false positives compared to conventional methods. As the biomedical community faces critical decisions in prioritizing putative driver mutations for deep experimental characterization to assess therapeutic potential, we offer our findings as a guide to avoid wasting valuable scientific resources on passenger hotspots.
biorxiv genomics 0-100-users 2019Towards a gold standard for benchmarking gene set enrichment analysis, bioRxiv, 2019-06-19
AbstractBackgroundAlthough gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc. In the absence of suitable gold standards, evaluations are commonly restricted to selected data sets and biological reasoning on the relevance of resulting enriched gene sets. However, this is typically incomplete and biased towards the goals of individual investigations.ResultsWe present a general framework for standardized and structured benchmarking of enrichment methods based on defined criteria for applicability, gene set prioritization, and detection of relevant processes. This framework incorporates a curated compendium of 75 expression data sets investigating 42 different human diseases. The compendium features microarray and RNA-seq measurements, and each dataset is associated with a precompiled GOKEGG relevance ranking for the corresponding disease under investigation. We perform a comprehensive assessment of 10 major enrichment methods on the benchmark compendium, identifying significant differences in (i) runtime and applicability to RNA-seq data, (ii) fraction of enriched gene sets depending on the type of null hypothesis tested, and (iii) recovery of the a priori defined relevance rankings. Based on these findings, we make practical recommendations on (i) how methods originally developed for microarray data can efficiently be applied to RNA-seq data, (ii) how to interpret results depending on the type of gene set test conducted, and (iii) which methods are best suited to effectively prioritize gene sets with high relevance for the phenotype investigated.ConclusionWe carried out a systematic assessment of existing enrichment methods, and identified best performing methods, but also general shortcomings in how gene set analysis is currently conducted. We provide a directly executable benchmark system for straightforward assessment of additional enrichment methods.Availability<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpbioconductor.orgpackagesGSEABenchmarkeR>httpbioconductor.orgpackagesGSEABenchmarkeR<jatsext-link>
biorxiv bioinformatics 100-200-users 2019