Mendelian randomization: a premature burial?
George Davey Smith
Mendelian randomization is a promising approach to help improve causal inference in observational studies, with widespread potential applications, including to prioritization of pharmacotherapeutic targets for evaluation in RCTs. From its initial proposal the limitations of Mendelian randomization approaches have been widely recognised and discussed, and recently Pickrell has reiterated these1. However this critique did not acknowledge recent developments in both methodological and empirical research, nor did it recognise many future opportunities for application of the Mendelian randomization approach. These issues are briefly reviewed here.
Evolution in spatial and spatiotemporal variable metapopulations changes a herbivore’s host plant rangeAnnelies De Roissart, Nicky Wybouw, David Renault, Thomas Van Leeuwen, Dries Bonte
The persistence and dynamics of populations largely depends on the way they are configured and integrated into space and the ensuing eco-evolutionary dynamics. We manipulated spatial and temporal variation in patch size in replicated experimental metapopulations of the herbivore mite Tetranychus urticae. Evolution over approximately 30 generations in the spatially and spatiotemporally variable metapopulations induced a significant divergence in life history traits, physiological endpoints and gene expression, but also a remarkable convergence relative to the stable reference patchy metapopulation in traits related to size and fecundity and in its transcriptional regulation. The observed evolutionary dynamics are tightly linked to demographic changes, more specifically frequent episodes of resource shortage, and increased the reproductive performance of mites on tomato, a challenging host plant. This points towards a general, adaptive stress response in stable spatial variable and spatiotemporal variable metapopulations that pre-adapts a herbivore arthropod to novel environmental stressors.
Collective Fluctuations in models of adaptation
Oskar Hallatschek, Lukas Geyrhofer
Subjects: Populations and Evolution (q-bio.PE); Statistical Mechanics (cond-mat.stat-mech); Biological Physics (physics.bio-ph)
The dynamics of adaptation is difficult to predict because it is highly stochastic even in large populations. The uncertainty emerges from number fluctuations, called genetic drift, arising in the small number of particularly fit individuals of the population. Random genetic drift in this evolutionary vanguard also limits the speed of adaptation, which diverges in deterministic models that ignore these chance effects. Several approaches have been developed to analyze the crucial role of noise on the expected dynamics of adaptation, including the mean fitness of the entire population, or the fate of newly arising beneficial deleterious mutations. However, very little is known about how genetic drift causes fluctuations to emerge on the population level, including fitness distribution variations and speed variations. Yet, these phenomena control the replicability of experimental evolution experiments and are key to a truly predictive understanding of evolutionary processes. Here, we develop an exact approach to these emergent fluctuations by a combination of computational and analytical methods. We show, analytically, that the infinite hierarchy of moment equations can be closed at any arbitrary order by a suitable choice of a dynamical constraint. This constraint regulates (rather than fixes) the population size, accounting for resource limitations. The resulting linear equations, which can be accurately solved numerically, exhibit fluctuation-induced terms that amplify short-distance correlations and suppress long-distance ones. Importantly, by accounting for the dynamics of sub-populations, we provide a systematic route to key population genetic quantities, such as fixation probabilities and decay rates of the genetic diversity.
BGT: efficient and flexible genotype query across many samples Heng Li
Subjects: Genomics (q-bio.GN)
Summary: BGT is a compact format, a fast command line tool and a simple web application for efficient and convenient query of whole-genome genotypes and frequencies across tens to hundreds of thousands of samples. On real data, it encodes the haplotypes of 32,488 samples across 39.2 million SNPs into a 7.4GB database and decodes a couple of hundred million genotypes per CPU second. The high performance enables real-time responses to complex queries.
Availability and implementation: https://github.com/lh3/bgt
The power of single molecule real-time sequencing technology in the de novo assembly of a eukaryotic genomeHiroaki Sakai, Naito Ken, Eri Ogiso-Tanaka, Yu Takahashi, Kohtaro Iseki, Chiaki Muto, Kazuhito Satou, Kuniko Teruya, Akino Shiroma, Makiko Shimoji, Takashi Hirano, Takeshi Itoh, Akito Kaga, Norihiko Tomooka
Second-generation sequencers (SGS) have been game-changing, achieving cost-effective whole genome sequencing in many non-model organisms. However, a large portion of the genomes still remains unassembled. We reconstructed azuki bean (Vigna angularis) genome using single molecule real-time (SMRT) sequencing technology and achieved the best contiguity and coverage among currently assembled legume crops. The SMRT-based assembly produced 100 times longer contigs with 100 times smaller amount of gaps compared to the SGS-based assemblies. A detailed comparison between the assemblies revealed that the SMRT-based assembly enabled a more comprehensive gene annotation than the SGS-based assemblies where thousands of genes were missing or fragmented. A chromosome-scale assembly was generated based on the high-density genetic map, covering 86% of the azuki bean genome. We demonstrated that SMRT technology, though still needed to be assisted by SGS data, can achieve a near-complete assembly of a eukaryotic genome.
Evolution of organismal stoichiometry in a 50,000-generation experiment with Escherichia coli
Caroline B. Turner, Brian D. Wade, Justin R. Meyer, Richard E. Lenski
Organismal stoichiometry refers to the relative proportion of chemical elements in the biomass of organisms, and it can have important effects on ecological interactions from population to ecosystem scales. Although stoichiometry has been studied extensively from an ecological perspective, little is known about rates and directions of evolutionary changes in elemental composition in response to nutrient limitation. We measured carbon, nitrogen, and phosphorus content of Escherichia coli evolved under controlled carbon-limited conditions for 50,000 generations. The bacteria evolved higher relative nitrogen and phosphorus content, consistent with selection for increased use of the more abundant elements. Total carbon assimilated also increased, indicating more efficient use of the limiting element. Altogether, our study shows that stoichiometry evolved over a relatively short time-period, and that it did so in a predictable direction given the carbon-limiting environment.
Improved ribosome-footprint and mRNA measurements provide insights into dynamics and regulation of yeast translation
David E Weinberg, Premal Shah, Stephen W Eichhorn, Jeffrey A Hussmann, Joshua B Plotkin, David P Bartel
Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a 10-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5′- untranslated regions. Collectively, our results reveal key features of translational control in yeast and provide a framework for executing and interpreting ribosome- profiling studies.