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Quantitative omnigenic model discovers interpretable genome-wide associations
No full textAs their statistical power grows, genome-wide association studies (GWAS) have identified an increasing number of loci underlying quantitative traits of interest. These loci are scattered throughout the genome and are individually responsible only for small fractions of the total heritable trait variance. The recently proposed omnigenic model provides a conceptual framework to explain these observations by postulating that numerous distant loci contribute to each complex trait via effect propagation through intracellular regulatory networks. We formalize this conceptual framework by proposing the “quantitative omnigenic model” (QOM), a statistical model that combines prior knowledge of the regulatory network topology with genomic data. By applying our model to gene expression traits in yeast, we demonstrate that QOM achieves similar gene expression prediction performance to traditional GWAS with hundreds of times less parameters, while simultaneously extracting candidate causal and quantitative chains of effect propagation through the regulatory network for every individual gene. We estimate the fraction of heritable trait variance in cis- and in trans-, break the latter down by effect propagation order, assess the trans- variance not attributable to transcriptional regulation, and show that QOM correctly accounts for the low-dimensional structure of gene expression covariance. We furthermore demonstrate the relevance of QOM for systems biology, by employing it as a statistical test for the quality of regulatory network reconstructions, and linking it to the propagation of nontranscriptional (including environmental) effects
Toward a common interpretation of the 3Rs principles in animal research
No full textMany scientific breakthroughs have depended on animal research, yet the ethical concerns surrounding the use of animals in experimentation have long prompted discussions about humane treatment and responsible scientific practice. First articulated by Russell and Burch, the 3Rs Principles of Replacement, Reduction, and Refinement have gained widespread recognition as basic guidelines for animal research. Over time, the 3Rs have transcended the research community, influencing policy decisions, animal welfare advocacy and public perception of animal experimentation. Despite their broad acceptance, interpretations of the 3Rs vary substantially, shaping statutory frameworks at various levels, with both technical and practical impacts
Codes for adversaries: Between worst-case and average-case jamming
No full textOver the last 70 years, information theory and coding has enabled communication technologies that have had an astounding impact on our lives. This is possible due to the match between encoding/decoding strategies and corresponding channel models. Traditional studies of channels have taken one of two extremes: Shannon-theoretic models are inherently average-case in which channel noise is governed by a memoryless stochastic process, whereas coding-theoretic (referred to as “Hamming”) models take a worst-case, adversarial, view of the noise. However, for several existing and emerging communication systems the Shannon/average-case view may be too optimistic, whereas the Hamming/worstcase view may be too pessimistic. This monograph takes up the challenge of studying adversarial channel models that lie between the Shannon and Hamming extremes
Causal inference for multiple risk factors and diseases from genomics data
No full textStatistical causal learning in genomics relies on the instrumental variable method of
Mendelian Randomization (MR). Currently, an overwhelming number of MR studies
purport to show causal relationships among a wide range of risk factors and outcomes.
Here, we show that selecting instrument variables from genome-wide association study
estimates leads to high false discovery rates for many MR approaches, which can be
greatly reduced by employing a graphical inference approach which: (i) explicitly tests
instrumental variable assumptions; (ii) distinguishes direct from indirect factors in very
high-dimensional data; (iii) discriminates pleiotropic from trait-specific markers, controlling for LD genome-wide; (iv) accommodates rare variants and binary outcomes in a
principled way; and (v) identifies potential unobserved latent confounding. For 17 traits
and 8.4M variants recorded for 458,747 individuals in the UK Biobank, we show that
standard MR analysis gives an abundance of findings that disappear under stringent
assumption checks, with many relationships reflecting potential unmeasured confounding. This implies that mixtures of temporal precedence and potential for reverse-causality
prohibit understanding the underlying nature of phenotypic and genetic correlations in
biobank data. We propose that well-curated longitudinal records are likely needed and
that our approach provides a first-step toward robust principled screening for potential
causal links
ISTA Thesis
No full textAcross the tree of life, distinct designs of cellular membranes have evolved that are both stable
and flexible. In bacteria and eukaryotes this trade-off is accomplished by single-headed lipids
that self-assemble into flexible bilayer membranes. By contrast, archaea in many cases possess
both bilayer and double-headed, monolayer spanning bolalipids. This composition is believed
to enable extremophile archaea to survive harsh environments. Here, through the creation of a
minimal computational model for bolalipid membranes, we discover trade-offs when forming
membranes using lipids of a single type. Similar to living archaea, we can tune the stiffness of
bolalipid molecules. We find that membranes made out of flexible bolalipid molecules resemble
bilayer membranes as they can adopt U-shaped conformations to enable higher curvatures.
Conversely, rigid bolalipid molecules, like those found in archaea at higher temperatures,
preferentially take on a straight conformation to self-assemble into liquid membranes that are
stable, stiff, prone to pore formation, and which tear during membrane reshaping. Strikingly,
however, our analysis reveals that it is possible to achieve the best of both worlds – membranes
that are fluid, stable at high temperatures and flexible enough to be reshaped without leaking –
through the inclusion of a small fraction of bilayer lipids into a bolalipid membrane. Additionally,
the curvature-dependent softening of bolalipid membranes made of lipids with tension-sensitive
conformation can also enable high rigidity at low curvatures while softening at high curvatures,
making the membrane effectively a plastic material. Taken together, our study compares the
different membrane designs across the tree of life and indicates how combining lipids can be
used to resolve trade-offs when generating membranes for (bio)technological applications
Evidence of a Slower-Z effect in Schistosoma japonicum
No full textSex-linked and autosomal loci experience different selective pressures and
evolutionary dynamics. X (or Z) chromosomes are often hemizygous, as Y (or W)
chromosomes often degenerate. Such hemizygous regions can be under greater
efficacy of selection, as recessive mutations are immediately exposed to selection in
the heterogametic sex (the so-called Faster-X or Faster-Z effect). However, in young
non-recombining regions, Y/W chromosomes often have many functional genes, and
many X/Z-linked loci are therefore diploid. The sheltering of recessive mutations on
the X/Z by the Y/W homolog is expected to drive a Slower-X (Slower-Z) effect for
diploid X/Z loci, i.e. a reduction in the efficacy of selection. While the Faster-X effect
has been studied extensively, much less is known empirically about the evolutionary
dynamics of diploid X or Z chromosomes. Here, we took advantage of published
population genomic data in the female-heterogametic human parasite Schistosoma
japonicum to characterize the gene content and diversity levels of the diploid and
hemizygous regions of the Z chromosome. We used different metrics of selective
pressures acting on genes to test for differences in the efficacy of selection in
hemizygous and diploid Z regions, relative to autosomes. We found consistent
patterns suggesting reduced Ne, and reduced efficacy of purifying selection, on both
hemizygous and diploid Z regions. Moreover, relaxed selection was particularly
pronounced for female-biased genes on the diploid Z, as predicted by Slower-Z
theory
LIPIcs
No full textAlgorithms with predictions is a new research direction that leverages machine learned predictions for algorithm design. So far a plethora of recent works have incorporated predictions to improve on worst-case bounds for online problems. In this paper, we initiate the study of complexity of dynamic data structures with predictions, including dynamic graph algorithms. Unlike online algorithms, the goal in dynamic data structures is to maintain the solution efficiently with every update.
We investigate three natural models of prediction: (1) δ-accurate predictions where each predicted request matches the true request with probability δ, (2) list-accurate predictions where a true request comes from a list of possible requests, and (3) bounded delay predictions where the true requests are a permutation of the predicted requests. We give general reductions among the prediction models, showing that bounded delay is the strongest prediction model, followed by list-accurate, and δ-accurate.
Further, we identify two broad problem classes based on lower bounds due to the Online Matrix Vector (OMv) conjecture. Specifically, we show that locally correctable dynamic problems have strong conditional lower bounds for list-accurate predictions that are equivalent to the non-prediction setting, unless list-accurate predictions are perfect. Moreover, we show that locally reducible dynamic problems have time complexity that degrades gracefully with the quality of bounded delay predictions. We categorize problems with known OMv lower bounds accordingly and give several upper bounds in the delay model that show that our lower bounds are almost tight.
We note that concurrent work by v.d.Brand et al. [SODA '24] and Liu and Srinivas [arXiv:2307.08890] independently study dynamic graph algorithms with predictions, but their work is mostly focused on showing upper bounds
BV solutions for mean curvature flow with constant angle: Allen-Cahn approximation and weak-strong uniqueness
No full textWe study weak solutions to mean curvature flow satisfying Young’s angle condition for general contact angles α ∈ (0, π). First, we construct BV solutions by using the Allen-Cahn approximation with boundary contact energy as proposed by Owen and Sternberg. Second, we prove the weak-strong uniqueness and stability for this solution concept. The main ingredient for both results is a relative energy, which can also be interpreted as a tilt excess
Fundamental Theories of Physics
No full textWe consider a gas of N bosons with interactions in the mean-field scaling regime. We review a recent proof of the asymptotic expansion of its spectrum and eigenstates and two applications of this result, namely the derivation of an Edgeworth expansion for fluctuations of one-body operators and the computation of the binding energy of an inhomogeneous Bose gas to any order. Finally, we collect related results for the dynamics of the weakly interacting Bose gas and for the regularized Nelson model
Toward the integration of speciation research
No full textSpeciation research—the scientific field focused on understanding the origin and diversity of species—has a long and complex history. While relevant to one another, the specific goals and activities of speciation researchers are highly diverse, and scattered across a collection of different perspectives. Thus, our understanding of speciation will benefit from efforts to bridge scientific findings and the diverse people who do the work. In this paper, we outline two ways of integrating speciation research: (i) scientific integration, through the bringing together of ideas, data, and approaches; and (ii) social integration, by creating ways for a diversity of researchers to participate in the scientific process. We then discuss five challenges to integration: (i) the multidisciplinary nature of speciation research, (ii) the complex language of speciation; (iii) a bias toward certain study systems; (iv) the challenges of working across scales; and (v) inconsistent measures and reporting standards. We provide practical steps that individuals and groups can take to help overcome these challenges, and argue that integration is a team effort in which we all have a role to play