Biology subjects

Rosset, S.

Publications and source records attributed to Rosset, S..

6 recordsLinked to original sources

bioRxiv2018

Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology

High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types. Corresponding software is available from: https://github.com/cozygene/TCA.

bioinformatics↗

bioRxiv2018

Boosting subdominant neutralizing antibody responses with a computationally designed epitope-focused immunogen

Throughout the last decades, vaccination has been key to prevent and eradicate infectious diseases. However, many pathogens (e.g. respiratory syncytial virus (RSV), influenza, dengue and others) have resisted vaccine development efforts, largely due to the failure to induce potent antibody responses targeting conserved epitopes. Deep profiling of human B-cells often reveals potent neutralizing antibodies that emerge from natural infection, but these specificities are generally subdominant (i.e., are present in low titers). A major challenge for next-generation vaccines is to overcome established immunodominance hierarchies and focus antibody responses on crucial neutralization epitopes. Here, we show that a computationally designed epitope-focused immunogen presenting a single RSV neutralization epitope elicits superior epitope-specific responses compared to the viral fusion protein. In addition, the epitope-focused immunogen efficiently boosts antibodies targeting the Palivizumab epitope, resulting in enhanced neutralization. Overall, we show that epitope-focused immunogens can boost subdominant neutralizing antibody responses in vivo and reshape established antibody hierarchies.

immunology↗

bioRxiv2018

Rosetta FunFolDes - a general framework for the computational design of functional proteins

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function, nevertheless, it remains a challenge for state-of-the-art methodologies. Here, we present a computational design approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins. We performed extensive benchmarks, where the most unexpected finding was that the design of function into proteins may not necessarily reside in the global minimum of the energetic landscape, which could have important implications in the field. We have computationally designed and experimentally characterized a distant structural template and a de novo \"functionless\" fold, two prototypical design challenges, to present important viral epitopes. Overall, we present an accessible strategy to repurpose old protein folds for new functions, which may lead to important improvements on the computational design of functional proteins.

bioinformatics↗

bioRxiv2018

Big data analysis of mitochondrial DNA substitution models: A regression approach elucidating the effects of codon position and neighboring nucleotides

We build on the up-to-date version of Phylotree, a comprehensive and continuously updating phylogeny of global human mtDNA variations (van Oven and Kayser 2009), to better understand the substitution mechanism of the mitochondrial DNA (mtDNA) and its most influential factors. We do so by composing Poisson and negative-binomial regression models relating the rate of occurrence of mtDNA substitutions to various factors. Important factors we identify include the identity of the codon at each position, confirming previous findings about the biological significance of different codons for the same amino acid. Importantly, we also identify a significant effect of neighboring sites. This effect cannot be attributed solely to CpG pairs. A similar effect of neighboring sites was recently described for autosomal DNA substitutions, and we speculate it is related to the basic mutational mechanism itself. Once codon composition and context are taken into account, there is no significant difference in substitution rate between different genes in mtDNA.

evolutionary biology↗

bioRxiv2018

Estimating Heritability and Genetic Correlation in Case Control Studies Directly and with Summary Statistics

Methods that estimate heritability and genetic correlations from genome-wide association studies have proven to be powerful tools for investigating the genetic architecture of common diseases and exposing unexpected relationships between disorders. Many relevant studies employ a case-control design, yet most methods are primarily geared towards analyzing quantitative traits. Here we investigate the validity of three common methods for estimating genetic heritability and genetic correlation. We find that the Phenotype-Correlation-Genotype-Correlation (PCGC) approach is the only method that can estimate both quantities accurately in the presence of important non-genetic risk factors, such as age and sex. We extend PCGC to work with summary statistics that take the case-control sampling into account, and demonstrate that our new method, PCGC-s, accurately estimates both heritability and genetic correlations and can be applied to large data sets without requiring individual-level genotypic or phenotypic information. Finally, we use PCGC-S to estimate the genetic correlation between schizophrenia and bipolar disorder, and demonstrate that previous estimates are biased due to incorrect handling of sex as a strong risk factor. PCGC-s is available at https://github.com/omerwe/PCGCs.

genetics↗

bioRxiv2017

An exact and efficient score test for variance components models

Testing for the existence of variance components in linear mixed models is a fundamental task in many applicative fields. In statistical genetics, the score test has recently become instrumental in the task of testing an association between a set of genetic markers and a phenotype. With few markers, this amounts to set-based variance component tests, which attempt to increase power in association studies by aggregating weak individual effects. When the entire genome is considered, it allows testing for the heritability of a phenotype, defined as the proportion of phenotypic variance explained by genetics. In the popular score-based Sequence Kernel Association Test (SKAT) method, the assumed distribution of the score test statistic is uncalibrated in small samples, with a correction being computationally expensive. This may cause severe inflation or deflation of p-values, even when the null hypothesis is true. Here, we characterize the conditions under which this discrepancy holds, and show it may occur also in large real datasets, such as a dataset from the Wellcome Trust Case Control Consortium 2 (n=13,950) study, and in particular when the individuals in the sample are unrelated. In these cases the SKAT approximation tends to be highly over-conservative and therefore underpowered. To address this limitation, we suggest an efficient method to calculate exact p-values for the score test in the case of a single variance component and a continuous response vector, which can speed up the analysis by orders of magnitude. Our results enable fast and accurate application of the score test in heritability and in set-based association tests. Our method is available in http://github.com/cozygene/RL-SKAT.

genetics↗