Program Abstracts


Identification and visualization of splicing bias from single cell RNA sequencing

Tal Shay BGU

Single cell RNA sequencing (scRNA-seq) has revolutionized the understanding of cell population heterogeneity in many biological fields, including immunology. While the number of available scRNA-seq datasets increases fast, the availability of analysis methods is lagging behind. We have created JingleBells, a repository of publicly available scRNA-seq datasets in a uniform annotated BAM format. That format is readily visible in IGV, a popular tool for RNA-seq visualization. This repository is accompanied by a suit of methods to identify splicing bias, where the single cell isoform usage is significantly different from the population level usage. I will describe the methods and their application to several publicly available immune datasets, and identify cases where isoforms usage is  regulated at the single cell level by a non-negligible proportion of the cells.

Dynamic Regulation of Chaperone Interaction Networks

Reut Shalgi, Technion

Protein homeostasis, the balance between protein synthesis, folding, localization and degradation, is a core principal that living organisms strive to maintain. Cells and organisms live in a continuously changing environment, and are required to constantly respond and adapt to various environmental cues. Thus, cells have evolved complex mechanisms to control protein homeostasis, at the hearts of which are the master regulators of protein folding and aggregation, molecular chaperones. We recently discovered that, in mammalian cells, dynamic association of chaperones with the ribosome serves to mediate translational control in response to proteotoxic stress. Using high-throughput LUMIER protein-protein interaction assays, we map chaperone interaction networks and explore their dynamics in response to changing cellular environments, and during disease states. We are generating and combining transcriptome-wide expression and translation data, with protein-protein interaction networks, towards the goal of gaining new insights into regulation of protein homeostasis under challenging environments. 

Non-functional protein interactions in crystal structures and in the cell

Emmanuel Levy – Weizmann

Proteins are naturally sticky objects, a fact reflected in the ~100,000 crystallographic structures solved to date. In order to form a crystal, a protein must indeed establish several surfaces of contact with copies of itself. The formation of so-called crystal contacts limits our ability to interpret structural data because it is hard to distinguish these non-functional interactions from real, biological ones. In a first part of the presentation, I will present a novel strategy to reliably discriminate between biological and non-biological interactions in crystal structures. In a second part of the presentation, I will present an analysis of protein sequences showing that non-functional interactions are selected against in cells. We will see how human and yeast proteins tune their sequence to minimize such non-functional interactions.

A needle in a haystack – computer science at the service of (meta) genomics

Noam Shental – OU

This talk presents several examples how group testing and compressed sensing assist in addressing practical problems in genomics and metagenomics. I will describe a method for efficient screening of large populations for carriers of either de novo or known rare mutations. In the context of metagenomics, I will describe a method for efficiently creating a library of all bacteria in a certain niche. 

Patterns of mutations in B cells reveal adaptive immune dynamics in health and disease.

Gur Yaari - BIU

Recent dramatic advances in high-throughput sequencing technologies have revolutionized the way scientific research is done. We are now capable of measuring features of immune responses, by sequencing the repertoires of human lymphocyte (T and B cells) receptors, on a scale never imagined before. As a consequence, the generation of big data sets has become routine and there is an urgent need for computational and analytical approaches to extract valuable biological information from these extremely large data sets. We and others have developed specific computational methods tailored for antibody (B cell receptor) repertoire analyses. Applying this suite of tools to antibody repertoire sequencing data reveals a more complete picture about the dynamics of the adaptive immune response in various clinical conditions. Here, I will demonstrate two examples of the applicability of these computational tools in the context of multiple sclerosis and celiac disease, and present my view about the future and challenges of this emerging field.

Analysis of rare variants in humans: from population genetics to association studies

Or Zuk - HUJI

Recent exome and whole genome sequencing enables, for the first time, a systematic analysis of rare variants and their association with common human traits. However, the methodology for association analysis of rare variants is not well established, mainly due to the need to aggregate multiple variants when testing for association.

We study rare variants from a population genetics perspective, and determine the effect of selection and demographics on the pathogenicity of single alleles.

We propose a simple two-class model for exonic rare variants, in which missense alleles are either benign, or have an effect on both fitness and phenotype. We fit the model parameters and use them to design association tests for rare variants with improved power.

We demonstrate the benefits of our model and our proposed tests by analyzing an early-onset myocardial exome sequencing dataset, and analyze the contribution of LDLR and APOA5 to disease risk.

Finally, we use recent large-scale exome sequencing data to estimate gene-specific and population-specific parameters in these models, offering new insights into selection forces acting on human genes, in addition to improved tests for association.

Combining DNA and RNA Information for Personalized Medicine

Noam Shomron – TAU

Next-generation sequencing (NGS) has probably been the most important tool for genomic research over the past few years. NGS has led to numerous discoveries and scientific breakthroughs in the genetic field. The sequencing technology is shifting from the research laboratory to the clinical arena. Multiple NGS protocols are used for reading both DNA and RNA molecules. I will present our integrative view achieved when measuring the levels of both DNA and RNA in a given tissue. This mapping is of potential relevance for treatment, leading to effective Personalized Medicine.

The next revolution in genomics: exploring complex genome assembly to pan-genome construction

Omer Barad - NRGene

Accurate and cost-effective de novo assembly of even the most complex genomes is now in reach. The talk will describe the successful full de-novo assembly of the hexaploid 16 Gb bread wheat genome and its wild relatives using NRGene's DenovoMAGICTM 2.0 tool.
The ability to assemble multiple wheat genomes in a most efficient manner paved the way to unravel the broad genomic diversity employed in breeding. Comparing the full genomic sequences of multiple varieties using GenoMAGIC tool will enable to reveal the full genomic diversity and construct a pangenome. The pangenome will be used to impute the full genome sequence of each wheat-derived line within large populations from a very low cost genotyping data, to enhance trait mapping, gene discovery and genomic selection.


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