Dr. Sarit Avrani

We study the interactions between freshwater cyanobacteria and their phages (viruses) and grazers. Bloom-forming cyanobacteria are an increasing global phenomenon that negatively impacts aquatic environments worldwide. These blooms are formed by multicellular cyanobacteria that form filaments or colonies. These cyanobacteria can be controlled by viruses and grazers of different groups. These predators apply different, at times contradictory, top-down selective pressures. We are interested in the implications of these interactions on the genome evolution and ecology of the cyanobacteria. We aim to answer questions such as: How does selection by phages or/and grazers affect the evolution of the cyanobacteria genomes? Does this selection take any part in shaping the size/structure of the cyanobacteria? What is the role of these different predators in enabling and/or restricting the cyanobacterial blooms? How can these predators survive seasons with low cyanobacteria abundance? What are the molecular mechanisms that confer resistance to the different predators and what is their role in this ecosystem? What part does lysogeny and lateral gene transfer take in these interactions? In order to answer such questions, we will use whole genome sequencing and comparative expression assays using RNA-seq as well as physiological characterization using fluorescence microscopy and microbiological and molecular biology methods.

Prof. Smadar Ben-Tabou deLeon

Developmental programs are capable of generating similar morphologies despite genetic variations and within broad environmental conditions. This flexibility of the developmental program is essential for keeping a wide genotypic pool adaptable in a changing environment and thus for the survival of the species. Yet, some changes in gene expression cause the evolution of novel body plans and are necessary for biodiversity. We study the developmental transcriptional programs that underlie developmental stability amidst genetic and environmental change, and identify changes in developmental gene regulatory network that drive evolutionary novelties.

There are multiple projects in the lab in which you can join and contribute. You will gain extensive knowledge and skills in next generation sequencing, bioinformatics, mathematical modeling, molecular biology, imaging, and embryology.
  • Study the molecular basis of developmental stability and adaptation by comparing developmental transcriptomes of related echinoderm species
  • Vascular Endothelial Growth Factor (VEGF) and the regulation of larval skeletogenesis in the sea urchin embryo as a model system for angiogenesis and biomineralization.
  • Differential expression of ribosomal proteins and their function in translational regulation during development.

Prof. Mickey Kosloff

  • Deciphering the molecular basis for signal transduction
  • Molecular switches in cancer
  • Structural and computational biology, structural bioinformatics
  • Protein engineering and design
  • Specificity in drug design

Prof. Abraham B. Korol

Our lab is developing new methods and algorithms for genome mapping analysis. We are focusing on three major problems: building high density genetic maps, mapping quantitative trait loci (QTL), and physical mapping of complex genomes (ordering and anchoring fingerprinted BAC libraries). All these subjects are computing intensive and we develop new mathematical and statistical methods, as well as sophisticated algorithms for discrete optimization, network analysis, etc. I addition to the development of new analytical tools we are interested in analyzing real world data, to characterize the properties of recombination, patterns of genome sequence organization, genome expression, analysis of real population structures, etc. Ongoing research projects in the lab include:

  • Evolutionary adaptation to stressful environments using Drosophila as a model.
  • Population genetics of multilocus systems (including non-linear dynamics).
  • Recombination variability, evolution of sex and recombination.
  • Genome evolution and structure on the above-gene level.
  • Genome mapping, including multilocus mapping and physical mapping.
  • Genetics of quantitative traits and its evolutionary and practical applications.

Corresponding studies are based on intimate interaction between field observations, laboratory experimentation, and theoretical analysis (using both mathematical modeling and computer simulations). Beside Drosophila, our studies target also other organisms (in collaboration with other labs, both within and outside the Institute of Evolution) that include plants, fungi, mammals, and humans. The main fields of our activity are related to evolutionary genetics and genomics (experimental and theoretical), genome structural and functional analysis, and bioinformatics.


Dr. Martin Mikl

Gene Regulation and RNA Systems Biology

We aim to understand the regulation of gene expression in its full complexity using molecular, systems and cell biological tools and employing experimental and computational approaches. RNA is at the center of this regulatory complexity, every aspect of its lifecycle can be regulated, from its production and processing to its intracellular localization and degradation. 

We are utilizing our ability to synthesize large collections of DNA sequences to get to a comprehensive understanding of the rules dictating gene expression across regulatory layers. Testing rationally designed sequences in a systematic and high-throughput manner provides a powerful means to boost our ability to identify complex regulatory relationships. Based on these datasets, we are developing models predicting the effect of genetic variation across gene regulatory layers. 

This allows us to address the following questions:

  • How is the information, when and how every gene in a cell is expressed, encoded in the DNA? 
  • How do genetic mutations change normal functioning and ultimately lead to disease? 
  • How are the many molecular mechanisms coordinated to ensure proper functioning of the cell?

Dr. Eyal Privman

Insect societies are a unique model system for investigating the genetic and evolutionary mechanisms at the basis of animal sociality. We study social evolution in ants using genomic tools: next generation sequencing technologies and computational analysis of molecular evolution. 2011 was the year of the genomic revolution for ant research. We used to know close to nothing about the genes of ants and then full genomes of seven ant species were published. Ten years later and the number of sequenced ant species is well over a hundred. These genomic sequences allow us to compare different species and look for the genes responsible for the evolution of sociality in ants. Furthermore, recent dramatic advances in sequencing technologies allow us to use whole genome sequencing of many individuals as a routine tool for focused studies on the recent evolution of social traits in specific systems such as the “social chromosome” of the fire ant Solenopsis invicta, and more recently in additional species such as the local desert ant Cataglyphis niger.

We sequence hundreds of individuals from study populations and identify hundreds of thousands of polymorphic loci. We use a range of statistical inference methods to reconstruct the recent history of these populations, identify genomic regions that experienced adaptive evolution, and identify genomic regions associated with variations in social behavior and social organization. We focus especially on olfactory receptors that are involved in chemical communication (pheromones), the main mode of communication in ant colonies. Using such genomic methods and evolutionary analysis we can identify the genes responsible for the evolution of sociality.

Prof. Daniel Sher

Our lab studies “aquatic chemical ecology” – the way aquatic organisms communicate through chemistry, the chemicals that mediate these interactions, and the way these interactions and chemicals affect entire ecosystems. This is a fascinating field of research that combines ecology, limnology/oceanography, biochemistry, physics and computational biology. The computational biology aspects involve genomic and metagenomic analysis of marine bacteria, as well as phylogenetic analysis. In addition, studying these interactions often brings with it the discovery of novel chemical compounds which have biotechnological, pharmacological or medical uses – antibiotics, for example, are often synthesized by microorganisms in order to fight other microbes.  Some of the questions we are interested in are:  Do marine bacteria communicate using chemical signals? What are the roles of venom in jellyfish, sea anemones, coral and hydra? How do marine invertebrates protect themselves against pathogens?

Prof. Sagi Snir

Our research is focused on mathematical and algorithmic solutions to problems in bioinformatics, in particular in the field of evolution. The tools we use are from fields such as combinatorial optimization, statistics and probability, mathematics, and information theory. Our research is characterized by ample collaborations with researchers from broad disciplines under the general framework of a systematic analysis of evolutionary processes aiming at finding biologically significant patterns. Below are the main field we focus at:

Phylogenetics, the reconstruction of the evolutionary history of a group of species, is increasingly integrated into modern biological areas such as preventive medicine and epidemiology. Understanding the biological mechanisms underlying the observed evolution of pathogen species is crucial for devising effective control strategies for important human, animal and plant diseases. Moreover, in light of the high mutational and speciation rates among RNA viruses, extremely accurate modeling and reconstruction is called for. Maximum Likelihood (ML) is currently considered as the most accurate phylogenetic method. In past works I developed analytical solutions to ML reconstruction. The novelty of that approach was application of algebraic geometry tools for obtaining the solution. These works have since sparked a wave of interest in the field, in particular at UC Berkeley where I later took on a position as a postdoctoral research fellow.

Another field I am pursuing is supertree reconstruction that is used for large scale phylogenetic reconstruction. Here, we developed an extremely fast method that is inspired by ideas of finding a maximum cut in a weighted graph by means of semidefinite programming (SDP). The method is used by leading labs in the world and has yielded several publications, both practical and theoretical.

Horizontal gene transfer (HGT), the passage of genetic material between genetically distant organisms, is a significant factor in microbial evolution, driving the diversification and speciation of microorganisms, especially pathogens. HGT plays a role in the emergence of novel human diseases, as well as promoting the spread of antibiotic resistance in bacteria species. The unexpectedly high frequency of HGT among prokaryotes made it a topical area in microbiology and medical research. Our research of HGT proceeds along seemingly unrelated tracks. In the first, the phylogenetic track, we have formulated several rigorous frameworks to detect and analyze HGT. These works were the first to model realistically HGT. We formulated both combinatorial and statistical models for the HGT phenomenon.

On a second, the sequence based track, we seek for intrinsic clues for HGT in the organism genomes. The advantage here is the speed of the methods and the alleviation of tasks such as sequence alignment or phylogenetic reconstruction. The method is able to trace HGT events in a community of organisms.

Sequence alignment – the grouping of homologous bases into one column – is fundamental to almost any task in comparative genomics. This translates to positing gaps in the genomic sequences to account for events of insertions and deletions (indels). The interrelationship between sequence alignment and phylogenetic reconstruction has drawn substantial attention recently. We have developed a combinatorial (as opposed to statistical) approach based on indel history. The novelty of this approach is the distinguishing between insertions and deletions and augmenting the analysis a dimension of “depth” extending it from the sequence space.