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Researchers
  • Dr.  Yuval Tabach
Dr Yuval Tabach
 
The Lab's Vision
Identify the genetic elements that make species resistant to extreme environments, cancer and aging.
Some of the major challenges in medicine, like increasing life span and reducing cancer have already been solved by nature, multiple times. Many species have evolved genetic mechanisms that make them resistant to cancer and some also show significantly long life span. Other species have developed extraordinary traits, such as resistance to hypoxia, ability to hibernate, regeneration of lost tissue or adaptation to extreme environments (Figure 1).
 
For example:
   •   The naked mole rat and Spalax are resistant to cancer and hypoxia and have a remarkable life span of more than 30 years.
   •   Wood frogs (Lithobates sylvaticus) are tolerant to freezing
   •   The Mexican walking fish (Ambystoma mexicanum) has an extraordinary ability for tissue regeneration.  
 
Using comparative genomics we can identify the genes that suppress cancer, have a role in aging and protect the organism under extreme environment.
 
A B​
Tardigrades (or water bears)

The naked mole rat
Figure 1: species across the tree of life have evolved to survive under extreme environments, to be resistant to cancer and to live significantly more than their relative species. A. Tardigrades (or water bears) are extremophile animals that can handle extreme levels of ionizing radiation at doses hundreds of times higher than the lethal dose for a human. They can go without food or water for more than 10 years and are tolerant to temperatures from -20C to 100C. B. The naked mole rat (in the image) and the blind mole rat, are small rodents that live in underground tunnels under low oxygen conditions. Through 40 million years of evolution, they have undergone structural and functional changes, which have made them resistant to cancer, tolerant to hypoxia and with an extremely long life span. 
 
 
Methodology and Research
Comparative genomics of hundreds of species to identify proteins function.
In the recent years we have been developing computational tools to simultaneously analyze genomes of hundreds of species. We have established a pipeline to identify proteins function, and assign them to biological pathways (Figure 2).
 
Validation in C. elegans – a powerful model organism
Using phylogenetic profile analysis and extensive amount of high-throughput and genomic data we identified novel proteins that have a key role in RNA interference. We validated and further analyzed our candidate genes, using two sensor C. elegans strains that turn bright when the RNAi machinery dysfunction. Using this approach we identified 88 new proteins in the small RNA machinery and found functional connection between the splicing machinery and RNAi. (Figure 2).
 
88 new proteins in the small RNA machinery and the functional connection between the splicing machinery and RNAi
Figure 2: our pipeline to identify 88 proteins that have a key role in RNA interference. Stage I – by Using 86 eukaryote genomes we identified list of genes that co-evolved with the known small RNA factors. This data was integrated with data from dozens of expression profiles, protein – protein interaction maps and RNAi screens to generate a list of candidate genes (see Tabach et al Nature, 2012). The 180 representative candidate genes were tested in C. elegans system using RNAi (stage ii). Using two different sensor C. elegans strains that express bright green GFP if the small RNA pathway is nonfunctional we identified 88 genes that are essential for the RNAi machinery function.
  
Identifying novel disease genes
We demonstrated that genes that belong to the same cancer pathways and diseases are significantly co-evolved (Figure 3) and using our method we were able to predict dozens of new disease and cancer genes (Tabach et al MSB, 2013). 
Genes associated with particular diseases have significantly higher coevolution scores ​Figure 3: Genes associated with particular diseases have significantly higher coevolution scores. The dots denote the random distribution of Co10 scores that emerge from a randomized set of 100 000 HPO gene sets. The color scale of the dots represents the number of random groups found at that position (red—one random group to purple when 410 random groups with the same size have the same Co10 score). The white lines represent the average of the random data (bold line) and 1–4 standard divisions from the average. Notice that there are a significant number of bona fide HPO groups with numbers of genes in those groups ranging from a few to hundreds that are far from the random expectation cloud of dots (Tabach et al MSB, 2013).
  
Currently we are analyzing the genomes of more than 450 species in order to identify the genes that have key role in cancer and aging as in variety of diseases such as Alzheimer or MD. In addition, we are working to understand the role of RNA toxicity on trinucleotide repeat disorders like Huntington, ataxia, Myotonic dystrophy and fragile X 
 
 
Research Projects
 
​Applying phylogenetic profile analysis, proteomic analysis, expression, and cancer patient genomic data to systematically identify new cancer genes
•​ ​Comparative genomics of long live species and centenarian data to identify longevity genes
•​
 
​Characterization of the crosstalk between the small RNA pathways, RNA splicing, Nonsense-Mediated Decay (NMD) and their association with human diseases
•​
​Understanding the role of RNA toxicity on trinucleotide repeat disorders like Huntington, ataxia, Myotonic dystrophy and fragile X
•​ ​Horizontal gene transfer in eukaryotes
•​
 
​The next step algorithm in phylogenetic profile analysis: more accurate, more species, publicly available and includes more genetic elements like mircoRNA and UCEs
 
 
 
ReferencesSusana Garcia, Yuval Tabach, et al. Identification of C. elegans trinucleotide repeat RNA toxicity pathways. Nature structural and molecular biology, 2014.
 
Schraga Schwartz, Sudeep D. Agarwala, Maxwell R. Mumbach, Marko Jovanovic, Philipp Mertins, Alexander Shishkin, Yuval Tabach, et al. High-resolution mapping reveals a conserved, widespread, dynamic meiotically regulated mRNA methylation program. Cell, 2013.
 
Yuval Tabach, Tamar Golan, et al. Human disease locus discovery and mapping to molecular pathways through phylogenetic profiling. Molecular Systems Biology, 2013.
 
Yuval Tabach, Allison Billi, et al. Identification of new small RNA pathway genes from correlated patterns of phylogenetic conservation and divergence. Nature, 2013.
 
Yuval Tabach*, Kogan I*, et al. Amplification of the 20q Chromosomal Arm Occurs Early in Tumorigenic Transformation and May Initiate Cancer. PLoS One, 2011.
 
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