Research

Overview

Image courtesy Kayser Creative

What makes each species unique? Research in The Carvunis Lab aims at understanding the molecular mechanisms of evolutionary change and innovation. Our approach is to examine systems biology in the light of evolution and evolution in the light of systems biology.

Systems biology is the study of biological networks. The information contained in the genome of every living cell encodes a specific set of biomolecules (eg. transcripts, proteins). These biomolecules interact with each other, with the genome and with the environment, forming intricate and dynamic networks that underlie all cellular processes. Biological networks define how organisms look and behave, whether they will die or thrive in different environments. Ultimately, biological networks influence the probability that genomic information will be propagated to the next generation. Thus studying networks will transform how we think about evolution.

Evolution is the process through which populations and species change over successive generations. We know a lot about how natural selection and random drift together govern the inheritance of genetic material. However, the mechanisms underpinning evolutionary innovation remain obscure. How do new genes appear? How do organisms adapt to changing environments? If biological networks performed their functions in the manner of predictable machines, they could not evolve. There must be organizational principles that make biological networks plastic and robust for evolutionary innovation to take place. We seek to discover what these principles are. Through this quest we hope to expand knowledge of how cells work and of how evolution works.

The research tools we rely on most are bioinformatics, yeast genetics and genomics. Generally though, we strive to foster an interdisciplinary and collaborative research environment where researchers can develop creative approaches to describe, engineer and predict the genetic and network-level determinants of species-specificity.

 

Where do genes come from?

The Birth of Venus, by Sandro Botticelli, Image Courtesy Artchive, 2016

It has become clear over the past decade that completely novel protein-coding genes can evolve de novo from the “dark matter” of the genome (non-genic sequences). A few years ago, we proposed that such de novo gene birth involves the existence and translation of transitory genetic elements that we called “proto-genes”. This work revealed that cellular networks involve many more biomolecules than we thought, and questioned how translation is regulated. We are now actively investigating how these proto-genes evolve and acquire novel functions.

How do cellular networks change?

Image Courtesy Kayser Creative, 2015

The dynamics of cellular network evolution have remained mysterious. Now that ‘omics data is becoming increasingly available for many species, we are able to start correlating genomic and network changes over time by developing “comparative interactomics” approaches. In recent work, we integrated disparate data sources to compare the evolutionary dynamics of transcriptional networks across animal lineages. We uncovered evidence that the rewiring of transcriptional networks in mammals, birds and insects takes place at the same rate over time, which is extremely surprising given the huge differences in reproduction and mutation rates between these animal classes. It is as if there was a transcriptional molecular clock shared across animals. We are investigating the implications of these findings.

Bioinformatics

The Vitruvian Rat, by GreenLabRat, Image Courtesy GreenLabRat at Deviant Art, 2016

We are developing predictive network models based on the concept of cellular hierarchies. We may one day use the resulting infrastructure to ask questions about biology like we use Siri in the iphone to ask questions about where to go for dinner. We plan to adapt this framework for comparative interactomics, with the goal of building an intelligent system for translating molecular information between human patients and model organisms used in biomedical research.