Investigating the molecular mechanisms underpinning the arthropod segmentation clock

Biography

I am an evolutionary biologist with a particular interest in evolutionary genetics and the evolution of development in animals. I developed my passion for this field during my time in Sheffield where I did an integrated master’s degree in Biology (2013-17). After taking evolutionary genetics modules I became increasingly intrigued by how genetic changes confer phenotypic changes. This led me to joining Gareth Fraser’s evolutionary developmental research lab. There I was researching the molecular mechanisms of scale patterning in zebrafish in order to infer their evolutionary relationship with other ectodermal appendages in vertebrates. My time in the lab gave me my first taste of real life research and a deeper understanding of broader evolutionary concepts. I am now applying my lab experience and understanding of evolutionary theory to my project in Dr Andrew Peel’s lab here at Leeds.

My Project

Background

My PhD project is concerned with the evolution of segmentation in bilateral animals. Segmented body plans have evolved within three separate phyla (Annelid worms, arthropods, and vertebrates) separated by over 500 million years of evolution. This design principle is a large part of why these groups are some of the most successful and diverse animals on the planet. How body segments are initially patterned along the anterior-posterior axis of the animal, and how these patterning mechanisms have evolved is what is of interest to me.

Vertebrate somites (the embryonic precursors to the vertebrae and other associated structures) are patterned sequentially by a dynamic system termed the segmentation clock. This relies on single cell genetic oscillations whereby the expression of a gene repeatedly turns on and off via its own auto-repression. The period of these oscillations sets the timing of the clock and determines the size and number of segments. The oscillations are synchronised between neighbouring cells and form dynamic waves of gene expression that propagate anteriorly through the tissue from the tail bud as the embryo grows. As the waves reach the anterior end of the embryo, the oscillations slow down and the wave essentially becomes fixed in one position. The phase of the wave then determines the segment boundaries.

This system was originally thought to be unique to vertebrates, until a breakthrough paper (co-authored by my supervisor (Sarrazin, Peel and Averof, 2012)) discovered that arthropods also display dynamic waves of gene expression during segment patterning. It has since been established that a similar “segmentation clock” is ancestral to arthropods which has led to new theories regarding the evolution of segmentation in this phyla. In some higher order insects, including the primary arthropod model Drosophila, a seemingly very different, derived form of segment patterning has been adopted whereby segments are patterned almost simultaneously, rather than sequentially. However, new research from the Peel lab and collaborators is beginning to reconcile these different strategies and theorise how they may have evolved.

Aims

I am using the red flour beetle (Tibolium castaneum) as a model to investigate the molecular mechanisms underpinning the arthropod segmentation clock. Using a mixture of experimental techniques such as in situ hybridisations and RNA interference I am hoping to characterise the expression and regulatory interactions between a series of candidate genes. The primary candidate genes at present are members of the Hairy/enhancer of split gene family that are the core oscillators in the vertebrate segmentation clock. Identifying a similar role for these genes in arthropods would provide us with a remarkable case of convergent evolution at the molecular level and highlight the evolutionary significance of this gene family. I am also hoping that my project will contribute to current research into the evolution of simultaneous segmentation in arthropods and expand our understanding of gene regulatory network evolution and broader system dynamics.