Graph Based Analysis for Gene Segment Organization In a Scrambled Genome

TL;DR

This paper introduces a graph-based method combined with topological data analysis to study complex gene segment arrangements in scrambled genomes, revealing intricate interleaving and overlapping patterns.

Contribution

The paper presents a novel approach using directed graphs and topological data analysis to characterize gene segment organization in highly scrambled genomes.

Findings

Identification of star-like graph structures indicating interleaving of gene segments

Detection of segments containing multiple other gene segments within a single gene

Observation of mutual interleaving among up to six genes

Abstract

DNA rearrangement processes recombine gene segments that are organized on the chromosome in a variety of ways. The segments can overlap, interleave or one may be a subsegment of another. We use directed graphs to represent segment organizations on a given locus where contigs containing rearranged segments represent vertices and the edges correspond to the segment relationships. Using graph properties we associate a point in a higher dimensional Euclidean space to each graph such that cluster formations and analysis can be performed with methods from topological data analysis. The method is applied to a recently sequenced model organism \textit{Oxytricha trifallax}, a species of ciliate with highly scrambled genome that undergoes massive rearrangement process after conjugation. The analysis shows some emerging star-like graph structures indicating that segments of a single gene can interleave, or even contain all of the segments from fifteen or more other genes in between its segments. We also observe that as many as six genes can have their segments mutually interleaving or overlapping.