A Pluralistic Account of Homology: Adapting the Models to the Data

Abstract

Defining homologous genes is important in many evolutionary studies but raises obvious issues. Some of these issues are conceptual and stem from our assumptions of how a gene evolves, others are practical, and depend on the algorithmic decisions implemented in existing software. Therefore, to make progress in the study of homology, both ontological and epistemological questions must be considered. In particular, defining homologous genes cannot be solely addressed under the classic assumptions of strong tree thinking, according to which genes evolve in a strictly tree-like fashion of vertical descent and divergence and the problems of homology detection are primarily methodological. Gene homology could also be considered under a different perspective where genes evolve as “public goods,” subjected to various introgressive processes. In this latter case, defining homologous genes becomes a matter of designing models suited to the actual complexity of the data and how such complexity arises, rather than trying to fit genetic data to some a priori tree-like evolutionary model, a practice that inevitably results in the loss of much information. Here we show how important aspects of the problems raised by homology detection methods can be overcome when even more fundamental roots of these problems are addressed by analyzing public goods thinking evolutionary processes through which genes have frequently originated. This kind of thinking acknowledges distinct types of homologs, characterized by distinct patterns, in phylogenetic and nonphylogenetic unrooted or multirooted networks. In addition, we define “family resemblances” to include genes that are related through intermediate relatives, thereby placing notions of homology in the broader context of evolutionary relationships. We conclude by presenting some payoffs of adopting such a pluralistic account of homology and family relationship, which expands the scope of evolutionary analyses beyond the traditional, yet relatively narrow focus allowed by a strong tree-thinking view on gene evolution.

Evolution by Pervasive Gene Fusion in Antibiotic Resistance and Antibiotic Synthesizing Genes

“…Haggerty et al [11] described the method of using an N-rooted fusion graph to depict a more accurate representation of the evolutionary history of these non-transitive sequences. Following this method proposed by Haggerty et al [11], Seaview was used to construct two maximum likelihood trees. Using the alignment data, these trees were midpoint rooted and merged manually onto an N-rooted fusion graph using the Adobe Illustrator software (Adobe Systems, San Jose, CA, USA).…”

“…The domains act like blocks of lego and the proteins are shown to be sharing these blocks with each other. Overall, the connected component consists of communities ("Tribes" sensu Haggerty et al [11]) held together by composite genes. Within the proteins domains act like biological lego blocks collectively forming the overall protein.…”

“…Networks were traditionally used in non-scientific fields, for example, in the mapping of railroads [7] and more recently in friendship relationships on social network sites such as Facebook [8]. Recently, this approach has been adapted to better understand evolution [1,[9][10][11][12]. Through the use of SSNs, Halary et al [13] investigated a molecular dataset of 571,044 protein sequences from the three domains of life.…”

“…The structure and nature of SSNs are explicitly different to that of phylogenetic trees due to the inclusion of hybrid nodes [11]. Thus, SSNs can show extended relationships that would be impossible to see using phylogenetic trees.…”

“…The addition of hybrid nodes means that SSNs can display composite genes, which is the focus of the current manuscript. A composite gene may arise as a consequence of recombination events such as horizontal gene transfer, gene fusion or fission, hybridisation or domain shuffling, whereby two previously separate genes recombine to create a new single gene [11,17]. For the purpose of this article, the focus lies on composite genes that have evolved by gene remodelling.…”