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Tumour suppressor genes fasta files for orthologous groups and hierarchical orthologous groups


Tejada-Martinez, Daniela; de Magalhães, João Pedro; Opazo, Juan C. (2021), Tumour suppressor genes fasta files for orthologous groups and hierarchical orthologous groups , Dryad, Dataset,


Cetaceans are the longest-living species of mammals and the largest in the history of the planet. They have developed mechanisms against diseases such cancer, although the underlying molecular bases of these remain unknown. The goal of this study was to investigate the role of natural selection in the evolution of 1077 tumour suppressor genes (TSGs) in cetaceans. We used a comparative genomic approach to analyse two sources of molecular variation in the form of dN/dS rates and gene copy number variation. We found a signal of positive selection in the ancestor of cetaceans within the CXCR2 gene, an important regulator of DNA-damage, tumour dissemination, and immune system. Further, in the ancestor of baleen whales, we found six genes exhibiting positive selection relating to such diseases as breast carcinoma, lung neoplasm (ADAMTS8) and leukaemia (ANXA1). The TSGs turnover rate (gene gain and loss) was almost 2.4-fold higher in cetaceans as compared to other mammals, and noticeably even faster in baleen whales. The molecular variants in TSGs found in baleen whales, combined with the faster gene turnover rate, could have favoured the evolution of their particular traits of anti-cancer resistance, gigantism and longevity. Additionally, we report 71 genes with duplications, of which 11 genes are linked to longevity (e.g. NOTCH3 and SIK1) and are important regulators of senescence, cell proliferation and metabolism. Overall, these results provide evolutionary evidence that natural selection in tumour suppressor genes could act on species with large body sizes and extended life span, providing novel insights into the genetic basis of disease resistance. 


Homology inference

We inferred homologous relationships between the 1077 tumour suppressor genes described for humans, which are available from publically accessible databases (Tumor Suppressor Gene Database, and the Tumor Associate Gene, (supplementary table 2), and the other 14 species included in our study using the program OMA standalone v.2.3.1 [37]. OMA standalone is a graph-based method that infers homology using strict pairwise sequence comparisons “all-against-all" based on evolutionary distances. It also has a survey of the relationships between species, which for this study were included a priori. We inferred two types of groupings: 1) OMA Groups (OG), containing the sets of orthologous genes (supplementary file 1), and 2) Hierarchical Orthologous Groups (HOGs, supplementary file 2). Briefly, tHOGs are those genes that have descended from a single ancestral gene within a species against which gene duplications and losses can be contrasted. This algorithm has previously shown high precision, minimising the errors in orthology assignment in comparison with other homology inference methods [38,39]. Using these HOGs groups, the number of copies of tumour suppressor genes was obtained on a per species basis.


Comisión Nacional de Investigación Científica y Tecnológica, Award: N°21170433

MECESUP, Award: AUS2003: Daniela Tejada Martinez

Fondo Nacional de Desarrollo Científico y Tecnológico, Award: 1160627

Ministerio de Economía, Fomento y Turismo, Award: Millennium Nucleus of Ion Channels Associated Diseases (MiNICAD)

The Biotechnology and Biological Sciences Research Council, Award: BB/R014949/1: AnAge

MECESUP, Award: AUS2003: Daniela Tejada Martinez