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Made available in DSpace on 2021-06-25T10:17:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-03-01 The lack of consensus concerning the biological meaning of entropy and complexity of genomes and the different ways to assess these data hamper conclusions concerning what are the causes of genomic entropy variation among species. This study aims to evaluate the entropy and complexity of genomic sequences of several species without using homologies to assess relationships among these variables and non-molecular data (e.g., the number of individuals) to seek a trigger of interspecific genomic entropy variation. The results indicate a relationship among genomic entropy, genome size, genomic complexity, and the number of individuals: species with a small number of individuals harbors large genome, and hence, low entropy but a higher complexity. We defined that the complexity of a genome relies on the entropy of each DNA segment within genome. Then, the entropy and complexity of a genome reflects its organization solely. Exons of vertebrates harbor smaller entropies than non-exon regions (likely by the repeats that accumulated from duplications), whereas other taxonomic groups do not present this pattern. Our findings suggest that small initial population might have defined current genomic entropy and complexity: actual genomes are less complex than ancestral ones. Besides, our data disagree with the relationship between phenotype and genomic entropies previously established. Finally, by establishing the relationship between genomic entropy/complexity with the number of individuals and genome size, under an evolutive perspective, ideas concerning the genomic variability may emerge. Department of Bioprocess and Biotechnology São Paulo State University (Unesp), Avenida Universitária, 3780 Department of Developmental Genetics Max-Planck-Institut für Herz- Und Lungenforschung, Ludwigstr., 43 Department of Bioprocess and Biotechnology São Paulo State University (Unesp), Avenida Universitária, 3780

We pragmatically delineate the trait repertoire that enables organismal niche specialization. We based our approach on the tenet, derived from evolutionary and complex-system considerations, that genomic units that can significantly contribute to fitness in a certain habitat will be comparatively more complex in organisms specialized to that habitat than their genomic homologs found in organisms from other habitats. We tested this in cyanobacteria forming harmful water blooms, for which decades-long efforts in ecological physiology and genomics exist. Our results essentially confirm that genomics and ecology can be linked through comparative complexity analyses, providing a tool that should be of general applicability for any group of organisms and any habitat, and enabling the posing of grounded hypotheses regarding the ecogenomic basis for diversification., Water bloom development due to eutrophication constitutes a case of niche specialization among planktonic cyanobacteria, but the genomic repertoire allowing bloom formation in only some species has not been fully characterized. We posited that the habitat relevance of a trait begets its underlying genomic complexity, so that traits within the repertoire would be differentially more complex in species successfully thriving in that habitat than in close species that cannot. To test this for the case of bloom-forming cyanobacteria, we curated 17 potentially relevant query metabolic pathways and five core pathways selected according to existing ecophysiological literature. The available 113 genomes were split into those of blooming (45) or nonblooming (68) strains, and an index of genomic complexity for each strain’s version of each pathway was derived. We show that strain versions of all query pathways were significantly more complex in bloomers, with complexity in fact correlating positively with strain blooming incidence in 14 of those pathways. Five core pathways, relevant everywhere, showed no differential complexity or correlations. Gas vesicle, toxin and fatty acid synthesis, amino acid uptake, and C, N, and S acquisition systems were most strikingly relevant in the blooming repertoire. Further, we validated our findings using metagenomic gene expression analyses of blooming and nonblooming cyanobacteria in natural settings, where pathways in the repertoire were differentially overexpressed according to their relative complexity in bloomers, but not in nonbloomers. We expect that this approach may find applications to other habitats and organismal groups.