Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Growth of Biological Complexity from Prokaryotes to Hominids Reflected in the Human Genome.

ABSTRACT: The growth of complexity in evolution is a most intriguing phenomenon. Using gene phylostratigraphy, we showed this growth (as reflected in regulatory mechanisms) in the human genome, tracing the path from prokaryotes to hominids. Generally, the different regulatory gene families expanded at different times, yet only up to the Euteleostomi (bony vertebrates). The only exception was the expansion of transcription factors (TF) in placentals; however, we argue that this was not related to increase in general complexity. Surprisingly, although TF originated in the Prokaryota while chromatin appeared only in the Eukaryota, the expansion of epigenetic factors predated the expansion of TF. Signaling receptors, tumor suppressors, oncogenes, and aging- and disease-associated genes (indicating vulnerabilities in terms of complex organization and strongly enrichment in regulatory genes) also expanded only up to the Euteleostomi. The complexity-related gene properties (protein size, number of alternative splicing mRNA, length of untranslated mRNA, number of biological processes per gene, number of disordered regions in a protein, and density of TF-TF interactions) rose in multicellular organisms and declined after the Euteleostomi, and possibly earlier. At the same time, the speed of protein sequence evolution sharply increased in the genes that originated after the Euteleostomi. Thus, several lines of evidence indicate that molecular mechanisms of complexity growth were changing with time, and in the phyletic lineage leading to humans, the most salient shift occurred after the basic vertebrate body plan was fixed with bony skeleton. The obtained results can be useful for evolutionary medicine.

SUBMITTER: Vinogradov AE

PROVIDER: S-EPMC8583824 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Genome complexity in the coelacanth is reflected in its adaptive immune system.

Project description:We have analyzed the available genome and transcriptome resources from the coelacanth in order to characterize genes involved in adaptive immunity. Two highly distinctive IgW-encoding loci have been identified that exhibit a unique genomic organization, including a multiplicity of tandemly repeated constant region exons. The overall organization of the IgW loci precludes typical heavy chain class switching. A locus encoding IgM could not be identified either computationally or by using several different experimental strategies. Four distinct sets of genes encoding Ig light chains were identified. This includes a variant sigma-type Ig light chain previously identified only in cartilaginous fishes and which is now provisionally denoted sigma-2. Genes encoding ?/? and ?/? T-cell receptors, and CD3, CD4, and CD8 co-receptors also were characterized. Ig heavy chain variable region genes and TCR components are interspersed within the TCR ?/? locus; this organization previously was reported only in tetrapods and raises questions regarding evolution and functional cooption of genes encoding variable regions. The composition, organization and syntenic conservation of the major histocompatibility complex locus have been characterized. We also identified large numbers of genes encoding cytokines and their receptors, and other genes associated with adaptive immunity. In terms of sequence identity and organization, the adaptive immune genes of the coelacanth more closely resemble orthologous genes in tetrapods than those in teleost fishes, consistent with current phylogenomic interpretations. Overall, the work reported described herein highlights the complexity inherent in the coelacanth genome and provides a rich catalog of immune genes for future investigations.

| S-EPMC4110200 | biostudies-literature

The Complexity and Phylogenetic Continuity of Laughter and Smiles in Hominids.

Project description:Laughter and smiles are often, but not always, associated with positive affect. These expressions of humans help to promote social relationships as well as the development of cognitive and socio-emotional skills and they may have a positive impact on health and well-being, hereby covering a selection of fitness-relevant benefits. Both laughter and smiles of positive affect also occur early in human development and across cultures, suggesting deep roots in human biology. The present work provides an evolutionary reconstruction of the evolution of human laughter and smiles of positive affect in form and function, based on the principle of maximum parsimony. According to the Complexity and Continuity Hypothesis, human laughter and smiles of positive affect must have evolved within the context of play from ancestral species. Furthermore, ancestral ape laughter and their open-mouth faces must already have been complex in form and function and changed over time via categorically different phylogenetic pathways to become characteristic, effective, and pervasive behaviors of everyday social interactions in humans.

| S-EPMC8210476 | biostudies-literature

Genome-wide discovery of missing genes in biological pathways of prokaryotes.

Project description:BackgroundReconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called "missing gene" problem.MethodsWe present a novel pathway-expansion method for identifying additional genes that are possibly involved in a target pathway after pathway mapping, to fill holes caused by missing genes as well as to expand the mapped pathway model. The basic idea of the algorithm is to identify genes in the target genome whose homologous genes share common operons with homologs of any mapped pathway genes in some reference genome, and to add such genes to the target pathway if their functions are consistent with the cellular function of the target pathway.ResultsWe have implemented this idea using a graph-theoretic approach and demonstrated the effectiveness of the algorithm on known pathways of E. coli in the KEGG database. On all KEGG pathways containing at least 5 genes, our method achieves an average of 60% positive predictive value (PPV) and the performance is increased with more seed genes added. Analysis shows that our method is highly robust.ConclusionsAn effective method is presented to find missing genes in biological pathways of prokaryotes, which achieves high prediction reliability on E. coli at a genome level. Numerous missing genes are found to be related to known E. coli pathways, which can be further validated through biological experiments. Overall this method is robust and can be used for functional inference.

| S-EPMC3044263 | biostudies-literature

Revisiting the hypothesis of an energetic barrier to genome complexity between eukaryotes and prokaryotes.

Project description:The absence of genome complexity in prokaryotes, being the evolutionary precursors to eukaryotic cells comprising all complex life (the prokaryote-eukaryote divide), is a long-standing question in evolutionary biology. A previous study hypothesized that the divide exists because prokaryotic genome size is constrained by bioenergetics (prokaryotic power per gene or genome being significantly lower than eukaryotic ones). However, this hypothesis was evaluated using a relatively small dataset due to lack of data availability at the time, and is therefore controversial. Accordingly, we constructed a larger dataset of genomes, metabolic rates, cell sizes and ploidy levels to investigate whether an energetic barrier to genome complexity exists between eukaryotes and prokaryotes while statistically controlling for the confounding effects of cell size and phylogenetic signals. Notably, we showed that the differences in bioenergetics between prokaryotes and eukaryotes were less significant than those previously reported. More importantly, we found a limited contribution of power per genome and power per gene to the prokaryote-eukaryote dichotomy. Our findings indicate that the prokaryote-eukaryote divide is hard to explain from the energetic perspective. However, our findings may not entirely discount the traditional hypothesis; in contrast, they indicate the need for more careful examination.

| S-EPMC7062059 | biostudies-literature

Predicting the optimal growth temperatures of prokaryotes using only genome derived features.

Project description:MOTIVATION:Optimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study of a prokaryote, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences. RESULTS:By applying the reverse ecology principle that an organism's genome includes identifiable adaptations to its native environment, we can predict a species' optimal growth temperature with an accuracy of 5.17°C root-mean-square error and a coefficient of determination of 0.835. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known. AVAILABILITY AND IMPLEMENTATION:Source code, genomes analyzed and features calculated are available at: https://github.com/DavidBSauer/OGT_prediction. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

| S-EPMC6748728 | biostudies-literature

The biological complexity of RKIP signaling in human cancers.

Project description:The Raf kinase inhibitory protein (RKIP) has been demonstrated to modulate different intracellular signaling pathways in cancers. Studies have shown that RKIP is frequently downregulated in cancers; therefore, attempts have been made to upregulate the expression of RKIP using natural and synthetic agents for the treatment of human malignancies. Moreover, various regulators such as specific proteins and microRNAs (miRNAs) that are involved in the regulation of RKIP expression have also been identified. RKIP mechanistically modulates the apoptotic regulators of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) signaling. Because of its critical role in human cancers, RKIP has drawn much research attention, and our understanding is expanding rapidly. Here, we summarize some of the biological complexities of RKIP regulation. However, we restrict our discussion to selected tumors by focusing on TRAIL, miRNAs and natural agents. Emerging evidence suggests a role for natural agents in RKIP regulation in cancer cells; therefore, naturally occurring agents may serve as cancer-targeting agents for cancer treatment. Although the literature suggests some advancement in our knowledge of RKIP biology, it is incomplete with regard to its preclinical and clinical efficacy; thus, further research is warranted. Furthermore, the mechanism by which chemotherapeutic drugs and novel compounds modulate RKIP and how nanotechnologically delivered RKIP can be therapeutically exploited remain to be determined.

| S-EPMC4650930 | biostudies-other

Hominids adapted to metabolize ethanol long before human-directed fermentation.

Project description:Paleogenetics is an emerging field that resurrects ancestral proteins from now-extinct organisms to test, in the laboratory, models of protein function based on natural history and Darwinian evolution. Here, we resurrect digestive alcohol dehydrogenases (ADH4) from our primate ancestors to explore the history of primate-ethanol interactions. The evolving catalytic properties of these resurrected enzymes show that our ape ancestors gained a digestive dehydrogenase enzyme capable of metabolizing ethanol near the time that they began using the forest floor, about 10 million y ago. The ADH4 enzyme in our more ancient and arboreal ancestors did not efficiently oxidize ethanol. This change suggests that exposure to dietary sources of ethanol increased in hominids during the early stages of our adaptation to a terrestrial lifestyle. Because fruit collected from the forest floor is expected to contain higher concentrations of fermenting yeast and ethanol than similar fruits hanging on trees, this transition may also be the first time our ancestors were exposed to (and adapted to) substantial amounts of dietary ethanol.

| S-EPMC4299227 | biostudies-literature

The reach of the genome signature in prokaryotes.

Project description:BACKGROUND: With the increased availability of sequenced genomes there have been several initiatives to infer evolutionary relationships by whole genome characteristics. One of these studies suggested good congruence between genome synteny, shared gene content, 16S ribosomal DNA identity, codon usage and the genome signature in prokaryotes. Here we rigorously test the phylogenetic signal of the genome signature, which consists of the genome-specific relative frequencies of dinucleotides, on 334 sequenced prokaryotic genome sequences. RESULTS: Intrageneric comparisons show that in general the genomic dissimilarity scores are higher than in intraspecific comparisons, in accordance with the suggested phylogenetic signal of the genome signature. Exceptions to this trend, (Bartonella spp., Bordetella spp., Salmonella spp. and Yersinia spp.), which have low average intrageneric genomic dissimilarity scores, suggest that members of these genera might be considered the same species. On the other hand, high genomic dissimilarity values for intraspecific analyses suggest that in some cases (e.g. Prochlorococcus marinus, Pseudomonas fluorescens, Buchnera aphidicola and Rhodopseudomonas palustris) different strains from the same species may actually represent different species. Comparing 16S rDNA identity with genomic dissimilarity values corroborates the previously suggested trend in phylogenetic signal, albeit that the dissimilarity values only provide low resolution. CONCLUSION: The genome signature has a distinct phylogenetic signal, independent of individual genetic marker genes. A reliable phylogenetic clustering cannot be based on dissimilarity values alone, as bootstrapping is not possible for this parameter. It can however be used to support or refute a given phylogeny and resulting taxonomy.

| S-EPMC1621082 | biostudies-other

Reduction in structural disorder and functional complexity in the thermal adaptation of prokaryotes.

Project description:Genomic correlates of evolutionary adaptation to very low or very high optimal growth temperature (OGT) values have been the subject of many studies. Whereas these provided a protein-structural rationale of the activity and stability of globular proteins/enzymes, the point has been neglected that adaptation to extreme temperatures could also have resulted from an increased use of intrinsically disordered proteins (IDPs), which are resistant to these conditions in vitro. Contrary to these expectations, we found a conspicuously low level of structural disorder in bacteria of very high (and very low) OGT values. This paucity of disorder does not reflect phylogenetic relatedness, i.e. it is a result of genuine adaptation to extreme conditions. Because intrinsic disorder correlates with important regulatory functions, we asked how these bacteria could exist without IDPs by studying transcription factors, known to harbor a lot of function-related intrinsic disorder. Hyperthermophiles have much less transcription factors, which have reduced disorder compared to their mesophilic counterparts. On the other hand, we found by systematic categorization of proteins with long disordered regions that there are certain functions, such as translation and ribosome biogenesis that depend on structural disorder even in hyperthermophiles. In all, our observations suggest that adaptation to extreme conditions is achieved by a significant functional simplification, apparent at both the level of the genome and individual genes/proteins.

| S-EPMC2920320 | biostudies-literature

Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity.

Project description:Endogenous cortical fluctuations captured by electroencephalograms (EEGs) reflect activity in large-scale brain networks that exhibit dynamic patterns over multiple time scales. Developmental changes in the coordination and integration of brain function leads to greater complexity in population level neural dynamics. In this study we examined multiscale entropy, a measure of signal complexity, in resting-state EEGs in a large (N = 405) cross-sectional sample of children and adolescents (9-16 years). Our findings showed consistent age-dependent increases in EEG complexity that are distributed across multiple temporal scales and spatial regions. Developmental changes were most robust as the age gap between groups increased, particularly between late childhood and adolescence, and were most prominent over fronto-central scalp regions. These results suggest that the transition from late childhood to adolescence is characterized by age-dependent changes in the underlying complexity of endogenous brain networks.

| S-EPMC8027532 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data