Investigating different duplication pattern of essential genes in mouse and human

Insights into the identification and evolutionary conservation of key genes in the transcriptional circuits of meiosis initiation and commitment in budding yeast

Initiation of meiosis in budding yeast does not commit the cells for meiosis. Thus, two distinct signaling cascades may differentially regulate meiosis initiation and commitment in budding yeast. To distinguish between the role of these signaling cascades, we reconstructed protein-protein interaction networks and gene regulatory networks with upregulated genes in meiosis initiation and commitment. Analyzing the integrated networks, we identified four master regulators (MRs) [Ume6p, Msn2p, Met31p, Ino2p], three transcription factors (TFs), and 279 target genes (TGs) unique for meiosis initiation, and three MRs [Ndt80p, Aro80p, Rds2p], 11 TFs, and 948 TGs unique for meiosis commitment. Functional enrichment analysis of these distinct members from the transcriptional cascades for meiosis initiation and commitment revealed that nutritional cues rewire gene expression for initiating meiosis and chromosomal recombination commits cells to meiosis. As meiotic chromosomal recombination is highly conserved in eukaryotes, we compared the evolutionary rate of unique members in the transcriptional cascade of two meiotic phases of Saccharomyces cerevisiae with members of the phylum Ascomycota, revealing that the transcriptional cascade governing chromosomal recombination during meiosis commitment has experienced greater purifying selection pressure (P value = 0.0013, 0.0382, 0.0448, 0.0369, 0.02967, 0.04937, 0.03046, 0.03357 and < 0.00001 for Ashbya gossypii, Yarrowia lipolytica, Debaryomyces hansenii, Aspergillus fumigatus, Neurospora crassa, Kluyveromyces lactis, Schizosaccharomyces pombe, Schizosaccharomyces cryophilus, and Schizosaccharomyces octosporus, respectively). This study demarcates crucial players driving meiosis initiation and commitment and demonstrates their differential rate of evolution in budding yeast.

Functional compensation of mouse duplicates by their paralogs expressed in the same tissues

Analyses in a number of organisms have shown that duplicated genes are less likely to be essential than singletons. This implies that genes can often compensate for the loss of their paralogs. However, it is unclear why the loss of some duplicates can be compensated by their paralogs, whereas the loss of other duplicates cannot. Surprisingly, initial analyses in mice did not detect differences in the essentiality of duplicates and singletons. Only subsequent analyses, using larger gene knockout datasets and controlling for a number of confounding factors, did detect significant differences. Previous studies have not taken into account the tissues in which duplicates are expressed. We hypothesized that in complex organisms, in order for a gene's loss to be compensated by one or more of its paralogs, such paralogs need to be expressed in at least the same set of tissues as the lost gene. To test our hypothesis, we classified mouse duplicates into two categories based on the expression patterns of their paralogs: "compensable duplicates" (those with paralogs expressed in all the tissues in which the gene is expressed) and "non-compensable duplicates" (those whose paralogs are not expressed in all the tissues where the gene is expressed). In agreement with our hypothesis, the essentiality of non-compensable duplicates is similar to that of singletons, whereas compensable duplicates exhibit a substantially lower essentiality. Our results imply that duplicates can often compensate for the loss of their paralogs, but only if they are expressed in the same tissues. Indeed, the compensation ability is more dependent on expression patterns than on protein sequence similarity. The existence of these two kinds of duplicates with different essentialities, which has been overlooked by prior studies, may have hindered the detection of differences between singletons and duplicates.

Elucidating the network features and evolutionary attributes of intra- and interspecific protein-protein interactions between human and pathogenic bacteria

Host–pathogen interaction is one of the most powerful determinants involved in coevolutionary processes covering a broad range of biological phenomena at molecular, cellular, organismal and/or population level. The present study explored host–pathogen interaction from the perspective of human–bacteria protein–protein interaction based on large-scale interspecific and intraspecific interactome data for human and three pathogenic bacterial species, Bacillus anthracis, Francisella tularensis and Yersinia pestis. The network features revealed a preferential enrichment of intraspecific hubs and bottlenecks for both human and bacterial pathogens in the interspecific human–bacteria interaction. Analyses unveiled that these bacterial pathogens interact mostly with human party-hubs that may enable them to affect desired functional modules, leading to pathogenesis. Structural features of pathogen-interacting human proteins indicated an abundance of protein domains, providing opportunities for interspecific domain-domain interactions. Moreover, these interactions do not always occur with high-affinity, as we observed that bacteria-interacting human proteins are rich in protein-disorder content, which correlates positively with the number of interacting pathogen proteins, facilitating low-affinity interspecific interactions. Furthermore, functional analyses of pathogen-interacting human proteins revealed an enrichment in regulation of processes like metabolism, immune system, cellular localization and transport apart from divulging functional competence to bind enzyme/protein, nucleic acids and cell adhesion molecules, necessary for host-microbial cross-talk.

Evolutionary rate heterogeneity between multi- and single-interface hubs across human housekeeping and tissue-specific protein interaction network: Insights from proteins' and its partners' properties

Integrating gene expression into protein-protein interaction network (PPIN) leads to the construction of tissue-specific (TS) and housekeeping (HK) sub-networks, with distinctive TS- and HK-hubs. All such hub proteins are divided into multi-interface (MI) hubs and single-interface (SI) hubs, where MI hubs evolve slower than SI hubs. Here we explored the evolutionary rate difference between MI and SI proteins within TS- and HK-PPIN and observed that this difference is present only in TS, but not in HK-class. Next, we explored whether proteins' own properties or its partners' properties are more influential in such evolutionary discrepancy. Statistical analyses revealed that this evolutionary rate correlates negatively with protein's own properties like expression level, miRNA count, conformational diversity and functional properties and with its partners' properties like protein disorder and tissue expression similarity. Moreover, partial correlation and regression analysis revealed that both proteins' and its partners' properties have independent effects on protein evolutionary rate.

Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution

Identification of various factors involved in adverse drug reactions in target proteins to develop therapeutic drugs with minimal/no side effect is very important. In this context, we have performed a comparative evolutionary rate analyses between the genes exhibiting drug side-effect(s) (SET) and genes showing no side effect (NSET) with an aim to increase the prediction accuracy of SET/NSET proteins using evolutionary rate determinants. We found that SET proteins are more conserved than the NSET proteins. The rates of evolution between SET and NSET protein primarily depend upon their noncomplex (protein complex association number = 0) forming nature, phylogenetic age, multifunctionality, membrane localization, and transmembrane helix content irrespective of their essentiality, total druggability (total number of drugs/target), m-RNA expression level, and tissue expression breadth. We also introduced two novel terms—killer druggability (number of drugs with killing side effect(s)/target), essential druggability (number of drugs targeting essential proteins/target) to explain the evolutionary rate variation between SET and NSET proteins. Interestingly, we noticed that SET proteins are younger than NSET proteins and multifunctional younger SET proteins are candidates of acquiring killing side effects. We provide evidence that higher killer druggability, multifunctionality, and transmembrane helices support the conservation of SET proteins over NSET proteins in spite of their recent origin. By employing all these entities, our Support Vector Machine model predicts human SET/NSET proteins to a high degree of accuracy (∼86%).

Injury, inflammation and the emergence of human-specific genes

In light of the central role of inflammation in normal wound repair and regeneration, we hypothesize that the preponderance of human‐specific genes expressed in human inflammatory cells is commensurate with the genetic versatility of inflammatory response and the emergence of injuries associated with uniquely hominid behaviors, like a bipedal posture and the use of tools, weapons and fire. The hypothesis underscores the need to study human‐specific signaling pathways in experimental models of injury and infers that a selection of human‐specific genes, driven in part by the response to injury, may have facilitated the emergence of multifunctional genes expressed in other tissues.

Laminin-binding integrin gene copy number alterations in distinct epithelial-type cancers

BACKGROUND

The laminin-binding integrin (LBI) family are cell adhesion molecules that are essential for invasion and metastasis of human epithelial cancers and cell adhesion mediated drug resistance. We investigated whether copy number alteration (CNA) or mutations of a five-gene signature (ITGB4, ITGA3, LAMB3, PLEC, and SYNE3), representing essential genes for LBI adhesion, would correlate with patient outcomes within human epithelial-type tumor data sets currently available in an open access format.

METHODS

We investigated the relative alteration frequency of an LBI signature panel (integrin β4 (ITGB4), integrin α3 (ITGA3), laminin β3 chain (LAMB3), plectin (PLEC), and nesprin 3 (SYNE3)), independent of the epithelial cancer type, within publically available and published data using cBioPortal and Oncomine software. We rank ordered the results using a 20% alteration frequency cut-off and limited the analysis to studies containing at least 100 samples. Kaplan-Meier survival curves were analyzed to determine if alterations in the LBI signature correlated with patient survival. The Oncomine data mining tool was used to compare the heat map expression of the LBI signature without SYNE3 (as this was not included in the Oncomine database) to drug resistance patterns.

RESULTS

Twelve different cancer types, representing 5,647 samples, contained at least a 20% alteration frequency of the five-gene LBI signature. The frequency of alteration ranged from 38.3% to 19.8%. Within the LBI signature, PLEC was the most commonly altered followed by LAMB3, ITGB4, ITGA3, and SYNE3 across all twelve cancer types. Within cancer types, there was little overlap of the individual amplified genes from each sample, suggesting different specific amplicons may alter the LBI adhesion structures. Of the twelve cancer types, overall survival was altered by CNA presence in bladder urothelial carcinoma (p=0.0143*) and cervical squamous cell carcinoma and endocervical adenocarcinoma (p=0.0432*). Querying the in vitro drug resistance profiles with the LBI signature demonstrated a positive correlation with cells resistant to inhibitors of HDAC (Vorinostat, Panobinostat) and topoisomerase II (Irinotecan). No correlation was found with the following agents: Bleomycin, Doxorubicin, Methotrexate, Gemcitabine, Docetaxel, Bortezomib, and Shikonen.

CONCLUSIONS

Our work has identified epithelial-types of human cancer that have significant CNA in our selected five-gene signature, which was based on the essential and genetically-defined functions of the protein product networks (in this case, the LBI axis). CNA of the gene signature not only predicted overall survival in bladder, cervical, and endocervical adenocarcinoma but also response to chemotherapy. This work suggests that future studies designed to optimize the gene signature are warranted.

GENERAL SIGNIFICANCE

The copy number alteration of structural components of the LBI axis in epithelial-type tumors may be promising biomarkers and rational targets for personalized therapy in preventing or arresting metastatic spread.

Global analysis of human duplicated genes reveals the relative importance of whole-genome duplicates originated in the early vertebrate evolution

Background

Gene duplication is a genetic mutation that creates functionally redundant gene copies that are initially relieved from selective pressures and may adapt themselves to new functions with time. The levels of gene duplication may vary from small-scale duplication (SSD) to whole genome duplication (WGD). Studies with yeast revealed ample differences between these duplicates: Yeast WGD pairs were functionally more similar, less divergent in subcellular localization and contained a lesser proportion of essential genes. In this study, we explored the differences in evolutionary genomic properties of human SSD and WGD genes, with the identifiable human duplicates coming from the two rounds of whole genome duplication occurred early in vertebrate evolution.

Results

We observed that these two groups of duplicates were also dissimilar in terms of their evolutionary and genomic properties. But interestingly, this is not like the same observed in yeast. The human WGDs were found to be functionally less similar, diverge more in subcellular level and contain a higher proportion of essential genes than the SSDs, all of which are opposite from yeast. Additionally, we explored that human WGDs were more divergent in their gene expression profile, have higher multifunctionality and are more often associated with disease, and are evolutionarily more conserved than human SSDs.

Conclusions

Our study suggests that human WGD duplicates are more divergent and entails the adaptation of WGDs to novel and important functions that consequently lead to their evolutionary conservation in the course of evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2392-0) contains supplementary material, which is available to authorized users.