Intrachromosomal colocalization strengthens co-expression, co-modification and evolutionary conservation of neighboring genes

Genes that are Used Together are More Likely to be Fused Together in Evolution by Mutational Mechanisms: A Bioinformatic Test of the Used-Fused Hypothesis

Cases of parallel or recurrent gene fusions in evolution as well as in genetic disease and cancer are difficult to explain, because unlike point mutations, they can require the repetition of a similar configuration of multiple breakpoints rather than the repetition of a single point mutation. The used-together-fused-together hypothesis holds that genes that are used together repeatedly and persistently in a specific context are more likely to undergo fusion mutation in the course of evolution for mechanistic reasons. This hypothesis offers to explain gene fusion in both evolution and disease under one umbrella. Using bioinformatic data, we tested this hypothesis against alternatives, including that all gene pairs can fuse by random mutation, but among pairs thus fused, those that had interacted previously are more likely to be favored by selection. Results show that across multiple measures of gene interaction, human genes whose orthologs are fused in one or more species are more likely to interact with each other than random pairs of genes of the same genomic distance between pair members; that an overlap exists between genes that fused in the course of evolution in non-human species and genes that undergo fusion in human cancers; and that across six primate species studied, fusions predominate over fissions and exhibit substantial evolutionary parallelism. Together, these results support the used-together-fused-together hypothesis over its alternatives. Multiple implications are discussed, including the relevance of mutational mechanisms to the evolution of genome organization, to the distribution of fitness effects of mutation, to evolutionary parallelism and more.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11692-022-09579-9.

Transperons: RNA operons as effectors of coordinated gene expression in eukaryotes

Coordinated gene expression allows spatiotemporal control of cellular processes and is achieved by the cotranscription/translation of functionally related genes/proteins. Prokaryotes evolved polycistronic messages (operons) to confer expression from a single promoter to efficiently cotranslate proteins functioning on the same pathway. Yet, despite having far greater diversity (e.g., gene number, distribution, modes of expression), eukaryotic cells employ individual promoters and monocistronic messages. Although gene expression is modular, it does not account for how eukaryotes achieve coordinated localized translation. The RNA operon theory states that mRNAs derived from different chromosomes assemble into ribonucleoprotein particles (RNPs) that act as functional operons to generate protein cohorts upon cotranslation. Work in yeast has now validated this theory and shown that intergenic associations and noncanonical histone functions create pathway-specific RNA operons (transperons) that regulate cell physiology. Herein the involvement of chromatin organization in transperon formation and programmed gene coexpression is discussed.

USP32 confers cancer cell resistance to YM155 via promoting ER-associated degradation of solute carrier protein SLC35F2

Background: The most commonly preferred chemotherapeutic agents to treat cancers are small-molecule drugs. However, the differential sensitivity of various cancer cells to small molecules and untargeted delivery narrow the range of potential therapeutic applications. The mechanisms responsible for drug resistance in a variety of cancer cells are also largely unknown. Several deubiquitinating enzymes (DUBs) are the main determinants of drug resistance in cancer cells.

Methods: We used CRISPR-Cas9 to perform genome-scale knockout of the entire set of genes encoding ubiquitin-specific proteases (USPs) and systematically screened for DUBs resistant to the clinically evaluated anticancer compound YM155. A series of in vitro and in vivo experiments were conducted to reveal the relationship between USP32 and SLC35F2 on YM155-mediated DNA damage in cancer cells.

Results: CRISPR-based dual-screening method identified USP32 as a novel DUB that governs resistance for uptake of YM155 by destabilizing protein levels of SLC35F2, a solute-carrier protein essential for the uptake of YM155. The expression of USP32 and SLC35F2 was negatively correlated across a panel of tested cancer cell lines. YM155-resistant cancer cells in particular exhibited elevated expression of USP32 and low expression of SLC35F2.

Conclusion: Collectively, our DUB-screening strategy revealed a resistance mechanism governed by USP32 associated with YM155 resistance in breast cancers, one that presents an attractive molecular target for anti-cancer therapies. Targeted genome knockout verified that USP32 is the main determinant of SLC35F2 protein stability in vitro and in vivo, suggesting a novel way to treat tumors resistant to small-molecule drugs.

Region-specific expression of young small-scale duplications in the human central nervous system

BACKGROUND

The duplication of genes is one of the main genetic mechanisms that led to the gain in complexity of biological tissue. Although the implication of duplicated gene expression in brain evolution was extensively studied through comparisons between organs, their role in the regional specialization of the adult human central nervous system has not yet been well described.

RESULTS

Our work explored intra-organ expression properties of paralogs through multiple territories of the human central nervous system (CNS) using transcriptome data generated by the Genotype-Tissue Expression (GTEx) consortium. Interestingly, we found that paralogs were associated with region-specific expression in CNS, suggesting their involvement in the differentiation of these territories. Beside the influence of gene expression level on region-specificity, we observed the contribution of both duplication age and duplication type to the CNS region-specificity of paralogs. Indeed, we found that small scale duplicated genes (SSDs) and in particular ySSDs (SSDs younger than the 2 rounds of whole genome duplications) were more CNS region-specific than other paralogs. Next, by studying the two paralogs of ySSD pairs, we observed that when they were region-specific, they tend to be specific to the same region more often than for other paralogs, showing the high co-expression of ySSD pairs. The extension of this analysis to families of paralogs showed that the families with co-expressed gene members (i.e. homogeneous families) were enriched in ySSDs. Furthermore, these homogeneous families tended to be region-specific families, where the majority of their gene members were specifically expressed in the same region.

CONCLUSIONS

Overall, our study suggests the involvement of ySSDs in the differentiation of human central nervous system territories. Therefore, we show the relevance of exploring region-specific expression of paralogs at the intra-organ level.

Gene Co-expression Is Distance-Dependent in Breast Cancer

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well-known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis- (intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using TCGA-derived RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans- co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the ratio of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans- co-expression in all molecular subtypes. We also observed that gene cis- co-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

The differential expression patterns of paralogs in response to stresses indicate expression and sequence divergences

BACKGROUND

Theoretically, paralogous genes generated through whole genome duplications should share identical expression levels due to their identical sequences and chromatin environments. However, functional divergences and expression differences have arisen due to selective pressures throughout evolution. A comprehensive investigation of the expression patterns of paralogous gene pairs in response to various stresses and a study of correlations between the expression levels and sequence divergences of the paralogs are needed.

RESULTS

In this study, we analyzed the expression patterns of paralogous genes under different types of stress and investigated the correlations between the expression levels and sequence divergences of the paralogs. We analyzed the differential expression patterns of the paralogs under four different types of stress (drought, cold, infection, and herbivory) and classified them into three main types according to their expression patterns. We then further analyzed the differential expression patterns under various degrees of stress and constructed corresponding co-expression networks of differentially expressed paralogs and transcription factors. Finally, we investigated the correlations between the expression levels and sequence divergences of the paralogs and identified positive correlations between expression level and sequence divergence. With regard to sequence divergence, we identified correlations between selective pressures and phylogenetic relationships.

CONCLUSIONS

These results shed light on differential expression patterns of paralogs in response to environmental stresses and are helpful for understanding the relationships between expression levels and sequences divergences.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

The co-expression networks of differentially expressed RBPs with TFs and LncRNAs related to clinical TNM stages of cancers

Background

RNA-binding proteins (RBPs) play important roles in cellular homeostasis by regulating the expression of thousands of transcripts, which have been reported to be involved in human tumorigenesis. Despite previous reports of the dysregulation of RBPs in cancers, the degree of dysregulation of RBPs in cancers and the intrinsic relevance between dysregulated RBPs and clinical TNM information remains unknown. Furthermore, the co-expressed networks of dysregulated RBPs with transcriptional factors and lncRNAs also require further investigation.

Results

Here, we firstly analyzed the deviations of expression levels of 1,542 RBPs from 20 cancer types and found that (1) RBPs are dysregulated in almost all 20 cancer types, especially in BLCA, COAD, READ, STAD, LUAD, LUSC and GBM with proportion of deviation larger than 300% compared with non-RBPs in normal tissues. (2) Up- and down-regulated RBPs also show opposed patterns of differential expression in cancers and normal tissues. In addition, down-regulated RBPs show a greater degree of dysregulated expression than up-regulated RBPs do. Secondly, we analyzed the intrinsic relevance between dysregulated RBPs and clinical TNM information and found that (3) Clinical TNM information for two cancer types—CHOL and KICH—is shown to be closely related to patterns of differentially expressed RBPs (DE RBPs) by co-expression cluster analysis. Thirdly, we identified ten key RBPs (seven down-regulated and three up-regulated) in CHOL and seven key RBPs (five down-regulated and two up-regulated) in KICH by analyzing co-expression correlation networks. Fourthly, we constructed the co-expression networks of key RBPs between 1,570 TFs and 4,147 lncRNAs for CHOL and KICH, respectively.

Conclusions

These results may provide an insight into the understanding of the functions of RBPs in human carcinogenesis. Furthermore, key RBPs and the co-expressed networks offer useful information for potential prognostic biomarkers and therapeutic targets for patients with cancers at the N and M stages in two cancer types CHOL and KICH.