Relationship between gene duplicability and diversifiability in the topology of biochemical networks

The Enrichment of miRNA-Targeted mRNAs in Translationally Less Active over More Active Polysomes

miRNAs moderately inhibit the translation and enhance the degradation of their target mRNAs via cognate binding sites located predominantly in the 3'-untranslated regions (UTR). Paradoxically, miRNA targets are also polysome-associated. We studied the polysome association by the comparative translationally less-active light- and more-active heavy-polysome profiling of a wild type (WT) human cell line and its isogenic mutant (MT) with a disrupted DICER1 gene and, thus, mature miRNA production. As expected, the open reading frame (ORF) length is a major determinant of light- to heavy-polysome mRNA abundance ratios, but is rendered less powerful in WT than in MT cells by miRNA-regulatory activities. We also observed that miRNAs tend to target mRNAs with longer ORFs, and that adjusting the mRNA abundance ratio with the ORF length improves its correlation with the 3'-UTR miRNA-binding-site count. In WT cells, miRNA-targeted mRNAs exhibit higher abundance in light relative to heavy polysomes, i.e., light-polysome enrichment. In MT cells, the DICER1 disruption not only significantly abrogated the light-polysome enrichment, but also narrowed the mRNA abundance ratio value range. Additionally, the abrogation of the enrichment due to the DICER1 gene disruption, i.e., the decreases of the ORF-length-adjusted mRNA abundance ratio from WT to MT cells, exhibits a nearly perfect linear correlation with the 3'-UTR binding-site count. Transcription factors and protein kinases are the top two most enriched mRNA groups. Taken together, the results provide evidence for the light-polysome enrichment of miRNA-targeted mRNAs to reconcile polysome association and moderate translation inhibition, and that ORF length is an important, though currently under-appreciated, transcriptome regulation parameter.

The Δ1-pyrroline-5-carboxylate synthetase family performs diverse physiological functions in stress responses in pear (Pyrus betulifolia)

Δ1-Pyrroline-5-carboxylate synthetase (P5CS) acts as the rate-limiting enzyme in the biosynthesis of proline in plants. Although P5CS plays an essential role in plant responses to environmental stresses, its biological functions remain largely unclear in pear (Pyrus betulifolia). In the present study, 11 putative pear P5CSs (PbP5CSs) were identified by comprehensive bioinformatics analysis and classified into five subfamilies. Segmental and tandem duplications contributed to the expansion and evolution of the PbP5CS gene family. Various cis-acting elements associated with plant development, hormone responses, and/or stress responses were identified in the promoters of PbP5CS genes. To investigate the regulatory roles of PbP5CS genes in response to abiotic and biotic stresses, gene expression patterns in publicly available data were explored. The tissue-specific expressional dynamics of PbP5CS genes indicate potentially important roles in pear growth and development. Their spatiotemporal expression patterns suggest key functions in multiple environmental stress responses. Transcriptome and real-time quantitative PCR analyses revealed that most PbP5CS genes exhibited distinct expression patterns in response to drought, waterlogging, salinity-alkalinity, heat, cold, and infection by Alternaria alternate and Gymnosporangium haraeanum. The results provide insight into the versatile functions of the PbP5CS gene family in stress responses. The findings may assist further exploration of the physiological functions of PbP5CS genes for the development and enhancement of stress tolerance in pear and other fruits.

Comparative Analysis of microRNA Binding Site Distribution and microRNA-Mediated Gene Expression Repression of Oncogenes and Tumor Suppressor Genes

MicroRNAs (miRNAs) are a family of short, noncoding RNAs that can regulate gene expression levels of over half of the human genome. Previous studies on the role of miRNAs in cancer showed overall widespread downregulation of miRNAs as a hallmark of human cancer, though individual miRNAs can be both tumor suppressive and oncogenic, and cancer genes are speculated to be more targeted by miRNA. However, the extents to which oncogenes and tumor suppressor genes (TSG) are controlled by miRNA have not been compared. To achieve this goal, we constructed lists of oncogenes and TSGs and compared them with each other, and with the whole protein-coding gene population, in terms of miRNA binding sites distribution and expression level changes upon genetic disruption of miRNA production. As expected, the results show that cancer gene mRNAs anchor more miRNA binding sites, and are under a higher degree of miRNA-mediated repression at both mRNA abundance and translation efficiency levels than the whole protein-coding gene population. Importantly, on average, TSG mRNAs are more highly targeted and regulated by miRNA than oncogene mRNAs. To the best of our knowledge, this is the first comparison of miRNA regulation of oncogenes and TSGs.

Uncovering the cellular capacity for intensive and specific feedback self-control of the argonautes and MicroRNA targeting activity

The miRNA pathway has three segments—biogenesis, targeting and downstream regulatory effectors. We aimed to better understand their cellular control by exploring the miRNA-mRNA-targeting relationships. We first used human evolutionarily conserved sites. Strikingly, AGOs 1–3 are all among the top 14 mRNAs with the highest miRNA site counts, along with ANKRD52, the phosphatase regulatory subunit of the recently identified AGO phosphorylation cycle; and the AGO phosphorylation cycle mRNAs share much more than expected miRNA sites. The mRNAs for TNRC6, which acts with AGOs to channel miRNA-mediated regulatory actions onto specific mRNAs, are also heavily miRNA-targeted. In contrast, upstream miRNA biogenesis mRNAs are not, and neither are downstream regulatory effectors. In short, binding site enrichment in miRNA targeting machinery mRNAs, but neither upstream biogenesis nor downstream effector mRNAs, was observed, endowing a cellular capacity for intensive and specific feedback control of the targeting activity. The pattern was confirmed with experimentally determined miRNA-mRNA target relationships. Moreover, genetic experiments demonstrated cellular utilization of this capacity. Thus, we uncovered a capacity for intensive, and specific, feedback-regulation of miRNA targeting activity directly by miRNAs themselves, i.e. segment-specific feedback auto-regulation of miRNA pathway, complementing miRNAs pairing with transcription factors to form hybrid feedback-loop.

Dependency Between Protein-Protein Interactions and Protein Variability and Evolutionary Rates in Vertebrates: Observed Relationships and Stochastic Modeling

Recent developments in sequencing and growth of bioinformatics resources provide us with vast depositories of protein network and single nucleotide polymorphism data. It allows us to re-examine, on a larger and more comprehensive scale, the relationship between protein–protein interactions and protein variability and evolutionary rates. This relationship has remained far from unambiguously resolved for quite a long time, reflecting shifting analysis approaches in the literature, and growing data availability. In this study, we utilized several public genomic databases to investigate this relationship in human, mouse, pig, chicken, and zebrafish. We observed strong non-linear relationship patterns (tending towards convex decreasing function shapes) between protein variability and the density of corresponding protein–protein interactions across all five species. To investigate further, we carried out stochastic simulations, modeling the interplay between protein connectivity and variability. Our results indicate that a simple negative linear correlation model, often suggested (or tacitly assumed) in the literature, as either a null or an alternative hypothesis, is not a good fit with the observed data. After considering different (but still relatively simple, and not overfitting) simulation models, we found that a convex decreasing protein variability–connectivity function (specifically, exponential decay) led to a much better fit with the real data. We conclude that simple correlation models might be inadequate for describing protein variability–connectivity interplay in vertebrates; they often tend towards false negatives (showing no more than marginal linear or rank correlation where there are in fact strong non-random patterns).

A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms

To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Sequentially more genes exhibited extreme (low or high) expression values from TR to RA, and then to TA; that is, cellular coordination of multiple transcriptome regulatory mechanisms leads to sequentially enhanced gene expression selectivity as the genetic information flow from the genome to the proteome. Second, contribution of the stabilization-by-translation regulatory mechanism to the cellular coordination process was assessed. The data enabled an estimation of mRNA stability, revealing a moderate but significant positive correlation between mRNA stability and translation activity. Third, the proportion of mRNA occupied by un-translated regions (UTR) exhibited a negative relationship with the level of this correlation, and was thus a major determinant of the mode of regulation of the mRNA. High-UTR-proportion mRNAs tend to defy the stabilization-by-translation regulatory mechanism, staying out of the polysome but remaining stable; mRNAs with little UTRs largely followed this regulation. In summary, we quantitatively delineated the relationship among multiple transcriptome regulation parameters, i.e., cellular coordination of corresponding regulatory mechanisms.

The Pattern of microRNA Binding Site Distribution

Micro-RNA (miRNA or miR) regulates at least 60% of the genes in the human genome through their target sites at mRNA 3'-untranslated regions (UTR), and defects in miRNA expression regulation and target sites are frequently observed in cancers. We report here a systematic analysis of the distribution of miRNA target sites. Using the evolutionarily conserved miRNA binding sites in the TargetScan database (release 7.1), we constructed a miRNA co-regulation network by connecting genes sharing common miRNA target sites. The network possesses characteristics of the ubiquitous small-world network. Non-hub genes in the network-those sharing miRNA target sites with small numbers of genes-tend to form small cliques with their neighboring genes, while hub genes exhibit high levels of promiscuousness in their neighboring genes. Additionally, miRNA target site distribution is extremely uneven. Among the miRNAs, the distribution concentrates on a small number of miRNAs, in that their target sites occur in an extraordinarily large number of genes, that is, they have large numbers of target genes. The distribution across the genes follows a similar pattern; the mRNAs of a small proportion of the genes contain extraordinarily large numbers of miRNA binding sites. Quantitatively, the patterns fit into the P_(K) ∝ K^-α relationship (P_(K): the number of miRNAs with K target genes or genes with K miRNA sites; α: a positive constant), the mathematical description of connection distribution among the nodes and a defining characteristic of the so-called scale-free networks-a subset of small-world networks. Notably, well-known tumor-suppressive miRNAs (Let-7, miR-15/16, 26, 29, 31, 34, 145, 200, 203-205, 223, and 375) collectively have more than expected target genes, and well-known cancer genes contain more than expected miRNA binding sites. In summary, miRNA target site distribution exhibits characteristics of the small-world network. The potential to use this pattern to better understand miRNA function and their oncological roles is discussed.

Castro LF. Evolutionary functional elaboration of the Elovl2/5 gene family in chordates

The biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFA) provides an intriguing example on how multi-enzymatic cascades evolve. Essential LC-PUFA, such as arachidonic, eicosapentaenoic, and docosahexaenoic acids (DHA), can be acquired from the diet but are also endogenously retailored from C18 precursors through consecutive elongations and desaturations catalyzed, respectively, by fatty acyl elongase and desaturase enzymes. The molecular wiring of this enzymatic pathway defines the ability of a species to biosynthesize LC-PUFA. Exactly when and how in animal evolution a functional LC-PUFA pathway emerged is still elusive. Here we examine key components of the LC-PUFA cascade, the Elovl2/Elovl5 elongases, from amphioxus, an invertebrate chordate, the sea lamprey, a representative of agnathans, and the elephant shark, a basal jawed vertebrate. We show that Elovl2 and Elovl5 emerged from genome duplications in vertebrate ancestry. The single Elovl2/5 from amphioxus efficiently elongates C18 and C20 and, to a marked lesser extent, C22 LC-PUFA. Lamprey is incapable of elongating C22 substrates. The elephant shark Elovl2 showed that the ability to efficiently elongate C22 PUFA and thus to synthesize DHA through the Sprecher pathway, emerged in the jawed vertebrate ancestor. Our findings illustrate how non-integrated "metabolic islands" evolve into fully wired pathways upon duplication and neofunctionalization.