A Model-Based Approach for Identifying Functional Intergenic Transcribed Regions and Noncoding RNAs.

With advances in transcript profiling, the presence of transcriptional activities in intergenic regions has been well established. However, whether intergenic expression reflects transcriptional noise or activity of novel genes remains unclear. We identified intergenic transcribed regions (ITRs) in 15 diverse flowering plant species and found that the amount of intergenic expression correlates with genome size, a pattern that could be expected if intergenic expression is largely nonfunctional. To further assess the functionality of ITRs, we first built machine learning models using Arabidopsis thaliana as a model that accurately distinguish functional sequences (benchmark protein-coding and RNA genes) and likely nonfunctional ones (pseudogenes and unexpressed intergenic regions) by integrating 93 biochemical, evolutionary, and sequence-structure features. Next, by applying the models genome-wide, we found that 4,427 ITRs (38%) and 796 annotated ncRNAs (44%) had features significantly similar to benchmark protein-coding or RNA genes and thus were likely parts of functional genes. Approximately 60% of ITRs and ncRNAs were more similar to nonfunctional sequences and were likely transcriptional noise. The predictive framework established here provides not only a comprehensive look at how functional, genic sequences are distinct from likely nonfunctional ones, but also a new way to differentiate novel genes from genomic regions with noisy transcriptional activities.

Defining Functional Genic Regions in the Human Genome through Integration of Biochemical, Evolutionary, and Genetic Evidence.

The human genome is dominated by large tracts of DNA with extensive biochemical activity but no known function. In particular, it is well established that transcriptional activities are not restricted to known genes. However, whether this intergenic transcription represents activity with functional significance or noise is under debate, highlighting the need for an effective method of defining functional genomic regions. Moreover, these discoveries raise the question whether genomic regions can be defined as functional based solely on the presence of biochemical activities, without considering evolutionary (conservation) and genetic (effects of mutations) evidence. Here, computational models integrating genetic, evolutionary, and biochemical evidence are established that provide reliable predictions of human protein-coding and RNA genes. Importantly, in addition to sequence conservation, biochemical features allow accurate predictions of genic sequences with phenotypic evidence under strong purifying selection, suggesting that they can be used as an alternative measure of selection. Moreover, 18.5% of annotated noncoding RNAs exhibit higher degrees of similarity to phenotype genes and, thus, are likely functional. However, 64.5% of noncoding RNAs appear to belong to a sequence class of their own, and the remaining 17% are more similar to pseudogenes and random intergenic sequences that may represent noisy transcription.

Determinants of nucleosome positioning and their influence on plant gene expression.

Nucleosome positioning influences the access of transcription factors (TFs) to their binding sites and gene expression. Studies in plant, animal, and fungal models demonstrate similar nucleosome positioning patterns along genes and correlations between occupancy and expression. However, the relationships among nucleosome positioning, cis-regulatory element accessibility, and gene expression in plants remain undefined. Here we showed that plant nucleosome depletion occurs on specific 6-mer motifs and this sequence-specific nucleosome depletion is predictive of expression levels. Nucleosome-depleted regions in Arabidopsis thaliana tend to have higher G/C content, unlike yeast, and are centered on specific G/C-rich 6-mers, suggesting that intrinsic sequence properties, such as G/C content, cannot fully explain plant nucleosome positioning. These 6-mer motif sites showed higher DNase I hypersensitivity and are flanked by strongly phased nucleosomes, consistent with known TF binding sites. Intriguingly, this 6-mer-specific nucleosome depletion pattern occurs not only in promoter but also in genic regions and is significantly correlated with higher gene expression level, a phenomenon also found in rice but not in yeast. Among the 6-mer motifs enriched in genes responsive to treatment with the defense hormone jasmonate, there are no significant changes in nucleosome occupancy, suggesting that these sites are potentially preconditioned to enable rapid response without changing chromatin state significantly. Our study provides a global assessment of the joint contribution of nucleosome occupancy and motif sequences that are likely cis-elements to the control of gene expression in plants. Our findings pave the way for further understanding the impact of chromatin state on plant transcriptional regulatory circuits.

Comparative genomic analyses highlight the contribution of pseudogenized protein-coding genes to human lincRNAs.

BACKGROUND: The regulatory roles of long intergenic noncoding RNAs (lincRNAs) in humans have been revealed through the use of advanced sequencing technology. Recently, three possible scenarios of lincRNA origins have been proposed: de novo origination from intergenic regions, duplication from other long noncoding RNAs, and pseudogenization from protein-coding genes. The first two scenarios are largely studied and supported, yet few studies focused on the evolution from pseudogenized protein-coding sequence to lincRNA. Due to the non-mutually exclusive nature of these three scenarios and the need of systematic investigation of lincRNA origination, we conducted a comparative genomics study to investigate the evolution of human lincRNAs. RESULTS: Combining with syntenic analysis and stringent Blastn e-value cutoff, we found that the majority of lincRNAs are aligned to intergenic regions of other species. Interestingly, 193 human lincRNAs could have protein-coding orthologs in at least two of nine vertebrates. Transposable elements in these conserved regions in human genome are much less than expectation. Moreover, 19% of these lincRNAs have overlaps with or are close to pseudogenes in the human genome. CONCLUSIONS: We suggest that a notable portion of lincRNAs could be derived from pseudogenized protein-coding genes. Furthermore, based on our computational analysis, we hypothesize that a subset of these lincRNAs could have potential to regulate their paralogs by functioning as competing endogenous RNAs. Our results provide evolutionary evidence of the relationship between human lincRNAs and protein-coding genes.

The CrdRS two-component system in Helicobacter pylori responds to nitrosative stress.

Helicobacter pylori inhabits the gastric mucosa where it senses and responds to various stresses via a two-component systems (TCSs) that enable its persistent colonization. The aim of this study was to investigate whether any of the three paired TCSs (ArsRS, FleRS and CrdRS) in H. pylori respond to nitrosative stress. The results showed that the expression of crdS was significantly increased upon exposure to nitric oxide (NO). crdS-knockout (ΔcrdS) and crdR/crdS-knockout (ΔcrdRS) H. pylori, but not arsS-knockout (ΔarsS) or fleS-knockout (ΔfleS) H. pylori, showed a significant loss of viability upon exposure to NO compared with wild-type strain. Knockin crdS (ΔcrdS-in) significantly restored viability in the presence of NO. Global transcriptional profiling analysis of wild-type and ΔcrdS H. pylori in the presence or absence of NO showed that 101 genes were differentially expressed, including copper resistance determinant A (crdA), transport, binding and envelope proteins. The CrdR binding motifs were investigated by competitive electrophoretic mobility shift assay, which revealed that the two AC-rich regions in the crdA promoter region are required for binding. These results demonstrate that CrdR-crdA interaction enables H. pylori to survive under nitrosative stress.

Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

Associations between intronic non-B DNA structures and exon skipping.

Non-B DNA structures are abundant in the genome and are often associated with critical biological processes, including gene regulation, chromosome rearrangement and genome stabilization. In particular, G-quadruplex (G4) may affect alternative splicing based on its ability to impede the activity of RNA polymerase II. However, the specific role of non-B DNA structures in splicing regulation still awaits investigation. Here, we provide a genome-wide and cross-species investigation of the associations between five non-B DNA structures and exon skipping. Our results indicate a statistically significant correlation of each examined non-B DNA structures with exon skipping in both human and mouse. We further show that the contributions of non-B DNA structures to exon skipping are influenced by the occurring region. These correlations and contributions are also significantly different in human and mouse. Finally, we detailed the effects of G4 by showing that occurring on the template strand and the length of G-run, which is highly related to the stability of a G4 structure, are significantly correlated with exon skipping activity. We thus show that, in addition to the well-known effects of RNA and protein structure, the relative positional arrangement of intronic non-B DNA structures may also impact exon skipping.

The impact of trans-regulation on the evolutionary rates of metazoan proteins.

Transcription factor (TF) and microRNA (miRNA) are two crucial trans-regulatory factors that coordinately control gene expression. Understanding the impacts of these two factors on the rate of protein sequence evolution is of great importance in evolutionary biology. While many biological factors associated with evolutionary rate variations have been studied, evolutionary analysis of simultaneously accounting for TF and miRNA regulations across metazoans is still uninvestigated. Here, we provide a series of statistical analyses to assess the influences of TF and miRNA regulations on evolutionary rates across metazoans (human, mouse and fruit fly). Our results reveal that the negative correlations between trans-regulation and evolutionary rates hold well across metazoans, but the strength of TF regulation as a rate indicator becomes weak when the other confounding factors that may affect evolutionary rates are controlled. We show that miRNA regulation tends to be a more essential indicator of evolutionary rates than TF regulation, and the combination of TF and miRNA regulations has a significant dependent effect on protein evolutionary rates. We also show that trans-regulation (especially miRNA regulation) is much more important in human/mouse than in fruit fly in determining protein evolutionary rates, suggesting a considerable variation in rate determinants between vertebrates and invertebrates.

Role of antisense RNAs in evolution of yeast regulatory complexity.

Antisense RNAs (asRNAs) are known to regulate gene expression. However, a genome-wide mechanism of asRNA regulation is unclear, and there is no good explanation why partial asRNAs are not functional. To explore its regulatory role, we investigated asRNAs using an evolutionary approach, as genome-wide experimental data are limited. We found that the percentage of genes coupling with asRNAs in Saccharomyces cerevisiae is negatively associated with regulatory complexity and evolutionary age. Nevertheless, asRNAs evolve more slowly when their sense genes are under more complex regulation. Older genes coupling with asRNAs are more likely to demonstrate inverse expression, reflecting the role of these asRNAs as repressors. Our analyses provide novel evidence, suggesting a minor contribution of asRNAs in developing regulatory complexity. Although our results support the leaky hypothesis for asRNA transcription, our evidence also suggests that partial asRNAs may have evolved as repressors. Our study deepens the understanding of asRNA regulatory evolution.

Evolution of cis-regulatory elements in yeast de novo and duplicated new genes.

BACKGROUND: New genes that originate from non-coding DNA rather than being duplicated from parent genes are called de novo genes. Their short evolution time and lack of parent genes provide a chance to study the evolution of cis-regulatory elements in the initial stage of gene emergence. Although a few reports have discussed cis-regulatory elements in new genes, knowledge of the characteristics of these elements in de novo genes is lacking. Here, we conducted a comprehensive investigation to depict the emergence and establishment of cis-regulatory elements in de novo yeast genes. RESULTS: In a genome-wide investigation, we found that the number of transcription factor binding sites (TFBSs) in de novo genes of S. cerevisiae increased rapidly and quickly became comparable to the number of TFBSs in established genes. This phenomenon might have resulted from certain characteristics of de novo genes; namely, a relatively frequent gain of TFBSs, an unexpectedly high number of preexisting TFBSs, or lower selection pressure in the promoter regions of the de novo genes. Furthermore, we identified differences in the promoter architecture between de novo genes and duplicated new genes, suggesting that distinct regulatory strategies might be employed by genes of different origin. Finally, our functional analyses of the yeast de novo genes revealed that they might be related to reproduction. CONCLUSIONS: Our observations showed that de novo genes and duplicated new genes possess mutually distinct regulatory characteristics, implying that these two types of genes might have different roles in evolution.

Impact of DNA-binding position variants on yeast gene expression.

Transcription factors (TFs) regulate gene expression by binding to specific binding sites (TFBSs) in gene promoters. TFBS motifs may contain one or more variable positions. Although the prevailing assumption is that nucleotide variants at such positions are functionally equivalent, there is increasing evidence that such variants play a role in regulation of gene expression. In this article, we propose a method for studying the relationship between the expression of target genes and nucleotide variants in TFBS motifs at a genome-wide scale in Saccharomyces cerevisiae, especially the combinatorial effects of variants at two positions. Our analysis shows that nucleotide variations in more than one-third of variable positions and in 20% of dependent position pairs are highly correlated to gene expression. We define such positions as 'functional'. However, some positions are only functional as dependent pairs, but not individually. In addition, a significant proportion of the functional positions have been well conserved across all yeast-related species studied. We also find that some positions require the presence of co-occurring TFs, while others maintain their functionality in the absence of a co-occurring TF. Our analysis supports the importance of nucleotide variants at variable positions of TFBSs in gene regulation.

Transgenic refractory Aedes aegypti lines are resistant to multiple serotypes of dengue virus.

The areas where dengue virus (DENV) is endemic have expanded rapidly, driven in part by the global spread of Aedes species, which act as disease vectors. DENV replicates in the mosquito midgut and is disseminated to the mosquito's salivary glands for amplification. Thus, blocking virus infection or replication in the tissues of the mosquito may be a viable strategy for reducing the incidence of DENV transmission to humans. Here we used the mariner Mos1 transposase to create an Aedes aegypti line that expresses virus-specific miRNA hairpins capable of blocking DENV replication. These microRNA are driven by the blood-meal-inducible carboxypeptidase A promoter or by the polyubiquitin promoter. The transgenic mosquitoes exhibited significantly lower infection rates and viral titers for most DENV serotypes 7 days after receiving an infectious blood meal. The treatment was also effective at day 14 post infection after a second blood meal had been administered. In viral transmission assay, we found there was significantly reduced transmission in these lines. These transgenic mosquitoes were effective in silencing most of the DENV genome; such an approach may be employed to control a dengue fever epidemic.

Somatic expression of piRNA and associated machinery in the mouse identifies short, tissue-specific piRNA.

Piwi-interacting RNAs (piRNAs) are small non-coding RNAs that associate with PIWI proteins for transposon silencing via DNA methylation and are highly expressed and extensively studied in the germline. Mature germline piRNAs typically consist of 24-32 nucleotides, with a strong preference for a 5' uridine signature, an adenosine signature at position 10, and a 2'-O-methylation signature at the 3' end. piRNA presence in somatic tissues, however, is not well characterized and requires further systematic evaluation. In the current study, we identified piRNAs and associated machinery from mouse somatic tissues representing the three germ layers. piRNA specificity was improved by combining small RNA size selection, sodium periodate treatment enrichment for piRNA over other small RNA, and small RNA next-generation sequencing. We identify PIWIL1, PIWIL2, and PIWIL4 expression in brain, liver, kidney, and heart. Of note, somatic piRNAs are shorter in length and tissue-specific, with increased occurrence of unique piRNAs in hippocampus and liver, compared to the germline. Hippocampus contains 5,494 piRNA-like peaks, the highest expression among all tested somatic tissues, followed by cortex (1,963), kidney (580), and liver (406). The study identifies 26 piRNA sequence species and 40 piRNA locations exclusive to all examined somatic tissues. Although piRNA expression has long been considered exclusive to the germline, our results support that piRNAs are expressed in several somatic tissues that may influence piRNA functions in the soma. Once confirmed, the PIWI/piRNA system may serve as a potential tool for future research in epigenome editing to improve human health by manipulating DNA methylation.

Borders of Cis-Regulatory DNA Sequences Preferentially Harbor the Divergent Transcription Factor Binding Motifs in the Human Genome.

Changes in cis-regulatory DNA sequences and transcription factor (TF) repertoires provide major sources of phenotypic diversity that shape the evolution of gene regulation in eukaryotes. The DNA-binding specificities of TFs may be diversified or produce new variants in different eukaryotic species. However, it is currently unclear how various levels of divergence in TF DNA-binding specificities or motifs became introduced into the cis-regulatory DNA regions of the genome over evolutionary time. Here, we first estimated the evolutionary divergence levels of TF binding motifs and quantified their occurrence at DNase I-hypersensitive sites. Results from our in silico motif scan and experimentally derived chromatin immunoprecipitation (TF-ChIP) show that the divergent motifs tend to be introduced in the edges of cis-regulatory regions, which is probably accompanied by the expansion of the accessible core of promoter-associated regulatory elements during evolution. We also find that the genes neighboring the expanded cis-regulatory regions with the most divergent motifs are associated with functions like development and morphogenesis. Accordingly, we propose that the accumulation of divergent motifs in the edges of cis-regulatory regions provides a functional mechanism for the evolution of divergent regulatory circuits.

Genome-wide analysis of enhancer RNA in gene regulation across 12 mouse tissues.

Enhancers play a crucial role in gene regulation but the participation of enhancer transcripts (i.e. enhancer RNA, eRNAs) in regulatory systems remains unclear. We provide a computational analysis on eRNAs using genome-wide data across 12 mouse tissues. The expression of genes targeted by transcribing enhancer is positively correlated with eRNA expression and significantly higher than expression of genes targeted by non-transcribing enhancers. This result implies eRNA transcription indicates a state of enhancer that further increases gene expression. This state of enhancer is tissue-specific, as the same enhancer differentially transcribes eRNAs across tissues. Therefore, the presence of eRNAs describes a tissue-specific state of enhancer that is generally associated with higher expressed target genes, surmising as to whether eRNAs have gene activation potential. We further found a large number of eRNAs contain regions in which sequences and secondary structures are similar to microRNAs. Interestingly, an increasing number of recent studies hypothesize that microRNAs may switch from their general repressive role to an activating role when targeting promoter sequences. Collectively, our results provide speculation that eRNAs may be associated with the selective activation of enhancer target genes.

Analysis of the association between transcription factor binding site variants and distinct accompanying regulatory motifs in yeast.

It is generally accepted that genes are regulated by the interactions between transcription factors (TFs) and their binding sites (TFBSs). Some studies have demonstrated that nucleotide variants at variable positions in TFBSs affect yeast gene regulation. Furthermore, variable positions in TFBSs in association with distinct accompanying regulatory motifs of other TFs (i.e., co-TFs) can also impact gene regulation in eukaryotes. Given that, even low-affinity TF-DNA interactions are abundant in vivo; we used both low- and high-affinity TFBSs and performed a genome-wide analysis of associations between variable positions and co-TFs. We found that, in Saccharomyces cerevisiae, approximately 14% of the variable positions in TFBSs demonstrate such associations. These associations occurred in close proximity on the same promoters (i.e., highly co-localized). Moreover, such associations were highly conserved between sensu stricto yeasts and also influenced gene expression, which were consistent with enriched functional categories.