Whole-Genome rVISTA: a tool to determine enrichment of transcription factor binding sites in gene promoters from transcriptomic data

Omics-Based Identification of Shared and Gender Disparity Routes in Hras12V-Induced Hepatocarcinogenesis: An Important Role for Dlk1-Dio3 Genomic Imprinting Region

The phenomenon of gender disparity is very profound in hepatocellular carcinoma (HCC). Although previous research has revealed important roles of microRNA (miRNA) in HCC, there are no studies investigating the role of miRNAs in gender disparity observed hepatocarcinogenesis. In the present study, we investigated the global miRNAomics changes related to Ras-induced male-prevalent hepatocarcinogenesis in a Hras12V-transgenic mouse model (Ras-Tg) by next-generation sequencing (NGS). We identified shared by also unique changes in miRNA expression profiles in gender-dependent hepatocarcinogenesis. Two hundred sixty-four differentially expressed miRNAs (DEMIRs) with q value ≤0.05 and fold change ≥2 were identified. A vertical comparison revealed that the lower numbers of DEMIRs in the hepatic tumor (T) compared with the peri-tumor precancerous tissue (P) of Ras-Tg and normal liver tissue of wild-type C57BL/6J mice (W) in males indicated that males are more susceptible to develop HCC. The expression pattern analysis revealed 43 common HCC-related miRNAs and 4 Ras-positive-related miRNAs between males and females. By integrating the mRNA transcriptomic data and using 3-node FFL analysis, a group of significant components commonly contributing to HCC between sexes were filtered out. A horizontal comparison showed that the majority of DEMIRs are located in the Dlk1-Dio3 genomic imprinting region (GIR) and that they are closely related to not only hepatic tumorigenesis but also to gender disparity in hepatocarcinogenesis. This is achieved by regulating multiple metabolic pathways, including retinol, bile acid, and steroid hormones. In conclusion, the identification of shared and gender-dependent DEMIRs in hepatocarcinogenesis provides valuable insights into the mechanisms that contribute to male-biased Ras-induced hepatic carcinogenesis.

Transcription factors–DNA interactions in rice: identification and verification

The completion of the rice genome sequence paved the way for rice functional genomics research. Additionally, the functional characterization of transcription factors is currently a popular and crucial objective among researchers. Transcription factors are one of the groups of proteins that bind to either enhancer or promoter regions of genes to regulate expression. On the basis of several typical examples of transcription factor analyses, we herein summarize selected research strategies and methods and introduce their advantages and disadvantages. This review may provide some theoretical and technical guidelines for future investigations of transcription factors, which may be helpful to develop new rice varieties with ideal traits.

Screening of Key Genes in Severe Burn Injury at Different Stages via Analyzing Gene Expression Data

Microarray analysis was performed to investigate the changes in gene expression profiles after severe burn injury at the early and middle stages, further discovering therapeutic targets for severe burn injury. Microarray data (GSE19743) were downloaded from Gene Expression Omnibus. First, differentially expressed genes (DEGs) at different stages were screened using limma package. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were then performed using DAVID. Protein-protein interaction (PPI) networks were also constructed using String database. Additionally, transcription factor binding site was detected using the Whole-Genome rVISTA. Compared with the healthy controls, 160 DEGs were identified in patients with early-stage burn injury and 261 DEGs were obtained in patients with middle-stage burn injury. Only 10 genes showed differential expression between the early and middle stages. KEGG functional analysis indicated that DEGs detected at the early stage were mainly enriched in the immune response, kinase activity, and signaling pathways and DEGs detected at the middle stage were involved in the immune response, protein and fat metabolism, and programmed cell death pathways. Three PPI networks were constructed and hub proteins with high degrees of connection were screened, such as lactotransferrin, interleukin 8, and perforin-1. Additionally, many transcription factor binding sites that may be involved in the regulation of these DEGs were also detected. A number of DEGs were identified in patients with early- and middle-stage burn injury, which helps to deepen the understanding about the molecular mechanism underlying severe burn injury.

Uromodulin p.Cys147Trp mutation drives kidney disease by activating ER stress and apoptosis

Uromodulin-associated kidney disease (UAKD) is caused by mutations in the uromodulin (UMOD) gene that result in a misfolded form of UMOD protein, which is normally secreted by nephrons. In UAKD patients, mutant UMOD is poorly secreted and accumulates in the ER of distal kidney epithelium, but its role in disease progression is largely unknown. Here, we modeled UMOD accumulation in mice by expressing the murine equivalent of the human UMOD p.Cys148Trp point mutation (UmodC147W/+ mice). Like affected humans, these UmodC147W/+ mice developed spontaneous and progressive kidney disease with organ failure over 24 weeks. Analysis of diseased kidneys and purified UMOD-producing cells revealed early activation of the PKR-like ER kinase/activating transcription factor 4 (PERK/ATF4) ER stress pathway, innate immune mediators, and increased apoptotic signaling, including caspase-3 activation. Unexpectedly, we also detected autophagy deficiency. Human cells expressing UMOD p.Cys147Trp recapitulated the findings in UmodC147W/+ mice, and autophagy activation with mTOR inhibitors stimulated the intracellular removal of aggregated mutant UMOD. Human cells producing mutant UMOD were susceptible to TNF-α- and TRAIL-mediated apoptosis due to increased expression of the ER stress mediator tribbles-3. Blocking TNF-α in vivo with the soluble recombinant fusion protein TNFR:Fc slowed disease progression in UmodC147W/+ mice by reducing active caspase-3, thereby preventing tubule cell death and loss of epithelial function. These findings reveal a targetable mechanism for disease processes involved in UAKD.

Genome-wide DNA methylation patterns in coronary heart disease

BACKGROUND

To better understand the molecular mechanisms of atherosclerosis, we conducted a comparative analysis of DNA methylation patterns in right coronary arteries in the area of advanced atherosclerotic plaques (CAP), great saphenous vein (GSV), and internal mammary artery (IMA) of patients affected by coronary heart disease.

METHODS

DNA methylation data (accession number E‑GEOD-62867) were divided into three paired groups: CAP vs. IMA, CAP vs. GSV, and IMA vs. GSV. Differentially methylated genes (DMGs) were extracted to analyze the changes in the DMGs in the three different tissues. The gplots package was used for the clustering and heatmap analysis of DMGs. Subsequently, DMG-related pathways were identified using DAVID (Database for Annotation, Visualization and Integrated Discovery) and transcription factors (TFs) were predicted.

RESULTS

Based on the filtering criterion of p < 0.05, and a mean beta value difference of ≥0.2, there were 252, 373, and 259 DMGs, respectively, in the CAP vs. IMA, CAP vs. GSV, and IMA vs. GSV groups. Interestingly, the S100A10 gene was hypomethylated in CAP compared with IMA and GSV. Clustering and heatmap analyses suggested that DMGs were segregated into two distinct clusters. Hypermethylated genes in CAP as compared with GSV were only involved in the pathway of fat digestion and absorption, while hypomethylated genes in CAP compared with GSV mainly participated in immune response-associated pathways (cytokine-cytokine receptor interaction, MAPK signaling pathway).

CONCLUSION

The DNA methylation differences in vascular tissues of patients with coronary artery disease may provide new insights into the mechanisms underlying the development of atherosclerosis. The functions identified here-cytokine-cytokine receptor interaction, MAPK signaling pathway, DMG (S100A10), and TF (NF-kB)-may serve as potential targets in the treatment of atherosclerosis.

Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through targeting critical genes in cellular system. However, it is unclear about which miRNAs play central roles in CRC’s pathogenesis and how they interact with transcription factors (TFs) to regulate the cancer-related genes.

Results

To address this issue, we systematically explored the major regulation motifs, namely feed-forward loops (FFLs), that consist of miRNAs, TFs and CRC-related genes through the construction of a miRNA-TF regulatory network in CRC. First, we compiled CRC-related miRNAs, CRC-related genes, and human TFs from multiple data sources. Second, we identified 13,123 3-node FFLs including 25 miRNA-FFLs, 13,005 TF-FFLs and 93 composite-FFLs, and merged the 3-node FFLs to construct a CRC-related regulatory network. The network consists of three types of regulatory subnetworks (SNWs): miRNA-SNW, TF-SNW, and composite-SNW. To enhance the accuracy of the network, the results were filtered by using The Cancer Genome Atlas (TCGA) expression data in CRC, whereby we generated a core regulatory network consisting of 58 significant FFLs. We then applied a hub identification strategy to the significant FFLs and found 5 significant components, including two miRNAs (hsa-miR-25 and hsa-miR-31), two genes (ADAMTSL3 and AXIN1) and one TF (BRCA1). The follow up prognosis analysis indicated all of the 5 significant components having good prediction of overall survival of CRC patients.

Conclusions

In summary, we generated a CRC-specific miRNA-TF regulatory network, which is helpful to understand the complex CRC regulatory mechanisms and guide clinical treatment. The discovered 5 regulators might have critical roles in CRC pathogenesis and warrant future investigation.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1796-4) contains supplementary material, which is available to authorized users.

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data

Many genetic variants that influence phenotypes of interest are located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which, therefore, are likely to be phenotypically important. LINSIGHT combines a generalized linear model for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the 'big data' available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell type, tissue specificity, and constraints at associated promoters.

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background

Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them.

Results

Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs).

Conclusions

The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3580-2) contains supplementary material, which is available to authorized users.

From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach

High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

Transcriptional and Linkage Analyses Identify Loci that Mediate the Differential Macrophage Response to Inflammatory Stimuli and Infection

Macrophages display flexible activation states that range between pro-inflammatory (classical activation) and anti-inflammatory (alternative activation). These macrophage polarization states contribute to a variety of organismal phenotypes such as tissue remodeling and susceptibility to infectious and inflammatory diseases. Several macrophage- or immune-related genes have been shown to modulate infectious and inflammatory disease pathogenesis. However, the potential role that differences in macrophage activation phenotypes play in modulating differences in susceptibility to infectious and inflammatory disease is just emerging. We integrated transcriptional profiling and linkage analyses to determine the genetic basis for the differential murine macrophage response to inflammatory stimuli and to infection with the obligate intracellular parasite Toxoplasma gondii. We show that specific transcriptional programs, defined by distinct genomic loci, modulate macrophage activation phenotypes. In addition, we show that the difference between AJ and C57BL/6J macrophages in controlling Toxoplasma growth after stimulation with interferon gamma and tumor necrosis factor alpha mapped to chromosome 3, proximal to the Guanylate binding protein (Gbp) locus that is known to modulate the murine macrophage response to Toxoplasma. Using an shRNA-knockdown strategy, we show that the transcript levels of an RNA helicase, Ddx1, regulates strain differences in the amount of nitric oxide produced by macrophage after stimulation with interferon gamma and tumor necrosis factor. Our results provide a template for discovering candidate genes that modulate macrophage-mediated complex traits.

Macrophages provide a first line of defense against invading pathogens and play an important role in the initiation and resolution of immune responses. When in contact with pathogens or immune factors, such as cytokines, macrophages assume activation states that range between pro-inflammatory (classical activation) and anti-inflammatory (alternative activation). Even though it is known that macrophages from different individuals are biased towards one of the various activation states, the genetic factors that define individual differences in macrophage activation are not fully understood. Additionally, although macrophages are important in infectious disease pathogenesis, how individual differences in macrophage activation contribute to individual differences in susceptibility to infectious disease is just emerging. We used macrophages from genetically segregating mice to show that discrete transcriptional programs, which are modulated by specific genomic regions, modulate differences in macrophage activation. Murine macrophages differences in controlling Toxoplasma growth mapped to chromosome 3, proximal to the Guanylate binding protein (Gbp) locus that is known to modulate the murine macrophage response to Toxoplasma. Using a shRNA-mediated knockdown approach, we show that the DEAD box polypeptide 1 (Ddx1) modulates nitric oxide production in macrophages stimulated with interferon gamma and tumor necrosis factor. These findings are a step towards the identification of genes that regulate macrophage phenotypes and disease outcome.

Emerging role of transcription factor-microRNA-target gene feed-forward loops in cancer

Transcriptional regulatory networks are biological network motifs that act in accordance with each other to play decisive roles in the pathological processes of cancer. One of the most common types, the feed-forward loop (FFL), has recently attracted interest. Three connected deregulated nodes, a transcription factor (TF), its downstream microRNA (miRNA) and their shared target gene can make up a class of cancer-involved FFLs as ≥1 of the 3 can act individually as a bona fide oncogene or a tumor suppressor. Numerous notable elements, such as p53, miR-17-92 cluster and cyclins, are proven members of their respective FFLs. Databases of interaction prediction, verification of experimental methods and confirmation of loops have been continually emerging during recent years. Development of TF-miRNA-target loops may help understand the mechanism of tumorgenesis at a higher level and explain the discovery and screening of the therapeutic target for drug exploitation.

Comprehensive analysis of gene-expression profile in chronic obstructive pulmonary disease

OBJECTIVE

To investigate the gene-expression profile of chronic obstructive pulmonary disease (COPD) patients and explore the possible therapeutic targets.

METHODS

The microarray raw dataset GSE29133, including three COPD samples and three normal samples, was obtained from Gene Expression Omnibus. After data preprocessing with the Affy package, Student's t-test was employed to identify the differentially expressed genes (DEGs). The up- and downregulated DEGs were then pooled for gene-ontology and pathway-enrichment analyses using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The upstream regulatory elements of these DEGs were also explored by using Whole-Genome rVISTA. Furthermore, we constructed a protein-protein interaction (PPI) network for DEGs. The surfactant protein D (SP-D) serum level and HLA-A gene frequency in COPD patients and healthy controls were also measured by enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction, respectively.

RESULTS

A total of 39 up- and 15 downregulated DEGs were screened. Most of the upregulated genes were involved in the immune response process, while the downregulated genes were involved in the steroid metabolic process. Moreover, we also found that HLA-A has the highest degree in the PPI network. The SP-D serum level and HLA-A gene frequency in COPD patients were significantly higher than those in healthy controls (13.62±2.09 ng/mL vs 10.28±2.86 ng/mL; 62.5% vs 12.5%; P<0.05).

CONCLUSION

Our results may help further the understanding of the mechanisms of COPD. The identified DEGs, especially HLA-A, may serve as diagnosis markers for COPD.

HIF1α Represses Cell Stress Pathways to Allow Proliferation of Hypoxic Fetal Cardiomyocytes

Transcriptional mediators of cell stress pathways, including HIF1α, ATF4, and p53, are key to normal development and play critical roles in disease, including ischemia and cancer. Despite their importance, mechanisms by which pathways mediated by these transcription factors interact with one another are not fully understood. In addressing the controversial role of HIF1α in cardiomyocytes (CMs) during heart development, we discovered a mid-gestational requirement for HIF1α for proliferation of hypoxic CMs, involving metabolic switching and a complex interplay among HIF1α, ATF4, and p53. Loss of HIF1α resulted in activation of ATF4 and p53, the latter inhibiting CM proliferation. Bioinformatic and biochemical analyses revealed unexpected mechanisms by which HIF1α intersects with ATF4 and p53 pathways. Our results highlight previously undescribed roles of HIF1α and interactions among major cell stress pathways that could be targeted to enhance proliferation of CMs in ischemia and may have relevance to other diseases, including cancer.

Transcriptional control of stem cell fate by E2Fs and pocket proteins

E2F transcription factors and their regulatory partners, the pocket proteins (PPs), have emerged as essential regulators of stem cell fate control in a number of lineages. In mammals, this role extends from both pluripotent stem cells to those encompassing all embryonic germ layers, as well as extra-embryonic lineages. E2F/PP-mediated regulation of stem cell decisions is highly evolutionarily conserved, and is likely a pivotal biological mechanism underlying stem cell homeostasis. This has immense implications for organismal development, tissue maintenance, and regeneration. In this article, we discuss the roles of E2F factors and PPs in stem cell populations, focusing on mammalian systems. We discuss emerging findings that position the E2F and PP families as widespread and dynamic epigenetic regulators of cell fate decisions. Additionally, we focus on the ever expanding landscape of E2F/PP target genes, and explore the possibility that E2Fs are not simply regulators of general ‘multi-purpose’ cell fate genes but can execute tissue- and cell type-specific gene regulatory programs.

Mitochondrial reprogramming induced by CaMKIIδ mediates hypertrophy decompensation

RATIONALE

Sustained activation of Gαq transgenic (Gq) signaling during pressure overload causes cardiac hypertrophy that ultimately progresses to dilated cardiomyopathy. The molecular events that drive hypertrophy decompensation are incompletely understood. Ca(2+)/calmodulin-dependent protein kinase II δ (CaMKIIδ) is activated downstream of Gq, and overexpression of Gq and CaMKIIδ recapitulates hypertrophy decompensation.

OBJECTIVE

To determine whether CaMKIIδ contributes to hypertrophy decompensation provoked by Gq.

METHODS AND RESULTS

Compared with Gq mice, compound Gq/CaMKIIδ knockout mice developed a similar degree of cardiac hypertrophy but exhibited significantly improved left ventricular function, less cardiac fibrosis and cardiomyocyte apoptosis, and fewer ventricular arrhythmias. Markers of oxidative stress were elevated in mitochondria from Gq versus wild-type mice and respiratory rates were lower; these changes in mitochondrial function were restored by CaMKIIδ deletion. Gq-mediated increases in mitochondrial oxidative stress, compromised membrane potential, and cell death were recapitulated in neonatal rat ventricular myocytes infected with constitutively active Gq and attenuated by CaMKII inhibition. Deep RNA sequencing revealed altered expression of 41 mitochondrial genes in Gq hearts, with normalization of ≈40% of these genes by CaMKIIδ deletion. Uncoupling protein 3 was markedly downregulated in Gq or by Gq expression in neonatal rat ventricular myocytes and reversed by CaMKIIδ deletion or inhibition, as was peroxisome proliferator-activated receptor α. The protective effects of CaMKIIδ inhibition on reactive oxygen species generation and cell death were abrogated by knock down of uncoupling protein 3. Conversely, restoration of uncoupling protein 3 expression attenuated reactive oxygen species generation and cell death induced by CaMKIIδ. Our in vivo studies further demonstrated that pressure overload induced decreases in peroxisome proliferator-activated receptor α and uncoupling protein 3, increases in mitochondrial protein oxidation, and hypertrophy decompensation, which were attenuated by CaMKIIδ deletion.

CONCLUSIONS

Mitochondrial gene reprogramming induced by CaMKIIδ emerges as an important mechanism contributing to mitotoxicity in decompensating hypertrophy.

Cyclic stretch of embryonic cardiomyocytes increases proliferation, growth, and expression while repressing Tgf-β signaling

Perturbed biomechanical stimuli are thought to be critical for the pathogenesis of a number of congenital heart defects, including Hypoplastic Left Heart Syndrome (HLHS). While embryonic cardiomyocytes experience biomechanical stretch every heart beat, their molecular responses to biomechanical stimuli during heart development are poorly understood. We hypothesized that biomechanical stimuli activate specific signaling pathways that impact proliferation, gene expression and myocyte contraction. The objective of this study was to expose embryonic mouse cardiomyocytes (EMCM) to cyclic stretch and examine key molecular and phenotypic responses. Analysis of RNA-Sequencing data demonstrated that gene ontology groups associated with myofibril and cardiac development were significantly modulated. Stretch increased EMCM proliferation, size, cardiac gene expression, and myofibril protein levels. Stretch also repressed several components belonging to the Transforming Growth Factor-β (Tgf-β) signaling pathway. EMCMs undergoing cyclic stretch had decreased Tgf-β expression, protein levels, and signaling. Furthermore, treatment of EMCMs with a Tgf-β inhibitor resulted in increased EMCM size. Functionally, Tgf-β signaling repressed EMCM proliferation and contractile function, as assayed via dynamic monolayer force microscopy (DMFM). Taken together, these data support the hypothesis that biomechanical stimuli play a vital role in normal cardiac development and for cardiac pathology, including HLHS.

The let-7/LIN-41 pathway regulates reprogramming to human induced pluripotent stem cells by controlling expression of prodifferentiation genes

Reprogramming differentiated cells into induced pluripotent stem cells (iPSCs) promotes a broad array of cellular changes. Here we show that the let-7 family of microRNAs acts as an inhibitory influence on the reprogramming process through a regulatory pathway involving prodifferentiation factors, including EGR1. Inhibiting let-7 in human cells promotes reprogramming to a comparable extent to c-MYC when combined with OCT4, SOX2, and KLF4, and persistence of let-7 inhibits reprogramming. Inhibiting let-7 during reprogramming leads to an increase in the level of the let-7 target LIN-41/TRIM71, which in turn promotes reprogramming and is important for overcoming the let-7 barrier to reprogramming. Mechanistic studies revealed that LIN-41 regulates a broad array of differentiation genes, and more specifically, inhibits translation of EGR1 through binding its cognate mRNA. Together our findings outline a let-7-based pathway that counteracts the activity of reprogramming factors through promoting the expression of prodifferentiation genes.