A GREB1-steroid receptor feedforward mechanism governs differential GREB1 action in endometrial function and endometriosis.

Cellular responses to the steroid hormones, estrogen (E2), and progesterone (P4) are governed by their cognate receptor's transcriptional output. However, the feed-forward mechanisms that shape cell-type-specific transcriptional fulcrums for steroid receptors are unidentified. Herein, we found that a common feed-forward mechanism between GREB1 and steroid receptors regulates the differential effect of GREB1 on steroid hormones in a physiological or pathological context. In physiological (receptive) endometrium, GREB1 controls P4-responses in uterine stroma, affecting endometrial receptivity and decidualization, while not affecting E2-mediated epithelial proliferation. Of mechanism, progesterone-induced GREB1 physically interacts with the progesterone receptor, acting as a cofactor in a positive feedback mechanism to regulate P4-responsive genes. Conversely, in endometrial pathology (endometriosis), E2-induced GREB1 modulates E2-dependent gene expression to promote the growth of endometriotic lesions in mice. This differential action of GREB1 exerted by a common feed-forward mechanism with steroid receptors advances our understanding of mechanisms that underlie cell- and tissue-specific steroid hormone actions.

CPSF3 inhibition blocks pancreatic cancer cell proliferation through disruption of core histone mRNA processing.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with limited effective treatment options, potentiating the importance of uncovering novel drug targets. Here, we target cleavage and polyadenylation specificity factor 3 (CPSF3), the 3' endonuclease that catalyzes mRNA cleavage during polyadenylation and histone mRNA processing. We find that CPSF3 is highly expressed in PDAC and is associated with poor prognosis. CPSF3 knockdown blocks PDAC cell proliferation and colony formation in vitro and tumor growth in vivo. Chemical inhibition of CPSF3 by the small molecule JTE-607 also attenuates PDAC cell proliferation and colony formation, while it has no effect on cell proliferation of nontransformed immortalized control pancreatic cells. Mechanistically, JTE-607 induces transcriptional readthrough in replication-dependent histones, reduces core histone expression, destabilizes chromatin structure, and arrests cells in the S-phase of the cell cycle. Therefore, CPSF3 represents a potential therapeutic target for the treatment of PDAC.

NUDT21 alters glioma migration through differential alternative polyadenylation of LAMC1.

PURPOSE: Gliomas and their surrounding microenvironment constantly interact to promote tumorigenicity, yet the underlying posttranscriptional regulatory mechanisms that govern this interplay are poorly understood. METHODS: Utilizing our established PAC-seq approach and PolyAMiner bioinformatic analysis pipeline, we deciphered the NUDT21-mediated differential APA dynamics in glioma cells. RESULTS: We identified LAMC1 as a critical NUDT21 alternative polyadenylation (APA) target, common in several core glioma-driving signaling pathways. qRT-PCR analysis confirmed that NUDT21-knockdown in glioma cells results in the preferred usage of the proximal polyA signal (PAS) of LAMC1. Functional studies revealed that NUDT21-knockdown-induced 3'UTR shortening of LAMC1 is sufficient to cause translational gain, as LAMC1 protein is upregulated in these cells compared to their respective controls. We demonstrate that 3'UTR shortening of LAMC1 after NUDT21 knockdown removes binding sites for miR-124/506, thereby relieving potent miRNA-based repression of LAMC1 expression. Remarkably, we report that the knockdown of NUDT21 significantly promoted glioma cell migration and that co-depletion of LAMC1 with NUDT21 abolished this effect. Lastly, we observed that LAMC1 3'UTR shortening predicts poor prognosis of low-grade glioma patients from The Cancer Genome Atlas. CONCLUSION: This study identifies NUDT21 as a core alternative polyadenylation factor that regulates the tumor microenvironment through differential APA and loss of miR-124/506 inhibition of LAMC1. Knockdown of NUDT21 in GBM cells mediates 3'UTR shortening of LAMC1, contributing to an increase in LAMC1, increased glioma cell migration/invasion, and a poor prognosis.

Emerging roles of alternative cleavage and polyadenylation (APA) in human disease.

In the messenger RNA (mRNA) maturation process, the 3'-end of pre-mRNA is cleaved and a poly(A) sequence is added, this is an important determinant of mRNA stability and its cellular functions. More than 60%-70% of human genes have three or more polyadenylation (APA) sites and can be cleaved at different sites, generating mRNA transcripts of varying lengths. This phenomenon is termed as alternative cleavage and polyadenylation (APA) and it plays role in key biological processes like gene regulation, cell proliferation, senescence, and also in various human diseases. Loss of regulatory microRNA binding sites and interactions with RNA-binding proteins leading to APA are largely investigated in human diseases. However, the functions of the core APA machinery and related factors during disease conditions remain largely unknown. In this review, we discuss the roles of polyadenylation machinery in relation to brain disease, cardiac failure, pulmonary fibrosis, cancer, infectious conditions, and other human diseases. Collectively, we believe this review will be a useful avenue for understanding the emerging role of APA in the pathobiology of various human diseases.

PolyA-miner: accurate assessment of differential alternative poly-adenylation from 3'Seq data using vector projections and non-negative matrix factorization.

Almost 70% of human genes undergo alternative polyadenylation (APA) and generate mRNA transcripts with varying lengths, typically of the 3' untranslated regions (UTR). APA plays an important role in development and cellular differentiation, and its dysregulation can cause neuropsychiatric diseases and increase cancer severity. Increasing awareness of APA's role in human health and disease has propelled the development of several 3' sequencing (3'Seq) techniques that allow for precise identification of APA sites. However, despite the recent data explosion, there are no robust computational tools that are precisely designed to analyze 3'Seq data. Analytical approaches that have been used to analyze these data predominantly use proximal to distal usage. With about 50% of human genes having more than two APA isoforms, current methods fail to capture the entirety of APA changes and do not account for non-proximal to non-distal changes. Addressing these key challenges, this study demonstrates PolyA-miner, an algorithm to accurately detect and assess differential alternative polyadenylation specifically from 3'Seq data. Genes are abstracted as APA matrices, and differential APA usage is inferred using iterative consensus non-negative matrix factorization (NMF) based clustering. PolyA-miner accounts for all non-proximal to non-distal APA switches using vector projections and reflects precise gene-level 3'UTR changes. It can also effectively identify novel APA sites that are otherwise undetected when using reference-based approaches. Evaluation on multiple datasets-first-generation MicroArray Quality Control (MAQC) brain and Universal Human Reference (UHR) PolyA-seq data, recent glioblastoma cell line NUDT21 knockdown Poly(A)-ClickSeq (PAC-seq) data, and our own mouse hippocampal and human stem cell-derived neuron PAC-seq data-strongly supports the value and protocol-independent applicability of PolyA-miner. Strikingly, in the glioblastoma cell line data, PolyA-miner identified more than twice the number of genes with APA changes than initially reported. With the emerging importance of APA in human development and disease, PolyA-miner can significantly improve data analysis and help decode the underlying APA dynamics.

An ultra-fast and scalable quantification pipeline for transposable elements from next generation sequencing data.

Transposable elements (TEs) are DNA sequences which are capable of moving from one location to another and represent a large proportion (45%) of the human genome. TEs have functional roles in a variety of biological phenomena such as cancer, neurodegenerative disease, and aging. Rapid development in RNA-sequencing technology has enabled us, for the first time, to study the activity of TE at the systems level.However, efficient TE analysis tools are not yet developed. In this work, we developed SalmonTE, a fast and reliable pipeline for the quantification of TEs from RNA-seq data. We benchmarked our tool against TEtranscripts, a widely used TE quantification method, and three other quantification methods using several RNA-seq datasets from Drosophila melanogaster and human cell-line. We achieved 20 times faster execution speed without compromising the accuracy. This pipeline will enable the biomedical research community to quantify and analyze TEs from large amounts of data and lead to novel TE centric discoveries.

Transcriptional Regulation by ATOH1 and its Target SPDEF in the Intestine.

BACKGROUND & AIMS: The transcription factor atonal homolog 1 (ATOH1) controls the fate of intestinal progenitors downstream of the Notch signaling pathway. Intestinal progenitors that escape Notch activation express high levels of ATOH1 and commit to a secretory lineage fate, implicating ATOH1 as a gatekeeper for differentiation of intestinal epithelial cells. Although some transcription factors downstream of ATOH1, such as SPDEF, have been identified to specify differentiation and maturation of specific cell types, the bona fide transcriptional targets of ATOH1 still largely are unknown. Here, we aimed to identify ATOH1 targets and to identify transcription factors that are likely to co-regulate gene expression with ATOH1. METHODS: We used a combination of chromatin immunoprecipitation and messenger RNA-based high-throughput sequencing (ChIP-seq and RNA-seq), together with cell sorting and transgenic mice, to identify direct targets of ATOH1, and establish the epistatic relationship between ATOH1 and SPDEF. RESULTS: By using unbiased genome-wide approaches, we identified more than 700 genes as ATOH1 transcriptional targets in adult small intestine and colon. Ontology analysis indicated that ATOH1 directly regulates genes involved in specification and function of secretory cells. De novo motif analysis of ATOH1 targets identified SPDEF as a putative transcriptional co-regulator of ATOH1. Functional epistasis experiments in transgenic mice show that SPDEF amplifies ATOH1-dependent transcription but cannot independently initiate transcription of ATOH1 target genes. CONCLUSIONS: This study unveils the direct targets of ATOH1 in the adult intestines and illuminates the transcriptional events that initiate the specification and function of intestinal secretory lineages.

SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples.

Conventionally, overall gene expressions from microarrays are used to infer gene networks, but it is challenging to account splicing isoforms. High-throughput RNA Sequencing has made splice variant profiling practical. However, its true merit in quantifying splicing isoforms and isoform-specific exon expressions is not well explored in inferring gene networks. This study demonstrates SpliceNet, a method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large dimensional trace. It goes beyond differentially expressed genes and infers splicing isoform network changes between normal and diseased samples. It eases the sample size bottleneck; evaluations on simulated data and lung cancer-specific ERBB2 and MAPK signaling pathways, with varying number of samples, evince the merit in handling high exon to sample size ratio datasets. Inferred network rewiring of well established Bcl-x and EGFR centered networks from lung adenocarcinoma expression data is in good agreement with literature. Gene level evaluations demonstrate a substantial performance of SpliceNet over canonical correlation analysis, a method that is currently applied to exon level RNA-Seq data. SpliceNet can also be applied to exon array data. SpliceNet is distributed as an R package available at http://www.jjwanglab.org/SpliceNet.

Inference of gene-phenotype associations via protein-protein interaction and orthology.

One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.