The E3 ubiquitin ligase Nedd4L preserves skeletal muscle stem cell quiescence by inhibiting their activation.

Adult stem cells play a critical role in tissue repair and maintenance. In tissues with slow turnover, including skeletal muscle, these cells are maintained in a mitotically quiescent state yet remain poised to re-enter the cell cycle to replenish themselves and regenerate the tissue. Using a panomics approach we show that the PAX7/NEDD4L axis acts against muscle stem cell activation in homeostatic skeletal muscle. Our findings suggest that PAX7 transcriptionally activates the E3 ubiquitin ligase Nedd4L and that the conditional genetic deletion of Nedd4L impairs muscle stem cell quiescence, with an upregulation of cell cycle and myogenic differentiation genes. Loss of Nedd4L in muscle stem cells results in the expression of doublecortin (DCX), which is exclusively expressed during their in vivo activation. Together, these data establish that the ubiquitin proteasome system, mediated by Nedd4L, is a key contributor to the muscle stem cell quiescent state in adult mice.

Accurate isoform quantification by joint short- and long-read RNA-sequencing.

Accurate quantification of transcript isoforms is crucial for understanding gene regulation, functional diversity, and cellular behavior. Existing RNA sequencing methods have significant limitations: short-read (SR) sequencing provides high depth but struggles with isoform deconvolution, whereas long-read (LR) sequencing offers isoform resolution at the cost of lower depth, higher noise, and technical biases. Addressing this gap, we introduce Multi-Platform Aggregation and Quantification of Transcripts (MPAQT), a generative model that combines the complementary strengths of different sequencing platforms to achieve state-of-the-art isoform-resolved transcript quantification, as demonstrated by extensive simulations and experimental benchmarks. By applying MPAQT to an in vitro model of human embryonic stem cell differentiation into cortical neurons, followed by machine learning-based modeling of transcript abundances, we show that untranslated regions (UTRs) are major determinants of isoform proportion and exon usage; this effect is mediated through isoform-specific sequence features embedded in UTRs, which likely interact with RNA-binding proteins that modulate mRNA stability. These findings highlight MPAQT's potential to enhance our understanding of transcriptomic complexity and underline the role of splicing-independent post-transcriptional mechanisms in shaping the isoform and exon usage landscape of the cell.

PHF6-mediated transcriptional control of NSC via Ephrin receptors is impaired in the intellectual disability syndrome BFLS.

The plant homeodomain zinc-finger protein, PHF6, is a transcriptional regulator, and PHF6 germline mutations cause the X-linked intellectual disability (XLID) Börjeson-Forssman-Lehmann syndrome (BFLS). The mechanisms by which PHF6 regulates transcription and how its mutations cause BFLS remain poorly characterized. Here, we show genome-wide binding of PHF6 in the developing cortex in the vicinity of genes involved in central nervous system development and neurogenesis. Characterization of BFLS mice harbouring PHF6 patient mutations reveals an increase in embryonic neural stem cell (eNSC) self-renewal and a reduction of neural progenitors. We identify a panel of Ephrin receptors (EphRs) as direct transcriptional targets of PHF6. Mechanistically, we show that PHF6 regulation of EphR is impaired in BFLS mice and in conditional Phf6 knock-out mice. Knockdown of EphR-A phenocopies the PHF6 loss-of-function defects in altering eNSCs, and its forced expression rescues defects of BFLS mice-derived eNSCs. Our data indicate that PHF6 directly promotes Ephrin receptor expression to control eNSC behaviour in the developing brain, and that this pathway is impaired in BFLS.

Pyruvate Kinase M (PKM) binds ribosomes in a poly-ADP ribosylation dependent manner to induce translational stalling.

In light of the numerous studies identifying post-transcriptional regulators on the surface of the endoplasmic reticulum (ER), we asked whether there are factors that regulate compartment specific mRNA translation in human cells. Using a proteomic survey of spatially regulated polysome interacting proteins, we identified the glycolytic enzyme Pyruvate Kinase M (PKM) as a cytosolic (i.e. ER-excluded) polysome interactor and investigated how it influences mRNA translation. We discovered that the PKM-polysome interaction is directly regulated by ADP levels-providing a link between carbohydrate metabolism and mRNA translation. By performing enhanced crosslinking immunoprecipitation-sequencing (eCLIP-seq), we found that PKM crosslinks to mRNA sequences that are immediately downstream of regions that encode lysine- and glutamate-enriched tracts. Using ribosome footprint protection sequencing, we found that PKM binding to ribosomes causes translational stalling near lysine and glutamate encoding sequences. Lastly, we observed that PKM recruitment to polysomes is dependent on poly-ADP ribosylation activity (PARylation)-and may depend on co-translational PARylation of lysine and glutamate residues of nascent polypeptide chains. Overall, our study uncovers a novel role for PKM in post-transcriptional gene regulation, linking cellular metabolism and mRNA translation.

Transcriptional reprogramming of skeletal muscle stem cells by the niche environment.

Adult stem cells are indispensable for tissue regeneration, but their function declines with age. The niche environment in which the stem cells reside plays a critical role in their function. However, quantification of the niche effect on stem cell function is lacking. Using muscle stem cells (MuSC) as a model, we show that aging leads to a significant transcriptomic shift in their subpopulations accompanied by locus-specific gain and loss of chromatin accessibility and DNA methylation. By combining in vivo MuSC transplantation and computational methods, we show that the expression of approximately half of all age-altered genes in MuSCs from aged male mice can be restored by exposure to a young niche environment. While there is a correlation between gene reversibility and epigenetic alterations, restoration of gene expression occurs primarily at the level of transcription. The stem cell niche environment therefore represents an important therapeutic target to enhance tissue regeneration in aging.

Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs.

Measuring mRNA decay in tumours is a prohibitive challenge, limiting our ability to map the post-transcriptional programs of cancer. Here, using a statistical framework to decouple transcriptional and post-transcriptional effects in RNA-seq data, we uncover the mRNA stability changes that accompany tumour development and progression. Analysis of 7760 samples across 18 cancer types suggests that mRNA stability changes are ~30% as frequent as transcriptional events, highlighting their widespread role in shaping the tumour transcriptome. Dysregulation of programs associated with >80 RNA-binding proteins (RBPs) and microRNAs (miRNAs) drive these changes, including multi-cancer inactivation of RBFOX and miR-29 families. Phenotypic activation or inhibition of RBFOX1 highlights its role in calcium signaling dysregulation, while modulation of miR-29 shows its impact on extracellular matrix organization and stemness genes. Overall, our study underlines the integral role of mRNA stability in shaping the cancer transcriptome, and provides a resource for systematic interrogation of cancer-associated stability pathways.

An integrated model of acinar to ductal metaplasia-related N7-methyladenosine regulators predicts prognosis and immunotherapy in pancreatic carcinoma based on digital spatial profiling.

Acinar-to-ductal metaplasia (ADM) is a recently recognized, yet less well-studied, precursor lesion of pancreatic ductal adenocarcinoma (PDAC) developed in the setting of chronic pancreatitis. Through digital spatial mRNA profiling, we compared ADM and adjacent PDAC tissues from patient samples to unveil the bridging genes during the malignant transformation of pancreatitis. By comparing the bridging genes with the 7-methylguanosine (m7G)-seq dataset, we screened 19 m7G methylation genes for a subsequent large sample analysis. We constructed the "m7G score" model based on the RNA-seq data for pancreatic cancer in The Cancer Genome Atlas (TCGA) database and The Gene Expression Omnibus (GEO) database. Tumors with a high m7G score were characterized by increased immune cell infiltration, increased genomic instability, higher response rate to combined immune checkpoint inhibitors (ICIs), and overall poor survival. These findings indicate that the m7G score is associated with tumor invasiveness, immune cell infiltration, ICI treatment response, and overall patients' survival. We also identified FN1 and ITGB1 as core genes in the m7Gscore model, which affect immune cell infiltration and genomic instability not only in pancreatic cancer but also in pan-cancer. FN1 and ITGB1 can inhibit immune T cell activition by upregulation of macrophages and neutrophils, thereby leading to immune escape of pancreatic cancer cells and reducing the response rate of ICI treatment.

Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding.

BACKGROUND: While methylation of CpG dinucleotides is traditionally considered antagonistic to the DNA-binding activity of most transcription factors (TFs), recent in vitro studies have revealed a more complex picture, suggesting that over a third of TFs may preferentially bind to methylated sequences. Expanding these in vitro observations to in vivo TF binding preferences is challenging since the effect of methylation of individual CpG sites cannot be easily isolated from the confounding effects of DNA accessibility and regional DNA methylation. Thus, in vivo methylation preferences of most TFs remain uncharacterized. RESULTS: We introduce joint accessibility-methylation-sequence (JAMS) models, which connect the strength of the binding signal observed in ChIP-seq to the DNA accessibility of the binding site, regional methylation level, DNA sequence, and base-resolution cytosine methylation. We show that JAMS models quantitatively explain TF occupancy, recapitulate cell type-specific TF binding, and have high positive predictive value for identification of TFs affected by intra-motif methylation. Analysis of 2209 ChIP-seq experiments results in high-confidence JAMS models for 260 TFs, revealing a negative association between in vivo TF occupancy and intra-motif methylation for 45% of studied TFs, as well as 16 TFs that are predicted to bind to methylated sites, including 11 novel methyl-binding TFs mostly from the multi-zinc finger family. CONCLUSIONS: Our study substantially expands the repertoire of in vivo methyl-binding TFs, but also suggests that most TFs that prefer methylated CpGs in vitro present themselves as methylation agnostic in vivo, potentially due to the balancing effect of competition with other methyl-binding proteins.

Analysis of mRNA Dynamics Using RNA Sequencing Data.

The RNA abundance of each gene is determined by its rates of transcription and RNA decay. Biochemical experiments that measure these rates, including transcription inhibition and metabolic labelling, are challenging to perform and are largely limited to in vitro settings. Most transcriptomic studies have focused on analyzing changes in RNA abundances without attributing those changes to transcriptional or posttranscriptional regulation. Estimating differential transcription and decay rates of RNA molecules would enable the identification of regulatory factors, such as transcription factors, RNA binding proteins, and microRNAs, that govern large-scale shifts in RNA expression. Here, we describe a protocol for estimating differential stability of RNA molecules between conditions using standard RNA-sequencing data, without the need for transcription inhibition or metabolic labeling. We apply this protocol to in vivo RNA-seq data from individuals with Alzheimer's disease and demonstrate how estimates of differential stability can be leveraged to infer the regulatory factors underlying them.

Spatially mapping the immune landscape of melanoma using imaging mass cytometry.

Melanoma is an immunogenic cancer with a high response rate to immune checkpoint inhibitors (ICIs). It harbors a high mutation burden compared with other cancers and, as a result, has abundant tumor-infiltrating lymphocytes (TILs) within its microenvironment. However, understanding the complex interplay between the stroma, tumor cells, and distinct TIL subsets remains a substantial challenge in immune oncology. To properly study this interplay, quantifying spatial relationships of multiple cell types within the tumor microenvironment is crucial. To address this, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously quantify the expression of 35 protein markers, characterizing the microenvironment of 5 benign nevi and 67 melanomas. We profiled more than 220,000 individual cells to identify melanoma, lymphocyte subsets, macrophage/monocyte, and stromal cell populations, allowing for in-depth spatial quantification of the melanoma microenvironment. We found that within pretreatment melanomas, the abundance of proliferating antigen-experienced cytotoxic T cells (CD8+CD45RO+Ki67+) and the proximity of antigen-experienced cytotoxic T cells to melanoma cells were associated with positive response to ICIs. Our study highlights the potential of multiplexed single-cell technology to quantify spatial cell-cell interactions within the tumor microenvironment to understand immune therapy responses.

Transcriptional control of brain tumor stem cells by a carbohydrate binding protein.

Brain tumor stem cells (BTSCs) and intratumoral heterogeneity represent major challenges in glioblastoma therapy. Here, we report that the LGALS1 gene, encoding the carbohydrate binding protein, galectin1, is a key regulator of BTSCs and glioblastoma resistance to therapy. Genetic deletion of LGALS1 alters BTSC gene expression profiles and results in downregulation of gene sets associated with the mesenchymal subtype of glioblastoma. Using a combination of pharmacological and genetic approaches, we establish that inhibition of LGALS1 signaling in BTSCs impairs self-renewal, suppresses tumorigenesis, prolongs lifespan, and improves glioblastoma response to ionizing radiation in preclinical animal models. Mechanistically, we show that LGALS1 is a direct transcriptional target of STAT3 with its expression robustly regulated by the ligand OSM. Importantly, we establish that galectin1 forms a complex with the transcription factor HOXA5 to reprogram the BTSC transcriptional landscape. Our data unravel an oncogenic signaling pathway by which the galectin1/HOXA5 complex maintains BTSCs and promotes glioblastoma.

A prometastatic splicing program regulated by SNRPA1 interactions with structured RNA elements.

Aberrant alternative splicing is a hallmark of cancer, yet the underlying regulatory programs that control this process remain largely unknown. Here, we report a systematic effort to decipher the RNA structural code that shapes pathological splicing during breast cancer metastasis. We discovered a previously unknown structural splicing enhancer that is enriched near cassette exons with increased inclusion in highly metastatic cells. We show that the spliceosomal protein small nuclear ribonucleoprotein polypeptide A' (SNRPA1) interacts with these enhancers to promote cassette exon inclusion. This interaction enhances metastatic lung colonization and cancer cell invasion, in part through SNRPA1-mediated regulation of PLEC alternative splicing, which can be counteracted by splicing modulating morpholinos. Our findings establish a noncanonical regulatory role for SNRPA1 as a prometastatic splicing enhancer in breast cancer.

Myf6/MRF4 is a myogenic niche regulator required for the maintenance of the muscle stem cell pool.

The function and maintenance of muscle stem cells (MuSCs) are tightly regulated by signals originating from their niche environment. Skeletal myofibers are a principle component of the MuSC niche and are in direct contact with the muscle stem cells. Here, we show that Myf6 establishes a ligand/receptor interaction between muscle stem cells and their associated muscle fibers. Our data show that Myf6 transcriptionally regulates a broad spectrum of myokines and muscle-secreted proteins in skeletal myofibers, including EGF. EGFR signaling blocks p38 MAP kinase-induced differentiation of muscle stem cells. Homozygous deletion of Myf6 causes a significant reduction in the ability of muscle to produce EGF, leading to a deregulation in EGFR signaling. Consequently, although Myf6-knockout mice are born with a normal muscle stem cell compartment, they undergo a progressive reduction in their stem cell pool during postnatal life due to spontaneous exit from quiescence. Taken together, our data uncover a novel role for Myf6 in promoting the expression of key myokines, such as EGF, in the muscle fiber which prevents muscle stem cell exhaustion by blocking their premature differentiation.

Model-based analysis of sample index hopping reveals its widespread artifacts in multiplexed single-cell RNA-sequencing.

Index hopping is the main cause of incorrect sample assignment of sequencing reads in multiplexed pooled libraries. We introduce a statistical model for estimating the sample index-hopping rate in multiplexed droplet-based single-cell RNA-seq data and for probabilistic inference of the true sample of origin of hopped reads. We analyze several datasets and estimate the sample index hopping probability to range between 0.003-0.009, a small number that counter-intuitively gives rise to a large fraction of phantom molecules - the fraction of phantom molecules exceeds 8% in more than 25% of samples and reaches as high as 85% in low-complexity samples. Phantom molecules lead to widespread complications in downstream analyses, including transcriptome mixing across cells, emergence of phantom copies of cells from other samples, and misclassification of empty droplets as cells. We demonstrate that our approach can correct for these artifacts by accurately purging the majority of phantom molecules from the data.

Multi-omic analysis reveals significantly mutated genes and DDX3X as a sex-specific tumor suppressor in cutaneous melanoma.

The high background tumor mutation burden in cutaneous melanoma limits the ability to identify significantly mutated genes (SMGs) that drive this cancer. To address this, we performed a mutation significance study of over 1,000 melanoma exomes, combined with a multi-omic analysis of 470 cases from The Cancer Genome Atlas. We discovered several SMGs with co-occurring loss-of-heterozygosity and loss-of-function mutations, including PBRM1, PLXNC1 and PRKAR1A, which encodes a protein kinase A holoenzyme subunit. Deconvolution of bulk tumor transcriptomes into cancer, immune and stromal components revealed a melanoma-intrinsic oxidative phosphorylation signature associated with protein kinase A pathway alterations. We also identified SMGs on the X chromosome, including the RNA helicase DDX3X, whose loss-of-function mutations were exclusively observed in males. Finally, we found that tumor mutation burden and immune infiltration contain complementary information on survival of patients with melanoma. In summary, our multi-omic analysis provides insights into melanoma etiology and supports contribution of specific mutations to the sex bias observed in this cancer.

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber isolation with Switching Mechanism at 5' end of RNA Template (SMART) technology. Using smfRNA-Seq, we first determined the genes that are expressed in the whole muscle, including in nonmyogenic cells. We also analyzed the differences in the transcriptome of myofibers from young and old mice to validate the effectiveness of this new method. Our results suggest that aging leads to significant changes in the expression of metabolic genes, such as Nos1, and structural genes, such as Myl1, in myofibers. We conclude that smfRNA-Seq is a powerful tool to study developmental, disease-related, and age-related changes in the gene expression profile of skeletal muscle.

Nuclear TARBP2 Drives Oncogenic Dysregulation of RNA Splicing and Decay.

Post-transcriptional regulation of RNA stability is a key step in gene expression control. We describe a regulatory program, mediated by the RNA binding protein TARBP2, that controls RNA stability in the nucleus. TARBP2 binding to pre-mRNAs results in increased intron retention, subsequently leading to targeted degradation of TARBP2-bound transcripts. This is mediated by TARBP2 recruitment of the m6A RNA methylation machinery to its target transcripts, where deposition of m6A marks influences the recruitment of splicing regulators, inhibiting efficient splicing. Interactions between TARBP2 and the nucleoprotein TPR then promote degradation of these TARBP2-bound transcripts by the nuclear exosome. Additionally, analysis of clinical gene expression datasets revealed a functional role for TARBP2 in lung cancer. Using xenograft mouse models, we find that TARBP2 affects tumor growth in the lung and that this is dependent on TARBP2-mediated destabilization of ABCA3 and FOXN3. Finally, we establish ZNF143 as an upstream regulator of TARBP2 expression.

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439.

Age-related variations in gene expression patterns of renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is known to occur across the adult lifetime traversing the spectrum of age-related organismal changes. Little is known as to how the aging process may affect the course of renal cell carcinoma (RCC) and the repertoire of genes involved. METHODS: Using The Cancer Genome Atlas (n = 436) and Cancer Genomics of the Kidney (n = 89) datasets, we applied regression analysis to examine associations between patient age and gene expression profiles in ccRCC tumors and normal kidney tissues. Pathway enrichment analysis was performed to identify cellular process that is affected by aging in ccRCC. Moreover, connectivity mapping analysis was used to predict age-dependent response to drug treatments. RESULTS: Our analysis revealed different age-dependent gene expression spectra in ccRCC and normal kidney tissues. These findings were significant and independently reproducible in both datasets examined. Age up-regulated genes, showing higher expression in older patients, were significantly enriched (false discovery rate <0.05) in normal tissues for pathways associated with immune response and extracellular matrix organization, whereas age up-regulated genes in tumors were enriched for metabolism and oxidation pathways. Strikingly, age down-regulated genes in normal cells were also enriched for metabolism and oxidation, while those in tumors were enriched for extracellular matrix organization. Further in silico analysis of potential drug targets predicted preferential efficacy of Phosphoinositide 3-kinase inhibitor or immunotherapy in association with age. CONCLUSION: We report on previously unrecognized associations between age and molecular underpinnings of RCC, including age-associated expression of genes implicated in RCC development or treatment.

Publisher Correction: Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease.

The original version of this Article contained an error in Figure 3, where panel d was inadvertently replaced with a duplicate of panel c during typesetting. Also, the legend of Figure 5f incorrectly read '310 AD patients (blue dots, r = -0.4) and 157 non-demented individuals (green dots, r = -0.1)', and should have read '310 AD patients (blue dots, r = -0.1) and 157 non-demented individuals (green dots, r = -0.4)'. Both of these errors have now been corrected in both the PDF and HTML versions of the Article.