Disentangling the splicing factor programs underlying complex molecular phenotypes.

The regulation of exon inclusion through alternative splicing tunes the cell's behavior by increasing the functional diversity of the transcriptome and the proteome. Splicing factors work in concert to generate gene isoform pools that contribute to cell phenotypes yet their activity is controlled by multiple regulatory and signaling layers. This hinders identification of functional, phenotype-specific splicing factors using traditional single-omic measurements, such as their mutational state or expression. To address this challenge, we propose repurposing the virtual inference of protein activity by enriched regulon analysis (VIPER) to measure splicing factor activity solely from their downstream exon transcriptomic inclusion signatures. This approach is effective in assessing the effect of co-occurring splicing factor perturbations, as well as their post-translational regulation. As proof of concept, we dissect recurrent splicing factor programs underlying tumorigenesis including aberrantly activated factors acting as oncogenes and inactivated ones acting as tumor suppressors, which are undetectable by more conventional methodologies. Activation and inactivation of these cancer splicing programs effectively stratifies overall survival, as well as cancer hallmarks such as proliferation and immune evasion. Altogether, repurposing network-based inference of protein activity for splicing factor networks distills common, functionally relevant splicing programs in otherwise heterogeneous molecular contexts.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences.

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes, and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy. Here, we present DeltaSplice, a deep neural network model optimized to learn the impact of mutations on quantitative changes in alternative splicing from the comparative analysis of homologous genes. The model architecture enables DeltaSplice to perform "reference-informed prediction" by incorporating the known splice site usage of a reference gene sequence to improve its prediction on splicing-altering mutations. We benchmarked DeltaSplice and several other state-of-the-art methods on various prediction tasks, including evolutionary sequence divergence on lineage-specific splicing and splicing-altering mutations in human populations and neurodevelopmental disorders, and demonstrated that DeltaSplice outperformed consistently. DeltaSplice predicted ∼15% of splicing quantitative trait loci (sQTLs) in the human brain as causal splicing-altering variants. It also predicted splicing-altering de novo mutations outside the splice sites in a subset of patients affected by autism and other neurodevelopmental disorders (NDDs), including 19 genes with recurrent splicing-altering mutations. Integration of splicing-altering mutations with other types of de novo mutation burdens allowed the prediction of eight novel NDD-risk genes. Our work expanded the capacity of in silico splicing models with potential applications in genetic diagnosis and the development of splicing-based precision medicine.

Oncogenic NOVA1 expression dysregulates alternative splicing in breast cancer.

Neuro-Oncological Ventral Antigen 1 (NOVA1) is best known for its role in mediating an alternative splicing (AS) program in neurons, yet was first discovered as an antigen expressed in breast tumors, causing rare autoimmune reactions and paraneoplastic neurological disorders (PNDs). The PND model suggests a plausible role of the tumor antigen expression in tumor suppression, whereas it has emerged that NOVA may function as an oncogene in a variety of cancers. In addition, whether NOVA mediates AS in breast cancer remains unanswered. Here we examine the AS profiles of breast invasive carcinoma (BRCA) tumor samples and demonstrate that ectopic NOVA1 expression led to the activation of neuron-like splicing patterns in many genes, including exons targeted by NOVA in the brain. The splicing dysregulation is especially prevalent in cell periphery and cytoskeleton genes related to cell-cell communication, actin-based movement, and neuronal functions. We find that NOVA1-mediated AS is most prominent in Luminal A tumors and high NOVA1 expression in this subtype is associated with poorer prognosis. Our results suggest that ectopic NOVA1 in tumors has regulatory activity affecting pathways with high relevance to tumor progression and that this might be a more general mechanism for PND antigens.

Reverse engineering neuron type-specific and type-orthogonal splicing-regulatory networks using single-cell transcriptomes.

Cell type-specific alternative splicing (AS) enables differential gene isoform expression between diverse neuron types with distinct identities and functions. Current studies linking individual RNA-binding proteins (RBPs) to AS in a few neuron types underscore the need for holistic modeling. Here, we use network reverse engineering to derive a map of the neuron type-specific AS regulatory landscape from 133 mouse neocortical cell types defined by single-cell transcriptomes. This approach reliably inferred the regulons of 350 RBPs and their cell type-specific activities. Our analysis revealed driving factors delineating neuronal identities, among which we validated Elavl2 as a key RBP for MGE-specific splicing in GABAergic interneurons using an in vitro ESC differentiation system. We also identified a module of exons and candidate regulators specific for long- and short-projection neurons across multiple neuronal classes. This study provides a resource for elucidating splicing regulatory programs that drive neuronal molecular diversity, including those that do not align with gene expression-based classifications.

Lineage-specific splicing regulation of MAPT gene in the primate brain.

Divergence of precursor messenger RNA (pre-mRNA) alternative splicing (AS) is widespread in mammals, including primates, but the underlying mechanisms and functional impact are poorly understood. Here, we modeled cassette exon inclusion in primate brains as a quantitative trait and identified 1,170 (∼3%) exons with lineage-specific splicing shifts under stabilizing selection. Among them, microtubule-associated protein tau (MAPT) exons 2 and 10 underwent anticorrelated, two-step evolutionary shifts in the catarrhine and hominoid lineages, leading to their present inclusion levels in humans. The developmental-stage-specific divergence of exon 10 splicing, whose dysregulation can cause frontotemporal lobar degeneration (FTLD), is mediated by divergent distal intronic MBNL-binding sites. Competitive binding of these sites by CRISPR-dCas13d/gRNAs effectively reduces exon 10 inclusion, potentially providing a therapeutically compatible approach to modulate tau isoform expression. Our data suggest adaptation of MAPT function and, more generally, a role for AS in the evolutionary expansion of the primate brain.

CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements.

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

A clinicopathological-imaging nomogram for the prediction of pathological complete response in breast cancer cases administered neoadjuvant therapy.

OBJECTIVE: To construct a user-friendly nomogram with MRI and clinicopathological parameters for the prediction of pathological complete response (pCR) after neoadjuvant therapy (NAT) in patients with breast cancer (BC). METHODS: We retrospectively enrolled consecutive female patients pathologically confirmed with breast cancer who received NAT followed by surgery between January 2018 and December 2022 as the development cohort. Additionally, we prospectively collected eligible candidates between January 2023 and December 2023 as an external validation group at our institution. Pretreatment MRI features and clinicopathological variables were collected, and the pre- and post-treatment background parenchymal enhancement (BPE) and the changes in BPE on two MRIs were compared between patients who achieved pCR and those who did not. Multivariable logistic regression analysis was used to identify independent variables associated with pCR in the development cohort. These independent variables were combined into a predictive nomogram for which performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, decision curve analysis, and external validation. RESULTS: In the development cohort, there were a total of 276 female patients with a mean age of 48.3 ± 8.7 years, while in the validation cohort, there were 87 female patients with a mean age of 49.0 ± 9.5 years. Independent prognostic factors of pCR included small tumor size, HER2(+), high Ki-67 index,high signal enhancement ratio (SER), low minimum value of apparent diffusion coefficient (ADCmin), and significantly decreased BPE after NAT(change of BPE). The nomogram, which incorporates the above parameters, demonstrated excellent predictive performance in both the development and external validation cohorts, with AUC values of 0.900 and 0.850, respectively. Additionally, the nomogram showed excellent calibration capacities, as indicated by Hosmer-Lemeshow test p values of 0.508 and 0.423 in the two cohorts. Furthermore, the nomogram provided greater net benefits compared to the default simple schemes in both cohorts. CONCLUSION: A nomogram constructed using tumor size, HER2 status, Ki-67 index, SER, ADCmin, and changes in pre- and post-NAT BPE demonstrated strong predictive performance, calibration ability, and greater net benefits for predicting pCR in patients with BC after NAT. This suggests that the user-friendly nomogram could be a valuable imaging biomarker for identifying suitable candidates for NAT.

D-arabinose induces cell cycle arrest by promoting autophagy via p38 MAPK signaling pathway in breast cancer.

Breast cancer patients often have a poor prognosis largely due to lack of effective targeted therapy. It is now well established that monosaccharide enhances growth retardation and chemotherapy sensitivity in tumor cells. We investigated whether D-arabinose has capability to restrict the proliferation of tumor cells and its mechanism. Here, we report that D-arabinose induced cytotoxicity is modulated by autophagy and p38 MAPK signaling pathway in breast cancer cell lines. The proliferation of cells was evaluated by CCK-8 and Colony formation assay. The distribution of cells in cell cycle phases was analyzed by flow cytometry. Cell cycle, autophagy and MAPK signaling related proteins were detected by western blotting. Mouse xenograft model was used to evaluate the efficacy of D-arabinose in vivo. The proliferation of cells was dramatically inhibited by D-arabinose exposure in a dose-dependent manner, which was relevant to cell cycle arrest, as demonstrated by G2/M cell cycle restriction and ectopic expression of cell cycle related proteins. Mechanistically, we further identified that D-arabinose is positively associated with autophagy and the activation of the p38 MAPK signaling in breast cancer. In contrast, 3-Ma or SB203580, the inhibitor of autophagy or p38 MAPK, reversed the efficacy of D-arabinose. Additionally, D-arabinose in vivo treatment could significantly inhibit xenograft growth of breast cancer cells. Our findings were the first to reveal that D-arabinose triggered cell cycle arrest by inducing autophagy through the activation of p38 MAPK signaling pathway in breast cancer cells.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences.

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy. Here, we present DeltaSplice, a deep neural network model optimized to learn the impact of mutations on quantitative changes in alternative splicing from the comparative analysis of homologous genes. The model architecture enables DeltaSplice to perform "reference-informed prediction" by incorporating the known splice site usage of a reference gene sequence to improve its prediction on splicing-altering mutations. We benchmarked DeltaSplice and several other state-of-the-art methods on various prediction tasks, including evolutionary sequence divergence on lineage-specific splicing and splicing-altering mutations in human populations and neurodevelopmental disorders, and demonstrated that DeltaSplice outperformed consistently. DeltaSplice predicted ~15% of splicing quantitative trait loci (sQTLs) in the human brain as causal splicing-altering variants. It also predicted splicing-altering de novo mutations outside the splice sites in a subset of patients affected by autism and other neurodevelopmental disorders, including 19 genes with recurrent splicing-altering mutations. Among the new candidate disease risk genes, MFN1 is involved in mitochondria fusion, which is frequently disrupted in autism patients. Our work expanded the capacity of in silico splicing models with potential applications in genetic diagnosis and the development of splicing-based precision medicine.

The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model.

PURPOSE: To compare machine learning (ML) models with logistic regression model in order to identify the optimal factors associated with mammography-occult (i.e. false-negative mammographic findings) magnetic resonance imaging (MRI)-detected newly diagnosed breast cancer (BC). MATERIAL AND METHODS: The present single-centre retrospective study included consecutive women with BC who underwent mammography and MRI (no more than 45 days apart) for breast cancer between January 2018 and May 2023. Various ML algorithms and binary logistic regression analysis were utilized to extract features linked to mammography-occult BC. These features were subsequently employed to create different models. The predictive value of these models was assessed using receiver operating characteristic curve analysis. RESULTS: This study included 1957 malignant lesions from 1914 patients, with an average age of 51.64 ± 9.92 years and a range of 20-86 years. Among these lesions, there were 485 mammography-occult BCs. The optimal features of mammography-occult BC included calcification status, tumour size, mammographic density, age, lesion enhancement type on MRI, and histological type. Among the different ML models (ANN, L1-LR, RF, and SVM) and the LR-based combined model, the ANN model with RF features was found to be the optimal model. It demonstrated the best discriminative performance in predicting mammography false- negative findings, with an AUC of 0.912, an accuracy of 86.90%, a sensitivity of 85.85%, and a specificity of 84.18%. CONCLUSION: Mammography-occult MRI-detected breast cancers have features that should be considered when performing breast MRI to improve the detection rate for breast cancer and aid in clinician management.

Structure-based prediction and characterization of photo-crosslinking in native protein-RNA complexes.

UV-crosslinking of protein and RNA in direct contacts has been widely used to study protein-RNA complexes while our understanding of the photo-crosslinking mechanisms remains poor. This knowledge gap is due to the challenge of precisely mapping the crosslink sites in protein and RNA simultaneously in their native sequence and structural contexts. Here we systematically analyze protein-RNA interactions and photo-crosslinking by bridging crosslinked nucleotides and amino acids mapped using different assays with protein-RNA complex structures. We developed a computational method PxR3D-map which reliably predicts crosslink sites using structural information characterizing protein-RNA interaction interfaces. Analysis of the informative features revealed that photo-crosslinking is facilitated by base stacking with not only aromatic residues, but also dipeptide bonds that involve glycine, and distinct mechanisms are utilized by different RNA-binding domains. Our work suggests protein-RNA photo-crosslinking is highly selective in the cellular environment, which can guide data interpretation and further technology development for UV-crosslinking-based assays.

Identification of Breast Cancer Immune-related Prognostic Characteristics in Tumor Microenvironment.

BACKGROUND: Accumulated evidence suggest that tumor microenvironment (TME) plays a crucial role in breast cancer (BRCA) progression and therapeutic effects. OBJECTIVE: This study aimed to characterize immune-related BRCA subtypes in TME, and identify genes with prognostic value. METHODS: RNA sequencing profiles with corresponding clinical data from The Cancer Genome Atlas (TCGA) database of BRCA patients were downloaded to evaluate immune infiltration using the single-sample gene set enrichment (ssGAEA) algorithm. Further, BRCA was clustered according to immune infiltration status by consensus clustering analysis. Using Venn analysis, differentially expressed genes (DEGs) were overlapped to obtain candidate genes. Kaplan-Meier (K-M) analysis was performed to identify prognostic genes, and the results were verified in the GEO and METABRIC datasets. RT-qPCR was conducted to detect the mRNA expression of prognostic genes. RESULTS: In the TCGA database, 3 immune-related BRCA subtypes were identified [cluster1 (C1), cluster2 (C2), and cluster3 (C2)]. The C2 subtype had better overall survival (OS) compared to the C1 subtype. Higher levels of immune markers and checkpoint protein were found in the C2 subtype than in others. By combining DEGs between BRCA and normal tissues, with the C1 and C2 subtypes associated with different OS, 25 BRCA candidate genes were identified. Among these, 8 genes were identified as prognostic genes for BRCA. RT-qPCR showed that the expressions of 2 genes were significantly elevated in BRCA tissues, while that of other genes were decreased. CONCLUSION: Three BRCA subtypes were identified with the immune index, which may help design advanced treatment of BRCA. The data code used for the analysis in this article was available on GitHub (https://github.com/tangzhn/BRCA1.git).

Deep screening of proximal and distal splicing-regulatory elements in a native sequence context.

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is impeded by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically dead CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identified not only known SREs, but also a novel distal intronic splicing enhancer, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

Multiomics analyses reveal DARS1-AS1/YBX1-controlled posttranscriptional circuits promoting glioblastoma tumorigenesis/radioresistance.

The glioblastoma (GBM) stem cell-like cells (GSCs) are critical for tumorigenesis/therapeutic resistance of GBM. Mounting evidence supports tumor-promoting function of long noncoding RNAs (lncRNAs), but their role in GSCs remains poorly understood. By combining CRISPRi screen with orthogonal multiomics approaches, we identified a lncRNA DARS1-AS1-controlled posttranscriptional circuitry that promoted the malignant properties of GBM cells/GSCs. Depleting DARS1-AS1 inhibited the proliferation of GBM cells/GSCs and self-renewal of GSCs, prolonging survival in orthotopic GBM models. DARS1-AS1 depletion also impaired the homologous recombination (HR)-mediated double-strand break (DSB) repair and enhanced the radiosensitivity of GBM cells/GSCs. Mechanistically, DARS1-AS1 interacted with YBX1 to promote target mRNA binding and stabilization, forming a mixed transcriptional/posttranscriptional feed-forward loop to up-regulate expression of the key regulators of G1-S transition, including E2F1 and CCND1. DARS1-AS1/YBX1 also stabilized the mRNA of FOXM1, a master transcription factor regulating GSC self-renewal and DSB repair. Our findings suggest DARS1-AS1/YBX1 axis as a potential therapeutic target for sensitizing GBM to radiation/HR deficiency-targeted therapy.

Systematic dissection of coordinated stromal remodeling identifies Sox10+ glial cells as a therapeutic target in myelofibrosis.

Remodeling of the tissue niche is often evident in diseases, yet, the stromal alterations and their contribution to pathogenesis are poorly characterized. Bone marrow fibrosis is a maladaptive feature of primary myelofibrosis (PMF). We performed lineage tracing and found that most collagen-expressing myofibroblasts were derived from leptin-receptor-positive (LepR+) mesenchymal cells, whereas a minority were from Gli1-lineage cells. Deletion of Gli1 did not impact PMF. Unbiased single-cell RNA sequencing (scRNA-seq) confirmed that virtually all myofibroblasts originated from LepR-lineage cells, with reduced expression of hematopoietic niche factors and increased expression of fibrogenic factors. Concurrently, endothelial cells upregulated arteriolar-signature genes. Pericytes and Sox10+ glial cells expanded drastically with heightened cell-cell signaling, suggesting important functional roles in PMF. Chemical or genetic ablation of bone marrow glial cells ameliorated fibrosis and improved other pathology in PMF. Thus, PMF involves complex remodeling of the bone marrow microenvironment, and glial cells represent a promising therapeutic target.

Characteristics of coal resources in China and statistical analysis and preventive measures for coal mine accidents.

In the process of green and smart mine construction under the context of carbon neutrality, China's coal safety situation has been continuously improved in recent years. In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents, this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years  (2017-2021), from four dimensions (accident level, type, region, and time), and then proposed the preventive measures based on accident statistical laws. The results show that the storage of coal resources has obvious geographic characteristics, mainly concentrated in the Midwest, with coal resources in Shanxi and Shaanxi accounting for about 49.4%. The proportion of coal consumption has dropped from 70.2% to 56% between 2011 and 2021, but still accounts for more than half of the all. Meanwhile, the accident-prone areas are positively correlated with the amount of coal production. Among different levels of coal mine accidents, general accidents had the highest number of accidents and deaths, with 692 accidents and 783 deaths, accounting for 87.6% and 54.64% respectively. The frequency of roof, gas, and transportation accidents is relatively high, and the number of single fatalities caused by gas accidents is the largest, about 4.18. In terms of geographical distribution of accidents, the safety situation in Shanxi Province is the most severe. From the time distribution of coal mine accidents, the accidents mainly occurred in July and August, and rarely occurred in February and December. Finally, the "4 + 4" safety management model is proposed, combining the statistical results with coal production in China. Based on the existing health and safety management systems, the managements are divided into four sub-categories, and more specific measures are suggested.

RANKL Promotes Chemotherapy Resistance in Breast Cancer Cells Through STAT3 Mediated Autophagy Induction.

BACKGROUND: This study was to investigate the functional role and mechanism of receptor activator of nuclear factor-kappa B ligand (RANKL) associated autophagy and chemoresistance in breast cancer. MATERIALS AND METHODS: Cell Counting Kit-8 (CCK-8) assay was used to detect the cell viability. Real-time polymerase chain reaction (PCR) was used for determining the relative mRNA levels of key genes and protein expression was assessed by Western blotting. Immunofluorescence was performed to evaluate the changes in the autophagy flux. Short hairpin (shRNA) was used to knockdown the expression of the target genes in breast cancer cells. Based on The Cancer Genome Atlas (TCGA) database, we explored the expression of receptor activator of nuclear factor-kappa B (RANK), autophagy and signal transducer and activator of transcription 3 (STAT3) signaling associated genes and analyzed their correlation with the prognosis of breast cancer patients. RESULTS: The findings showed that receptor activator of nuclear factor-kappa B ligand (RANKL), the ligand of RANK, could effectively enhance the chemoresistance potential of breast cancer cells. Our results showed that RANKL induced autophagy and enhanced the expression of autophagy associated genes in breast cancer cells. The knockdown of RANK suppressed RANKL mediated autophagy induction in these cells. Furthermore, the inhibition of autophagy suppressed RANKL mediated chemoresistance in breast cancer cells. We found STAT3 signaling pathway was involved in RANKL-induced autophagy. Analysis of the expression of RANK, and autophagy and STAT3 signaling associated genes in breast cancer tissues showed that the expression of autophagy and STAT3 signaling associated genes was correlated with the prognosis of breast cancer patients. CONCLUSION: The present study suggests that the RANKL/RANK axis may potentially mediate chemoresistance in breast cancer cells by inducing autophagy through the STAT3 signaling pathway.

A cell-type-specific alternative splicing regulator shapes synapse properties in a trans-synaptic manner.

The specification of synaptic properties is fundamental for the function of neuronal circuits. "Terminal selector" transcription factors coordinate terminal gene batteries that specify cell-type-specific properties. Moreover, pan-neuronal splicing regulators have been implicated in directing neuronal differentiation. However, the cellular logic of how splicing regulators instruct specific synaptic properties remains poorly understood. Here, we combine genome-wide mapping of mRNA targets and cell-type-specific loss-of-function studies to uncover the contribution of the RNA-binding protein SLM2 to hippocampal synapse specification. Focusing on pyramidal cells and somatostatin (SST)-positive GABAergic interneurons, we find that SLM2 preferentially binds and regulates alternative splicing of transcripts encoding synaptic proteins. In the absence of SLM2, neuronal populations exhibit normal intrinsic properties, but there are non-cell-autonomous synaptic phenotypes and associated defects in a hippocampus-dependent memory task. Thus, alternative splicing provides a critical layer of gene regulation that instructs specification of neuronal connectivity in a trans-synaptic manner.

The germ cell-specific RNA binding protein RBM46 is essential for spermatogonial differentiation in mice.

Control over gene expression is exerted, in multiple stages of spermatogenesis, at the post-transcriptional level by RNA binding proteins (RBPs). We identify here an essential role in mammalian spermatogenesis and male fertility for 'RNA binding protein 46' (RBM46). A highly evolutionarily conserved gene, Rbm46 is also essential for fertility in both flies and fish. We found Rbm46 expression was restricted to the mouse germline, detectable in males in the cytoplasm of premeiotic spermatogonia and meiotic spermatocytes. To define its requirement for spermatogenesis, we generated Rbm46 knockout (KO, Rbm46-/-) mice; although male Rbm46-/- mice were viable and appeared grossly normal, they were infertile. Testes from adult Rbm46-/- mice were small, with seminiferous tubules containing only Sertoli cells and few undifferentiated spermatogonia. Using genome-wide unbiased high throughput assays RNA-seq and 'enhanced crosslinking immunoprecipitation' coupled with RNA-seq (eCLIP-seq), we discovered RBM46 could bind, via a U-rich conserved consensus sequence, to a cohort of mRNAs encoding proteins required for completion of differentiation and subsequent meiotic initiation. In summary, our studies support an essential role for RBM46 in regulating target mRNAs during spermatogonia differentiation prior to the commitment to meiosis in mice.

Zhurong reveals recent aqueous activities in Utopia Planitia, Mars.

The Mars' climate is cold and dry in the most recent epoch, and liquid water activities are considered extremely limited. Previous orbital data only show sporadic hydrous minerals in the northern lowlands of Mars excavated by large impacts. Using the short-wave infrared spectral data obtained by the Zhurong rover of China's Tianwen-1 mission, which landed in southern Utopia Planitia on Mars, we identify hydrated sulfate/silica materials on the Amazonian terrain at the landing site. These hydrated minerals are associated with bright-toned rocks, interpreted to be duricrust developed locally. The lithified duricrusts suggest that formation with substantial liquid water originates by either groundwater rising or subsurface ice melting. In situ evidence for aqueous activities identified at Zhurong's landing site indicates a more active Amazonian hydrosphere for Mars than previously thought.