DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes.

Although transcriptomics data is typically used to analyze mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g. healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, ie reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions. Here, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, vs. state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data. DifferentialRegulation is distributed as a Bioconductor R package.

DESpace: spatially variable gene detection via differential expression testing of spatial clusters.

MOTIVATION: Spatially resolved transcriptomics (SRT) enables scientists to investigate spatial context of mRNA abundance, including identifying spatially variable genes (SVGs), i.e. genes whose expression varies across the tissue. Although several methods have been proposed for this task, native SVG tools cannot jointly model biological replicates, or identify the key areas of the tissue affected by spatial variability. RESULTS: Here, we introduce DESpace, a framework, based on an original application of existing methods, to discover SVGs. In particular, our approach inputs all types of SRT data, summarizes spatial information via spatial clusters, and identifies spatially variable genes by performing differential gene expression testing between clusters. Furthermore, our framework can identify (and test) the main cluster of the tissue affected by spatial variability; this allows scientists to investigate spatial expression changes in specific areas of interest. Additionally, DESpace enables joint modeling of multiple samples (i.e. biological replicates); compared to inference based on individual samples, this approach increases statistical power, and targets SVGs with consistent spatial patterns across replicates. Overall, in our benchmarks, DESpace displays good true positive rates, controls for false positive and false discovery rates, and is computationally efficient. AVAILABILITY AND IMPLEMENTATION: DESpace is freely distributed as a Bioconductor R package at https://bioconductor.org/packages/DESpace.

Ten simple rules for computational biologists collaborating with wet lab researchers.

Computational biologists are frequently engaged in collaborative data analysis with wet lab researchers. These interdisciplinary projects, as necessary as they are to the scientific endeavor, can be surprisingly challenging due to cultural differences in operations and values. In this Ten Simple Rules guide, we aim to help dry lab researchers identify sources of friction and provide actionable tools to facilitate respectful, open, transparent, and rewarding collaborations.

2D pelvic floor ultrasound imaging in identifying levator ani muscle trauma agrees highly with 4D ultrasound imaging.

INTRODUCTION AND HYPOTHESIS: The objective was to evaluate the agreement between 2D and 4D translabial ultrasound (TLUS) technique in showing levator ani muscle (LAM) states after vaginal birth. METHODS: In a prospective observational cohort study between March 2017 and April 2019 we evaluated LAM states (intact, hematoma, partial, complete avulsion) of primiparous women having given birth vaginally with singletons in vertex presentation ≥ 36+0 gestational weeks by using 2D and 4D TLUS within 1-4 days postpartum (assessment A1) and again 6-10 weeks postpartum (assessment A2). Cohen's Kappa analysis was performed for each side separately to evaluate the test agreement between the two ultrasound techniques at every assessment period. RESULTS: A total of 224 women participated at A1 and 213 at A2. The agreement between the two ultrasound techniques was good to very good at A1 (Cohen`s kappa right-sided 0.78, left-sided 0.82) and very good at A2 (Cohen`s kappa both sides 0.88). The agreement was best when assessing an intact LAM or a complete avulsion (Cohen`s kappa between 0.78-0.92 for complete avulsions). CONCLUSIONS: The comparison between 2D and 4D TLUS showed a good to very good agreement in LAM trauma immediately after birth as well as 6-10 weeks postpartum. Therefore, 2D ultrasound could also be a valuable method for demonstrating a LAM abnormality and could be used in settings where 3D/4D ultrasound equipment is not available.

The evolution of levator ani muscle trauma over the first 9 months after vaginal birth.

INTRODUCTION AND HYPOTHESIS: The objective was to investigate the evolution of levator ani muscle (LAM) trauma over the first 9 months after birth and to evaluate their agreement between different assessment periods. METHODS: From March 2017 to April 2019 we prospectively evaluated LAM states (intact, hematoma, partial or complete avulsion) of primiparous women after vaginal birth by using 4D translabial ultrasound (TLUS) at three different assessment periods. All women were examined 1-4 days (A1) and 6-10 weeks (A2) postpartum, and women with a trauma additionally 6-9 months postpartum (A3). Cohen's Kappa analysis was performed to evaluate the test agreement between the assessment periods. RESULTS: Thirty-two percent of the women at A1 had a LAM trauma and 24% at A2. The higher number of LAM injuries at A1 can be explained by hematomas (14%), of which 51% spontaneously resolved at A2, 35% revealed themselves as partial, and 12% as complete avulsions. At A3, we observed anatomical improvement from complete to partial avulsions (23%) and few partial avulsions changed into an intact LAM (3%); none of the complete avulsions changed into an intact LAM. The agreement of 4D TLUS between A1 and A2 was moderate to good (0.64 for the right-sided LAM/0.60 for the left-sided LAM) and between A2 and A3 good to very good (0.76 right-sided/0.84 left-sided). CONCLUSIONS: Levator ani muscle trauma can reliably be diagnosed during all assessment periods. However, the agreement between A1 and A2 was only moderate to good. This can be explained by hematomas inside the LAM that were only observed early postpartum. We observed some anatomical improvement at A3, but no complete avulsion improved to an intact LAM.

DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes.

Motivation: Although transcriptomics data is typically used to analyse mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g., healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, i.e., reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions. Results: Here, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, versus state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data. Availability and implementation: DifferentialRegulation is distributed as a Bioconductor R package.

Circular RNA circBCBM1 promotes breast cancer brain metastasis by modulating miR-125a/BRD4 axis.

Circular RNAs (circRNAs) play critical roles in tumorigenesis and the progression of various cancers. We previously identified a novel upregulated circRNA, circBCBM1 (hsa_circ_0001944), in the context of breast cancer brain metastasis. However, the potential biological function and molecular mechanism of circBCBM1 in breast cancer brain metastasis remain largely unknown. In this study, we confirmed that circBCBM1 was a stable and cytoplasmic circRNA. Functionally, circBCBM1 promoted the proliferation and migration of 231-BR cells in vitro and growth and brain metastasis in vivo. Mechanistically, circBCBM1 acted as an endogenous miR-125a sponge to inhibit miR-125a activity, resulting in the upregulation of BRD4 (bromodomain containing 4) and subsequent upregulation of MMP9 (matrix metallopeptidase 9) through Sonic hedgehog (SHH) signaling pathway. Importantly, circBCBM1 was markedly upregulated in the breast cancer brain metastasis cells and clinical tissue and plasma samples; besides, circBCBM1 overexpression in primary cancerous tissues was associated with shorter brain metastasis-free survival (BMFS) of breast cancer patients. These findings indicate that circBCBM1 is involved in breast cancer brain metastasis via circBCBM1/miR-125a/BRD4 axis. CircBCBM1 may serve as a novel diagnostic and prognostic biomarker and potential therapeutic target for breast cancer brain metastasis.

Synthesis and photophysical properties of water-soluble sulfonato-Salen-type Schiff bases and their applications of fluorescence sensors for Cu2+ in water and living cells.

A series of water-soluble sulfonato-Salen-type ligands derived from different diamines including 1,2-ethylenediamine (Et-1-Et-4), 1,2-cyclohexanediamine (Cy-1 and Cy-2), 1,2-phenylenediamine (Ph-1-Ph-3 and PhMe-1-PhMe-4), and dicyano-1,2-ethenediamine (CN-1) has been designed and prepared. Sulfonate groups of ligands ensure good stability and solubility in water without affecting their excited state properties. These ligands exhibit strong UV/Vis-absorption and blue, green, or orange fluorescence. Time-dependent-density functional theory calculations have been undertaken to reveal the influence of ligand nature, especially sulfonate groups, on the frontier molecular orbitals. Since their fluorescence is selectively quenched by Cu(2+), the sulfonato-Salen-type ligands can be used as highly selective and sensitive turn-off fluorescence sensors for the detection of Cu(2+) in water and fluorescence imaging in living cells.