Multimodality Video Acquisition System for the Assessment of Vital Distress in Children.

In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient's numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management.

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA.

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

ARGLU1 is a transcriptional coactivator and splicing regulator important for stress hormone signaling and development.

Stress hormones bind and activate the glucocorticoid receptor (GR) in many tissues including the brain. We identified arginine and glutamate rich 1 (ARGLU1) in a screen for new modulators of glucocorticoid signaling in the CNS. Biochemical studies show that the glutamate rich C-terminus of ARGLU1 coactivates multiple nuclear receptors including the glucocorticoid receptor (GR) and the arginine rich N-terminus interacts with splicing factors and binds to RNA. RNA-seq of neural cells depleted of ARGLU1 revealed significant changes in the expression and alternative splicing of distinct genes involved in neurogenesis. Loss of ARGLU1 is embryonic lethal in mice, and knockdown in zebrafish causes neurodevelopmental and heart defects. Treatment with dexamethasone, a GR activator, also induces changes in the pattern of alternatively spliced genes, many of which were lost when ARGLU1 was absent. Importantly, the genes found to be alternatively spliced in response to glucocorticoid treatment were distinct from those under transcriptional control by GR, suggesting an additional mechanism of glucocorticoid action is present in neural cells. Our results thus show that ARGLU1 is a novel factor for embryonic development that modulates basal transcription and alternative splicing in neural cells with consequences for glucocorticoid signaling.

Protein coding genes as hosts for noncoding RNA expression.

With the emergence of high-throughput sequence characterization methods and the subsequent improvements in gene annotations, it is becoming increasingly clear that a large proportion of eukaryotic protein-coding genes (as many as 50% in human) serve as host genes for non-coding RNA genes. Amongst the most extensively characterized embedded non-coding RNA genes, small nucleolar RNAs and microRNAs represent abundant families. Encoded individually or clustered, in sense or antisense orientation with respect to their host and independently expressed or dependent on host expression, the genomic characteristics of embedded genes determine their biogenesis and the extent of their relationship with their host gene. Not only can host genes and the embedded genes they harbour be co-regulated and mutually modulate each other, many are functionally coupled playing a role in the same cellular pathways. And while host-non-coding RNA relationships can be highly conserved, mechanisms have been identified, and in particular an association with transposable elements, allowing the appearance of copies of non-coding genes nested in host genes, or the migration of embedded genes from one host gene to another. The study of embedded non-coding genes and their relationship with their host genes increases the complexity of cellular networks and provides important new regulatory links that are essential to properly understand cell function.

Simultaneous sequencing of coding and noncoding RNA reveals a human transcriptome dominated by a small number of highly expressed noncoding genes.

Comparing the abundance of one RNA molecule to another is crucial for understanding cellular functions but most sequencing techniques can target only specific subsets of RNA. In this study, we used a new fragmented ribodepleted TGIRT sequencing method that uses a thermostable group II intron reverse transcriptase (TGIRT) to generate a portrait of the human transcriptome depicting the quantitative relationship of all classes of nonribosomal RNA longer than 60 nt. Comparison between different sequencing methods indicated that FRT is more accurate in ranking both mRNA and noncoding RNA than viral reverse transcriptase-based sequencing methods, even those that specifically target these species. Measurements of RNA abundance in different cell lines using this method correlate with biochemical estimates, confirming tRNA as the most abundant nonribosomal RNA biotype. However, the single most abundant transcript is 7SL RNA, a component of the signal recognition particle. Structured noncoding RNAs (sncRNAs) associated with the same biological process are expressed at similar levels, with the exception of RNAs with multiple functions like U1 snRNA. In general, sncRNAs forming RNPs are hundreds to thousands of times more abundant than their mRNA counterparts. Surprisingly, only 50 sncRNA genes produce half of the non-rRNA transcripts detected in two different cell lines. Together the results indicate that the human transcriptome is dominated by a small number of highly expressed sncRNAs specializing in functions related to translation and splicing.

CoCo: RNA-seq read assignment correction for nested genes and multimapped reads.

MOTIVATION: Next-generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage. RESULTS: Here we present count corrector (CoCo), a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bedgraph comparisons. AVAILABILITY AND IMPLEMENTATION: The CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/coco. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The cellular landscape of mid-size noncoding RNA.

Noncoding RNA plays an important role in all aspects of the cellular life cycle, from the very basic process of protein synthesis to specialized roles in cell development and differentiation. However, many noncoding RNAs remain uncharacterized and the function of most of them remains unknown. Mid-size noncoding RNAs (mncRNAs), which range in length from 50 to 400 nucleotides, have diverse regulatory functions but share many fundamental characteristics. Most mncRNAs are produced from independent promoters although others are produced from the introns of other genes. Many are found in multiple copies in genomes. mncRNAs are highly structured and carry many posttranscriptional modifications. Both of these facets dictate their RNA-binding protein partners and ultimately their function. mncRNAs have already been implicated in translation, catalysis, as guides for RNA modification, as spliceosome components and regulatory RNA. However, recent studies are adding new mncRNA functions including regulation of gene expression and alternative splicing. In this review, we describe the different classes, characteristics and emerging functions of mncRNAs and their relative expression patterns. Finally, we provide a portrait of the challenges facing their detection and annotation in databases. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

Colorectal cancer cells respond differentially to autophagy inhibition in vivo.

Autophagy has both tumor-promoting and -suppressing effects in cancer, including colorectal cancer (CRC), with transformed cells often exhibiting high autophagic flux. In established tumors, autophagy inhibition can lead to opposite responses resulting in either tumor cell death or hyperproliferation. The functional mechanisms underlying these differences are poorly understood. The present study aimed to investigate the relationship between the autophagic capacities of CRC cells and their sensitivities to autophagy inhibition. All studied CRC cell lines showed high basal autophagic flux. However, only HCT116 and Caco-2/15 cells displayed regulated autophagic flux upon starvation. Knockdown of ATG5 (which disrupts autophagosome elongation) or RAB21 (which decreases autophagosome/lysosome fusion) had little effect on CRC cell proliferation in vitro. Nonetheless, inhibition of autophagy in vivo had a substantial cell line-dependent impact on tumor growth, with some cells displaying decreased (HCT116 and Caco-2/15) or increased (SW480 and LoVo) proliferation. RNA sequencing and Western blot analyses in hyperproliferative SW480 tumors revealed that the mTORC2 and AKT pathways were hyperactivated following autophagy impairment. Inhibition of either mTOR or AKT activities rescued the observed hyperproliferation in autophagy-inhibited SW480 and reduced tumor growth. These results highlight that autophagy inhibition can lead, in specific cellular contexts, to compensatory mechanisms promoting tumor growth.

Enhanced snoMEN Vectors Facilitate Establishment of GFP-HIF-1α Protein Replacement Human Cell Lines.

The snoMEN (snoRNA Modulator of gene ExpressioN) vector technology was developed from a human box C/D snoRNA, HBII-180C, which contains an internal sequence that can be manipulated to make it complementary to RNA targets, allowing knock-down of targeted genes. Here we have screened additional human nucleolar snoRNAs and assessed their application for gene specific knock-downs to improve the efficiency of snoMEN vectors. We identify and characterise a new snoMEN vector, termed 47snoMEN, that is derived from box C/D snoRNA U47, demonstrating its use for knock-down of both endogenous cellular proteins and G/YFP-fusion proteins. Using multiplex 47snoMEM vectors that co-express multiple 47snoMEN in a single transcript, each of which can target different sites in the same mRNA, we document >3-fold increase in knock-down efficiency when compared with the original HBII-180C based snoMEN. The multiplex 47snoMEM vector allowed the construction of human protein replacement cell lines with improved efficiency, including the establishment of novel GFP-HIF-1α replacement cells. Quantitative mass spectrometry analysis confirmed the enhanced efficiency and specificity of protein replacement using the 47snoMEN-PR vectors. The 47snoMEN vectors expand the potential applications for snoMEN technology in gene expression studies, target validation and gene therapy.