Deletion of Ultraconserved Elements Yields Viable Mice

Ultraconserved elements have been suggested to retain extended perfect sequence identity between the human, mouse, and rat genomes due to essential functional properties. To investigate the necessities of these elements in vivo, we removed four noncoding ultraconserved elements (ranging in length from 222 to 731 base pairs) from the mouse genome. To maximize the likelihood of observing a phenotype, we chose to delete elements that function as enhancers in a mouse transgenic assay and that are near genes that exhibit marked phenotypes both when completely inactivated in the mouse and when their expression is altered due to other genomic modifications. Remarkably, all four resulting lines of mice lacking these ultraconserved elements were viable and fertile, and failed to reveal any critical abnormalities when assayed for a variety of phenotypes including growth, longevity, pathology, and metabolism. In addition, more targeted screens, informed by the abnormalities observed in mice in which genes in proximity to the investigated elements had been altered, also failed to reveal notable abnormalities. These results, while not inclusive of all the possible phenotypic impact of the deleted sequences, indicate that extreme sequence constraint does not necessarily reflect crucial functions required for viability

Mutations in \u3ci\u3eDMRT3\u3c/i\u3e Affect Locomotion in Horses and Spinal Circuit Function in Mice

Locomotion in mammals relies on a central pattern-generating circuitry of spinal interneurons established during development that coordinates limb movement. These networks produce left–right alternation of limbs as well as coordinated activation of flexor and extensor muscles. Here we show that a premature stop codon in the DMRT3 gene has a major effect on the pattern of locomotion in horses. The mutation is permissive for the ability to perform alternate gaits and has a favorable effect on harness racing performance. Examination of wild-type and Dmrt3-null mice demonstrates that Dmrt3 is expressed in the dI6 subdivision of spinal cord neurons, takes part in neuronal specification within this subdivision, and is critical for the normal development of a coordinated locomotor network controlling limb movements. Our discovery positions Dmrt3 in a pivotal role for configuring the spinal circuits controlling stride in vertebrates. The DMRT3 mutation has had a major effect on the diversification of the domestic horse, as the altered gait characteristics of a number of breeds apparently require this mutation

Optimizing Operation Room Utilization—A Prediction Model

Background: Operating rooms are the core of hospitals. They are a primary source of revenue and are often seen as one of the bottlenecks in the medical system. Many efforts are made to increase throughput, reduce costs, and maximize incomes, as well as optimize clinical outcomes and patient satisfaction. We trained a predictive model on the length of surgeries to improve the productivity and utility of operative rooms in general hospitals. Methods: We collected clinical and administrative data for the last 10 years from two large general public hospitals in Israel. We trained a machine learning model to give the expected length of surgery using pre-operative data. These data included diagnoses, laboratory tests, risk factors, demographics, procedures, anesthesia type, and the main surgeon’s level of experience. We compared our model to a naïve model that represented current practice. Findings: Our prediction model achieved better performance than the naïve model and explained almost 70% of the variance in surgery durations. Interpretation: A machine learning-based model can be a useful approach for increasing operating room utilization. Among the most important factors were the type of procedures and the main surgeon’s level of experience. The model enables the harmonizing of hospital productivity through wise scheduling and matching suitable teams for a variety of clinical procedures for the benefit of the individual patient and the system as a whole

Optimizing Operation Room Utilization—A Prediction Model

Background: Operating rooms are the core of hospitals. They are a primary source of revenue and are often seen as one of the bottlenecks in the medical system. Many efforts are made to increase throughput, reduce costs, and maximize incomes, as well as optimize clinical outcomes and patient satisfaction. We trained a predictive model on the length of surgeries to improve the productivity and utility of operative rooms in general hospitals. Methods: We collected clinical and administrative data for the last 10 years from two large general public hospitals in Israel. We trained a machine learning model to give the expected length of surgery using pre-operative data. These data included diagnoses, laboratory tests, risk factors, demographics, procedures, anesthesia type, and the main surgeon’s level of experience. We compared our model to a naïve model that represented current practice. Findings: Our prediction model achieved better performance than the naïve model and explained almost 70% of the variance in surgery durations. Interpretation: A machine learning-based model can be a useful approach for increasing operating room utilization. Among the most important factors were the type of procedures and the main surgeon’s level of experience. The model enables the harmonizing of hospital productivity through wise scheduling and matching suitable teams for a variety of clinical procedures for the benefit of the individual patient and the system as a whole

Mapping cis-Regulatory Domains in the Human Genome Using Multi-Species Conservation of Synteny

Our inability to associate distant regulatory elements with the genes that they regulate has largely precluded their examination for sequence alterations contributing to human disease. One major obstacle is the large genomic space surrounding targeted genes in which such elements could potentially reside 1. In order to delineate gene regulatory boundaries we used whole-genome human-mouse-chicken (HMC) and human-mouse-frog (HMF) multiple alignments to compile conserved blocks of synteny (CBS), under the hypothesis that these blocks have been kept intact throughout evolution at least in part by the requirement of regulatory elements to stay linked to the genes that they regulate. A total of 2,116 and 1,942 CBS >200 kb were assembled for HMC and HMF respectively, encompassing 1.53 and 0.86 Gb of human sequence. To support the existence of complex long-range regulatory domains within these CBS we analyzed the prevalence and distribution of chromosomal aberrations leading to position effects (disruption of a gene s regulatory environment) 1,2, observing a clear bias not only for mapping onto CBS but also for longer CBS size. Our results provide a genome wide dataset characterizing the regulatory domains of genes and the conserved regulatory elements within them

Deletion of ultraconserved elements yields viable mice

Ultraconserved elements have been suggested to retain extended perfect sequence identity between the human, mouse, and rat genomes due to essential functional properties. To investigate the necessities of these elements in vivo, we removed four non-coding ultraconserved elements (ranging in length from 222 to 731 base pairs) from the mouse genome. To maximize the likelihood of observing a phenotype, we chose to delete elements that function as enhancers in a mouse transgenic assay and that are near genes that exhibit marked phenotypes both when completely inactivated in the mouse as well as when their expression is altered due to other genomic modifications. Remarkably, all four resulting lines of mice lacking these ultraconserved elements were viable and fertile, and failed to reveal any critical abnormalities when assayed for a variety of phenotypes including growth, longevity, pathology and metabolism. In addition more targeted screens, informed by the abnormalities observed in mice where genes in proximity to the investigated elements had been altered, also failed to reveal notable abnormalities. These results, while not inclusive of all the possible phenotypic impact of the deleted sequences, indicate that extreme sequence constraint does not necessarily reflect crucial functions required for viability

Comparative genomic analysis reveals a distant liver enhancer upstream of the COUP-TFII gene

COUP-TFII is a central nuclear hormone receptor that tightly regulates the expression of numerous target lipid metabolism genes in vertebrates. However, it remains unclear how COUP-TFII itself is transcriptionally controlled since studies with its promoter and upstream region fail to recapitulate the genes liver expression. In an attempt to identify liver enhancers in the vicinity of COUP-TFII, we employed a comparative genomic approach. Initial comparisons between humans and mice of the 3,470kb gene poor region surrounding COUP-TFII revealed 2,023 conserved non-coding elements. To prioritize a subset of these elements for functional studies, we performed further genomic comparisons with the orthologous pufferfish (Fugu rubripes) locus and uncovered two anciently conserved non-coding sequences (CNS) upstream of COUP-TFII (CNS-62kb and CNS-66kb). Testing these two elements using reporter constructs in liver (HepG2) cells revealed that CNS-66kb, but not CNS-62kb, yielded robust in vitro enhancer activity. In addition, an in vivo reporter assay using naked DNA transfer with CNS-66kb linked to luciferase displayed strong reproducible liver expression in adult mice, further supporting its role as a liver enhancer. Together, these studies further support the utility of comparative genomics to uncover gene regulatory sequences based on evolutionary conservation and provide the substrates to better understand the regulation and expression of COUP-TFII

miR-155: A Potential Biomarker for Predicting Mortality in COVID-19 Patients

COVID-19, a pandemic of severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2), continues to pose diagnostic and therapeutic challenges due to its unpredictable clinical course. Prognostic biomarkers may improve care by enabling quick identification of patients who can be safely discharged home versus those who may need careful respiratory monitoring and support. MicroRNAs (miRNAs) have risen to prominence as biomarkers for many disease states and as tools to assist in medical decisions. In the present study, we aimed to examine circulating miRNAs in hospitalized COVID-19 patients and to explore their potential as biomarkers for disease severity. We studied, by quantitative PCR, the expressions of miR-21, miR-146a, miR-146b, miR-155, and miR-499 in peripheral blood. We found that mild COVID-19 patients had 2.5-fold less circulating miR-155 than healthy people, and patients with a severe COVID-19 disease had 5-fold less circulating miR-155 than healthy people. In addition, we found that miR-155 is a good predictor of COVID-19 mortality. We suggest that examining miR-155 levels in patients’ blood, upon admission to hospital, will ameliorate the care given to COVID-19 patients