tiny-count: a counting tool for hierarchical classification and quantification of small RNA-seq reads with single-nucleotide precision.

Summary: tiny-count is a highly flexible counting tool that allows for hierarchical classification and quantification of small RNA reads from high-throughput sequencing data. Selection rules can be used to filter reads by 5' nucleotide, length, position of alignments in relation to reference features, and by the number of mismatches to reference sequences. tiny-count can quantify reads aligned to a genome or directly to small RNA or transcript sequences. With tiny-count, users can quantify a single class of small RNAs or multiple classes in parallel. tiny-count can resolve distinct classes of small RNAs, for example, piRNAs and siRNAs, produced from the same locus. It can distinguish small RNA variants, such as miRNAs and isomiRs, with single-nucleotide precision. tRNA, rRNA, and other RNA fragments can also be quantified. tiny-count can be run alone or as part of tinyRNA, a workflow that provides a basic all-in-one command line-based solution for small RNA-seq data analysis, with documentation and statistics generated at each step for accurate and reproducible results. Availability and implementation: tiny-count and other tinyRNA tools are implemented in Python, C++, Cython, and R, and the workflow is coordinated with CWL. tiny-count and tinyRNA are free and open-source software distributed under the GPLv3 license. tiny-count can be installed via Bioconda (https://anaconda.org/bioconda/tiny-count) and both tiny-count and tinyRNA documentation and software downloads are available at https://github.com/MontgomeryLab/tinyRNA. Reference data, including genome and feature information, for certain species can be found at https://www.MontgomeryLab.org.

A Probabilistic Approach to Surgical Tasks and Skill Metrics.

Identifying and quantifying the activities that compose surgery is essential for effective interventions, computer-aided analyses and the advancement of surgical data science. For example, recent studies have shown that objective metrics (referred to as objective performance indicators, OPIs) computed during key surgical tasks correlate with surgeon skill and clinical outcomes. Unambiguous identification of these surgical tasks can be particularly challenging for both human annotators and algorithms. Each surgical procedure has multiple approaches, each surgeon has their own level of skill, and the initiation and termination of surgical tasks can be subject to interpretation. As such, human annotators and machine learning models face the same basic problem, accurately identifying the boundaries of surgical tasks despite variable and unstructured information. For use in surgeon feedback, OPIs should also be robust to the variability and diversity in this data. To mitigate this difficulty, we propose a probabilistic approach to surgical task identification and calculation of OPIs. Rather than relying on tasks that are identified by hard temporal boundaries, we demonstrate an approach that relies on distributions of start and stop times, for a probabilistic interpretation of when the task was performed. We first use hypothetical data to outline how this approach is superior to other conventional approaches. Then we present similar analyses on surgical data. We find that when surgical tasks are identified by their individual probabilities, the resulting OPIs are less sensitive to noise in the identification of the start and stop times. These results suggest that this probabilistic approach holds promise for the future of surgical data science.

Combining tRNA sequencing methods to characterize plant tRNA expression and post-transcriptional modification.

Differences in tRNA expression have been implicated in a remarkable number of biological processes. There is growing evidence that tRNA genes can play dramatically different roles depending on both expression and post-transcriptional modification, yet sequencing tRNAs to measure abundance and detect modifications remains challenging. Their secondary structure and extensive post-transcriptional modifications interfere with RNA-seq library preparation methods and have limited the utility of high-throughput sequencing technologies. Here, we combine two modifications to standard RNA-seq methods by treating with the demethylating enzyme AlkB and ligating with tRNA-specific adapters in order to sequence tRNAs from four species of flowering plants, a group that has been shown to have some of the most extensive rates of post-transcriptional tRNA modifications. This protocol has the advantage of detecting full-length tRNAs and sequence variants that can be used to infer many post-transcriptional modifications. We used the resulting data to produce a modification index of almost all unique reference tRNAs in Arabidopsis thaliana, which exhibited many anciently conserved similarities with humans but also positions that appear to be 'hot spots' for modifications in angiosperm tRNAs. We also found evidence based on northern blot analysis and droplet digital PCR that, even after demethylation treatment, tRNA-seq can produce highly biased estimates of absolute expression levels most likely due to biased reverse transcription. Nevertheless, the generation of full-length tRNA sequences with modification data is still promising for assessing differences in relative tRNA expression across treatments, tissues or subcellular fractions and help elucidate the functional roles of tRNA modifications.

A tudor domain protein, SIMR-1, promotes siRNA production at piRNA-targeted mRNAs in C. elegans.

piRNAs play a critical role in the regulation of transposons and other germline genes. In Caenorhabditis elegans, regulation of piRNA target genes is mediated by the mutator complex, which synthesizes high levels of siRNAs through the activity of an RNA-dependent RNA polymerase. However, the steps between mRNA recognition by the piRNA pathway and siRNA amplification by the mutator complex are unknown. Here, we identify the Tudor domain protein, SIMR-1, as acting downstream of piRNA production and upstream of mutator complex-dependent siRNA biogenesis. Interestingly, SIMR-1 also localizes to distinct subcellular foci adjacent to P granules and Mutator foci, two phase-separated condensates that are the sites of piRNA-dependent mRNA recognition and mutator complex-dependent siRNA amplification, respectively. Thus, our data suggests a role for multiple perinuclear condensates in organizing the piRNA pathway and promoting mRNA regulation by the mutator complex.

In the biological world, a process known as RNA interference helps cells to switch genes on and off and to defend themselves against harmful genetic material. This mechanism works by deactivating RNA sequences, the molecular templates cells can use to create proteins. Overall, RNA interference relies on the cell creating small RNA molecules that can target and inhibit the harmful RNA sequences that need to be silenced. More precisely, in round worms such as Caenorhabditis elegans, RNA interference happens in two steps. First, primary small RNAs identify the target sequences, which are then combatted by newly synthetised, secondary small RNAs. A number of proteins are also involved in both steps of the process. RNA interference is particularly important to preserve fertility, guarding sex cells against 'rogue' segments of genetic information that could be passed on to the next generation. In future sex cells, the proteins involved in RNA interference cluster together, forming a structure called a germ granule. Yet, little is known about the roles and identity of these proteins. To fill this knowledge gap, Manage et al. focused on the second stage of the RNA interference pathway in the germ granules of C. elegans, examining the molecules that physically interact with a key protein. This work revealed a new protein called SIMR-1. Looking into the role of SIMR-1 showed that the protein is required to amplify secondary small RNAs, but not to identify target sequences. However, it only promotes the creation of secondary small RNAs if a specific subtype of primary small RNAs have recognized the target RNAs for silencing. Further experiments also showed that within the germ granule, SIMR-1 is present in a separate substructure different from any compartment previously identified. This suggests that each substep of the RNA interference process takes place at a different location in the granule. In both C. elegans and humans, disruptions in the RNA interference pathway can lead to conditions such as cancer or infertility. Dissecting the roles of the proteins involved in this process in roundworms may help to better grasp how this process unfolds in mammals, and how it could be corrected in the case of disease.

How to Bring Surgery to the Next Level: Interpretable Skills Assessment in Robotic-Assisted Surgery.

INTRODUCTION: A surgeon's technical skills are an important factor in delivering optimal patient care. Most existing methods to estimate technical skills remain subjective and resource intensive. Robotic-assisted surgery (RAS) provides a unique opportunity to develop objective metrics using key elements of intraoperative surgeon behavior which can be captured unobtrusively, such as instrument positions and button presses. Recent studies have shown that objective metrics based on these data (referred to as objective performance indicators [OPIs]) correlate to select clinical outcomes during robotic-assisted radical prostatectomy. However, the current OPIs remain difficult to interpret directly and, therefore, to use within structured feedback to improve surgical efficiencies. METHODS: We analyzed kinematic and event data from da Vinci surgical systems (Intuitive Surgical, Inc., Sunnyvale, CA, USA) to calculate values that can summarize the use of robotic instruments, referred to as OPIs. These indicators were mapped to broader technical skill categories of established training protocols. A data-driven approach was then applied to further sub-select OPIs that distinguish skill for each technical skill category within each training task. This subset of OPIs was used to build a set of logistic regression classifiers that predict the probability of expertise in that skill to identify targeted improvement and practice. The final, proposed feedback using OPIs was based on the coefficients of the logistic regression model to highlight specific actions that can be taken to improve. RESULTS: We determine that for the majority of skills, only a small subset of OPIs (2-10) are required to achieve the highest model accuracies (80-95%) for estimating technical skills within clinical-like tasks on a porcine model. The majority of the skill models have similar accuracy as models predicting overall expertise for a task (80-98%). Skill models can divide a prediction into interpretable categories for simpler, targeted feedback. CONCLUSION: We define and validate a methodology to create interpretable metrics for key technical skills during clinical-like tasks when performing RAS. Using this framework for evaluating technical skills, we believe that surgical trainees can better understand both what can be improved and how to improve.

Widespread roles for piRNAs and WAGO-class siRNAs in shaping the germline transcriptome of Caenorhabditis elegans.

Piwi-interacting RNAs (piRNAs) and small interfering RNAs (siRNAs) are distinct classes of small RNAs required for proper germline development. To identify the roles of piRNAs and siRNAs in regulating gene expression in Caenorhabditis elegans, we subjected small RNAs and mRNAs from the gonads of piRNA and siRNA defective mutants to high-throughput sequencing. We show that piRNAs and an abundant class of siRNAs known as WAGO-class 22G-RNAs are required for proper expression of spermatogenic and oogenic genes. WAGO-class 22G-RNAs are also broadly required for transposon silencing, whereas piRNAs are largely dispensable. piRNAs, however, have a critical role in controlling histone gene expression. In the absence of piRNAs, histone mRNAs are misrouted into the nuclear RNAi pathway involving the Argonaute HRDE-1, concurrent with a reduction in the expression of many histone mRNAs. We also show that high-level gene expression in the germline is correlated with high level 22G-RNA production. However, most highly expressed genes produce 22G-RNAs through a distinct pathway that presumably involves the Argonaute CSR-1. In contrast, genes targeted by the WAGO branch of the 22G-RNA pathway are typically poorly expressed and respond unpredictably to loss of 22G-RNAs. Our results point to broad roles for piRNAs and siRNAs in controlling gene expression in the C. elegans germline.

henn-1/HEN1 Promotes Germline Immortality in Caenorhabditis elegans.

The germline contains an immortal cell lineage that ensures the faithful transmission of genetic and, in some instances, epigenetic information from one generation to the next. Here, we show that in Caenorhabditis elegans, the small RNA 3'-2'-O-methyltransferase henn-1/HEN1 is required for sustained fertility across generations. In the absence of henn-1, animals become progressively less fertile, becoming sterile after ∼30 generations at 25°C. Sterility in henn-1 mutants is accompanied by severe defects in germline proliferation and maintenance. The requirement for henn-1 in transgenerational fertility is likely due to its role in methylating and, thereby, stabilizing Piwi-interacting RNAs (piRNAs). However, despite being essential for piRNA stability in embryos, henn-1 is not required for piRNA stability in adults. Thus, we propose that methylation is important for the role of piRNAs in establishing proper gene silencing during early stages of development but is dispensable for their role in the proliferated germline.

ALG-5 is a miRNA-associated Argonaute required for proper developmental timing in the Caenorhabditis elegans germline.

Caenorhabditis elegans contains 25 Argonautes, of which, ALG-1 and ALG-2 are known to primarily interact with miRNAs. ALG-5 belongs to the AGO subfamily of Argonautes that includes ALG-1 and ALG-2, but its role in small RNA pathways is unknown. We analyzed by high-throughput sequencing the small RNAs associated with ALG-5, ALG-1 and ALG-2, as well as changes in mRNA expression in alg-5, alg-1 and alg-2 mutants. We show that ALG-5 defines a distinct branch of the miRNA pathway affecting the expression of genes involved in immunity, defense, and development. In contrast to ALG-1 and ALG-2, which associate with most miRNAs and have general roles throughout development, ALG-5 interacts with only a small subset of miRNAs and is specifically expressed in the germline where it localizes alongside the piRNA and siRNA machinery at P granules. alg-5 is required for optimal fertility and mutations in alg-5 lead to a precocious transition from spermatogenesis to oogenesis. Our results provide a near-comprehensive analysis of miRNA-Argonaute interactions in C. elegans and reveal a new role for miRNAs in the germline.

MORC-1 Integrates Nuclear RNAi and Transgenerational Chromatin Architecture to Promote Germline Immortality.

Germline-expressed endogenous small interfering RNAs (endo-siRNAs) transmit multigenerational epigenetic information to ensure fertility in subsequent generations. In Caenorhabditis elegans, nuclear RNAi ensures robust inheritance of endo-siRNAs and deposition of repressive H3K9me3 marks at target loci. How target silencing is maintained in subsequent generations is poorly understood. We discovered that morc-1 is essential for transgenerational fertility and acts as an effector of endo-siRNAs. Unexpectedly, morc-1 is dispensable for siRNA inheritance but is required for target silencing and maintenance of siRNA-dependent chromatin organization. A forward genetic screen identified mutations in met-1, which encodes an H3K36 methyltransferase, as potent suppressors of morc-1(-) and nuclear RNAi mutant phenotypes. Further analysis of nuclear RNAi and morc-1(-) mutants revealed a progressive, met-1-dependent enrichment of H3K36me3, suggesting that robust fertility requires repression of MET-1 activity at nuclear RNAi targets. Without MORC-1 and nuclear RNAi, MET-1-mediated encroachment of euchromatin leads to detrimental decondensation of germline chromatin and germline mortality.

Transgenerational Inheritance: Perpetuating RNAi.

Reversible changes in gene expression independent of the genetic code can be transmitted from one generation to the next via poorly understood mechanisms. In worms, a histone-modifying enzyme is necessary to keep small RNA-guided transgenerational gene silencing in check.

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

BACKGROUND: Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. RESULTS: The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). CONCLUSIONS: Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Drug Selection in the Genomic Age: Application of the Coexpression Extrapolation Principle for Drug Repositioning in Cancer Therapy.

The use of patient-specific data in drug and dose selection is becoming an increasingly important component in cancer therapy. Basing drug choice on molecular aspects of the tumor is consistent with the identification of cancer as a molecular disease or diseases, even within the same histological type, and its treatment specific to the background from which it arose and exists. Multiple examples exist of single-gene mutations, and over- or underexpression that convey either sensitivity or resistance to a given agent. What about the picture that global gene expression in a cancer presents regarding drug sensitivity or resistance? Coexpression extrapolation (COXEN) is a methodology that acts as a Rosetta stone between patterns of gene expression that correlate to drug responses in vitro and those in tumors of untreated patients to predict chemosensitivity in such tumors even to drugs that are not specifically indicated for that histotype. Further applications of COXEN in drug discovery allow for in silico screens correlating drug response and gene expression in a genetically diverse cell panel to gene expression patterns in a target tumor with the potential for identifying and repurposing compounds. Here we discuss how COXEN is being developed and tested for application in drug selection, repositioning, and repurposing in oncology.

piRNAs and piRNA-Dependent siRNAs Protect Conserved and Essential C. elegans Genes from Misrouting into the RNAi Pathway.

piRNAs silence foreign genes, such as transposons, to preserve genome integrity, but they also target endogenous mRNAs by mechanisms that are poorly understood. Caenorhabditis elegans piRNAs interact with both transposon and nontransposon mRNAs to initiate sustained silencing via the RNAi pathway. To assess the dysregulation of gene silencing caused by lack of piRNAs, we restored RNA silencing in RNAi-defective animals in the presence or absence of piRNAs. In the absence of piRNAs and a cellular memory of piRNA activity, essential and conserved genes are misrouted into the RNAi pathway to produce siRNAs that bind the nuclear Argonaute HRDE-1, resulting in dramatic defects in germ cell proliferation and function such that the animals are sterile. Inactivation of RNAi suppresses sterility, indicating that aberrant siRNAs produced in the absence of piRNAs target essential genes for silencing. Thus, by reanimating RNAi, we uncovered a role for piRNAs in protecting essential genes from RNA silencing.