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

Tate, Alex J / Brown, Kristen C / Montgomery, Taiowa A

Bioinformatics advances

2023 Volume 3, Issue 1, Page(s) vbad065

Abstract: 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 ...

Abstract	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.
Language	English
Publishing date	2023-05-18
Publishing country	England
Document type	Journal Article
ISSN	2635-0041
ISSN (online)	2635-0041
DOI	10.1093/bioadv/vbad065
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Article ; Online: A Probabilistic Approach to Surgical Tasks and Skill Metrics.

Berniker, Max / Bhattacharyya, Kiran D / Brown, Kristen C / Jarc, Anthony

IEEE transactions on bio-medical engineering

2022 Volume 69, Issue 7, Page(s) 2212–2219

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Benchmarking ; Clinical Competence ; Feedback ; Humans ; Machine Learning ; Surgeons
Language	English
Publishing date	2022-06-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	160429-6
ISSN	1558-2531 ; 0018-9294
ISSN (online)	1558-2531
ISSN	0018-9294
DOI	10.1109/TBME.2021.3139538
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Article ; Online: The long and short of lifespan regulation by Argonautes.

Brown, Kristen C / Montgomery, Taiowa A

PLoS genetics

2018 Volume 14, Issue 6, Page(s) e1007415

MeSH term(s)	Argonaute Proteins ; Longevity
Chemical Substances	Argonaute Proteins
Language	English
Publishing date	2018-06-21
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	2186725-2
ISSN	1553-7404 ; 1553-7390
ISSN (online)	1553-7404
ISSN	1553-7390
DOI	10.1371/journal.pgen.1007415
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Article ; Online: Transgenerational Inheritance: Perpetuating RNAi.

Brown, Kristen C / Montgomery, Taiowa A

Current biology : CB

2017 Volume 27, Issue 10, Page(s) R383–R385

Abstract: 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 ... ...

Abstract	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.
Language	English
Publishing date	2017-05-22
Publishing country	England
Document type	Journal Article
ZDB-ID	1071731-6
ISSN	1879-0445 ; 0960-9822
ISSN (online)	1879-0445
ISSN	0960-9822
DOI	10.1016/j.cub.2017.03.061
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Article: How to Bring Surgery to the Next Level: Interpretable Skills Assessment in Robotic-Assisted Surgery.

Brown, Kristen C / Bhattacharyya, Kiran D / Kulason, Sue / Zia, Aneeq / Jarc, Anthony

Visceral medicine

2020 Volume 36, Issue 6, Page(s) 463–470

Abstract: 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 ... ...

Abstract	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.
Language	English
Publishing date	2020-10-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2850733-2
ISSN	2297-475X ; 2297-4725
ISSN (online)	2297-475X
ISSN	2297-4725
DOI	10.1159/000512437
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Article ; Online: Combining tRNA sequencing methods to characterize plant tRNA expression and post-transcriptional modification.

Warren, Jessica M / Salinas-Giegé, Thalia / Hummel, Guillaume / Coots, Nicole L / Svendsen, Joshua M / Brown, Kristen C / Drouard, Laurence / Sloan, Daniel B

RNA biology

2020 Volume 18, Issue 1, Page(s) 64–78

Abstract: 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 ... ...

Abstract	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
MeSH term(s)	Arabidopsis/genetics ; Gene Expression Regulation, Plant ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Magnoliopsida/genetics ; Plastids/genetics ; RNA Processing, Post-Transcriptional ; RNA, Plant/genetics ; RNA, Transfer/genetics ; Sequence Analysis, RNA
Chemical Substances	RNA, Plant ; RNA, Transfer (9014-25-9)
Language	English
Publishing date	2020-07-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2159587-2
ISSN	1555-8584 ; 1555-8584
ISSN (online)	1555-8584
ISSN	1555-8584
DOI	10.1080/15476286.2020.1792089
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Article ; Online: Drug Selection in the Genomic Age: Application of the Coexpression Extrapolation Principle for Drug Repositioning in Cancer Therapy.

Gustafson, Daniel L / Fowles, Jared S / Brown, Kristen C / Theodorescu, Dan

Assay and drug development technologies

2015 Volume 13, Issue 10, Page(s) 623–627

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Antineoplastic Agents/pharmacology ; Antineoplastic Agents/therapeutic use ; Computer Simulation ; Drug Discovery ; Drug Repositioning/methods ; Drug Resistance, Neoplasm/genetics ; Gene Expression Regulation, Neoplastic/drug effects ; Humans ; Neoplasms/drug therapy ; Neoplasms/genetics ; Pharmacogenetics/methods ; Reproducibility of Results
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2015-12
Publishing country	United States
Document type	Journal Article
ISSN	1557-8127
ISSN (online)	1557-8127
DOI	10.1089/adt.2015.29012.dlgdrrr
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Article ; Online: ALG-5 is a miRNA-associated Argonaute required for proper developmental timing in the Caenorhabditis elegans germline.

Brown, Kristen C / Svendsen, Joshua M / Tucci, Rachel M / Montgomery, Brooke E / Montgomery, Taiowa A

Nucleic acids research

2017 Volume 45, Issue 15, Page(s) 9093–9107

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Animals ; Argonaute Proteins/genetics ; Argonaute Proteins/metabolism ; Caenorhabditis elegans/classification ; Caenorhabditis elegans/genetics ; Caenorhabditis elegans/growth & development ; Caenorhabditis elegans/metabolism ; Caenorhabditis elegans Proteins/genetics ; Caenorhabditis elegans Proteins/metabolism ; Gene Expression Regulation, Developmental ; Germ Cells/growth & development ; Germ Cells/metabolism ; Hermaphroditic Organisms/genetics ; Hermaphroditic Organisms/growth & development ; Hermaphroditic Organisms/metabolism ; High-Throughput Nucleotide Sequencing ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Mutation ; Oogenesis/genetics ; Phylogeny ; Protein Isoforms/genetics ; Protein Isoforms/metabolism ; RNA, Helminth/genetics ; RNA, Helminth/metabolism ; RNA, Messenger/genetics ; RNA, Messenger/metabolism ; RNA, Small Interfering/genetics ; RNA, Small Interfering/metabolism ; RNA-Binding Proteins/genetics ; RNA-Binding Proteins/metabolism ; Spermatogenesis/genetics
Chemical Substances	ALG-1 protein, C elegans ; ALG-2 protein, C elegans ; ALG-5 protein, C elegans ; Argonaute Proteins ; Caenorhabditis elegans Proteins ; MicroRNAs ; Protein Isoforms ; RNA, Helminth ; RNA, Messenger ; RNA, Small Interfering ; RNA-Binding Proteins
Language	English
Publishing date	2017-09-06
Publishing country	England
Document type	Journal Article
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkx536
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Article ; Online: Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

Fowles, Jared S / Brown, Kristen C / Hess, Ann M / Duval, Dawn L / Gustafson, Daniel L

BMC bioinformatics

2016 Volume 17, Page(s) 93

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Animals ; Biomarkers, Pharmacological ; Bone Neoplasms/genetics ; Dog Diseases ; Dogs ; Doxorubicin ; Gene Expression/genetics ; Humans ; Osteosarcoma/genetics ; Treatment Outcome
Chemical Substances	Biomarkers, Pharmacological ; Doxorubicin (80168379AG)
Language	English
Publishing date	2016-02-19
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-016-0942-8
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Article ; Online: piRNAs and piRNA-Dependent siRNAs Protect Conserved and Essential C. elegans Genes from Misrouting into the RNAi Pathway.

Phillips, Carolyn M / Brown, Kristen C / Montgomery, Brooke E / Ruvkun, Gary / Montgomery, Taiowa A

Developmental cell

2015 Volume 34, Issue 4, Page(s) 457–465

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Animals ; Caenorhabditis elegans/genetics ; Caenorhabditis elegans Proteins/genetics ; Caenorhabditis elegans Proteins/metabolism ; Conserved Sequence ; Female ; Fertility ; Genes, Essential ; Genes, Helminth ; High-Throughput Nucleotide Sequencing ; Molecular Sequence Data ; Protein Binding ; RNA Interference ; RNA, Small Interfering/metabolism
Chemical Substances	Caenorhabditis elegans Proteins ; RNA, Small Interfering
Language	English
Publishing date	2015-08-24
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2054967-2
ISSN	1878-1551 ; 1534-5807
ISSN (online)	1878-1551
ISSN	1534-5807
DOI	10.1016/j.devcel.2015.07.009
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