Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching

Peterson, Mark P.; Malloy, Jacob T.; Marden, James H.; Buonaccorsi, Vincent P.

doi:10.24918/cs.2015.14

Cited by 12 publications

(14 citation statements)

References 6 publications

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“…We identified differentially expressed (DE) genes using rnaseqWrapper [15] and DESeq [16] packages for R [17] with a false discovery rate threshold of 0.05. We determined which gene ontology (GO) terms were over-represented among DE genes using the 'weight' algorithm from topGO [18] R package with a significance threshold of 0.05.…”

Section: Methodsmentioning

confidence: 99%

Differential gene expression in seasonal sympatry: mechanisms involved in diverging life histories

et al. 2016

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In an era of climate change, understanding the genetic and physiological mechanisms underlying flexibility in phenology and life history has gained greater importance. These mechanisms can be elucidated by comparing closely related populations that differ in key behavioural and physiological traits such as migration and timing of reproduction. We compared gene expression in two recently diverged dark-eyed Junco (Junco hyemalis) subspecies that live in seasonal sympatry during winter and early spring, but that differ in behaviour and physiology, despite exposure to identical environmental cues. We identified 547 genes differentially expressed in blood and pectoral muscle. Genes involved in lipid transport and metabolism were highly expressed in migrant juncos, while genes involved in reproductive processes were highly expressed in resident breeders. Seasonal differences in gene expression in closely related populations residing in the same environment provide significant insights into mechanisms underlying variation in phenology and life history, and have potential implications for the role of seasonal timing differences in gene flow and reproductive isolation.

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Section: Methodsmentioning

confidence: 99%

Differential gene expression in seasonal sympatry: mechanisms involved in diverging life histories

et al. 2016

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“…The nuclear ROIs were expanded for 2 μm with a custom Cell-Profiler script and considered as cells. The signal-dots were counted in these cell-ROIs using Cell-Profiler 3.15 (60), Fiji (62, 63) and R-RStudio (58, 64–67) custom scripts (https://github.com/AlexSount/SCRINSHOT).…”

Section: Methodsmentioning

confidence: 99%

SCRINSHOT, a spatial method for single-cell resolution mapping of cell states in tissue sections

Sountoulidis¹,

Liontos²,

Nguyen³

et al. 2020

Preprint

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16 17 ǂ Corresponding authors: Christos Samakovlis (christos.samakovlis@scilifelab.se), Alexandros 18 Sountoulidis (alexandros.sountoulidis@scilifelab.se) 19 20 Keywords: SCRINSHOT, padlock-probe, multiplex RNA FISH, spatial cell-type map, lung 21 22 2 23 Abstract 24 Changes in cell identities and positions underlie tissue development and disease progression. 25 Although, single-cell mRNA sequencing (scRNA-Seq) methods rapidly generate extensive lists of 26 cell-states, spatially resolved single-cell mapping presents a challenging task. We developed 27 SCRINSHOT (Single Cell Resolution IN Situ Hybridization On Tissues), a sensitive, multiplex 28 RNA mapping approach. Direct hybridization of padlock probes on mRNA is followed by 29 circularization with SplintR ligase and rolling circle amplification (RCA) of the hybridized padlock 30 probes. Sequential detection of RCA-products using fluorophore-labeled oligonucleotides profiles 31 thousands of cells in tissue sections. We evaluated SCRINSHOT specificity and sensitivity on 32 murine and human organs. SCRINSHOT quantification of marker gene expression shows high 33 correlation with published scRNA-Seq data over a broad range of gene expression levels. We 34 demonstrate the utility of SCRISHOT by mapping the locations of abundant and rare cell types 35 along the murine airways. The amenability, multiplexity and quantitative qualities of SCRINSHOT 36 facilitate single cell mRNA profiling of cell-state alterations in tissues under a variety of native and 37 experimental conditions. 38 39 40 41 42 43 44 45 65addressed by the sequential fluorescence in situ hybridization (seqFISH) (14, 15) and the 66 multiplexed error-robust FISH (MERFISH) (4). These approaches utilize sequential rounds of 67 hybridization of FISH probes or barcode-based primary probes to detect multiple RNA species. 68The outstanding throughput of these methods makes them strong candidates for generation of 69 spatial transcriptome maps in tissues. However, since the principle of these techniques is similar 70 to smFISH, they require large number of gene-specific probes, confocal or super-resolution 4 71 microscopy to deconvolve the signals and complicated algorithms for both probe design and 72 analysis. Nevertheless, the low signal-to-noise ratio still remains a major technical challenge of 73 these methods, especially for tissue sections with strong auto-fluorescence from structural 74 extracellular matrix components like collagen and elastin (16). New strategies for signal 75 amplifications, such as branched-DNA amplification (RNAScope) (17) and hybridization chain 76 reaction (18, 19), have been recently combined with sophisticated probe design (AmpFISH) (20) 77 to increase sensitivity and specificity of smFISH. 78 Padlock probes have been successfully used to detect RNA species (21). They are linear DNA 79 molecules, with complementary arms to the target mRNA sequence and a common "backbone". 80 Upon hybridization with the target sequence, they can be ligated, creating circular single-stranded 81...

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“…In a semester-long computational genetics course using publicly available genomics data, students acquired competencies in bioinformatics tools and peer-peer collaboration that allowed them to co-author papers with their instructors ( 15 ). Other authors have developed learning activities that utilize genomics data to introduce undergraduate students to RNAseq sequence assembly and data analysis pipeline in the R statistical environment ( 16 ). In all, these and similar articles are geared towards transmitting both course knowledge and scientific research skills.…”

Section: Introductionmentioning

confidence: 99%

Investigating Cell Signaling with Gene Expression Datasets

Wachira

Hughes‐Darden

Nkwanta

2019

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Modern molecular biology is a data- and computationally-intensive field with few instructional resources for introducing undergraduate students to the requisite skills and techniques for analyzing large data sets. This Lesson helps students: (i) build an understanding of the role of signal transduction in the control of gene expression; (ii) improve written scientific communication skills through engagement in literature searches, data analysis, and writing reports; and (iii) develop an awareness of the procedures and protocols for analyzing and making inferences from high-content quantitative molecular biology data. The Lesson is most suited to upper level biology courses because it requires foundational knowledge on cellular organization, protein structure and function, and the tenets of information flow from DNA to proteins. The first step lays the foundation for understanding cell signaling, which can be accomplished through assigned readings and presentations. In subsequent active learning sessions, data analysis is integrated with exercises that provide insight into the structure of scientific papers. The Lesson emphasizes the role of quantitative methods in research and helps students gain experience with functional genomics databases and data analysis, which are important skills for molecular biologists. Assessment is conducted through mini-reports designed to gauge students’ perceptions of the purpose of each step, their awareness of the possible limitations of the methods utilized, and the ability to identify opportunities for further investigation. Summative assessment is conducted through a final report. The modules are suitable for complementing wet-laboratory experiments and can be adapted for different courses that use molecular biology data.

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Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching

Cited by 12 publications

References 6 publications

Differential gene expression in seasonal sympatry: mechanisms involved in diverging life histories

Differential gene expression in seasonal sympatry: mechanisms involved in diverging life histories

SCRINSHOT, a spatial method for single-cell resolution mapping of cell states in tissue sections

Investigating Cell Signaling with Gene Expression Datasets

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