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bioRxivScientific Communication & Education

G-OnRamp: Generating genome browsers to facilitate undergraduate-driven collaborative genome annotation

L. Sargent, Y. Liu, W. Leung, N. T. Mortimer, D. Lopatto, J. Goecks, S. C. R. Elgin

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Abstract

Scientists are sequencing new genomes at an increasing rate with the goal of associating genome contents with phenotypic traits. After a new genome is sequenced and assembled, structural gene annotation is often the first step in analysis. Despite advances in computational gene prediction algorithms, most eukaryotic genomes still benefit from manual gene annotation. Undergraduates can become skilled annotators, and in the process learn both about genes/genomes and about how to utilize large datasets. Data visualizations provided by a genome browser are essential for manual gene annotation, enabling annotators to quickly evaluate multiple lines of evidence (e.g., sequence similarity, RNA-Seq, gene predictions, repeats). However, creating genome browsers requires extensive computational skills; lack of the expertise required remains a major barrier for many biomedical researchers and educators.\n\nTo address these challenges, the Genomics Education Partnership (GEP; https://gep.wustl.edu/) has partnered with the Galaxy Project (https://galaxyproject.org) to develop G-OnRamp (http://g-onramp.org), a web-based platform for creating UCSC Assembly Hubs and JBrowse genome browsers. G-OnRamp can also convert a JBrowse instance into an Apollo instance for collaborative genome annotations in research and educational settings. G-OnRamp enables researchers to easily visualize their experimental results, educators to create Course-based Undergraduate Research Experiences (CUREs) centered on genome annotation, and students to participate in genomics research.\n\nDevelopment of G-OnRamp was guided by extensive user feedback from in-person workshops. Sixty-five researchers and educators from over 40 institutions participated in these workshops, which produced over 20 genome browsers now available for research and education. For example, genome browsers for four parasitoid wasp species were used in a CURE engaging 142 students taught by 13 faculty members -- producing a total of 192 gene models. G-OnRamp can be deployed on a personal computer or on cloud computing platforms, and the genome browsers produced can be transferred to the CyVerse Data Store for long-term access.

In-depth summary

Claude Opus 5.5 · xhigh effort · 8 Nov 2026 · from the full text of version 1 (2 Oct 2019) · CC BY 4.0

Galaxy-based platform builds UCSC Assembly Hubs, JBrowse and Apollo annotation browsers without bioinformatics expertise; parasitoid wasp browsers supported undergraduate research courses producing 192 gene models.

Manual eukaryotic gene annotation depends on genome browsers that integrate evidence tracks, yet building them demands computational skills many biologists and educators lack, and existing options either need bioinformatics expertise or cap assembly size. G-OnRamp packages preconfigured Galaxy tools and workflows so researchers and Course-based Undergraduate Research Experience (CURE) instructors can generate browsers and run collaborative annotation.

Key results

  1. ShownG-OnRamp workflows turned user-supplied assemblies of widely varying size and fragmentation into publicly accessible genome browsers that are stored for long-term access.

    More than 20 public browsers were made by workshop attendees and prototype testers. Assemblies from the 2017 and 2018 workshops ranged from 70Mb to 2.1Gb, with 53 to 271,888 scaffolds (Table 1A). The browsers are stored on the CyVerse Data Store and linked from the G-OnRamp website. · G-OnRamp workshops and evaluation; G-OnRamp overview

  2. ShownBrowsers for four parasitoid wasp species supported a Genomics Education Partnership (GEP) CURE across several institutions. The project studied how lipid synthesis pathways evolved and included genes with no informant homology.

    The abstract reports 142 students and 13 faculty producing 192 gene models. In S8, 15 GEP faculty designed wasp CUREs; the Fig 7A legend breaks implementations down by institution type (n = 15) and by course level and format (n = 16). All faculty survey respondents planned to continue (14 responded; n = 10 after N.A. answers were excluded). · Abstract; G-OnRamp in a CURE: Examining lipid synthesis…; Figure legends

  3. ShownPost-course quiz scores of wasp-project students did not differ significantly from those of other GEP students, who used UCSC mirror Drosophila browsers for the Muller F element project.

    The mean score was 9.1 (N = 173; SD = 3.6) for the wasp group vs 9.5 (N = 1185; SD = 3.5) for other GEP students, with data pooled over 2017-2018 and 2018-2019. The difference is reported as not significant; the statistical test is not named. · G-OnRamp in a CURE: Examining lipid synthesis…; Figure legends

  4. SuggestedOn the SURE survey, wasp-project students self-reported slightly higher gains in understanding how science is done and in research skills. The authors caution against over-reading this result.

    Wasp group N ranged from 181 to 195; other GEP (Drosophila) students N ranged from 1200 to 1270. The wasp group scored significantly higher on some items. The authors flag the small sample size, and no effect sizes or p-values are reported. · G-OnRamp in a CURE: Examining lipid synthesis…; Figure legends

  5. SuggestedWorkshop attendees (researchers and faculty at primarily undergraduate institutions) mostly reported that G-OnRamp helped their research and teaching, and that they intended to keep using it.

    53 participants from over 40 institutions attended two beta-tester workshops in 2017 and two train-the-trainer workshops in 2018. The anonymous survey had N = 35 of 53 eligible (response rate 66.0%). On each item, 20% to 38% answered not applicable, and these answers were excluded from the percentages. · G-OnRamp workshops and evaluation; G-OnRamp features; Figure legends

Methods, data and reproducibility

Galaxy-based platform running four concurrent sub-workflows (sequence similarity, ab initio gene prediction, RNA-Seq analysis, repeat identification) on a target assembly; archive-creator tools build UCSC Assembly Hubs or JBrowse, Apollo tools add managed collaboration, and utility was assessed by surveys and post-course quizzes.

  • Genome assemblies brought by workshop attendees and prototype testers and turned into public browsers (assemblies 70Mb to 2.1Gb; 53 to 271,888 scaffolds) · multiple species (not named in text) · n = over 20 genome browsers
  • Parasitoid wasp genome assemblies with RNA-Seq, de novo transcriptome and proteomics evidence, used to annotate lipid synthesis genes · parasitoid wasps (four species; names not given) · n = four species
  • Informant genomes used for homology-based construction of gene models · Nasonia vitripennis; Drosophila melanogaster
  • Apollo reconciliation example: the eIF4G1 ortholog, whose reconciled model uses a non-canonical GC splice donor · D. takahashii
  • Anonymous survey of G-OnRamp workshop participants covering demographics and perceived utility · n = 35 of 53 eligible (66.0% response)
  • Likert survey (5-point) of GEP faculty who used G-OnRamp wasp browsers in their courses · n = 14 responded; n = 10 after N.A. removal
  • Post-course annotation test scores, wasp CURE students vs other GEP students, pooled over 2017-2018 and 2018-2019 · n = 173 (wasp) vs 1185 (other GEP)
  • SURE survey self-reported research gains, wasp-project students vs other GEP students · n = 181 to 195 (wasp) vs 1200 to 1270 (other GEP)
Methods & tools
Galaxy (19.05), UCSC Genome Browser / Assembly Hubs, JBrowse (1.16.6), Apollo (2.4.1), Augustus, BLAST, Top-Hat, Hub Archive Creator (HAC), JBrowse Archive Creator, CyVerse Data Store export tool, CloudLaunch / AWS Amazon Machine Image, VirtualBox virtual appliance
Software & environment
G-OnRamp 1.1 bundles Galaxy 19.05, Apollo 2.4.1 and JBrowse 1.16.6. It ships as a VirtualBox appliance for local testing and training, and as an Amazon Machine Image launched via CloudLaunch or found under EC2 Community AMIs.
Reproducibility gaps
The text gives no accessions for the wasp assemblies, RNA-Seq or proteomics data. The Table 1A browser list is not reproduced. Survey and quiz data are not released, and the statistical tests are not specified.
Limitations (6)
  • The authors caution that the wasp group's higher SURE self-reported gains should be interpreted carefully because the sample size is small. · stated by the authors
  • Survey respondents named the lack of homology to an informant genome as a main difficulty in annotating new species. In such cases students must rely on RNA-Seq, proteomics and ab initio predictions. · stated by the authors
  • Installing from the open-source GitHub scripts gives finer control but adds complexity that requires technical expertise, unlike the VirtualBox appliance or the AWS image. · stated by the authors
  • The authors acknowledge that it is difficult to isolate the effect of the research component itself on student outcomes in CUREs. · stated by the authors
  • The wasp vs GEP comparison is observational: projects, browsers, organisms and institutions all differ between groups. A non-significant difference, with no named test or equivalence analysis, does not show equal effectiveness. · noted in this summary
  • Evidence of utility rests mainly on self-report surveys (faculty n = 10 after exclusions). Counts differ between sections (sixty-five vs 53 workshop participants; 13 vs 15 faculty), and gene-model accuracy is not benchmarked. · noted in this summary

Read this if you run a genomics teaching program or an annotation project and need UCSC Assembly Hub, JBrowse or Apollo browsers for a new assembly without in-house bioinformatics support.

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