- Welcome to the Museum Genomics Community!
- Discuss Museum Genomics with other Researchers
- Contribute Relevant Museum Genomics Literature to the Community
- Ensure Contributions to Museum Genomics Follow Best Practices
- Follow Museum Genomics Research on Twitter
- Provide Feedback and Suggestions for Community Engagement
- Just Give me the Data Files!
Welcome to the webpage accompanying Card et al. Museum Genomics. 2021. Annual Review of Genetics 55: 633-659. https://doi.org/10.1146/annurev-genet-071719-020506. This webpage is maintained by Daren Card.
While this website was initially created to archive data files associated with this review, I am also experimenting with ways of extending its utility. Namely, I hypothesize that enabling ways in which the museum genomics community can interact with this website in a dynamic manner may yield dividends for this research community. Most data repositories are static in nature and only allow a one-way flow of information from the authors to the audience. I am aiming to make this website dynamic and bidirectional in an open way by taking advantage of the version control, collaboration, and hosting capabilities of Git and GitHub. The initial, raw data repository will always be available through the badge link at the top of this page and is also preserved in the commit history of this repository (see commit bb39d07 or release v1.0). However, I am also experimenting with adding new features to the webpage that foster interaction among museum genomics researchers, thus creating more of a "living" supplement for the research article. I welcome feedback on these ideas and their implementation.
Finally, please note the Code of Conduct that governs the interactions that take place in this community and be kind and respectful to others!
Please see below for information on how to interact with this webpage and retrieve data files associated with this article.
With any research article, it is always possible to contact the corresponding author to ask questions, provide feedback, or commence research discussions. However, these interactions are often hidden from public view. This is certainly appropriate for some correspondance, but in other cases, it may make sense to have a public forum to facilitate interactions between the authors and audience and among community members. It seems horribly inefficient for an author to respond to the same question from many readers through email, for example, when viable alternatives are well established. In an effort to demonstrate this manner of discussion, I am leveraging GitHub Issues. Each GitHub repository, including the one hosting this webpage and the archived data files, has an associated Issue forum, which is normally used to support software by allowing users to report problems or request features. I am co-opting this functionality to make a simple forum where anyone can come to ask the author questions, provide feedback, or initiate other types of research interactions.
Please visit the Museum Genomics Researcher Forum and interact with other museum genomics researchers through existing discussion threads or submit a new forum post to start a new thread.
If you publish research in museum genomics, please also submit the corresponding DOI (digital object identifier) using the form below to help keep track of emerging research in this field. My goal with this feature is to facilitate the collection and curation of new literature within museum genomics so that there is a central location where interested parties can retrieve a relevant bibliography. Ideally, through community engagement and shared effort, a thorough body of relevant literature will be built, which may prove useful for future reviews of this young and growing research field. If we collect and curate physical natural history materials, why not do the same with the peer-reviewed literature that we create? I encourage other museum scientists who work with and publish genomics data to continue long traditions of contributing to community collections by submitting their work using the following form.
<iframe src="https://docs.google.com/forms/d/e/1FAIpQLSfTAK3YdDZp33oym3lChU2kezQNqv-3HsBYxdfmh4Sa6Ua_IQ/viewform?embedded=true" width="640" height="603" frameborder="0" marginheight="0" marginwidth="0">Loading…</iframe>In progress: If interest materializes and other researchers begin adding DOIs for relevant literature, I will work to automate the collation of a bibliography based on user submissions. I will share this bibliography through this webpage so that others can quickly and easily engage with peer-reviewed literature in this field. For now, you can view a running list of the submitted DOIs at this Google Sheet.
The most important action any museum genomicists can take is to properly document and share the list of specimens or samples used in a study! Often this list is included as a supplementary table and is vital for allowing readers and other scientists to contextualize or replicate research. To assist researchers in their efforts to document this important information, we have created a downloadable museum genomics sample table template. Hover over the table headers for notes about the information that should be included in each field and the form that information should take. The fields in this template represent the minimum amount of sample information that should be provided in any study, but additional columns with information can always be included. Field headers can also be renamed as needed.
I have created an automated Twitter bot that will retweet and like relevant research based on the keywords "museum genomics" or the hashtag #MuseumGenomics. Users can follow this bot/account to stay up to date on research and other content that uses these keywords or hashtag. Researchers are also welcomed to tag relevant research products with the #MuseumGenomics hashtag and it will be retweeted and liked. I see this bot as a nice supplement to the DOI collection form described above for collecting relevant research and it also facilitates more natural interactions between scientists in this community using a popular social media platform. See the following digest for Twitter content recently highlighted by the Museum Genomics bot.
Tweets by MuseumGenomics <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
Note: Details on the Twitter bot used for this purpose and how it is run can be found at https://github.com/anniedotexe/Twitter-Retweet-Bot.
Do you have other ideas for how this webpage could engage audience members in the field of museum genomics or broader biological research? I would love to hear them! Or are you passionate about science communication and wish to discuss these experiments? Please reach out to Daren! I have already created a Museum Genomics Researcher Forum thread to solicit feedback and encourage this dialogue. You can also create your own new discussion thread.
The raw data associated with several figures is described and linked below. An archive of this data repository has been created through Zenodo with an accompanying DOI, which can be accessed at https://doi.org/10.5281/zenodo.5093841.
File Name: Figure1_Museum_growth_trends_2010-2019.txt
Data on temporal patterns of cryogenic collection growth for five major natural history collecions between 2010 and 2019: American Museum of Natural History (AMNH), Louisiana State University Museum of Natural Science (LSUMZ), Harvard University Museum of Comparative Zoology (MCZ), University of New Mexico Museum of Southwest Biology (MSB), and University of California Museum of Vertebrate Zoology (MVZ). All counts only reflect newly collected and catalogued samples with an associated voucher specimen but each of these collections also has significant numbers of samples with no associated voucher specimens and previously collected samples that have been more recently added to cryogenic collections. For examples, MSB has collected and cryopreserved 8,886 fish genomic samples between 2010 and 2019, but none had associated voucher specimens.
Both annual and cumulative counts of catalogued records per collection are available in a tab-delimited text file. The fields are the institution (see codes above), the collection, the year, the annual number of catalogued records, and the cumulative sum per year of catalogued records per collection and institution. Please see a hypothetical example below where 10 new records are added per year for each of three collections at two different institution.
| Institution | Collection | Year | Annual_count | Collection_running_count |
|---|---|---|---|---|
| MCZ | Ornithology | 2010 | 10 | 10 |
| MCZ | Ornithology | 2011 | 10 | 20 |
| MCZ | Ornithology | 2012 | 10 | 30 |
| MCZ | Herpetology | 2010 | 10 | 10 |
| MCZ | Herpetology | 2011 | 10 | 20 |
| MCZ | Herpetology | 2012 | 10 | 30 |
| AMNH | Herpetology | 2010 | 10 | 10 |
| AMNH | Herpetology | 2011 | 10 | 20 |
| AMNH | Herpetology | 2012 | 10 | 30 |
Figure 2. Empirical Patterns of Genome Assembly Contiguity for Avian Genome Assemblies Based on Varying Tissue Type and Preservation Protocol
File Name: Figure2_Edwards_Lab_Genome_Quality_Tissue_Preservation.txt
The Edwards laboratory at Harvard University has gathered internal data on genome assembly scaffold contiguity (N50) for avian genome assemblies generated in recent years. All assemblies utilized 10x Genomics but the original input tissue samples were collected from various tissues and were preserved using different protocols.
For each genome in this dataset, the scientific name, common name, technology utilized (10x Genomics), source of tissue and preservation mode, genome size estimate, approximate sequencing coverage, and contig and scaffold contiguity metrics (N50; in Mb) are available in a tab-delimited text file.
Figure 5. Overview of Holdings of Next-Generation, RNA-ready Genomic Samples for Diverse Avian Species in the Museum of Comparative Zoology at Harvard University
File Names: Figure5_MCZ_RNAquality_Tissues.txt and Figure5_Jetz2012_HackettBackbone_Phylogeny.tre
The Ornithology Collection at the Museum of Comparative Zoology has since 2012 collected high quality genomic samples from diverse avian taxa around the globe. These samples are compatible with RNA-seq and other methods utilizing very high quality tissue samples (long read sequencing, functional genomics, etc.), which are rare in most natural history collections in 2021. Most samples were minced and preserved in RNAlater within 10 minutes of sacrifice and then flash frozen in liquid nitrogen after ~12 hours at cool temperatures. A small percentage of samples were directly flash frozen without RNAlater.
A matrix with counts of high quality samples from 13 different tissue types in 101 avian species is available as a tab-delimited text file. The phylogeny used for plotting was the consensus taken from Jetz (2012; 10.1038/nature11631) with the Hackett backbone available from birdtree.org and this phylogeny is also available in Newick format.