Hi everybody,
Join us next Wednesday, August 7th, at 12 PM CDT for our monthly webinar. *Seth
Murray <https://soilcrop.tamu.edu/people/murray-seth-c/> *(Texas A&M
University, TAMU) will present on temporal field phenomics.
I have included below more details about the webinar and the Zoom link to
attend the webinar.
I hope you will join us.
Best,
Annarita
:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:
*Abstracts:*
*Capturing Nature AND Nurture with Temporal Field Phenomics to Breed Better
Crops*
An organism’s phenome results from genotype (nature), environment and
management effects (nurture) and their interactions, as well as measurement
error. For over 30 years, DNA sequencing and genomics tools have advanced
genotyping to where genomes can now be routinely saturated with
measurements. In contrast, most focus in high throughput phenotyping and
phenomics to date has been on automating previously known “traits” as
measurable and interpretable phenotypes; akin to focusing on measuring a
single DNA marker rather than measuring a saturated genome. Tools such as
unoccupied aerial systems (UAS, aka UAVs, drones) collecting temporal
phenomic measurements in the field now allow novel methods in plant
breeding and new insights into plant biology. Viewing phenomics as a
platform for discovery, similar to genomics, opens new methods for
capturing phenomena in nature and nurture. To date, our experience with
phenomic prediction from UAS in maize breeding for cumulative, complex
phenotypes such as grain yield suggests it’s possible to predict organismal
performance in untested environments; in fact possibly better than
gold-standard genomic methods. Surprising insights into biology have also
been made in through these activities predicting plant disease and
resistance, evaluating genotypic resilience to stress, and identifying
early season growth periods for crop improvement that have not been able to
be selected. Method development and data analytics in phenomics are large
investments, but worth making. Successfully measuring the phenome will
impact every aspect of science and society, in biological disciplines from
germplasm curators, physiologists to breeders, to education, the courtroom
and policy.
*| 1P ET | 12P CT | 11A MT | 10A PT |*
Find your local time here
<https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…>
*Join Zoom
Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09
<https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>*
Meeting ID: 820 3835 6125
Passcode: 160683
ReplyForward
Dear all,
Thank you for being part of the AgBioData community. We are almost at the
end of a three-year National Science Foundation (NSF) RCN project. We want
to estimate the impact of these years' efforts on increasing the awareness
and implementation of FAIR practices in the ag research community.
*If you haven't already*, we invite you to participate in a *brief survey* *on
the impact of AgBioData activities on FAIR data management awareness*. This
survey, which follows up on one we ran in 2022, will help us quantify any
significant change in the implementation of FAIR practices since the
beginning of the project.
Click here <https://tinyurl.com/AgBioData24> to participate in this survey.
Your participation in this survey is crucial for our mission to enhance
FAIR data in agricultural research. It will provide insights to help us
define the consortium's directions and secure future funding. We want to
emphasize that your participation is entirely voluntary and anonymous.
Best,
Annarita
Dear all,
A friendly reminder of *tomorrow's appointment* with the scRNA Biocuration
WG *at 8 a.m. PST / 10 a.m. CST / 11 a.m. EST / 5 p.m. CET* (Zoom link
<https://us06web.zoom.us/j/85091905235?pwd=Oqhn0Pvy3iXd5jObJi0JyacJy0bgmf.1>
).
Muskan Kapoor, a graduate research assistant in Tuggle's lab, will discuss
the current state of developing a single-cell data portal for farm animals.
There are more details on the talk at the bottom of this email.
I hope you will join us.
Best,
Annarita
----------------------------------------------------------------------------------------------------------------
*Abstract*:
*Building a FAIR data ecosystem for incorporating single-cell genomics data
into agricultural G2P research*
The agriculture genomics community has numerous data submission standards
available, but the standards for describing and storing single-cell (SC,
e.g., scRNA-seq) data are comparatively underdeveloped. To bridge this gap,
we leveraged recent advancements in human genomics infrastructure, such as
the integration of the Human Cell Atlas Data Portal with Terra, a secure,
scalable, open-source platform for biomedical researchers to access data,
run analysis tools, and collaborate, co-developed by the Broad Institute of
MIT and Harvard, Microsoft, and Verily. In parallel, the Single Cell
Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal
for high-throughput sequencing datasets, including plants, protists, and
animals (including humans). Developing data tools connecting these
resources would offer significant advantages to the agricultural genomics
community. The FAANG data portal at EMBL-EBI emphasizes delivering rich
metadata and highly accurate and reliable annotation of farmed animals but
is not computationally linked to either of these resources. Herein, we
describe a pilot-scale project that determines whether the current FAANG
metadata standards for livestock can be used to ingest scRNA-seq datasets
into Terra in a manner consistent with HCA Data Portal standards.
Importantly, rich scRNA-seq metadata can now be brokered through the FAANG
data portal using a semi-automated process, thereby avoiding the need for
substantial expert curation. We have further extended the functionality of
this tool so that validated and ingested SC files within the HCA Data
Portal are transferred to Terra for further analysis. In addition, we
verified data ingestion into Terra, hosted on Azure, and demonstrated the
use of a workflow to analyze the first ingested porcine scRNA-seq dataset.
Additionally, we have also developed prototype tools to visualize the
output of scRNA-seq analyses on genome browsers to compare gene expression
patterns across tissues and cell populations. This JBrowse tool now
features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk
RNA-seq experiments. We intend to further build upon these existing tools
to construct a scientist-friendly data resource and analytical ecosystem
based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC
principles to facilitate SC-level genomic analysis through data ingestion,
storage, retrieval, re-use, visualization, and comparative annotation
across agricultural species.
ReplyForward
Dear all,
The AgBioData Standards for Genetic Variation Working Group (SGV) is
preparing a white paper to support the adoption of rsIDs for agriculture
and seeks your valuable input and data to further our research efforts.
They invite the AgBioData community to join them on* July 18 at 11:00 ET *to
review the material and *discuss collaboration opportunities*. In
particular, the SGV is looking for the following information:
1. Genetic Markers Linked to Traits:
-
A list of genetic markers associated with specific traits used by the
breeding and research community across various agricultural species,
including plants, animals, and insects. See an example here
<https://docs.google.com/spreadsheets/d/167DaYxbdKejoL0l6UhGqMPu-GbGsW6vIok7…>
.
-
Information on the species and traits these markers are linked to and
the methodologies/platforms employed for genotyping in your community.
2. Functional Validation and Fitness Outcomes:
-
Examples of genetic variations that have been functionally validated,
including descriptions of the phenotypic differences these
variations lead
to.
-
Case studies or data demonstrating these genetic variations have
resulted in measurable fitness outcomes for the species in question.
-
Information on related publications and any supporting data available.
-
We would like to request examples from each of the different
species/database providers for review at the upcoming GV working group
meeting in July.
3. Standards and Data Access for Genetic & Phenotypic Variation:
FAIR/ Interoperability
-
Standard formats for exchanging information, identifiers, formats,
and controlled vocabulary on:
- Germplasm
- Genetic Variation
- Phenotypes
-
Types of views and files provided for data access.
-
Future targets for operating, displaying, or providing access to
these data types.
-
Usage of rsIDs and potential barriers to their adoption in your
resource.
-
For more information on RSIDs, please look at the following
document RefSNPs: Clustered Variants
<https://docs.google.com/document/d/1PHXqW7M50mE5SSl4Zprd904KCr9nWzSR4L8sx3U…>
4. Collaboration Opportunities:
-
Barriers encountered when working with these data types.
-
Opportunities for collaboration or data standards, sharing, and
interoperability.
We really appreciate your support and look forward to your positive
response to the request for information in any of the four categories.
*If you are willing to participate or are interested in contributing to our
initiative and would like to collaborate, please complete this form
(https://forms.gle/jcjWnLibHEKuESJe6 <https://forms.gle/jcjWnLibHEKuESJe6>)
by July 16. *We will follow up with you with the Zoom link and other
resources.
Best,
The AgBioData Standards for Genetic Variation WG
Dear all,
The scRNA Biocuration WG invites you to an open meeting on *July 17th at 8
a.m. PST / 10 a.m. CST / 11 a.m. EST / 5 p.m. CET* (Zoom link
<https://us06web.zoom.us/j/85091905235?pwd=Oqhn0Pvy3iXd5jObJi0JyacJy0bgmf.1>
).
Muskan Kapoor, a graduate research assistant in Tuggle lab, will discuss
the current state of developing a single-cell data portal for farm animals.
More details on the talk at the bottom of this email.
I hope you will join us.
Best,
Annarita
----------------------------------------------------------------------------------------------------------------
*Abstract*:
*Building a FAIR data ecosystem for incorporating single-cell genomics data
into agricultural G2P research*
The agriculture genomics community has numerous data submission standards
available, but the standards for describing and storing single-cell (SC,
e.g., scRNA-seq) data are comparatively underdeveloped. To bridge this gap,
we leveraged recent advancements in human genomics infrastructure, such as
the integration of the Human Cell Atlas Data Portal with Terra, a secure,
scalable, open-source platform for biomedical researchers to access data,
run analysis tools, and collaborate, co-developed by the Broad Institute of
MIT and Harvard, Microsoft, and Verily. In parallel, the Single Cell
Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal
for high-throughput sequencing datasets, including plants, protists, and
animals (including humans). Developing data tools connecting these
resources would offer significant advantages to the agricultural genomics
community. The FAANG data portal at EMBL-EBI emphasizes delivering rich
metadata and highly accurate and reliable annotation of farmed animals but
is not computationally linked to either of these resources. Herein, we
describe a pilot-scale project that determines whether the current FAANG
metadata standards for livestock can be used to ingest scRNA-seq datasets
into Terra in a manner consistent with HCA Data Portal standards.
Importantly, rich scRNA-seq metadata can now be brokered through the FAANG
data portal using a semi-automated process, thereby avoiding the need for
substantial expert curation. We have further extended the functionality of
this tool so that validated and ingested SC files within the HCA Data
Portal are transferred to Terra for further analysis. In addition, we
verified data ingestion into Terra, hosted on Azure, and demonstrated the
use of a workflow to analyze the first ingested porcine scRNA-seq dataset.
Additionally, we have also developed prototype tools to visualize the
output of scRNA-seq analyses on genome browsers to compare gene expression
patterns across tissues and cell populations. This JBrowse tool now
features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk
RNA-seq experiments. We intend to further build upon these existing tools
to construct a scientist-friendly data resource and analytical ecosystem
based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC
principles to facilitate SC-level genomic analysis through data ingestion,
storage, retrieval, re-use, visualization, and comparative annotation
across agricultural species.