Rex T. Nelson

Dr. Rex T. Nelson

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 December 2020 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
ABAnne V Brown
Anne V Brown
SCShawn I Conners
Shawn I Conners
WHWei Huang
Wei Huang
AWAndrew P Wilkey
Andrew P Wilkey
DGDavid Grant
David Grant
RNRex T. Nelson
Rex T. Nelson
SoyBase, a USDA genetic and genomics database, holds professionally curated soybean genetic and genomic data, which is integrated and made accessible to researchers and breeders. The site holds several reference genome assemblies, as well as genetic maps, thousands of mapped traits, expression and epigenetic data, pedigree information, and extensive variant and genotyping data sets. SoyBase displays include genetic, genomic, and epigenetic maps of the soybean genome. Gene expression data is presented in the genome viewer as heat maps and pictorial and tabular displays in gene report pages. Millions of sequence variants have been added, representing variations across various collections of cultivars. This variant data is explorable using new interactive tools to visualize the distribution of those variants across the genome, between selected accessions. SoyBase holds several reference-quality soybean genome assemblies, accessible via various query tools and browsers, including a new visualization system for exploring the soybean pan-genome. SoyBase also serves as a nexus of announcements pertinent to the greater soybean research community. The database also includes a soybean-specific anatomic and biochemical trait ontology. The database can be accessed at https://soybase.org.

27 December 2018 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
ABAnne V Brown
Anne V Brown
JCJacqueline D Campbell
Jacqueline D Campbell
TATeshale Assefa
Teshale Assefa
DGDavid Grant
David Grant
RNRex T. Nelson
Rex T. Nelson
SCSteven B Cannon
Steven B Cannon
As sequencing prices drop, genomic data accumulates—seemingly at a steadily increasing pace. Most genomic data potentially have value beyond the initial purpose—but only if shared with the scientific community. This, of course, is often easier said than done. Some of the challenges in sharing genomic data include data volume (raw file sizes and number of files), complexities, formats, nomenclatures, metadata descriptions, and the choice of a repository. In this paper, we describe 10 quick tips for sharing open genomic data.

21 November 2024 in The Plant Genome
Verified
Journal Article
Open access
RSRobert M. Stupar
Robert M. Stupar
ALAnna Locke
Anna Locke
DADoug K. Allen
Doug K. Allen
MSMinviluz G. Stacey
Minviluz G. Stacey
JMJianxin Ma
Jianxin Ma
JOJamie O'Rourke
Jamie O'Rourke
This strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [ Glycine max (L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024–2028). This work is the result of deliberations among over 50 soybean researchers during a 2‐day workshop in St Louis, MO, USA, at the end of 2022. The plan is divided into seven traditional areas/disciplines: Breeding, Biotic Interactions, Physiology and Abiotic Stress, Functional Genomics, Biotechnology, Genomic Resources and Datasets, and Computational Resources. One additional section was added, Training the Next Generation of Soybean Researchers, when it was identified as a pressing issue during the workshop. This installment of the soybean genomics strategic plan provides a snapshot of recent progress while looking at future goals that will improve resources and enable innovation among the community of basic and applied soybean researchers. We hope that this work will inform our community and increase support for soybean research.

18 November 2021 in Plants
Verified
Journal Article
Open access
PDF file
ABAnne V Brown
Anne V Brown
DGDavid Grant
David Grant
RNRex T. Nelson
Rex T. Nelson
Seeds, especially those of certain grasses and legumes, provide the majority of the protein and carbohydrates for much of the world’s population. Therefore, improvements in seed quality and yield are important drivers for the development of new crop varieties to feed a growing population. Quantitative Trait Loci (QTL) have been identified for many biologically interesting and agronomically important traits, including many seed quality traits. QTL can help explain the genetic architecture of the traits and can also be used to incorporate traits into new crop cultivars during breeding. Despite the important contributions that QTL have made to basic studies and plant breeding, knowing the exact gene(s) conditioning each QTL would greatly improve our ability to study the underlying genetics, biochemistry and regulatory networks. The data sets needed for identifying these genes are increasingly available and often housed in species- or clade-specific genetics and genomics databases. In this demonstration, we present a generalized walkthrough of how such databases can be used in these studies using SoyBase, the USDA soybean Genetics and Genomics Database, as an example.

23 January 2026 in Genetics
Verified
Journal Article
Closed access
JCJacqueline D Campbell
Jacqueline D Campbell
CCConnor T Cameron
Connor T Cameron
ACAlan Cleary
Alan Cleary
SDSudhansu Dash
Sudhansu Dash
ELEvan Lavelle
Evan Lavelle
RNRex T. Nelson
Rex T. Nelson
Here, we describe a collection of genomic database portals, SoyBase (https://soybase.org), Legume Information System (https://legumeinfo.org), and PeanutBase (https://peanutbase.org), that support breeding and research work in the legume plant family. The legume family includes important crops such as soybean, peanut, common bean, lentils, chickpeas, as well as approximately 20,000 other species that are important in all terrestrial ecosystems. Beyond the value of the portals for species in this large clade (as well as for plant biology more generally), the database and site architecture of these portals will be of interest to developers of similar genomic sites, as the data management and software solutions are generic and should be applicable to a wide variety of organisms. The architecture for these sites has been designed for rapid, modular, flexible development well suited to genomic data and to rapid incorporation of new data. Website content is handled with a static site generator (Jekyll). Interactive applications are developed using javascript encapsulated as Web Components that access back-end data via APIs for stability and flexibility. This architecture allows for both code portability and for customization to serve the unique needs of each research community.