Abstract
Alfalfa (Medicago sativa L.) is a globally vital forage crop valued for its perennial growth and multiple annual harvests. A breeding effort is underway to improve the crop for productivity and persistence against biotic and abiotic stresses using “creeping rootedness,” a trait where plants exhibit horizontal root growth, similar to rhizomes, with increased vegetative ground surface area. In this study, we genotyped a breeding population of 648 alfalfa lines segregating for creeping rootedness using the 3K DArTag marker panel to identify trait-associated genomic loci and evaluate the feasibility of genomic prediction to accelerate breeding cycles. Using genome-wide association studies (GWAS), we identified three quantitative trait loci (QTLs), with one major QTL located on chromosome 6.1 associated with this trait. Genomic prediction showed moderate predictive ability (r = 0.68) for creeping rootedness. A significant advancement in this study was the development and utilization of the Breeding Insight Genomics Application (BIGapp), an R Shiny application designed to streamline the processing of genomic data through an intuitive interface. This tool makes integrating genomics into existing breeding programs accessible, regardless of species ploidy or the researcher's coding proficiency. The identified QTL will be essential in future efforts to develop new alfalfa cultivars with the creeping rootedness trait and accelerate the breeding cycle, with BIGapp playing a pivotal role in these advancements.
| Original language | English |
|---|---|
| Article number | e70067 |
| Journal | Plant Genome |
| Volume | 18 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s). The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.
Funding
We thank Alexandra Casa for reviewing the phenotypic data, Kristen Lind for assisting with the development of the BIGapp training materials, and our colleagues at Breeding Insight for their review and suggestions for the BIGapp. We thank DArT for genotyping the alfalfa accessions. These materials are based upon efforts from Breeding Insight (RID: SCR_026645), a USDA-ARS initiative hosted by Cornell University. The work is supported by the US Department of Agriculture under agreement numbers (8062-21000-043-004-A, 8062-21000-052-002-A, and 8062-21000-052-003-A). Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Agriculture. In addition, any reference to specific brands or types of products or services does not constitute or imply an endorsement by the US Department of Agriculture for those products or services. We thank Alexandra Casa for reviewing the phenotypic data, Kristen Lind for assisting with the development of the BIGapp training materials, and our colleagues at Breeding Insight for their review and suggestions for the BIGapp. We thank DArT for genotyping the alfalfa accessions. These materials are based upon efforts from Breeding Insight (RID: SCR_026645), a USDA‐ARS initiative hosted by Cornell University. The work is supported by the US Department of Agriculture under agreement numbers ( 8062‐21000‐043‐004‐A , 8062‐21000‐052‐002‐A , and 8062‐21000‐052‐003‐A ). Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Agriculture. In addition, any reference to specific brands or types of products or services does not constitute or imply an endorsement by the US Department of Agriculture for those products or services.
| Funders | Funder number |
|---|---|
| USDA-Agricultural Research Service | |
| U.S. Department of Agriculture | 8062‐21000‐043‐004‐A, 8062‐21000‐052‐003‐A |
ASJC Scopus subject areas
- Genetics
- Agronomy and Crop Science
- Plant Science