Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
(N/A)
Non Technical Summary
Improving fiber quality is essential if cotton wants to continue to remain competitive against man-made fibers. In particular, yarn quality needs to be improved to take advantageof recent innovations with vortex spinning technology. Our current system of quantifying and applying a monetary value to cotton fiber quality in the marketplace uses HVI measurements, which fails to capture many important fiber characteristics that affect yarn quality. AFIS measurements can evaluate a wider range of fiber characteristics and is superior at predicting spinning performance. Unfortunately, AFIS is a much slower and more expensive method of fiber analysis compared to HVI and prohibitive for wide-spread use in cotton breeding programs, therefore effective SNP markers could reduce the cost and improve the efficacy of selecting lines with improved fiber quality. It is the goal of this project to identify QTL markers associated with AFIS fiber measurements with the 63 K SNP Array in two segregating populations, one with high quality fiber and another with low quality fiber. Fiber traits qualitywill be measured from multiple generations of the population in moderate to low stress environments. This will allow us determine a large amount of GxE effects that often confound the use of QTL markers associated with fiber traits. We hope to identify early generation field conditions that would allow these types of QTL markers to be portable across populations and environments, which would in turn lead to faster and more precise improvements in fiber quality?.
Animal Health Component
60%
Research Effort Categories
Basic
10%
Applied
60%
Developmental
30%
Goals / Objectives
Determine optimal testing/selection environments for fiber quality: evaluate moderate and low stress growing conditions for cotton plants to identify how the changes in conditions can affect the decision-making process within a breeding program based on changes in fiber quality as well as the effectiveness of SNP based QTL markers in predicting the best genotypes for advancement.Find SNP markers for QTLs related to fiber length distribution, elongation, and fineness: by focusing on these particular traits, we will enhance genetic rates of gain for traits that directly impact yarn quality.Explore relationships between selection environment and genotypes in regard to fiber quality: by testing two complete cohort populations over multiple years, locations, production systems, we will be able elucidate important interactions that affect our ability to predict fiber quality in breeding populations and environments.
Project Methods
The initiation of the project will need to commence with single plant selections in the fall of 2023from two targeted populations. We will also recruit a PhD graduate student for the project. This will allow us to have the student enrolled in graduate school by June2023. In 2024, we will conduct a replicated trial with two replications to collect DNA and fiber samples. We also will use this trial as a seed increase. In 2025, we will grow all the same lines in replicated trials with low stress and moderate stress at College Station. This will allow us to evaluate the efficacy of the SNP markers and the reliability of the 2024 fiber phenotypes in predicting breeding line performances in 2025. In 2026, the same field activities as practiced in 2026 will occur, but we will add an additional location at the Texas A&M Research and Extension Center at Weslaco, where we routinely conduct field trials and seed increases. By testing at Weslaco, this will allow us to determine how many years and testing environments are needed to obtain enough phenotype data that matches with genotype data to the degree that we could create a portable fiber prediction system across locations and pedigrees. In addition, there will be preliminary analysis and reporting of results. The project will conclude, and findings disseminated in 2026.Dr. Lori Hinze, USDA-ARS, College Station, TX, has agreed to provide facilities and consultation to the graduate student who will be responsible for genotyping the breeding lines.Genomic DNA will be extracted from young leaves of single plants representing a selection of 200 G. hirsutum genotypes following the protocol described in Hulse-Kemp et al. (2015). DNA from young leaves will be extracted using NucleoSpin Plant II kits (MACHEREY-NAGEL, USA), quantified using PicoGreen, and normalized to 50 ng/μL prior to genotyping. Standardized DNA at 50ng/ul will be processed according to Illumina manufacture protocols and hybridized to the CottonSNP63K array. Single-base extension was performed, and the chips were then read using the Illumina iScan. Image files were saved for cluster file analysis. All image files were uploaded into a single project containing all individual samples. Data for the 63,058 markers were clustered using the GenomeStudio Genotyping Module (V 1.9.4, Illumina, Inc.) then all markers were viewed and manually curated, taking into account the sample type and known segregation ratios, to obtain the best cluster file for genotyping tetraploid cotton available at: (http://www.cottongen.org/node/add/cotton-cluster-file-request).