A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane

The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for gen...

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Main Authors: Md. Sariful Islam, Keo Corak, Per McCord, Amanda M. Hulse-Kemp, Alexander E. Lipka
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Plant Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2023.1205999/full
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author Md. Sariful Islam
Keo Corak
Per McCord
Per McCord
Amanda M. Hulse-Kemp
Amanda M. Hulse-Kemp
Alexander E. Lipka
author_facet Md. Sariful Islam
Keo Corak
Per McCord
Per McCord
Amanda M. Hulse-Kemp
Amanda M. Hulse-Kemp
Alexander E. Lipka
author_sort Md. Sariful Islam
collection DOAJ
description The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.
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spelling doaj.art-5c8a6e23cef4467585e3708c8a82c1e82023-08-02T09:12:39ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-08-011410.3389/fpls.2023.12059991205999A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcaneMd. Sariful Islam0Keo Corak1Per McCord2Per McCord3Amanda M. Hulse-Kemp4Amanda M. Hulse-Kemp5Alexander E. Lipka6Sugarcane Field Station, USDA-ARS, Canal Point, FL, United StatesGenomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United StatesSugarcane Field Station, USDA-ARS, Canal Point, FL, United StatesIrrigated Agriculture Research and Extension Center, Washington State University, Prosser, WA, United StatesGenomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United StatesDepartment of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, United StatesDepartment of Crop Sciences, University of Illinois, Urbana-Champaign, IL, United StatesThe sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.https://www.frontiersin.org/articles/10.3389/fpls.2023.1205999/fullcandidate geneGWASgenomic selectionmarker trait associationsugarcane production
spellingShingle Md. Sariful Islam
Keo Corak
Per McCord
Per McCord
Amanda M. Hulse-Kemp
Amanda M. Hulse-Kemp
Alexander E. Lipka
A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
Frontiers in Plant Science
candidate gene
GWAS
genomic selection
marker trait association
sugarcane production
title A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
title_full A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
title_fullStr A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
title_full_unstemmed A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
title_short A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
title_sort first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane
topic candidate gene
GWAS
genomic selection
marker trait association
sugarcane production
url https://www.frontiersin.org/articles/10.3389/fpls.2023.1205999/full
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