A genome-wide association study and genomic prediction for yield-related traits in a self-progeny mapping population of LCP 85-384 sugarcane.

Authors: Pan, Yong-Bao; XIONG, HAIZHENG - University Of Arkansas; PHIRI, THERESA MAKAWA - University Of Arkansas; SONG, JINJIN - University Of Illinois; MING, RAY - University Of Illinois; SHI, AINONG - University Of Arkansas

Submitted to: International Society of Sugar Cane Technologists Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 4/22/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Sugarcane varieties (Saccharum spp. hybrids) are interspecific polyploid and aneuploid hybrids with 110-130 chromosomes. A conventional breeding cycle takes 12 years and is extremely laborious due to visual selection and multi-year and multi-location evaluations of yield-related traits and biotic/abiotic stress responses. To develop trait-specific DNA markers for marker-assisted selection, we have conducted genome-wide association (GWAS) and genomic prediction (GP) studies using a validated self-progeny mapping population of the cultivar LCP 85-384. Phenotyping data [plant height, stalk number, stalk weight, stalk diameter, fiber content, total sugar (Brix), polarization associated with sucrose (Pol), theoretical recoverable sugar (TRS), and purity] were collected from replicated plant-cane and first-ratoon crops of the self-progenies. Genotyping was performed using amplified fragment length polymorphism (AFLP), simple sequence repeats (SSR), target region amplification polymorphism (TRAP), and restriction site-associated DNA sequencing (RADseq)-based single nucleotide polymorphism (SNP). The GWAS was conducted via a spectrum of statistical methodologies, including mixed linear model (MLM), generalized linear model (GLM), and single marker regression (SMR) algorithms of TASSEL 5 and FarmCPU of GAPIT 3. Notably, the exhaustive analyses culminated in the identification of 77 significant markers, including 11 markers associated with stalk number, 9 with stalk weight, 21 with stalk diameter, 5 with plant height, 13 with fiber content, 9 with sucrose content, 1 with Brix, 4 with Pol, and 4 with TRS. To assess the predictive power of these markers, GP was conducted using ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL) models. The predictive accuracies ranged from 0.36 to 0.54 for plant height and stalk traits, 0.55 to 0.58 for fiber content, and 0.54 to 0.57 for sucrose content. The integrated approach combining GWAS and GP represents a valuable tool for enhancing sugarcane breeding and significant advancements in sugarcane improvement efforts.

Technical Abstract: Sugarcane varieties (Saccharum spp. hybrids) are interspecific polyploid and aneuploid hybrids with 110-130 chromosomes. A conventional breeding cycle takes 12 years and is extremely laborious due to visual selection and multi-year and multi-location evaluations of yield-related traits and biotic/abiotic stress responses. To develop trait-specific DNA markers for marker-assisted selection, we have conducted genome-wide association (GWAS) and genomic prediction (GP) studies using a validated self-progeny mapping population of the cultivar LCP 85-384. Phenotyping data [plant height, stalk number, stalk weight, stalk diameter, fiber content, total sugar (Brix), polarization associated with sucrose (Pol), theoretical recoverable sugar (TRS), and purity] were collected from replicated plant-cane and first-ratoon crops of the self-progenies. Genotyping was performed using amplified fragment length polymorphism (AFLP), simple sequence repeats (SSR), target region amplification polymorphism (TRAP), and restriction site-associated DNA sequencing (RADseq)-based single nucleotide polymorphism (SNP). The GWAS was conducted via a spectrum of statistical methodologies, including mixed linear model (MLM), generalized linear model (GLM), and single marker regression (SMR) algorithms of TASSEL 5 and FarmCPU of GAPIT 3. Notably, the exhaustive analyses culminated in the identification of 77 significant markers, including 11 markers associated with stalk number, 9 with stalk weight, 21 with stalk diameter, 5 with plant height, 13 with fiber content, 9 with sucrose content, 1 with Brix, 4 with Pol, and 4 with TRS. To assess the predictive power of these markers, GP was conducted using ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL) models. The predictive accuracies ranged from 0.36 to 0.54 for plant height and stalk traits, 0.55 to 0.58 for fiber content, and 0.54 to 0.57 for sucrose content. The integrated approach combining GWAS and GP represents a valuable tool for enhancing sugarcane breeding and significant advancements in sugarcane improvement efforts.