Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane (Saccharum spp.)

Abstract

Sugarcane (Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome-wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield. Abbreviations: DAPC, discriminant analysis of principal components; GWAS, genome-wide association study; indels, insertions and deletions; NGS, next-generation sequencing; NROH, total number of ROHs; ROH, run of homozygosity; SROH, sum total length of ROHs; SNP, single nucleotide polymorphisms; TES, target enrichment sequencing; WCSRG, world collection of sugarcane and related grasses. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Global transcriptome changes of elongating internode of sugarcane in response to mepiquat chloride

“…Notably, the most abundant GO term regarding the biological process of GT42 isoforms, included metabolic process and cellular process. Thus, this functional isoform showed similar assignment of function to previous results from sugarcane [46][47][48]. Based on these data, GT42 had a functional constitution similar to that of other sugarcane varieties.…”

Global Transcriptome Changes of Elongating Internode of Sugarcane in Response to Mepiquat Chloride

“…The most abundant biological process GO term of GT42 isoforms contained metabolic process and cellular process. Thus, this functional isoform showed similar function assignment with previous results from sugarcane [46][47][48]. Based on these data, the GT42 had similar functional constitution of genes with other sugarcane varieties.…”

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance

“…In contrast with the differences arisen from the type of marker used, we observed little divergence between the results of the methods used for each marker dataset; the separation of genotypes into groups was overall similar, with consistent correspondences between groups identified in each analysis. Additionally, eventual discrepancies between methods did not result in significant differences in the inflation of the models used for both FarmCPU and codominant mixed modeling analyses; the inflation patterns observed in Q-Q plots were similar to those of previous studies applying similar genotyping and marker-trait association methodologies (Barreto et al, 2019; Yang et al, 2019a, 2019b, 2020). For both association mapping strategies, we opted to perform ensuing association analyses using the covariates that resulted in the value of λ closest to 1.…”

“…We evaluated the impact of using genomic references from various backgrounds in variant calling. In previous sugarcane GWASs, variant calling was performed using the genome of S. bicolor (Fickett et al, 2019; Yang et al, 2019a, 2019b, 2020), and until recently, this was sugarcane’s closest relative with a well- assembled and annotated genome; however, in our analyses, this reference yielded a number of markers considerably inferior to other references, which discouraged its use. The reference that yielded the largest number of markers was the methyl-filtered genome of the SP70-1143 cultivar, in agreement with the results of a previous study employing GBS (Balsalobre et al, 2017).…”

“…We evaluated the impact of using genomic references from various backgrounds in variant calling from GBS. In previous sugarcane GWASs, this was performed using the genome of S. bicolor 30,[42][43][44] , a close relative species with a well-assembled and annotated genome; however, in our analyses, this reference yielded a number of markers considerably inferior to other references. The methyl-filtered genome of the SP70-1143 cultivar yielded the most markers, in agreement with a previous study employing GBS 45 ; this is a plausible outcome, as this method avoids sampling of methylated regions 46 which were also filtered out for this genomic assembly 47 .…”