ArticleScientific reports2021
Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Multiomic insights into sucrose accumulation in sugarcane.Plant molecular biology · 2025Article
- Sugarcane yellow leaf virus impairs the transcriptomic defense response of sugarcane to its new aphid vector Melanaphis sorghi.BMC plant biology · 2025Article
- Yellow Leaf Disease Resistance andPlants (Basel, Switzerland) · 2023Article
- Prospecting true ScYLV resistance in3 Biotech · 2023Article
- A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane.Frontiers in plant science · 2023Article
- Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits inFrontiers in plant science · 2023Article
- A divide-and-conquer approach for genomic prediction in rubber tree using machine learning.Scientific reports · 2022Article
- Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study.Molecular genetics and genomics : MGG · 2022Article
- Sugarcane multitrophic interactions: Integrating belowground and aboveground organisms.Genetics and molecular biology · 2022Article
- Combining genomic selection with genome-wide association analysis identified a large-effect QTL and improved selection for red rot resistance in sugarcane.Frontiers in plant science · 2022Article
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Authors and funding
11 authors.
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Abstract
Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.
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