| Full text | |
| Author(s): Show less - |
Gonzaga Pimenta, Ricardo Jose
[1]
;
Aono, Alexandre Hild
[1]
;
Villavicencio Burbano, Roberto Carlos
[2]
;
Coutinho, Alisson Esdras
[3]
;
da Silva, Carla Cristina
[1]
;
Antonio dos Anjos, Ivan
[4]
;
Perecin, Dilermando
[3]
;
de Andrade Landell, Marcos Guimaraes
[4]
;
Goncalves, Marcos Cesar
[5]
;
Pinto, Luciana Rossini
[4]
;
de Souza, Anete Pereira
[6, 1]
Total Authors: 11
|
| Affiliation: | [1] Univ Campinas UNICAMP, Ctr Mol Biol & Genet Engn CBMEG, Campinas, SP - Brazil
[2] Littoral Polytech Super Sch ESPOL, Gustavo Galindo Velasco Campus, Guayaquil - Ecuador
[3] Sao Paulo State Univ Unesp, Jaboticabal, SP - Brazil
[4] Agron Inst Campinas IAC APTA, Adv Ctr Technol Res Sugarcane Agribusiness, Ribeirao Preto, SP - Brazil
[5] Biol Inst IB APTA, Plant Protect Res Ctr, Sao Paulo, SP - Brazil
[6] Univ Campinas UNICAMP, Inst Biol, Dept Plant Biol, Campinas, SP - Brazil
Total Affiliations: 6
|
| Document type: | Journal article |
| Source: | SCIENTIFIC REPORTS; v. 11, n. 1 AUG 3 2021. |
| Web of Science Citations: | 1 |
| 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. (AU) | |
| FAPESP's process: | 19/03232-6 - Genome wide selection in sugarcane using machine learning and complex networks for economically important traits |
| Grantee: | Alexandre Hild Aono |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |
| FAPESP's process: | 15/24346-9 - Allelic variation analysis in genes of economic importance among hom(oe)ologous regions of sugarcane (Saccharum spp.) genome |
| Grantee: | Carla Cristina da Silva |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/18588-8 - Association mapping in sugarcane targeting tolerance to yellow leaf virus |
| Grantee: | Ricardo José Gonzaga Pimenta |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 19/21682-9 - Associative mapping and transcriptomic in the investigation of sugarcane yellow leaf virus resistance |
| Grantee: | Ricardo José Gonzaga Pimenta |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |