Detecting Sugarcane yellow leaf virus infection in asymptomatic leaves with hyperspectral remote sensing and associated leaf pigment changes

Abstract A new distribution map is provided for Sugarcane yellow leaf virus. Luteoviridae: Polerovirus. Hosts: sugarcane (Saccharum officinarum), barley (Hordeum vulgare), sorghum (Sorghum bicolor). Information is given on the geographical distribution in Asia (China, Fujian, Guangdong, Guangxi, Guizhou, Hainan, Jiangxi, Yunnan, India, Andhra Pradesh, Bihar, Haryana, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Punjab, Tamil Nadu, Uttar Pradesh, Uttarakhand, Indonesia, Malaysia, Philippines, Sri Lanka, Taiwan, Thailand), Africa (Egypt, Kenya, Mauritius, Reunion, South Africa, Tunisia), North America (USA, Florida, Hawaii, Louisiana, Texas), Central America & Caribbean (Barbados, Costa Rica, Cuba, Guadeloupe, Guatemala, Martinique, Nicaragua, Puerto Rico), South America (Argentina, Brazil, Colombia, Ecuador, Peru, Venezuela).

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

Scientific Reports ◽

10.1038/s41598-021-95116-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ricardo José Gonzaga Pimenta ◽

Alexandre Hild Aono ◽

Roberto Carlos Villavicencio Burbano ◽

Alisson Esdras Coutinho ◽

Carla Cristina da Silva ◽

...

Keyword(s):

Virus Resistance ◽

Machine Learning Algorithms ◽

Energy Crop ◽

Yellow Leaf ◽

Sugarcane Yellow Leaf Virus ◽

Association Analyses ◽

Sugarcane Breeding ◽

Genetic Base ◽

Genome Wide ◽

Leaf Virus

AbstractSugarcane 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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