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.

The breeding of sugarcane, a leading sugar and energy crop, is complicated by the extremely complex sugarcane genome, which burdens research in the area and delays the development of new cultivars. One of the main viral diseases that affect this crop is sugarcane yellow leaf (SCYL), which is caused by the sugarcane yellow leaf virus (SCYLV). The most common symptom of SCYL is the yellowing of leaf midribs and blades, but asymptomatic cases are frequent. Regardless of the manifestation of SCYL, infection by SCYLV can lead to substantial yield losses, making resistance to this virus highly relevant to sugarcane breeding. However, the genetic basis of this trait has not been widely explored or explained. In this context, genome-wide association studies (GWASs) have arisen as promising tools for the identification of molecular markers associated with SCYLV resistance that can be employed in marker-assisted selection. In the present work, we performed a GWAS on sugarcane using codominant markers and genotypes of interest for breeding. A panel of 97 sugarcane genotypes inoculated with SCYLV was analyzed for SCYL symptom severity, and viral titer was estimated by reverse transcription quantitative PCR (RT-qPCR). A genotyping-by-sequencing (GBS) library was constructed for 94 individuals of this population, enabling the identification of 38,710 SNPs and 32,178 indels with information on allele proportion (AP) and position on the Saccharum spontaneum genome. For association analyses, several combinations of population structure and kinship were tested to reduce model inflation, and diverse marker-trait association mixed models were employed. We identified 35 markers significantly associated with SCYL symptom severity and 22 markers strongly associated with SCYLV titer that can be applied in breeding programs upon validation. By aligning the sequences flanking these markers with their coding sequences in several plant species, we annotated the functions of 7 genes. The possible involvement of these candidates in the response to SCYLV infection is discussed.

In this study, we investigated resistance traits to the sugarcane borer Diatraea saccharalis Fab. (Lepidoptera: Crambidae) in the leaves and stalks of six sugarcane cultivars in a series of greenhouse and laboratory assays. Investigation of plant factors and infestation rates to better discriminate stalk damage by the sugarcane borer indicated that infestation of 7-month-old, single plants with 20 larvae at the third or fourth instar per plant was suitable to assess tunneling length. Three cultivars (i.e. SP803280, RB928064, and RB835486) had lower stalk damage (i.e. tunnel length) than cultivar SP891115, which exhibited relatively greater susceptibility to tunneling by the borer. The time required for the larvae to enter the sugarcane stalk was longer for cultivar SP803280, indicating resistance traits on the stalk surface, which correlated with lower stalk damage. Larvae feeding on SP813250 stalks had the lowest weight gain, indicating that this cultivar has resistance traits to larval development within its stalks. Cultivars RB867515 and SP891115 resulted in the highest mortality of early-stage larvae feeding on leaves, indicating the presence of resistance factors in their leaves. Multi-trait cluster and principal component analyses placed the cultivars into three and four clusters, respectively. The cultivars placed in different groups that exhibited resistance to leaf feeding, stalk entrance, and tunneling by the sugarcane borer could be used for crossings in sugarcane breeding programs with the goal of obtaining higher levels of resistance to D. saccharalis.

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With the development of new cultivars, a precise genetic characterization is essential for improvement programs or for cultivar registration and protection. Molecular markers have been complementing the traditional morphological and agronomic characterization techniques because they are virtually unlimited, cover the whole genome and are not environmentally influenced. Genetic characterization constitutes the basis for studies involving estimates of genetic similarity. Therefore, the objective of the present study was to evaluate the genetic similarity between ten coriander genotypes (nine cultivars and one line) using ISSR markers. The cultivars used were: Americano, Asteca, Palmeira, Português, Santo, Supéria, Tabocas, Tapacurá, Verdão and the experimental line HTV-9299. The genetic similarity between the cultivars was estimated using 227 banded regions of ISSR molecular markers. The UBC 897 oligonucleotide generated the highest number of fragments (16), resulting in a higher polymorphism. The results indicate that the twenty-nine oligonucleotides chosen were satisfactory for detecting polymorphism. Based on the grouping analysis determined from the similarity data, there were two groups and two sub-groups. The calculated similarity for the genotypes varied from 52 to 75%. The lowest similarity was observed between Português and Verdão, at 52%. The highest similarity was found between Português and Palmeira, at 75%. The ISSR is efficient for identifying DNA polymorphism in coriander.

Genome-wide selection (GWS) uses simultaneously the effect of the thousands markers covering the entire genome to predict genomic breeding values for individuals under selection. The possible benefits of GWS are the reduction of the breeding cycle, increase in gains per unit of time, and decrease of costs. However, the success of the GWS is dependent on the choice of the method to predict the effects of markers. Thus, the objective of this work was to predict genomic breeding values (GEBV) through artificial neural networks (ANN), based on the estimation of the effect of the markers, compared to the Ridge Regression-Best Linear Unbiased Predictor/Genome Wide Selection (RR-BLUP/GWS). Simulations were performed by software R to provide correlations concerning ANN and RR-BLUP/GWS. The prediction methods were evaluated using correlations between phenotypic and genotypic values and predicted GEBV. The results showed the superiority of the ANN in predicting GEBV in simulations with higher and lower marker densities, with higher levels of linkage disequilibrium and heritability.

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