Biology subjects

da Silva, M. F.

Publications and source records attributed to da Silva, M. F..

3 recordsLinked to original sources

bioRxiv2022

Multiomic investigation of sugarcane mosaic virus resistance in sugarcane

Sugarcane mosaic virus (SCMV) is the main etiological agent of sugarcane mosaic disease, which affects sugarcane, maize and other economically important grass species. Despite the extensive characterization of quantitative trait loci controlling resistance to SCMV in maize, the genetic basis of this trait is largely unexplored in sugarcane. Here, a genome-wide association study was performed and machine learning coupled to feature selection was used for the genomic prediction of resistance to SCMV in a diverse panel of sugarcane accessions. This ultimately led to the identification of nine single nucleotide polymorphisms (SNPs) explaining up to 29.9% of the phenotypic variance and a 73-SNP set that predicted resistance with high accuracy, precision, recall, and F1 scores. Both marker sets were validated in additional sugarcane genotypes, in which the SNPs explained up to 23.6% of the phenotypic variation and predicted resistance with a maximum accuracy of 69.1%. Synteny analyses showed that the gene responsible for the major SCMV resistance in maize is probably absent in sugarcane, explaining why such a major resistance source is thus far unknown in this crop. Lastly, using sugarcane RNA sequencing data, markers associated with the resistance to SCMV in sugarcane were annotated and a gene coexpression network was constructed to identify the predicted biological processes involved in SCMV resistance. This allowed the identification of candidate resistance genes and confirmed the involvement of stress responses, photosynthesis and regulation of transcription and translation in the resistance to this virus. These results provide a viable marker-assisted breeding approach for sugarcane and identify target genes for future molecular studies on resistance to SCMV.

plant biology↗

bioRxiv2022

Differential adaptive potential and vulnerability to climate-driven habitat loss in Brazilian mangroves

Geographic and environmental differences have been identified as factors influencing Brazilian mangrove trees genetic diversity. Geographically, distinct species have convergent spatial genetic structures, indicating a limited gene flow between northern and southern populations. Environmentally, genomic studies and common garden experiments have found evidence of local adaptations along the latitudinal gradient of the Brazilian coast. However, little is known about how such adaptive heterogeneity could be affected by a rapidly changing climate in the coming decades, and the combination of deforestation and climate-induced habitat loss may affect these forests and their genetic diversity. Here, we applied two genomic-environmental association methods to model the turnover of potentially adaptive alleles for two dominant mangrove trees: Avicennia germinans and A. schaueriana. We analyzed a total of 134 individuals from six populations of A. germinans and ten populations of A. schaueriana spanning the Brazilian coast from 1 {degrees}S to 28 {degrees}S. Gradient forest models identified temperature-related variables as the most important predictors for A. germinans outlier loci, whereas both temperature and precipitation were important for A. schaueriana. We modeled allele frequencies and projected them for future climatic scenarios to estimate adaptively driven vulnerability. We assessed climate-driven habitat loss through climate-only distribution models and calculated annual deforestation rates for each sampled region. Finally, to assess the vulnerability of individual populations, we combined the environmental suitability, deforestation data, and adaptive vulnerability projections. For both species, subtropical populations presented a higher vulnerability than equatorial populations to climate-driven habitat loss. We also identified deforestation rates at the sampled sites that were alarmingly higher than the global average mangrove deforestation rate. Our results provide improved estimates of the impacts of ongoing climate change and human-caused habitat loss on the distribution of mangroves and highlight the importance of site-based conservation strategies that consider individual subtropical and equatorial mangrove forests.

evolutionary biology↗

bioRxiv2020

The Lanata trichome mutation increases stomatal conductance and reduces leaf temperature in tomato

Background and aimsTrichomes are epidermal structures with an enormous variety of ecological functions and economic applications. Glandular trichomes produce a rich repertoire of secondary metabolites, whereas non-glandular trichomes create a physical barrier against biotic and abiotic stressors. Intense research is underway to understand trichome development and function and enable breeding of more resilient crops. However, little is known on how enhanced trichome density would impinge on leaf photosynthesis, gas exchange and energy balance. MethodsPrevious work has compared multiple species differing in trichome density, instead here we analyzed monogenic trichome mutants in a single tomato genetic background (cv. Micro-Tom). We determined growth parameters, leaf spectral properties, gas exchange and leaf temperature in the hairs absent (h), Lanata (Ln) and Woolly (Wo) trichome mutants. Key resultsShoot dry mass, leaf area, leaf spectral properties and cuticular conductance were not affected by the mutations. However, the Ln mutant showed increased carbon assimilation (A) possibly associated with higher stomatal conductance (gs), since there were no differences in stomatal density or stomatal index between genotypes. Leaf temperature was furthermore reduced in Ln in the early hours of the afternoon. ConclusionsWe show that a single monogenic mutation can increase glandular trichome density, a desirable trait for crop breeding, whilst concomitantly improving leaf gas exchange and reducing leaf temperature. HIGHLIGHTA monogenic mutation in tomato increases trichome density and optimizes gas exchange and leaf temperature

plant biology↗