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Grape breeding programs are mostly focused on developing new varieties with high production volume, sugar contents, and phenolic compound diversity combined with resistance and tolerance to the main pathogens under culture and adverse environmental conditions. The 'Niagara' variety (Vitis labrusca × Vitis vinifera) is one of the most widely produced and commercialized table grapes in Brazil. In this work, we selected three Niagara somatic variants with contrasting berry phenotypes and performed morphological and transcriptomic analyses of their berries. Histological sections of the berries were also performed to understand anatomical and chemical composition differences of the berry skin between the genotypes. An RNA-Seq pipeline was implemented, followed by global coexpression network modeling. 'Niagara Steck', an intensified russet mutant with the most extreme phenotype, showed the largest difference in expression and showed selection of coexpressed network modules involved in the development of its russet-like characteristics. Enrichment analysis of differently expressed genes and hub network modules revealed differences in transcription regulation, auxin signaling and cell wall and plasmatic membrane biogenesis. Cutin- and suberin-related genes were also differently expressed, supporting the anatomical differences observed with microscopy.
Assuntos
Vitis , Vitis/metabolismo , Melhoramento Vegetal , Perfilação da Expressão Gênica , Frutas/metabolismo , BrasilRESUMO
The mountains in the Atlantic Forest domain are environments that harbor a high biodiversity, including species adapted to colder climates that were probably influenced by the climatic variations of the Pleistocene. To understand the phylogeographic pattern and assess the taxonomic boundaries between two sister montane species, a genomic study of the butterflies Actinote mantiqueira and A. alalia (Nymphalidae: Acraeini) was conducted. Analyses based on partial sequences of the mitochondrial gene COI (barcode region) failed to recover any phylogenetic or genetic structure discriminating the two species or sampling localities. However, single nucleotide polymorphisms gathered using Genotyping-by-Sequencing provided a strong isolation pattern in all analyses (genetic distance, phylogenetic hypothesis, clustering analyses, and F ST statistics) which is consistent with morphology, separating all individuals of A. alalia from all populations of A. mantiqueira. The three sampled mountain ranges where A. mantiqueira populations occur-Serra do Mar, Serra da Mantiqueira, and Poços de Caldas Plateau-were identified as three isolated clusters. Paleoclimate simulations indicate that both species' distributions changed according to climatic oscillations in the Pleistocene period, with the two species potentially occurring in areas of lower altitude during glacial periods when compared to the interglacial periods (as the present). Besides, a potential path between their distribution through the Serra do Mar Mountain range was inferred. Therefore, the Pleistocene climatic fluctuation had a significant impact on the speciation process between A. alalia and A. mantiqueira, which was brought on by isolation at different mountain summits during interglacial periods, as shown by the modeled historical distribution and the observed genetic structure.
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Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.
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A wide array of molecular markers has been used to investigate the genetic diversity among common bean species. However, the best combination of markers for studying such diversity among common bean cultivars has yet to be determined. Few reports have examined the genetic diversity of the carioca bean, commercially one of the most important common beans in Brazil. In this study, we examined the usefulness of two molecular marker systems (simple sequence repeats - SSRs and amplified fragment length polymorphisms - AFLPs) for assessing the genetic diversity of carioca beans. The amount of information provided by Roger's modified genetic distance was used to analyze SSR data and Jaccards similarity coefficient was used for AFLP data. Seventy SSRs were polymorphic and 20 AFLP primer combinations produced 635 polymorphic bands. Molecular analysis showed that carioca genotypes were quite diverse. AFLPs revealed greater genetic differentiation and variation within the carioca genotypes (Gst = 98 percent and Fst = 0.83, respectively) than SSRs and provided better resolution for clustering the carioca genotypes. SSRs and AFLPs were both suitable for assessing the genetic diversity of Brazilian carioca genotypes since the number of markers used in each system provided a low coefficient of variation. However, fingerprint profiles were generated faster with AFLPs, making them a better choice for assessing genetic diversity in the carioca germplasm.
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The Araucaria angustifolia (Bert.) O. Kuntze, also named the "paraná pine" (pinheiro-do-Paraná in Portuguese), is a native conifer species naturally occurring in the Brazilian Tropical Atlantic Forest which in Brazil is mostly limited to the southern Brazilian states of Paraná, Santa Catarina and Rio Grande do Sul. Chloroplast DNA markers (cpDNA) are useful in populational genetic studies because of their low substitution rate and the uniparental transmission. The conservation of cpDNA genes between species has allowed the design of consensus chloroplast primers that have had a great impact on population genetics and phylogenetic studies. In this study we used the polymerase chain reaction technique combined with restriction enzyme fragment length polymorphism (PCR-RFLP) to characterize the genetic diversity of the chloroplast genome in nine natural A. angustifolia populations. Among the 141 trees surveyed we found 12 different cpDNA haplotypes and demonstrated that A. angustifolia has high levels of total diversity (hT = 0.612) and an average within-population diversity (hS) of 0.441, suggesting the presence of high within-population variation. The estimated genetic divergence could be helpful in designing breeding programs and species conservation strategies, although additional studies with a larger number of populations and trees is essential for a better understanding of gene flow and the inheritance of major Araucaria angustifolia traits.
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A microsatellite marker (SSR) was chosen to simulate a target allele and three criteria (02, 04 and 06 markers per chromosome) were tested to evaluate the most efficient parameters for performing marker-assisted backcross (MAB) selection. We used 53 polymorphic SSRs to genotype 186 BC1 maize (Zea mays L.) plants produced by crossing the inbred maize lines L-08-05 (donor parent) and L-14-4B (recurrent parent). The second backcross (BC2) generation was produced with 180 plants and screened with markers which were not recovered from the first backcross (BC1) generation. A total of 480 plants were evaluated in the third backcross (BC3) generation from which 48 plants were selected for parental genotype recovery. Recurrent genotype recovery averages in three backcross generations were compatible with those expected in BC4 or BC5, indicating genetic gain due to the marker-assisted backcrossing. The target marker (polymorphic microsatellite PHI037) was efficiently transferred. Six markers per chromosome showed a high level of precision for parental estimates at different levels of maize genome saturation and donor alleles were not present in the selected recovered pure lines. Phenotypically, the plants chosen based on this criterion (06 markers per chromosome) were closer to the recurrent parent than any other selected by other criteria (02 or 04 markers per chromosome). This approach allowed the understanding that six microsatellites per chromosome is a more efficient parameter than 02 and 04 markers per chromosome for deriving a marker-assisted backcross (MAB) experiment in three backcross generations
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Repetições de Microssatélites , Zea mays/genética , Cruzamentos Genéticos , Marcadores Genéticos , EndogamiaRESUMO
A modified reciprocal recurrent selection (RRS) method, which employed one cycle of high-intensity selection, was applied to two tropical maize (Zea mays L.) populations, BR-105 and BR-106, originating the improved synthetics IG-3 and IG-4, respectively. In the present study the effects of this kind of selection on the genetic structure of these populations and their synthetics were investigated at 30 microsatellite (SSR) loci. A total of 125 alleles were revealed. A reduction in the number of alleles was observed after selection, as well as changes in allele frequencies. In nearly 13 percent (BR-105) and 7 percent (BR-106) of the loci evaluated, the changes in allele frequencies were not explained, exclusively due to the effects of genetic drift. The effective population sizes estimated for the synthetics using 30 SSR loci were similar to those theoretically expected after selection. The genetic differentiation (G ST) between the synthetics increased to 77 percent compared with the original populations. The estimated R ST values, a genetic differentiation measure proper for microsatellite data, were similar to those obtained for G ST. Despite the high level of selection applied, the total gene diversity found in the synthetics allows them to be used in a new RRS cycle
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Produção Agrícola , Variação Genética , Repetições de Microssatélites , Zea mays/genética , Frequência do Gene , Marcadores Genéticos , Genética PopulacionalRESUMO
The objective of this study was to evaluate whether different similarity coefficients used with dominant markers can influence the results of cluster analysis, using eighteen inbred lines of maize from two different populations, BR-105 and BR-106. These were analyzed by AFLP and RAPD markers and eight similarity coefficients were calculated: Jaccard, Sorensen-Dice, Anderberg, Ochiai, Simple-matching, Rogers and Tanimoto, Ochiai II and Russel and Rao. The similarity matrices obtained were compared by the Spearman correlation, cluster analysis with dendrograms (UPGMA, WPGMA, Single Linkage, Complete Linkage and Neighbour-Joining methods), the consensus fork index between all pairs of dendrograms, groups obtained through the Tocher optimization procedure and projection efficiency in a two-dimensional space. The results showed that for almost all methodologies and marker systems, the Jaccard, Sorensen-Dice, Anderberg and Ochiai coefficient showed close results, due to the fact that all of them exclude negative co-occurrences. Significant alterations in the results for the Simple Matching, Rogers and Tanimoto, and Ochiai II coefficients were not observed either, probably due to the fact that they all include negative co-occurrences. The Russel and Rao coefficient presented very different results from the others in almost all the cases studied and should not be used, because it excludes the negative co-occurrences in the numerator and includes them in the denominator of their expression. Due to the fact that the negative co-occurrences do not necessarily mean that the regions of the DNA are identical, the use of coefficients that do not include negative co-occurrences was suggested.