Global interest in sugarcane has increased significantly in recent years due to its economic impact on sustainable energy production. Sugarcane breeding and better agronomic practices have contributed to a huge increase in sugarcane yield in the last 30 years. Additional increases in sugarcane yield are expected to result from the use of biotechnology tools in the near future. Genetically modified (GM) sugarcane that incorporates genes to increase resistance to biotic and abiotic stresses could play a major role in achieving this goal. However, to bring GM sugarcane to the market, it is necessary to follow a regulatory process that will evaluate the environmental and health impacts of this crop. The regulatory review process is usually accomplished through a comparison of the biology and composition of the GM cultivar and a non-GM counterpart. This review intends to provide information on non-GM sugarcane biology, genetics, breeding, agronomic management, processing, products and byproducts, as well as the current technologies used to develop GM sugarcane, with the aim of assisting regulators in the decision-making process regarding the commercial release of GM sugarcane cultivars.

Accuracy in quantitative real-time polymerase chain reaction (qPCR) requires the use of stable endogenous controls. Normalization with multiple reference genes is the gold standard, but their identification is a laborious task, especially in species with limited sequence information. Coffee (Coffea ssp.) is an important agricultural commodity and, due to its economic relevance, is the subject of increasing research in genetics and biotechnology, in which gene expression analysis is one of the most important fields. Notwithstanding, relatively few works have focused on the analysis of gene expression in coffee. Moreover, most of these works have used less accurate techniques such as northern blot assays instead of more accurate techniques (e.g., qPCR) that have already been extensively used in other plant species. Aiming to boost the use of qPCR in studies of gene expression in coffee, we uncovered reference genes to be used in a number of different experimental conditions. Using two distinct algorithms implemented by geNorm and Norm Finder, we evaluated a total of eight candidate reference genes (psaB, PP2A, AP47, S24, GAPDH, rpl39, UBQ10, and UBI9) in four different experimental sets (control versus drought-stressed leaves, control versus droughtstressed roots, leaves of three different coffee cultivars, and four different coffee organs). The most suitable combination of reference genes was indicated in each experimental set for use as internal control for reliable qPCR data normalization. This study also provides useful guidelines for reference gene selection for researchers working with coffee plant samples under conditions other than those tested here.

Coffee is one of the most valuable agricultural commodities and ranks second on international trade exchanges. The genus Coffea belongs to the Rubiaceae family which includes other important plants. The genus contains about 100 species but commercial production is based only on two species, Coffea arabica and Coffea canephora that represent about 70 % and 30 % of the total coffee market, respectively. The Brazilian Coffee Genome Project was designed with the objective of making modern genomics resources available to the coffee scientific community, working on different aspects of the coffee production chain. We have single-pass sequenced a total of 214,964 randomly picked clones from 37 cDNA libraries of C. arabica, C. canephora and C. racemosa, representing specific stages of cells and plant development that after trimming resulted in 130,792, 12,381 and 10,566 sequences for each species, respectively. The ESTs clustered into 17,982 clusters and 32,155 singletons. Blast analysis of these sequences revealed that 22 % had no significant matches to sequences in the National Center for Biotechnology Information database (of known or unknown function). The generated coffee EST database resulted in the identification of close to 33,000 different unigenes. Annotated sequencing results have been stored in an online database at http: //www.lge.ibi.unicamp.br/cafe. Resources developed in this project provide genetic and genomic tools that may hold the key to the sustainability, competitiveness and future viability of the coffee industry in local and international markets. Key words: Coffea, cDNA, EST, transcriptome.Projeto Genoma Brasileiro Café: recursos genômicos baseados em ESTs: O café é um dos principais produtos agrícolas, sendo considerado o segundo item em importância do comércio internacional de "commodities". O gênero Coffea pertence à família Rubiaceae que também inclui outras plantas importantes. Este gênero contém aproximadamente 100 espécies, mas a produção comercial é baseada somente em duas espécies, Coffea arabica e Coffea canephora, que representam aproximadamente 70 % e 30 % do mercado total de café, respectivamente. O Projeto Genoma Café Brasileiro foi desenvolvido com o objetivo de disponibilizar os modernos recursos da genômica à comunidade científica e aos diferentes segmentos da cadeia produtiva do café. Para isso, foram seqüenciados 214.964 clones escolhidos aleatoriamente de 37 bibliotecas de cDNA de C. arabica, C. canephora e C. racemosa representando estádios específicos do desenvolvimento de células e de tecidos do cafeeiro, resultando em 130.792, 12.381 e 10.566 seqüências de cada espécie, respectivamente, após processo de trimagem. Os ESTs foram agrupados em 17.982 contigs e em 32.155 singletons. A comparação destas seqüências pelo programa BLAST revelou que 22 % não tiveram nenhuma similaridade significativa às seqüências no banco de dados do National Center for Biotechnology Information (de função conhecida ou desconhecida). A base de dados de ESTs do cafeeiro resultou na identificação de...

The present palette of opsin-based optogenetic tools lacks a light-gated potassium (K(+)) channel desirable for silencing of excitable cells. Here, we describe the construction of a blue-light-induced K(+) channel 1 (BLINK1) engineered by fusing the plant LOV2-Jα photosensory module to the small viral K(+) channel Kcv. BLINK1 exhibits biophysical features of Kcv, including K(+) selectivity and high single-channel conductance but reversibly photoactivates in blue light. Opening of BLINK1 channels hyperpolarizes the cell to the K(+) equilibrium potential. Ectopic expression of BLINK1 reversibly inhibits the escape response in light-exposed zebrafish larvae. BLINK1 therefore provides a single-component optogenetic tool that can establish prolonged, physiological hyperpolarization of cells at low light intensities.

Over the years, several studies have been performed to analyse plant–pathogen interactions. Recently, functional genomic strategies, including proteomics and transcriptomics, have contributed to the effort of defining gene and protein function and expression profiles. Using these ‘omic’ approaches, pathogenicity‐ and defence‐related genes and proteins expressed during phytopathogen infections have been identified and enormous datasets have been accumulated. However, the understanding of molecular plant–pathogen interactions is still an intriguing area of investigation. Proteomics has dramatically evolved in the pursuit of large‐scale functional assignment of candidate proteins and, by using this approach, several proteins expressed during phytopathogenic interactions have been identified. In this review, we highlight the proteins expressed during plant–virus, plant–bacterium, plant–fungus and plant–nematode interactions reported in proteomic studies, and discuss these findings considering the advantages and limitations of current proteomic tools.

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The Somatic embryogenesis receptor-like kinase (SERK) gene plays an important role in plant somatic and zygotic embryogenesis induction. The gene encodes an LRR-containing receptor-like kinase protein. Studies have been carried out focusing on different aspects of its function, but definitive conclusions on its role are far from being reached. SERK expression is generally detected in cells in which somatic or zygotic embryogenesis has been triggered. Transgenic lettuce lines were produced to silence the endogenous SERK gene using antisense RNA. The average number of seeds per flower in the R(1) and R(2) generations was similar for both transgenic and non-transgenic lines. However, a reduction in the number of viable grained seeds was observed in four studied transgenic lines. Endogenous SERK expression analysis revealed the absence of detectable LsSERK gene transcripts in three transgenic lines, which presented a reduction in their ability to form in vitro somatic embryonic structures. In addition, transgenic lines showed enhanced susceptibility to the pathogenic fungus Sclerotinia sclerotiorum, when compared to control plants. The results support the idea that SERK genes might not only be involved in plant growth and development, but probably also in a general mechanism of biotic and abiotic stress perception.

Metabolomics analysis of wild type Arabidopsis thaliana plants, under control and drought stress conditions revealed several metabolic pathways that are induced under water deficit. The metabolic response to drought stress is also associated with ABA dependent and independent pathways, allowing a better understanding of the molecular mechanisms in this model plant. Through combining an in silico approach and gene expression analysis by quantitative real-time PCR, the present work aims at identifying genes of soybean metabolic pathways potentially associated with water deficit. Digital expression patterns of Arabidopsis genes, which were selected based on the basis of literature reports, were evaluated under drought stress condition by Genevestigator. Genes that showed strong induction under drought stress were selected and used as bait to identify orthologs in the soybean genome. This allowed us to select 354 genes of putative soybean orthologs of 79 Arabidopsis genes belonging to 38 distinct metabolic pathways. The expression pattern of the selected genes was verified in the subtractive libraries available in the GENOSOJA project. Subsequently, 13 genes from different metabolic pathways were selected for validation by qPCR experiments. The expression of six genes was validated in plants undergoing drought stress in both pot-based and hydroponic cultivation systems. The results suggest that the metabolic response to drought stress is conserved in Arabidopsis and soybean plants.