A minimal cytomegalovirus intron A variant can improve transgene expression in different mammalian cell lines.

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Glossario de biotecnologia vegetal.

bitstream/item/107353/1/CNPH-GLOSS.-DE-BIOTEC.-VEG.-00.pd

Utilização da casca de coco como substrato agrícola.

bitstream/CNPAT/7908/1/doc52.pd

Recombinant proteins in plants.

Edição do Congress of the Brazilian Biotechnology Society, Florianópolis, 2013

Impact of climate change on rainfed sugarcane in Veracruz, Mexico

Objective: To estimate the expected quantitative changes of the rainfed sugarcane yield in four sugar mills in the state of Veracruz using climate change scenarios for the end of the 21st century and considering that the same climate change could also affect soil fertility. Design/methodology/approach: The data on the cultivated area with the rainfed sugarcane such as topography, principal properties of soil fertility, crop yields for the beginning of the 21st century, current climatic data from the meteorological stations and future ones based on existing climate change scenarios were analyzed. Then, by means of a physiological model of this crop based on biological, climatic and soil characteristics, proposed by IIASA/FAO, the current and future agricultural productivity of sugarcane was calculated. The actual productivity calculated with this model was compared with the observed data. Then, the productivity of this crop for the end of the 21st century was calculated. The comparative impact on the productivity of the expected changes in some climatic components and corresponding expected modification in soil fertility was assessed. Results: The results of calculations indicate that if the CO2 concentration in the atmosphere increases by 2 or 2.7 times at the end of the 21st century and the current varieties of sugarcane and their crop management will conserve, the yield of sugarcane will decrease up to 20% depending on the climate change scenario and location of the plot. The main climatic factor influencing the decrease in sugarcane productivity is the expected decrease in precipitation. Limitations on study/implications: Monthly average climatic variables are used for both current and future productivity calculations since there are no estimates of daily data. There are also no predictions on the development of crop management technology as well as on the expected change in pests and diseases for the end of the 21st century. Findings/conclusions: The IISA/FAO physiological model of sugarcane growth based on agroecological principles, considering even limited number of climatic variables, is useful for calculating of sugarcane productivity with correlations greater than 90% for calculated and observed data. This allowed us to estimate the expected impact of climate change in the productivity of rainfed sugarcane in Veracruz State of Mexico at the end of 21st century

Comparative transcriptomics of cupuassu (Theobroma grandiflorum) offers insights into the early defense mechanism to Moniliophthora perniciosa, the causal agent of witches' broom disease.

Na publicação; Joseilde Oliveira Silva-Werneck

Screening non-coding RNAs in transcriptomes from neglected species using PORTRAIT: case study of the pathogenic fungus Paracoccidioides brasiliensis

<p>Abstract</p> <p>Background</p> <p>Transcriptome sequences provide a complement to structural genomic information and provide snapshots of an organism's transcriptional profile. Such sequences also represent an alternative method for characterizing neglected species that are not expected to undergo whole-genome sequencing. One difficulty for transcriptome sequencing of these organisms is the low quality of reads and incomplete coverage of transcripts, both of which compromise further bioinformatics analyses. Another complicating factor is the lack of known protein homologs, which frustrates searches against established protein databases. This lack of homologs may be caused by divergence from well-characterized and over-represented model organisms. Another explanation is that non-coding RNAs (ncRNAs) may be caught during sequencing. NcRNAs are RNA sequences that, unlike messenger RNAs, do not code for protein products and instead perform unique functions by folding into higher order structural conformations. There is ncRNA screening software available that is specific for transcriptome sequences, but their analyses are optimized for those transcriptomes that are well represented in protein databases, and also assume that input ESTs are full-length and high quality.</p> <p>Results</p> <p>We propose an algorithm called PORTRAIT, which is suitable for ncRNA analysis of transcriptomes from poorly characterized species. Sequences are translated by software that is resistant to sequencing errors, and the predicted putative proteins, along with their source transcripts, are evaluated for coding potential by a support vector machine (SVM). Either of two SVM models may be employed: if a putative protein is found, a protein-dependent SVM model is used; if it is not found, a protein-independent SVM model is used instead. Only <it>ab initio </it>features are extracted, so that no homology information is needed. We illustrate the use of PORTRAIT by predicting ncRNAs from the transcriptome of the pathogenic fungus <it>Paracoccidoides brasiliensis </it>and five other related fungi.</p> <p>Conclusion</p> <p>PORTRAIT can be integrated into pipelines, and provides a low computational cost solution for ncRNA detection in transcriptome sequencing projects.</p