Most of the proteins that are used in mitochondria are imported through the double membrane of the organelle. The information that guides the protein to mitochondria is contained in its sequence and structure, although no direct evidence can be obtained. In this article, discriminant analysis has been performed with 47 parameters and a large set of mitochondrial proteins extracted from the SwissProt database. A computational method that facilitates the analysis and objective prediction of mitochondrially imported proteins has been developed. If only the amino acid sequence is considered, 75–97% of the mitochondrial proteins studied have been predicted to be imported into mitochondria. Moreover, the existence of mitochondrial‐targeting sequences is predicted in 76–94% of the analyzed mitochondrial precursor proteins. As a practical application, the number of unknown yeast open reading frames that might be mitochondrial proteins has been predicted, which revealed that many of them are clustered.

Manuel G. Claros, Gunnar von Heijne; TopPred II: an improved software for membrane protein structure predictions, Bioinformatics, Volume 10, Issue 6, 1 Decembe

The paper describes the Macintosh program MitoProt, which is suitable for studying mitochondrion-related proteins. MitoProt supplies a series of parameters that permit theoretical evaluation of mitochondrial targeting sequences, as well as calculation of the most hydrophobic fragment of 17 residues in the sequence, and a new parameter called mesohydrophobicity. The last two calculations are important for predicting the putative importability of a protein into mitochondria. Taken together, targeting sequence and hydrophobicity characteristics enable one to predict whether a given protein could be mitochondrial when no previous information on the nature of the sequence is available.

Background: High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to avoid database contamination with artefactual sequences. The arrival of pyrosequencing enhances this problem and necessitates customisable pre-processing algorithms. Results: SeqTrim has been implemented both as a Web and as a standalone command line application. Already-published and newly-designed algorithms have been included to identify sequence inserts, to remove low quality, vector, adaptor, low complexity and contaminant sequences, and to detect chimeric reads. The availability of several input and output formats allows its inclusion in sequence processing workflows. Due to its specific algorithms, SeqTrim outperforms other pre-processors implemented as Web services or standalone applications. It performs equally well with sequences from EST libraries, SSH libraries, genomic DNA libraries and pyrosequencing reads and does not lead to over-trimming. Conclusions: SeqTrim is an efficient pipeline designed for pre-processing of any type of sequence read, including next-generation sequencing. It is easily configurable and provides a friendly interface that allows users to know what happened with sequences at every pre-processing stage, and to verify pre-processing of an individual sequence if desired. The recommended pipeline reveals more information about each sequence than previously described pre-processors and can discard more sequencing or experimental artefacts.

Maritime pine (Pinus pinasterAit.) is a widely distributed conifer species in Southwestern Europe and one of the most advanced models for conifer research. In the current work, comprehensive characterization of the maritime pine transcriptome was performed using a combination of two different next‐generation sequencing platforms, 454 and Illumina. De novo assembly of the transcriptome provided a catalogue of 26 020 unique transcripts in maritime pine trees and a collection of 9641 full‐length cDNAs. Quality of the transcriptome assembly was validated by RT‐PCR amplification of selected transcripts for structural and regulatory genes. Transcription factors and enzyme‐encoding transcripts were annotated. Furthermore, the available sequencing data permitted the identification of polymorphisms and the establishment of robust single nucleotide polymorphism (SNP) and simple‐sequence repeat (SSR) databases for genotyping applications and integration of translational genomics in maritime pine breeding programmes. All our data are freely available at SustainpineDB, the P. pinaster expressional database. Results reported here on the maritime pine transcriptome represent a valuable resource for future basic and applied studies on this ecological and economically important pine species.

In spite of the biological and economic importance of plants, relatively few plant species have been sequenced. Only the genome sequence of plants with relatively small genomes, most of them angiosperms, in particular eudicots, has been determined. The arrival of next-generation sequencing technologies has allowed the rapid and efficient development of new genomic resources for non-model or orphan plant species. But the sequencing pace of plants is far from that of animals and microorganisms. This review focuses on the typical challenges of plant genomes that can explain why plant genomics is less developed than animal genomics. Explanations about the impact of some confounding factors emerging from the nature of plant genomes are given. As a result of these challenges and confounding factors, the correct assembly and annotation of plant genomes is hindered, genome drafts are produced, and advances in plant genomics are delayed.