An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

Characterization of human gene expression changes after olive oil ingestion: an exploratory approach

Olive oil consumption is protective against risk factors for cardiovascular and cancer diseases. A nutrigenomic approach was performed to assess whether changes in gene expression could occur in human peripheral blood mononuclear cells after oli ve oil ingestion at postprandial state. Six healthy male volunteers ingested, at fasting state, 50 ml of olive oil. Prior to intervention a 1-week washout period with a controlled diet and sunflower oil as the only source of fat was followed. During the 3 days before and on the intervention day, a very low-phenolic compound diet was followed. At baseline (0 h) and at post-ingestion (6 h), total RNA was isolated and gene expression (29,082 genes) was evaluated by microarray. From microarray data, nutrient-gene interactions were observed in genes related to metabolism, cellular processes, cancer, and atherosclerosis (e.g. USP48 by 2.16; OGT by 1.68-fold change) and associated processes such as inflammation (e.g. AKAP13 by 2.30; IL-10 by 1.66-fold change) and DNA damage (e.g. DCLRE1C by 1.47; POLK by 1.44- fold change). When results obtained by microarray were verified by qRT-PCR in nine genes, full concordance was achieved only in the case of up-regulated genes. Changes were observed at a real-life dose of olive oil, as it is daily consumed in some Mediterranean areas. Our results support the hypothesis that postprandial protective changes related to olive oil consumption could be mediated through gene expression changes.

Genetic characterization of the ABO blood group in Neandertals

Background: The high polymorphism rate in the human ABO blood group gene seems to be related to susceptibility to different pathogens. It has been estimated that all genetic variation underlying the human ABO alleles appeared along the human lineage, after the divergence from the chimpanzee lineage. A paleogenetic analysis of the ABO blood group gene in Neandertals allows us to directly test for the presence of the ABO alleles in these extinct humans. Results: We have analysed two male Neandertals that were retrieved under controlled conditions at the El Sidron site in Asturias (Spain) and that appeared to be almost free of modern human DNA contamination. We find a human specific diagnostic deletion for blood group O (O01 haplotype) in both Neandertal individuals. Conclusion: These results suggest that the genetic change responsible for the O blood group in humans predates the human and Neandertal divergence. A potential selective event associated with the emergence of the O allele may have therefore occurred after humans separated from their common ancestor with chimpanzees and before the human-Neandertal population divergence.

Reassessing the role of mitochondrial DNA mutations in autism spectrum disorder

Background: There is increasing evidence that impairment of mitochondrial energy metabolism plays an important role in the pathophysiology of autism spectrum disorders (ASD; OMIM number: 209850). A significant proportion of ASD cases display biochemical alterations suggestive of mitochondrial dysfunction and several studies have reported that mutations in the mitochondrial DNA (mtDNA) molecule could be involved in the disease phenotype. Methods: We analysed a cohort of 148 patients with idiopathic ASD for a number of mutations proposed in the literature as pathogenic in ASD. We also carried out a case control association study for the most common European haplogroups (hgs) and their diagnostic single nucleotide polymorphisms (SNPs) by comparing cases with 753 healthy and ethnically matched controls.Results: We did not find statistical support for an association between mtDNA mutations or polymorphisms and ASD.Conclusions: Our results are compatible with the idea that mtDNA mutations are not a relevant cause of ASD and the frequent observation of concomitant mitochondrial dysfunction and ASD could be due to nuclear factors influencing mitochondrion functions or to a more complex interplay between the nucleus and the mitochondrion/mtDNA.

Traducción comentada de “Genetically Modified Organisms (GMOs): Transgenic Crops and Recombinant DNA Technology”

The purpose of this paper is to provide a translation into Spanish of a review articleabout genetically modified organisms (GMOs) entitled “Genetically ModifiedOrganisms (GMOs): Transgenic Crops and Recombinant DNA Technology” publishedby the well-known scientific journal Nature. In a world where English has become thelingua franca when it comes to transferring scientific knowledge and information, itmust be taken into account that not everyone—from scientist to the general public—hasa good enough command of English so that they can feel comfortable enough reading inthis language. Translators are consequently needed resulting from a great demand oftranslation activity into, for example, Spanish. This is the reason why the proposedSpanish translation is followed by a detailed analysis emphasizing the difficulties andproblems that characterize scientific—and also general—translation (i.e. terminology,syntax, semantics, pragmatics, and ideology), for which different approaches as how tosolve them are provided. On the basis of the analysis, it can be concluded thatexperience will be of much help to scientific translators, given that specificterminological knowledge and style requirements must always be born in mind whentranslating in this field. Moreover, this paper is intended to serve as a guide forTranslation students specializing in the field of science and the expectation is to helpthem make the right decisions when it comes to translating. However, it is clear that itcan only be thought of as an introduction that should be completed with further researchand documentation tasks in order to offer a complete reference tool: the ultimatehandbook of scientific translation.