Characterization of high-grade prostate cancer at multiparametric MRI using a radiomic-based computer-aided diagnosis system as standalone and second reader.

PURPOSE: The purpose of this study was to develop and test across various scanners a zone-specific region-of-interest (ROI)-based computer-aided diagnosis system (CAD) aimed at characterizing, on MRI, International Society of Urological Pathology (ISUP) grade≥2 prostate cancers. MATERIALS AND METHODS: ROI-based quantitative models were selected in multi-vendor training (265 pre-prostatectomy MRIs) and pre-test (112 pre-biopsy MRIs) datasets. The best peripheral and transition zone models were combined and retrospectively assessed in internal (158 pre-biopsy MRIs) and external (104 pre-biopsy MRIs) test datasets. Two radiologists (R1/R2) retrospectively delineated the lesions targeted at biopsy in test datasets. The CAD area under the receiver operating characteristic curve (AUC) for characterizing ISUP≥2 cancers was compared to that of the Prostate Imaging-Reporting and Data System version2 (PI-RADSv2) score prospectively assigned to targeted lesions. RESULTS: The best models used the 25th apparent diffusion coefficient (ADC) percentile in transition zone and the 2nd ADC percentile and normalized wash-in rate in peripheral zone. The PI-RADSv2 AUCs were 82% (95% confidence interval [CI]: 74-87) and 86% (95% CI: 81-91) in the internal and external test datasets respectively. They were not different from the CAD AUCs obtained with R1 and R2 delineations, in the internal (82% [95% CI: 76-89], P = 0.95 and 85% [95% CI: 78-91], P = 0.55) and external (82% [95% CI: 74-91], P = 0.41 and 86% [95% CI:78-95], P = 0.98) test datasets. The CAD yielded sensitivities of 86-89% and 90-91%, and specificities of 64-65% and 69-75% in the internal and external test datasets respectively. CONCLUSION: The CAD performance for characterizing ISUP grade≥2 prostate cancers on MRI is not different from that of PI-RADSv2 score across two test datasets.

Reproducibility of apparent diffusion coefficient measurement in normal prostate peripheral zone at 1.5T MRI.

PURPOSE: The purpose of this study was to quantify the influence of factors of variability on apparent diffusion coefficient (ADC) estimation in the normal prostate peripheral zone (PZ). MATERIALS AND METHODS: Fifty healthy volunteers underwent in 2017 (n = 17) or 2020 (n = 33) two-point (0, 800 s/mm²) prostate diffusion-weighted imaging in the morning on 1.5 T scanners A and B from different manufacturers. Additional five-point (50, 150, 300, 500, 800 s/mm²) acquisitions were performed on scanner B in the morning and evening. ADC was measured in PZ at midgland using ADC maps reconstructed with various b-value combinations. ADC distributions from 2017 and 2020 were compared using Wilcoxon rank sum test. ADC obtained in the same volunteers were compared using Bland Altman methodology. The 95% confidence interval upper limit of the repeatability/reproducibility coefficient defined the lowest detectable ADC difference. RESULTS: Forty-nine participants with a mean age of 24.6 ± 3.8 [SD] years (range: 21-37 years) were finally included. ADC distributions from 2017 and 2020 were not significantly different and were combined. Despite high individual variability, there was no significant bias (10 × 10-6 mm²/s, P = 0.58) between ADC measurements made on both scanners. On scanner B, differences in lowest b-values chosen within the 0-500 s/mm² range for two-point ADC computation induced significant biases (56-109 × 10-6 mm²/s, P < 0.0001). ADC was significantly lower in the morning (bias: 33 × 10-6 mm²/s, P = 0.006). The number of b-values had little influence on ADC values. The lowest detectable ADC difference varied from 85 × 10-6 to 311 × 10-6 mm²/s across scanners, b-value combinations and periods of the day. CONCLUSIONS: The MRI scanner, the lowest b-value used and the period of the day induce substantial variability in ADC computation.

Characterization of Prostate Cancer with Gleason Score of at Least 7 by Using Quantitative Multiparametric MR Imaging: Validation of a Computer-aided Diagnosis System in Patients Referred for Prostate Biopsy.

Purpose To determine the performance of a computer-aided diagnosis (CAD) system trained at characterizing cancers in the peripheral zone (PZ) with a Gleason score of at least 7 in patients referred for multiparametric magnetic resonance (MR) imaging before prostate biopsy. Materials and Methods Two institutional review board-approved prospective databases of patients who underwent multiparametric MR imaging before prostatectomy (database 1) or systematic and targeted biopsy (database 2) were retrospectively used. All patients gave informed consent for inclusion in the databases. A CAD combining the 10th percentile of the apparent diffusion coefficient and the time to peak of enhancement was trained to detect cancers in the PZ with a Gleason score of at least 7 in 106 patients from database 1. The CAD was tested in 129 different patients from database 2. All targeted lesions were prospectively scored at biopsy by using a five-level Likert score. The CAD scores were retrospectively calculated. Biopsy results were used as the reference standard. Areas under the receiver operating characteristic curves (AUCs) were computed for CAD and Likert scores by using binormal smoothing for per-lesion and per-lobe analyses, and a density function for per-patient analysis. Results The CAD outperformed the Likert score in the overall population and all subgroups, except in the transition zone. The difference was statistically significant for the overall population (AUC, 0.95 [95% confidence interval {CI}: 0.90, 0.98] vs 0.88 [95% CI: 0.68, 0.96]; P = .02) at per-patient analysis, and for less-experienced radiologists (<1 year) at per-lesion (AUC, 0.90 [95% CI: 0.81, 0.95] vs 0.83 [95% CI: 0.73, 0.90]; P = .04) and per-lobe (AUC, 0.92 [95% CI: 0.80, 0.96] vs 0.84 [95% CI: 0.72, 0.91]; P = .04) analysis. Conclusion The CAD outperformed the Likert score prospectively assigned at biopsy in characterizing cancers with a Gleason score of at least 7. © RSNA, 2018 Online supplemental material is available for this article.

Stiffness of benign and malignant prostate tissue measured by shear-wave elastography: a preliminary study.

OBJECTIVES: To measure benign and malignant prostate tissue stiffness using shear-wave elastography (SWE). METHODS: Thirty consecutive patients underwent transrectal SWE in the axial and sagittal planes before prostatectomy. After reviewing prostatectomy specimens, two radiologists measured stiffness in regions corresponding to cancers, lateral and median benign peripheral zone (PZ) and benign transition zone (TZ). RESULTS: Cancers were stiffer than benign PZ and TZ. All tissue classes were stiffer on sagittal than on axial imaging, in TZ than in PZ, and in median PZ than in lateral PZ. At multivariate analysis, the nature of tissue (benign or malignant; P < 0.00001), the imaging plane (axial or sagittal; P < 0.00001) and the location within the prostate (TZ, median PZ or lateral PZ; P = 0.0065) significantly and independently influenced tissue stiffness. On axial images, the thresholds maximising the Youden index in TZ, lateral PZ and median PZ were respectively 62 kPa, 33 kPa and 49 kPa. On sagittal images, the thresholds were 76 kPa, 50 kPa and 72 kPa, respectively. CONCLUSIONS: SWE can distinguish prostate malignant and benign tissues. Tissue stiffness is influenced by the imaging plane and the location within the gland. KEY POINTS: • Prostate cancers were stiffer than the benign peripheral zone • All tissue classes were stiffer on sagittal than on axial imaging • All tissue classes were stiffer in the transition zone than in the peripheral zone • All tissue classes were stiffer in the median than in the lateral peripheral zone • Taking into account imaging plane and zonal anatomy can improve cancer detection.

Quantitative Analysis of Prostate Multiparametric MR Images for Detection of Aggressive Prostate Cancer in the Peripheral Zone: A Multiple Imager Study.

Purpose To assess the intermanufacturer variability of quantitative models in discriminating cancers with a Gleason score of at least 7 among peripheral zone (PZ) lesions seen at 3-T multiparametric magnetic resonance (MR) imaging. Materials and Methods An institutional review board-approved prospective database of 257 patients who gave written consent and underwent T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging before prostatectomy was retrospectively reviewed. It contained outlined lesions found to be suspicious for malignancy by two independent radiologists and classified as malignant or benign after correlation with prostatectomy whole-mount specimens. One hundred six patients who underwent imaging with 3-T MR systems from two manufacturers were selected (data set A, n = 72; data set B, n = 34). Eleven parameters were calculated in PZ lesions: normalized T2-weighted signal intensity, skewness and kurtosis of T2-weighted signal intensity, T2 value, wash-in rate, washout rate, time to peak (TTP), mean apparent diffusion coefficient (ADC), 10th percentile of the ADC, and skewness and kurtosis of the histogram of the ADC values. Parameters were selected on the basis of their specificity for a sensitivity of 0.95 in diagnosing cancers with a Gleason score of at least 7, and the area under the receiver operating characteristic curve (AUC) for the models was calculated. Results The model of the 10th percentile of the ADC with TTP yielded the highest AUC in both data sets. In data set A, the AUC was 0.90 (95% confidence interval [CI]: 0.85, 0.95) or 0.89 (95% CI: 0.82, 0.94) when it was trained in data set A or B, respectively. In data set B, the AUC was 0.84 (95% CI: 0.74, 0.94) or 0.86 (95% CI: 0.76, 0.95) when it was trained in data set A or B, respectively. No third variable added significantly independent information in any data set. Conclusion The model of the 10th percentile of the ADC with TTP yielded accurate results in discriminating cancers with a Gleason score of at least 7 among PZ lesions at 3 T in data from two manufacturers. (©) RSNA, 2016 Online supplemental material is available for this article.

How accurate is multiparametric MR imaging in evaluation of prostate cancer volume?

PURPOSE: To assess the factors influencing multiparametric (MP) magnetic resonance (MR) imaging accuracy in estimating prostate cancer histologic volume (Vh). MATERIALS AND METHODS: A prospective database of 202 patients who underwent MP MR imaging before radical prostatectomy was retrospectively used. Institutional review board approval and informed consent were obtained. Two independent radiologists delineated areas suspicious for cancer on images (T2-weighted, diffusion-weighted, dynamic contrast material-enhanced [DCE] pulse sequences) and scored their degree of suspicion of malignancy by using a five-level Likert score. One pathologist delineated cancers on whole-mount prostatectomy sections and calculated their volume by using digitized planimetry. Volumes of MR true-positive lesions were measured on T2-weighted images (VT2), on ADC maps (VADC), and on DCE images [VDCE]). VT2, VADC, VDCE and the greatest volume determined on images from any of the individual MR pulse sequences (Vmax) were compared with Vh (Bland-Altman analysis). Factors influencing MP MR imaging accuracy, or A, calculated as A = Vmax/Vh, were evaluated using generalized linear mixed models. RESULTS: For both readers, Vh was significantly underestimated with VT2 (P < .0001, both), VADC (P < .0001, both), and VDCE (P = .02 and P = .003, readers 1 and 2, respectively), but not with Vmax (P = .13 and P = .21, readers 1 and 2, respectively). Mean, 25th percentile, and 75th percentile, respectively, for Vmax accuracy were 0.92, 0.54, and 1.85 for reader 1 and 0.95, 0.57, and 1.77 for reader 2. At generalized linear mixed (multivariate) analysis, tumor Likert score (P < .0001), Gleason score (P = .009), and Vh (P < .0001) significantly influenced Vmax accuracy (both readers). This accuracy was good in tumors with a Gleason score of 7 or higher or a Likert score of 5, with a tendency toward underestimation of Vh; accuracy was poor in small (<0.5 cc) or low-grade (Gleason score ≤6) tumors, with a tendency toward overestimation of Vh. CONCLUSION: Vh can be estimated by using Vmax in aggressive tumors or in tumors with high Likert scores.

Detection of genomic loci associated with environmental variables using generalized linear mixed models.

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress.

Impaired liver function in Xenopus tropicalis exposed to benzo[a]pyrene: transcriptomic and metabolic evidence.

BACKGROUND: Despite numerous studies suggesting that amphibians are highly sensitive to cumulative anthropogenic stresses, the role pollutants play in the decline of amphibian populations remains unclear. Amongst the most common aquatic contaminants, polycyclic aromatic hydrocarbons (PAHs) have been shown to induce several adverse effects on amphibian species in the larval stages. Conversely, adults exposed to high concentrations of the ubiquitous PAH, benzo[a]pyrene (BaP), tolerate the compound thanks to their highly efficient hepatic detoxification mechanisms. Due to this apparent lack of toxic effect on adults, no studies have examined in depth the potential toxicological impact of PAH on the physiology of adult amphibian livers. This study sheds light on the hepatic responses of Xenopus tropicalis when exposed to high environmentally relevant concentrations of BaP, by combining a high throughput transcriptomic approach (mRNA deep sequencing) and a characterization of cellular and physiological modifications to the amphibian liver. RESULTS: Transcriptomic changes observed in BaP-exposed Xenopus were further characterized using a time-dependent enrichment analysis, which revealed the pollutant-dependent gene regulation of important biochemical pathways, such as cholesterol biosynthesis, insulin signaling, adipocytokines signaling, glycolysis/gluconeogenesis and MAPK signaling. These results were substantiated at the physiological level with the detection of a pronounced metabolic disorder resulting in a possible insulin resistance-like syndrome phenotype. Hepatotoxicity induced by lipid and cholesterol metabolism impairments was clearly identified in BaP-exposed individuals. CONCLUSIONS: Our data suggested that BaP may disrupt overall liver physiology, and carbohydrate and cholesterol metabolism in particular, even after short-term exposure. These results are further discussed in terms of how this deregulation of liver physiology can lead to general metabolic impairment in amphibians chronically exposed to contaminants, thereby illustrating the role xenobiotics might play in the global decline in amphibian populations.

Development of an Arabis alpina genomic contig sequence data set and application to single nucleotide polymorphisms discovery.

The alpine plant Arabis alpina is an emerging model in the ecological genomic field which is well suited to identifying the genes involved in local adaptation in contrasted environmental conditions, a subject which remains poorly understood at molecular level. This study presents the assembly of a pool of A. alpina genomic fragments using next-generation sequencing technologies. These contigs cover 172 Mb of the A. alpina genome (i.e. 50% of the genome) and were shown to contain sequences giving positive hits against 96% of the 458 CEGMA core genes (Core Eukaryotic Genes Mapping Approach), a set of highly conserved eukaryotic genes. Regions presenting high nucleic sequence identity with 77% of the close relative Arabidopsis thaliana's genes were found with an unbiased distribution across the different functional categories of A. thaliana genes. This new resource was tested using a resequencing assay to identify polymorphic sites. Sixteen samples were successfully analysed and 127,041 single-nucleotide polymorphisms identified. This contig data set will contribute to improving our understanding of the ecology of Arabis alpina, thus constituting an important resource for future ecological genomic studies.

Meeting review. Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics.

A workshop recently held at the École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

Influence of imaging and histological factors on prostate cancer detection and localisation on multiparametric MRI: a prospective study.

OBJECTIVES: To assess factors influencing prostate cancer detection on multiparametric (T2-weighted, diffusion-weighted, and dynamic contrast-enhanced) MRI. METHODS: One hundred and seventy-five patients who underwent radical prostatectomy were included. Pre-operative MRI performed at 1.5 T (n = 71) or 3 T (n = 104), with (n = 58) or without (n = 117) an endorectal coil were independently interpreted by two radiologists. A five-point subjective suspicion score (SSS) was assigned to all focal abnormalities (FAs). MR findings were then compared with whole-mount sections. RESULTS: Readers identified 192-214/362 cancers, with 130-155 false positives. Detection rates for tumours of <0.5 cc (cm(3)), 0.5-2 cc and >2 cc were 33-45/155 (21-29 %), 15-19/35 (43-54 %) and 8-9/12 (67-75 %) for Gleason ≤6, 17/27 (63 %), 42-45/51 (82-88 %) and 34/35 (97 %) for Gleason 7 and 4/5 (80 %), 13/14 (93 %) and 28/28 (100 %) for Gleason ≥8 cancers respectively. At multivariate analysis, detection rates were influenced by tumour Gleason score, histological volume, histological architecture and location (P < 0.0001), but neither by field strength nor coils used for imaging. The SSS was a significant predictor of both malignancy of FAs (P < 0.005) and aggressiveness of tumours (P < 0.00001). CONCLUSIONS: Detection rates were significantly influenced by tumour characteristics, but neither by field strength nor coils used for imaging. The SSS significantly stratified the risk of malignancy of FAs and aggressiveness of detected tumours. KEY POINTS: • Prostate cancer volume, Gleason score, architecture and location are MRI predictors of detection. • Field strength and coils used do not influence the tumour detection rate. • Multiparametric MRI is accurate for detecting aggressive tumours. • A subjective suspicion score can stratify the risk of malignancy and tumour aggressiveness.

Complete Arabis alpina chloroplast genome sequence and insight into its polymorphism.

The alpine plant Arabis alpina (alpine rock-cress) is a thoroughly studied species in the fields of perennial plant flowering regulation, phylogeography, and adaptation to harsh alpine climatic conditions. We report the complete A. alpina chloroplast genome sequence obtained through de novo assembly of Illumina paired-end reads produced by total DNA sequencing. The A. alpina cp circular genome is 152,866 bp in length and built of two inverted repeats of 26,933 bp separated by unique regions: a large single copy of 82,338 bp and a small single copy of 17,938 bp. The genome contains 131 genes, some of them being duplicated in the inverted repeats. Seventy-nine unique protein-coding genes were annotated, together with 29 tRNA genes and 4 ribosomal RNA genes. Sequencing and mapping of 23 additional A. alpina DNA samples enabled to gain insight into the intraspecies polymorphism of the sequenced cp genome. Genetic variability among genomes was detected as 44 indels, most of them being located in noncoding regions, and 130 single-nucleotide polymorphisms, 37 of them corresponding to mutations in coding regions. A. alpina chloroplast genome sequence will be helpful in population studies or investigations of chloroplast functions of this alpine plant species.

Effects of season and experimental warming on the bacterial community in a temperate mountain forest soil assessed by 16S rRNA gene pyrosequencing.

Climate warming may induce shifts in soil microbial communities possibly altering the long-term carbon mineralization potential of soils. We assessed the response of the bacterial community in a forest soil to experimental soil warming (+4 °C) in the context of seasonal fluctuations. Three experimental plots were sampled in the fourth year of warming in summer and winter and compared to control plots by 16S rRNA gene pyrosequencing. We sequenced 17,308 amplicons per sample and analysed operational taxonomic units at genetic distances of 0.03, 0.10 and 0.25, with respective Good's coverages of 0.900, 0.977 and 0.998. Diversity indices did not differ between summer, winter, control or warmed samples. Summer and winter samples differed in community structure at a genetic distance of 0.25, corresponding approximately to phylum level. This was mainly because of an increase of Actinobacteria in winter. Abundance patterns of dominant taxa (> 0.06% of all reads) were analysed individually and revealed, that seasonal shifts were coherent among related phylogenetic groups. Seasonal community dynamics were subtle compared to the dynamics of soil respiration. Despite a pronounced respiration response to soil warming, we did not detect warming effects on community structure or composition. Fine-scale shifts may have been concealed by the considerable spatial variation.

Soil sampling and isolation of extracellular DNA from large amount of starting material suitable for metabarcoding studies.

DNA metabarcoding refers to the DNA-based identification of multiple species from a single complex and degraded environmental sample. We developed new sampling and extraction protocols suitable for DNA metabarcoding analyses targeting soil extracellular DNA. The proposed sampling protocol has been designed to reduce, as much as possible, the influence of local heterogeneity by processing a large amount of soil resulting from the mixing of many different cores. The DNA extraction is based on the use of saturated phosphate buffer. The sampling and extraction protocols were validated first by analysing plant DNA from a set of 12 plots corresponding to four plant communities in alpine meadows, and, second, by conducting pilot experiments on fungi and earthworms. The results of the validation experiments clearly demonstrated that sound biological information can be retrieved when following these sampling and extraction procedures. Such a protocol can be implemented at any time of the year without any preliminary knowledge of specific types of organisms during the sampling. It offers the opportunity to analyse all groups of organisms using a single sampling/extraction procedure and opens the possibility to fully standardize biodiversity surveys.

Transcription profiling of resistance to Bti toxins in the mosquito Aedes aegypti using next-generation sequencing.

The control of mosquitoes transmitting infectious diseases relies mainly on the use of chemical insecticides. However, resistance to most chemical insecticides threatens mosquito control programs. In this context, the spraying of toxins produced by the bacteria Bacillus thuringiensis subsp. israelensis (Bti) in larval habitats represents an alternative to chemical insecticides and is now widely used for mosquito control. Recent studies suggest that resistance of mosquitoes to Bti toxin may occur locally but mechanisms have not been characterized so far. In the present study, we investigated gene transcription level variations associated with Bti toxin resistance in the mosquito Aedes aegypti using a next-generation sequencing approach. More than 6 million short cDNA tags were sequenced from larvae of two strains sharing the same genetic background: a Bti toxins-resistant strain and a susceptible strain. These cDNA tags were mapped with a high coverage (308 reads per position in average) to more than 6000 genes of Ae. aegypti genome and used to quantify and compare the transcription level of these genes between the two mosquito strains. Among them, 86 genes were significantly differentially transcribed more than 4-fold in the Bti toxins resistant strain comparatively to the susceptible strain. These included gene families previously associated with Bti toxins resistance such as serine proteases, alkaline phosphatase and alpha-amylase. These results are discussed in regards of potential Bti toxins resistance mechanisms in mosquitoes.

Transcriptome response to pollutants and insecticides in the dengue vector Aedes aegypti using next-generation sequencing technology.

BACKGROUND: The control of mosquitoes transmitting infectious diseases relies mainly on the use of chemical insecticides. However, mosquito control programs are now threatened by the emergence of insecticide resistance. Hitherto, most research efforts have been focused on elucidating the molecular basis of inherited resistance. Less attention has been paid to the short-term response of mosquitoes to insecticides and pollutants which could have a significant impact on insecticide efficacy. Here, a combination of LongSAGE and Solexa sequencing was used to perform a deep transcriptome analysis of larvae of the dengue vector Aedes aegypti exposed for 48 h to sub-lethal doses of three chemical insecticides and three anthropogenic pollutants. RESULTS: Thirty millions 20 bp cDNA tags were sequenced, mapped to the mosquito genome and clustered, representing 6850 known genes and 4868 additional clusters not located within predicted genes. Mosquitoes exposed to insecticides or anthropogenic pollutants showed considerable modifications of their transcriptome. Genes encoding cuticular proteins, transporters, and enzymes involved in the mitochondrial respiratory chain and detoxification processes were particularly affected. Genes and molecular mechanisms potentially involved in xenobiotic response and insecticide tolerance were identified. CONCLUSIONS: The method used in the present study appears as a powerful approach for investigating fine transcriptome variations in genome-sequenced organisms and can provide useful informations for the detection of novel transcripts. At the biological level, despite low concentrations and no apparent phenotypic effects, the significant impact of these xenobiotics on mosquito transcriptomes raise important questions about the 'hidden impact' of anthropogenic pollutants on ecosystems and consequences on vector control.

The GC-heterogeneity of teleost fishes.

BACKGROUND: One of the most striking features of mammalian and birds chromosomes is the variation in the guanine-cytosine (GC) content that occurs over scales of hundreds of kilobases to megabases; this is known as the "isochore" structure. Among other vertebrates the presence of isochores depends upon the taxon; isochore are clearly present in Crocodiles and turtles but fish genome seems very homogeneous on GC content. This has suggested a unique isochore origin after the divergence between Sarcopterygii and Actinopterygii, but before that between Sauropsida and mammals. However during more than 30 years of analysis, isochore characteristics have been studied and many important biological properties have been associated with the isochore structure of human genomes. For instance, the genes are more compact and their density is highest in GC rich isochores. RESULTS: This paper shows in teleost fish genomes the existence of "GC segmentation" sharing some of the characteristics of isochores although teleost fish genomes presenting a particular homogeneity in CG content. The entire genomes of T nigroviridis and D rerio are now available, and this has made it possible to check whether a mosaic structure associated with isochore properties can be found in these fishes. In this study, hidden Markov models were trained on fish genes (T nigroviridis and D rerio) which were classified by using the isochore class of their human orthologous. A clear segmentation of these genomes was detected. CONCLUSION: The GC content is an excellent indicator of isochores in heterogeneous genomes as mammals. The segmentation we obtained were well correlated with GC content and other properties associated to GC content such as gene density, the number of exons per gene and the length of introns. Therefore, the GC content is the main property that allows the detection of isochore but more biological properties have to be taken into account. This method allows detecting isochores in homogeneous genomes.

A markovian approach for the prediction of mouse isochores.

Hidden Markov models (HMMs) are effective tools to detect series of statistically homogeneous structures, but they are not well suited to analyse complex structures. For example, the duration of stay in a state of a HMM must follow a geometric law. Numerous other methodological difficulties are encountered when using HMMs to segregate genes from transposons or retroviruses, or to determine the isochore classes of genes. The aim of this paper is to analyse these methodological difficulties, and to suggest new tools for the exploration of genome data. We show that HMMs can be used to analyse complex gene structures with bell-shaped length distribution by using convolution of geometric distributions. Thus, we have introduced macros-states to model the distributions of the lengths of the regions. Our study shows that simple HMM could be used to model the isochore organisation of the mouse genome. This potential use of markovian models to help in data exploration has been underestimated until now.

A computational prediction of isochores based on hidden Markov models.

Mammalian genomes are organised into a mosaic of regions (in general more than 300 kb in length), with differing, relatively homogeneous G+C contents. The G+C content is the basic characteristic of isochores, but they have also been associated with many other biological properties. For instance, the genes are more compact and their density is highest in G+C rich isochores. Various ways of locating isochores in the human genome have been developed, but such methods use only the base composition of the DNA sequences. The present paper proposes a new method, based on a hidden Markov model, which takes into account several of the biological properties associated with the isochore structure of a genome. This method leads to good segmentation of the human genome into isochores, and also permits a new analysis of the known heterogeneity of G+C rich isochores: most (60%) of the G+C poor genes embedded in G+C rich isochores have UTR sequences characteristic of G+C rich genes. This genomic feature is discussed in the context of both evolution and genome function.