Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons

Weighted Gene Coexpression Network Analysis Reveals the Critical lncRNAs and mRNAs in Development of Hirschsprung's Disease

Hirschsprung's disease (HSCR) is a common newborn defect. This study aimed to identify critical genes involved in the development of HSCR. Differently expressed genes (DEGs) of public data set GSE98502 were analyzed using paired t-test. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8. Besides, Coexpression network of long noncoding RNAs (lncRNAs)-mRNAs (message RNA) were constructed using weighted gene coexpression network analysis. The key modules were filtered out by calculating the module-trait correlations. Then, hub genes were screened and the expression of these genes was further validated in an independent data set GSE96854. We identified 864 DEGs enriched in 19 GO biological functions such as negative regulation of growth and regulation of heart contraction; 11 KEGG pathways such as mineral absorption and protein digestion and absorption. lncRNAs-mRNAs coexpressed network was constructed, including 8 modules and 177 genes. Hub lncRNAs, including LINC00619, LINC00924, LINC00261, and DRAIC, were identified. Hub mRNAs, including CYCS, CCND1, BDKRB, ITGA6, and TNNC1, were mainly enriched in cancer pathways, p53 signaling pathway, and calcium signaling pathway. The expressions of the hub mRNAs were successfully validated by another independent GSE96854 data set. Our findings indicated the hub lncRNAs, including LINC00619, LINC00924, LINC00261, and DRAIC, as well as hub mRNAs, including CYCS, CCND1, BDKRB, ITGA6, and TNNC1, might involve in the progression of HSCR, and these genes might provide new clinical biomarkers for risk evaluation of HSCR.

Comparison of alternative mixture model methods to analyze bacterial CGH experiments with multi-genome arrays

BACKGROUND

Microarray-based comparative genomic hybridization (aCGH) is used for rapid comparison of genomes of different bacterial strains. The purpose is to evaluate the distribution of genes from sequenced bacterial strains (control) among unsequenced strains (test). We previously compared the use of single strain versus multiple strain control with arrays covering multiple genomes. The conclusion was that a multiple strain control promoted a better separation of signals between present and absent genes.

FINDINGS

We now extend our previous study by applying the Expectation-Maximization (EM) algorithm to fit a mixture model to the signal distribution in order to classify each gene as present or absent and by comparing different methods for analyzing aCGH data, using combinations of different control strain choices, two different statistical mixture models, with or without normalization, with or without logarithm transformation and with test-over-control or inverse signal ratio calculation. We also assessed the impact of replication on classification accuracy. Higher values of accuracy have been achieved using the ratio of control-over-test intensities, without logarithmic transformation and with a strain mix control. Normalization and the type of mixture model fitted by the EM algorithm did not have a significant impact on classification accuracy. Similarly, using the average of replicate arrays to perform the classification does not significantly improve the results.

CONCLUSIONS

Our work provides a guiding benchmark comparison of alternative methods to analyze aCGH results that can impact on the analysis of currently ongoing comparative genomic projects or in the re-analysis of published studies.

Gene duplication in an African cichlid adaptive radiation

BACKGROUND

Gene duplication is a source of evolutionary innovation and can contribute to the divergence of lineages; however, the relative importance of this process remains to be determined. The explosive divergence of the African cichlid adaptive radiations provides both a model for studying the general role of gene duplication in the divergence of lineages and also an exciting foray into the identification of genomic features that underlie the dramatic phenotypic and ecological diversification in this particular lineage. We present the first genome-wide study of gene duplication in African cichlid fishes, identifying gene duplicates in three species belonging to the Lake Malawi adaptive radiation (Metriaclima estherae, Protomelas similis, Rhamphochromis "chilingali") and one closely related species from a non-radiated riverine lineage (Astatotilapia tweddlei).

RESULTS

Using Astatotilapia burtoni as reference, microarray comparative genomic hybridization analysis of 5689 genes reveals 134 duplicated genes among the four cichlid species tested. Between 51 and 55 genes were identified as duplicated in each of the three species from the Lake Malawi radiation, representing a 38%-49% increase in number of duplicated genes relative to the non-radiated lineage (37 genes). Duplicated genes include several that are involved in immune response, ATP metabolism and detoxification.

CONCLUSIONS

These results contribute to our understanding of the abundance and type of gene duplicates present in cichlid fish lineages. The duplicated genes identified in this study provide candidates for the analysis of functional relevance with regard to phenotype and divergence. Comparative sequence analysis of gene duplicates can address the role of positive selection and adaptive evolution by gene duplication, while further study across the phylogenetic range of cichlid radiations (and more generally in other adaptive radiations) will determine whether the patterns of gene duplication seen in this study consistently accompany rapid radiation.

Lytic infection of Lactococcus lactis by bacteriophages Tuc2009 and c2 triggers alternative transcriptional host responses

Here we present an entire temporal transcriptional profile of Lactococcus lactis subsp. cremoris UC509.9 undergoing lytic infection with two distinct bacteriophages, Tuc2009 and c2. Furthermore, corresponding high-resolution whole-phage genome tiling arrays of both bacteriophages were performed throughout lytic infection. Whole-genome microarrays performed at various time points postinfection demonstrated a rather modest impact on host transcription. The majority of changes in the host transcriptome occur during late infection stages; few changes in host gene transcription occur during the immediate and early infection stages. Alterations in the L. lactis UC509.9 transcriptome during lytic infection appear to be phage specific, with relatively few differentially transcribed genes shared between cells infected with Tuc2009 and those infected with c2. Despite the apparent lack of a coordinated general phage response, three themes common to both infections were noted: alternative transcription of genes involved in catabolic flux and energy production, differential transcription of genes involved in cell wall modification, and differential transcription of genes involved in the conversion of ribonucleotides to deoxyribonucleotides. The transcriptional profiles of both bacteriophages during lytic infection generally correlated with the findings of previous studies and allowed the confirmation of previously predicted promoter sequences. In addition, the host transcriptional response to lysogenization with Tuc2009 was monitored along with tiling array analysis of Tuc2009 in the lysogenic state. Analysis identified 44 host genes with altered transcription during lysogeny, 36 of which displayed levels of transcription significantly reduced from those for uninfected cells.

Functional performance of aCGH design for clinical cytogenetics

Array-comparative genomic hybridization (aCGH) technology enables rapid, high-resolution analysis of genomic rearrangements. With the use of it, genome copy number changes and rearrangement breakpoints can be detected and analyzed at resolutions down to a few kilobases. An exon array CGH approach proposed recently accurately measures copy-number changes of individual exons in the human genome. The crucial and highly non-trivial starting task is the design of an array, i.e. the choice of appropriate (multi)set of oligos. The success of the whole high-level analysis depends on the quality of the design. Also, the comparison of several alternative designs of array CGH constitutes an important step in development of new diagnostic chip. In this paper, we deal with these two often neglected issues. We propose a new approach to measure the quality of array CGH designs. Our measures reflect the robustness of rearrangements detection to the noise (mostly experimental measurement error). The method is parametrized by the segmentation algorithm used to identify aberrations. We implemented the efficient Monte Carlo method for testing noise robustness within DNAcopy procedure. Developed framework has been applied to evaluation of functional quality of several optimized array designs.

Single cell analysis of gene expression patterns during carbon starvation in Bacillus subtilis reveals large phenotypic variation

How cells dynamically respond to fluctuating environmental conditions depends on the architecture and noise of the underlying genetic circuits. Most work characterizing stress pathways in the model bacterium Bacillus subtilis has been performed on bulk cultures using ensemble assays. However, investigating the single cell response to stress is important since noise might generate significant phenotypic heterogeneity. Here, we study the stress response to carbon source starvation and compare both population and single cell data. Using a top-down approach, we investigate the transcriptional dynamics of various stress-related genes of B. subtilis in response to carbon source starvation and to increased cell density. Our data reveal that most of the tested gene-regulatory networks respond highly heterogeneously to starvation and cells show a large degree of variation in gene expression. The level of highly dynamic diversification within B. subtilis populations under changing environments reflects the necessity to study cells at the single cell level.

Comparative transcriptomic analysis of streptococcus pseudopneumoniae with viridans group streptococci

BACKGROUND

Streptococcus pseudopneumoniae, is a novel member of the genus Streptococcus, falling close to related members like S. pneumoniae, S. mitis, and S. oralis. Its recent appearance has shed light on streptococcal infections, which has been unclear till recently. In this study, the transcriptome of S. pseudopneumoniae CCUG 49455T was analyzed using the S. pneumoniae R6 microarray platform and compared with those of S. pneumoniae KCTC 5080T, S. mitis KCTC 3556T, and S. oralis KCTC 13048T strains.

RESULTS

Comparative transcriptome analysis revealed the extent of genetic relatedness among the species, and implies that S. pseudopneumoniae is the most closely related to S. pneumoniae. A total of 489, 444 and 470 genes were upregulated while 347, 484 and 443 were downregulated relative to S. pneumoniae in S. pseudopneumoniae, S. oralis and S. mitis respectively. Important findings were the up-regulation of TCS (two component systems) and transposase which were found to be specific to S. pseudopneumoniae.

CONCLUSIONS

This study provides insight to the current understanding of the genomic content of S. pseudopneumoniae. The comparative transcriptome analysis showed hierarchical clustering of expression data of S. pseudopneumoniae with S. pneumoniae and S. mitis with S. oralis. This proves that transcriptional profiling can facilitate in elucidating the genetic distance between closely related strains.

Genetic diversity of Streptococcus suis isolates as determined by comparative genome hybridization

Background

Streptococcus suis is a zoonotic pathogen that causes infections in young piglets. S. suis is a heterogeneous species. Thirty-three different capsular serotypes have been described, that differ in virulence between as well as within serotypes.

Results

In this study, the correlation between gene content, serotype, phenotype and virulence among 55 S. suis strains was studied using Comparative Genome Hybridization (CGH). Clustering of CGH data divided S. suis isolates into two clusters, A and B. Cluster A isolates could be discriminated from cluster B isolates based on the protein expression of extracellular factor (EF). Cluster A contained serotype 1 and 2 isolates that were correlated with virulence. Cluster B mainly contained serotype 7 and 9 isolates. Genetic similarity was observed between serotype 7 and serotype 2 isolates that do not express muramidase released protein (MRP) and EF (MRP^-EF^-), suggesting these isolates originated from a common founder. Profiles of 25 putative virulence-associated genes of S. suis were determined among the 55 isolates. Presence of all 25 genes was shown for cluster A isolates, whereas cluster B isolates lacked one or more putative virulence genes. Divergence of S. suis isolates was further studied based on the presence of 39 regions of difference. Conservation of genes was evaluated by the definition of a core genome that contained 78% of all ORFs in P1/7.

Conclusions

In conclusion, we show that CGH is a valuable method to study distribution of genes or gene clusters among isolates in detail, yielding information on genetic similarity, and virulence traits of S. suis isolates.

Assessment of the diversity of dairy Lactococcus lactis subsp. lactis isolates by an integrated approach combining phenotypic, genomic, and transcriptomic analyses

The intrasubspecies diversity of six strains of Lactococcus lactis subsp. lactis was investigated at the genomic level and in terms of phenotypic and transcriptomic profiles in an ultrafiltration cheese model. The six strains were isolated from various sources, but all exhibited a dairy phenotype (growth in ultrafiltration cheese model and high acidification rate). The six strains exhibited similar behaviors in terms of growth during cheese ripening, while different acidification capabilities were detected. Even if all strains displayed large genomic similarities, sharing a large core genome of almost 2,000 genes, the expression of this core genome directly in the cheese matrix revealed major strain-specific differences that potentially could account for the observed different acidification capabilities. This work demonstrated that significant transcriptomic polymorphisms exist even among Lactococcus lactis subsp. lactis strains with the same dairy origin.

Mixed-culture transcriptome analysis reveals the molecular basis of mixed-culture growth in Streptococcus thermophilus and Lactobacillus bulgaricus

Many food fermentations are performed using mixed cultures of lactic acid bacteria. Interactions between strains are of key importance for the performance of these fermentations. Yogurt fermentation by Streptococcus thermophilus and Lactobacillus bulgaricus (basonym, Lactobacillus delbrueckii subsp. bulgaricus) is one of the best-described mixed-culture fermentations. These species are believed to stimulate each other's growth by the exchange of metabolites such as folic acid and carbon dioxide. Recently, postgenomic studies revealed that an upregulation of biosynthesis pathways for nucleotides and sulfur-containing amino acids is part of the global physiological response to mixed-culture growth in S. thermophilus, but an in-depth molecular analysis of mixed-culture growth of both strains remains to be established. We report here the application of mixed-culture transcriptome profiling and a systematic analysis of the effect of interaction-related compounds on growth, which allowed us to unravel the molecular responses associated with batch mixed-culture growth in milk of S. thermophilus CNRZ1066 and L. bulgaricus ATCC BAA-365. The results indicate that interactions between these bacteria are primarily related to purine, amino acid, and long-chain fatty acid metabolism. The results support a model in which formic acid, folic acid, and fatty acids are provided by S. thermophilus. Proteolysis by L. bulgaricus supplies both strains with amino acids but is insufficient to meet the biosynthetic demands for sulfur and branched-chain amino acids, as becomes clear from the upregulation of genes associated with these amino acids in mixed culture. Moreover, genes involved in iron uptake in S. thermophilus are affected by mixed-culture growth, and genes coding for exopolysaccharide production were upregulated in both organisms in mixed culture compared to monocultures. The confirmation of previously identified responses in S. thermophilus using a different strain combination demonstrates their generic value. In addition, the postgenomic analysis of the responses of L. bulgaricus to mixed-culture growth allows a deeper understanding of the ecology and interactions of this important industrial food fermentation process.

A critical assessment of cross-species detection of gene duplicates using comparative genomic hybridization

Background

Comparison of genomic DNA among closely related strains or species is a powerful approach for identifying variation in evolutionary processes. One potent source of genomic variation is gene duplication, which is prevalent among individuals and species. Array comparative genomic hybridization (aCGH) has been successfully utilized to detect this variation among lineages. Here, beyond the demonstration that gene duplicates among species can be quantified with aCGH, we consider the effect of sequence divergence on the ability to detect gene duplicates.

Results

Using the X chromosome genomic content difference between male D. melanogaster and female D. yakuba and D. simulans, we describe a decrease in the ability to accurately measure genomic content (copy number) for orthologs that are only 90% identical. We demonstrate that genome characteristics (e.g. chromatin environment and non-orthologous sequence similarity) can also affect the ability to accurately measure genomic content. We describe a normalization strategy and statistical criteria to be used for the identification of gene duplicates among any species group for which an array platform is available from a closely related species.

Conclusions

Array CGH can be used to effectively identify gene duplication and genome content; however, certain biases are present due to sequence divergence and other genome characteristics resulting from the divergence between lineages. Highly conserved gene duplicates will be more readily recovered by aCGH. Duplicates that have been retained for a selective advantage due to directional selection acting on many loci in one or both gene copies are likely to be under-represented. The results of this study should inform the interpretation of both previously published and future work that employs this powerful technique.

Using comparative genomic hybridization to survey genomic sequence divergence across species: a proof-of-concept from Drosophila

Background

Genome-wide analysis of sequence divergence among species offers profound insights into the evolutionary processes that shape lineages. When full-genome sequencing is not feasible for a broad comparative study, we propose the use of array-based comparative genomic hybridization (aCGH) in order to identify orthologous genes with high sequence divergence. Here we discuss experimental design, statistical power, success rate, sources of variation and potential confounding factors. We used a spotted PCR product microarray platform from Drosophila melanogaster to assess sequence divergence on a gene-by-gene basis in three fully sequenced heterologous species (D. sechellia, D. simulans, and D. yakuba). Because complete genome assemblies are available for these species this study presents a powerful test for the use of aCGH as a tool to measure sequence divergence.

Results

We found a consistent and linear relationship between hybridization ratio and sequence divergence of the sample to the platform species. At higher levels of sequence divergence (< 92% sequence identity to D. melanogaster) ~84% of features had significantly less hybridization to the array in the heterologous species than the platform species, and thus could be identified as "diverged". At lower levels of divergence (≥ 97% identity), only 13% of genes were identified as diverged. While ~40% of the variation in hybridization ratio can be accounted for by variation in sequence identity of the heterologous sample relative to D. melanogaster, other individual characteristics of the DNA sequences, such as GC content, also contribute to variation in hybridization ratio, as does technical variation.

Conclusions

Here we demonstrate that aCGH can accurately be used as a proxy to estimate genome-wide divergence, thus providing an efficient way to evaluate how evolutionary processes and genomic architecture can shape species diversity in non-model systems. Given the increased number of species for which microarray platforms are available, comparative studies can be conducted for many interesting lineages in order to identify highly diverged genes that may be the target of natural selection.

Analysis of the genome content of Lactococcus garvieae by genomic interspecies microarray hybridization

Background

Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH) experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms.

Results

The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of ≥ 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258) have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections.

Conclusions

In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.

Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens

Microarray comparative genomic hybridisation (aCGH) provides an estimate of the relative abundance of genomic DNA (gDNA) taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043) and Dickeya dadantii 3937 (Dda3937); and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE) Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.

Effect of FliK mutation on the transcriptional activity of the {sigma}54 sigma factor RpoN in Helicobacter pylori

Helicobacter pylori is a motile Gram-negative bacterium that colonizes and persists in the human gastric mucosa. The flagellum gene regulatory circuitry of H. pylori is unique in many aspects compared with the Salmonella/Escherichia coli paradigms, and some regulatory checkpoints remain unclear. FliK controls the hook length during flagellar assembly. Microarray analysis of a fliK-null mutant revealed increased transcription of genes under the control of the sigma(54) sigma factor RpoN. This sigma factor has been shown to be responsible for transcription of the class II flagellar genes, including flgE and flaB. No genes higher in the flagellar hierarchy had altered expression, suggesting specific and localized FliK-dependent feedback on the RpoN regulon. FliK thus appears to be involved in three processes: hook-length control, export substrate specificity and control of RpoN transcriptional activity.

Improved analysis of bacterial CGH data beyond the log-ratio paradigm

Background

Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach.

Results

A data set containing 32 hybridizations of sequenced versus sequenced genomes have been used to test and compare methods. A ROC-analysis has been performed to illustrate the ability to rank probes with respect to Present/Absent calls. Classification into Present and Absent is compared with that of a gaussian mixture model.

Conclusion

The results indicate our proposed method is an improvement of existing methods with respect to ranking and classification of probes, especially for multi-genome arrays.

PreP+07: improvements of a user friendly tool to preprocess and analyse microarray data

Background

Nowadays, microarray gene expression analysis is a widely used technology that scientists handle but whose final interpretation usually requires the participation of a specialist. The need for this participation is due to the requirement of some background in statistics that most users lack or have a very vague notion of. Moreover, programming skills could also be essential to analyse these data. An interactive, easy to use application seems therefore necessary to help researchers to extract full information from data and analyse them in a simple, powerful and confident way.

Results

PreP+07 is a standalone Windows XP application that presents a friendly interface for spot filtration, inter- and intra-slide normalization, duplicate resolution, dye-swapping, error removal and statistical analyses. Additionally, it contains two unique implementation of the procedures – double scan and Supervised Lowess-, a complete set of graphical representations – MA plot, RG plot, QQ plot, PP plot, PN plot – and can deal with many data formats, such as tabulated text, GenePix GPR and ArrayPRO. PreP+07 performance has been compared with the equivalent functions in Bioconductor using a tomato chip with 13056 spots. The number of differentially expressed genes considering p-values coming from the PreP+07 and Bioconductor Limma packages were statistically identical when the data set was only normalized; however, a slight variability was appreciated when the data was both normalized and scaled.

Conclusion

PreP+07 implementation provides a high degree of freedom in selecting and organizing a small set of widely used data processing protocols, and can handle many data formats. Its reliability has been proven so that a laboratory researcher can afford a statistical pre-processing of his/her microarray results and obtain a list of differentially expressed genes using PreP+07 without any programming skills. All of this gives support to scientists that have been using previous PreP releases since its first version in 2003.