Hierarchical Clustering Dendrogram Research Articles

Micro-habitats Utilizations, Feeding Niche Overlapping, and Management Systems Impacts on Community Tolerances of Wasp Species within Oil Palm Plantations.

A study on micro-habitats utilizations, feeding niche overlapping, and management systems impacts pertaining to hymenopteran community were evaluated at five chosen oil palm age stands within FELDA Sungai Tekam oil palm plantations, Pahang. Samplings were done within the duration of one year, employing the standard Malaise traps, starting from February 2013 till February 2014, involving both hot and wet seasons. 60 species, from 17 families and 35 subfamilies were successfully collected during the sampling periods. Eight defined micro-habitats were elaborated, with the subdivisions of major, minor, stable, and risky micro-habitat types. Management systems impacts were associated with the applications of chemical herbicides and fertilizers. Species groups were formed using Two-Way Hierarchical Cluster Dendrogram, following 75% of information remaining. Three species groups were formed for hot and wet seasons respectively, with the first group involved nearly half of the overall hymenopteran community. Beneficial nectariferous plants, heaps of chipped rotting oil palm trunks, and remnants of rotting forest logs were all the prominent micro-habitats associated will all cases of hymenopteran species groups, for both cases of major and minor micro-habitat types. Application of BASTA, Glyphosate-Type-A and Type-B herbicides, as well as NK-Mix, Borax, and GML chemical fertilizers were all highly correlated with hymenopteran species groups, showing the high tolerance of most hymenopteran species towards the employed management systems, with reference to minor micro-habitats. Strong feeding ecological niches and plexus values between species of similar species groups formed were specifically associated with discrete but connected minor micro-habitats with weaker food chains, collectively forming larger stable food webs within major micro-habitats. Suggestions on maintaining minor micro-habitats for the survival of most hymenopteran community, as well as the sustenance of their food sources were also discussed.

Micro-habitats Utilizations, Feeding Niche Overlapping, and Management Systems Impacts on Community Tolerances of Wasp Species within Oil Palm Plantations.

A study on micro-habitats utilizations, feeding niche overlapping, and management systems impacts pertaining to hymenopteran community were evaluated at five chosen oil palm age stands within FELDA Sungai Tekam oil palm plantations, Pahang. Samplings were done within the duration of one year, employing the standard Malaise traps, starting from February 2013 till February 2014, involving both hot and wet seasons. 60 species, from 17 families and 35 subfamilies were successfully collected during the sampling periods. Eight defined micro-habitats were elaborated, with the subdivisions of major, minor, stable, and risky micro-habitat types. Management systems impacts were associated with the applications of chemical herbicides and fertilizers. Species groups were formed using Two-Way Hierarchical Cluster Dendrogram, following 75% of information remaining. Three species groups were formed for hot and wet seasons respectively, with the first group involved nearly half of the overall hymenopteran community. Beneficial nectariferous plants, heaps of chipped rotting oil palm trunks, and remnants of rotting forest logs were all the prominent micro-habitats associated will all cases of hymenopteran species groups, for both cases of major and minor micro-habitat types. Application of BASTA, Glyphosate-Type-A and Type-B herbicides, as well as NK-Mix, Borax, and GML chemical fertilizers were all highly correlated with hymenopteran species groups, showing the high tolerance of most hymenopteran species towards the employed management systems, with reference to minor micro-habitats. Strong feeding ecological niches and plexus values between species of similar species groups formed were specifically associated with discrete but connected minor micro-habitats with weaker food chains, collectively forming larger stable food webs within major micro-habitats. Suggestions on maintaining minor micro-habitats for the survival of most hymenopteran community, as well as the sustenance of their food sources were also discussed.Â

Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages.

Background The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales. Description We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes. Conclusions Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at https://github.com/bsiranosian/tango_final.

Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages

Background The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales. Description We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes. Conclusions Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at https://github.com/bsiranosian/tango_final.

Cell-type phylogenetics and the origin of endometrial stromal cells.

A challenge of genome annotation is the identification of genes performing specific biological functions. Here, we propose a phylogenetic approach that utilizes RNA-seq data to infer the historical relationships among cell types and to trace the pattern of gene-expression changes on the tree. The hypothesis is that gene-expression changes coincidental with the origin of a cell type will be important for the function of the derived cell type. We apply this approach to the endometrial stromal cells (ESCs), which are critical for the initiation and maintenance of pregnancy. Our approach identified well-known regulators of ESCs, PGR and FOXO1, as well as genes not yet implicated in female fertility, including GATA2 and TFAP2C. Knockdown analysis confirmed that they are essential for ESC differentiation. We conclude that phylogenetic analysis of cell transcriptomes is a powerful tool for discovery of genes performing cell-type-specific functions.

Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages

Background The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales. Description We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes. Conclusions Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at https://github.com/bsiranosian/tango_final.

Link Clustering with Extended Link Similarity and EQ Evaluation Division

Link Clustering (LC) is a relatively new method for detecting overlapping communities in networks. The basic principle of LC is to derive a transform matrix whose elements are composed of the link similarity of neighbor links based on the Jaccard distance calculation; then it applies hierarchical clustering to the transform matrix and uses a measure of partition density on the resulting dendrogram to determine the cut level for best community detection. However, the original link clustering method does not consider the link similarity of non-neighbor links, and the partition density tends to divide the communities into many small communities. In this paper, an Extended Link Clustering method (ELC) for overlapping community detection is proposed. The improved method employs a new link similarity, Extended Link Similarity (ELS), to produce a denser transform matrix, and uses the maximum value of EQ (an extended measure of quality of modularity) as a means to optimally cut the dendrogram for better partitioning of the original network space. Since ELS uses more link information, the resulting transform matrix provides a superior basis for clustering and analysis. Further, using the EQ value to find the best level for the hierarchical clustering dendrogram division, we obtain communities that are more sensible and reasonable than the ones obtained by the partition density evaluation. Experimentation on five real-world networks and artificially-generated networks shows that the ELC method achieves higher EQ and In-group Proportion (IGP) values. Additionally, communities are more realistic than those generated by either of the original LC method or the classical CPM method.

Analysis of Chinese Olive Cultivars Difference by the Structural Characteristics of Oligosaccharides

Chinese olive (Canarium album (Lour.) Raeusch) is a subtropical fruit, which has been used in traditional Chinese medicine since ancient age. In the present work, the structural characteristics of oligosaccharides from C. album fruit (OCAF) fleshes were investigated. By gas chromatography analysis, both OCAF and free sugar fractions comprised fructose, glucose, and galactose, and the molar percentages varied between cultivars. Moreover, galactose was found to be the dominant monosaccharide in OCAF, while glucose was the dominant one in free sugar fraction. The glycosidic linkages of OCAF were →6)-Gal-(1→, →6)-Glu-(1→, →4)-Fru-(2→, and →1)-Gal. Hierarchical cluster dendrogram indicated that oligosaccharides of “XZ” and “HP” cultivars had a greater proximity than the others, while the oligosaccharides of “TS” cultivar had the most significant difference to the other cultivars. The growth-stimulating effect of OCAF on Lactobacillus bulgaricus and Streptococcus thermophilus was observed to vary in a dose-dependent manner.

Relationship of age and body mass index to the expression of obesity and osteoarthritis-related genes in human meniscus

ObjectiveAging and obesity contribute to the initiation and progression of osteoarthritis with little information on their relation to gene expression in joint tissues, particularly the meniscus. Here, we test the hypothesis that patient age and body mass index (BMI) correlate with the expression of osteoarthritis- and obesity-related gene signatures in the meniscus.DesignMeniscus was obtained from patients (N=68) undergoing arthroscopic partial meniscectomy. The mRNA expression of twenty-four osteoarthritis-related and four obesity-related genes in meniscus was assessed by qRT-PCR. The relationship between gene expression and patient age and BMI was analyzed using Spearman’s rank-order correlation. Hierarchical cluster dendrogram and heat maps were generated to study inter-gene associations.ResultsAge was negatively correlated (P<0.05) with the expression of MMP-1 (r=−0.447), NFκB2 (r=−0.361), NFκBIA (r=−0.312), IκBA (r=−0.308), IL-8 (r=−0.305), ADAMTS-4 (r=−0.294), APLN (r=−0.250) and IL-6 (r=−0.244). Likewise, BMI was negatively correlated with the expression of APLN (r=−0.328), ACAN (r=−0.268) and MMP-1 (r=−0.261). After adjusting for the correlation between age and BMI (r=0.310; P=0.008), the only independent effect of BMI on gene expression was for APLN (r=−0.272). However, age had an independent effect on expression on ADAMTS-4 (r=−0.253), MMP-1 (r=−0.399), IL-8 (r=−0.327), COL1A1 (r=−0.287), NFκBIA (r=−0.278), NFκB2 (r=−0.312) and IκBA (r=−0.299). The gene-correlation analysis identified four clusters of potentially relevant genes: transcription factors, matrix degrading enzymes, cytokines and chemokines, and obesity genes.ConclusionAge and BMI were negatively correlated with several osteoarthritis- and obesity-related genes. While the bulk of these changes appeared to be driven by age, expression of APLN was related to BMI. Inter-gene correlations implicated a common regulatory role of strongly correlated genes. Although age-related variations in gene expression are potentially more pertinent than obesity-related differences for the role of the meniscus in osteoarthritis development, further investigation into the role of APLN in meniscus and joint health is warranted.

Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis

BackgroundBatch effects due to sample preparation or array variation (type, charge, and/or platform) may influence the results of microarray experiments and thus mask and/or confound true biological differences. Of the published approaches for batch correction, the algorithm “Combating Batch Effects When Combining Batches of Gene Expression Microarray Data” (ComBat) appears to be most suitable for small sample sizes and multiple batches.MethodsSynovial fibroblasts (SFB; purity > 98%) were obtained from rheumatoid arthritis (RA) and osteoarthritis (OA) patients (n = 6 each) and stimulated with TNF-α or TGF-β1 for 0, 1, 2, 4, or 12 hours. Gene expression was analyzed using Affymetrix Human Genome U133 Plus 2.0 chips, an alternative chip definition file, and normalization by Robust Multi-Array Analysis (RMA). Data were batch-corrected for different acquiry dates using ComBat and the efficacy of the correction was validated using hierarchical clustering.ResultsIn contrast to the hierarchical clustering dendrogram before batch correction, in which RA and OA patients clustered randomly, batch correction led to a clear separation of RA and OA. Strikingly, this applied not only to the 0 hour time point (i.e., before stimulation with TNF-α/TGF-β1), but also to all time points following stimulation except for the late 12 hour time point. Batch-corrected data then allowed the identification of differentially expressed genes discriminating between RA and OA. Batch correction only marginally modified the original data, as demonstrated by preservation of the main Gene Ontology (GO) categories of interest, and by minimally changed mean expression levels (maximal change 4.087%) or variances for all genes of interest. Eight genes from the GO category “extracellular matrix structural constituent” (5 different collagens, biglycan, and tubulointerstitial nephritis antigen-like 1) were differentially expressed between RA and OA (RA > OA), both constitutively at time point 0, and at all time points following stimulation with either TNF-α or TGF-β1.ConclusionBatch correction appears to be an extremely valuable tool to eliminate non-biological batch effects, and allows the identification of genes discriminating between different joint diseases. RA-SFB show an upregulated expression of extracellular matrix components, both constitutively following isolation from the synovial membrane and upon stimulation with disease-relevant cytokines or growth factors, suggesting an “imprinted” alteration of their phenotype.

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering

High-throughput sequencing of 16S rRNA genes has increased our understanding of microbial community structure, but now even higher-throughput methods to the Illumina scale allow the creation of much larger datasets with more samples and orders-of-magnitude more sequences that swamp current analytic methods. We developed a method capable of handling these larger datasets on the basis of assignment of sequences into an existing taxonomy using a supervised learning approach (taxonomy-supervised analysis). We compared this method with a commonly used clustering approach based on sequence similarity (taxonomy-unsupervised analysis). We sampled 211 different bacterial communities from various habitats and obtained ∼1.3 million 16S rRNA sequences spanning the V4 hypervariable region by pyrosequencing. Both methodologies gave similar ecological conclusions in that β-diversity measures calculated by using these two types of matrices were significantly correlated to each other, as were the ordination configurations and hierarchical clustering dendrograms. In addition, our taxonomy-supervised analyses were also highly correlated with phylogenetic methods, such as UniFrac. The taxonomy-supervised analysis has the advantages that it is not limited by the exhaustive computation required for the alignment and clustering necessary for the taxonomy-unsupervised analysis, is more tolerant of sequencing errors, and allows comparisons when sequences are from different regions of the 16S rRNA gene. With the tremendous expansion in 16S rRNA data acquisition underway, the taxonomy-supervised approach offers the potential to provide more rapid and extensive community comparisons across habitats and samples.

IGEMDOCK: a graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis

BackgroundPharmacological interactions are useful for understanding ligand binding mechanisms of a therapeutic target. These interactions are often inferred from a set of active compounds that were acquired experimentally. Moreover, most docking programs loosely coupled the stages (binding-site and ligand preparations, virtual screening, and post-screening analysis) of structure-based virtual screening (VS). An integrated VS environment, which provides the friendly interface to seamlessly combine these VS stages and to identify the pharmacological interactions directly from screening compounds, is valuable for drug discovery.ResultsWe developed an easy-to-use graphic environment, iGEMDOCK, integrating VS stages (from preparations to post-screening analysis). For post-screening analysis, iGEMDOCK provides biological insights by deriving the pharmacological interactions from screening compounds without relying on the experimental data of active compounds. The pharmacological interactions represent conserved interacting residues, which often form binding pockets with specific physico-chemical properties, to play the essential functions of a target protein. Our experimental results show that the pharmacological interactions derived by iGEMDOCK are often hot spots involving in the biological functions. In addition, iGEMDOCK provides the visualizations of the protein-compound interaction profiles and the hierarchical clustering dendrogram of the compounds for post-screening analysis.ConclusionsWe have developed iGEMDOCK to facilitate steps from preparations of target proteins and ligand libraries toward post-screening analysis. iGEMDOCK is especially useful for post-screening analysis and inferring pharmacological interactions from screening compounds. We believe that iGEMDOCK is useful for understanding the ligand binding mechanisms and discovering lead compounds. iGEMDOCK is available at http://gemdock.life.nctu.edu.tw/dock/igemdock.php.

Aquatic contaminants alter genes involved in neurotransmitter synthesis and gonadotropin release in largemouth bass

Many aquatic contaminants potentially affect the central nervous system, however the underlying mechanisms of how toxicants alter normal brain function are not well understood. The objectives of this study were to compare the effects of emerging and prevalent environmental contaminants on the expression of brain transcripts with a role in neurotransmitter synthesis and reproduction. Adult male largemouth bass ( Micropterus salmoides) were injected once for a 96 h duration with control (water or oil) or with one of two doses of a single chemical to achieve the following body burdens (μg/g): atrazine (0.3 and 3.0), toxaphene (10 and 100), cadmium (CdCl 2) (0.000067 and 0.00067), polychlorinated biphenyl (PCB) 126 (0.25 and 2.5), and phenanthrene (5 and 50). Partial largemouth bass gene segments were cloned for enzymes involved in neurotransmitter (glutamic acid decarboxylase 65, GAD65; tyrosine hydroxylase) and estrogen (brain aromatase; CYP19b) synthesis for real-time PCR assays. In addition, neuropeptides regulating feeding (neuropeptide Y) and reproduction (chicken GnRH-II, cGnRH-II; salmon GnRH, sGnRH) were also investigated. Of the chemicals tested, only cadmium, PCB 126, and phenanthrene showed any significant effects on the genes tested, while atrazine and toxaphene did not. Cadmium (0.000067 μg/g) significantly increased cGnRH-II mRNA while PCB 126 (0.25 μg/g) decreased GAD65 mRNA. Phenanthrene decreased GAD65 and tyrosine hydroxylase mRNA levels at the highest dose (50 μg/g) but increased cGnRH-II mRNA at the lowest dose (5 μg/g). CYP19b, NPY, and sGnRH mRNA levels were unaffected by any of the treatments. A hierarchical clustering dendrogram grouped PCB 126 and phenanthrene more closely than other chemicals with respect to the genes tested. This study demonstrates that brain transcripts important for neurotransmitter synthesis neuroendocrine function are potential targets for emerging and prevalent aquatic contaminants.

A new method for hierarchical clustering combination

In the field of pattern recognition, combining different classifiers into a robust classifier is a common approach for improving classification accuracy. Recently, this trend has also been used to improve clustering performance especially in non-hierarchical clustering approaches. Generally hierarchical clustering is preferred in comparison with the partitional clustering for applications when the exact number of the clusters is not determined or when we are interested in finding the relation between clusters. To the best of our knowledge clustering combination methods proposed so far are based on partitional clustering and hierarchical clustering has been ignored. In this paper, a new method for combining hierarchical clustering is proposed. In this method, in the first step the primary hierarchical clustering dendrograms are converted to matrices. Then these matrices, which describe the dendrograms, are aggregated (using the matrix summation operator) into a final matrix with which the final clustering is formed. The effectiveness of different well known dendrogram descriptors and the one proposed by us for representing the dendrograms are evaluated and compared. The results show that all these descriptor work well and more accurate results (hierarchy of clusters) are obtained using hierarchical combination than combination of partitional clusterings.

Fast Gene Ontology based clustering for microarray experiments

BackgroundAnalysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses.ResultsWe present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster.ConclusionOur R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Automatic detection of cohesive subgroups within social hypertext: A heuristic approach

The problem of identifying cohesive subgroups in social hypertext is reviewed. A computationally efficient three-step framework for identifying cohesive subgroups is proposed, referred to as the Social Cohesion Analysis of Networks (SCAN) method. In the first step of this method (Select), people within a social network are screened using a level of network centrality to select possible subgroup members. In the second step (Collect), the people selected in the first step are collected into subgroups identified at each point in time using hierarchical cluster analysis. In the third step (Choose), similarity modeling is used to choose cohesive subgroups based on the similarity of subgroups when compared across different points in time. The application of this SCAN method is then demonstrated in a case study where a subgroup is automatically extracted from a social network formed based on the online interactions of a group of about 150 people that occurred over a two-year period. In addition, this paper also demonstrates that similarity-based cohesion can provide a different, and in this case more compelling, subgroup representation than a method based on splitting a hierarchical clustering dendrogram using an optimality criterion.

Potential Chemosignals in the Anogenital Gland Secretion of Giant Pandas, Ailuropoda melanoleuca, Associated with Sex and Individual Identity

With a combination of dichloromethane extraction and analysis by gas chromatography-mass spectrometry (GC-MS), we found 39 compounds (corresponding to 38 GC peaks) in the anogenital gland secretion (AGS) of captive adult giant pandas, Ailuropoda melanoleuca, during the non-mating season. In addition to indole, squalene, and some of the straight-chain fatty acids that had been characterized previously from the AGS of giant pandas, we identified several new compounds such as decenal, two isomers of decadienal, phenylacetic acid, 5-methylhydantoin, hydroquinone, phenylpropanoic acid, and erucic acid. Quantitative comparison of the relative abundances of the 20 main GC peaks revealed that 5-methylhydantoin, indole, and erucic acid are putative female pheromones, whereas squalene and hydroquinone are putative male pheromones. In addition to the presence of a few individual-specific compounds, the relative abundances of most of the 21 constituents varied more among individuals than within individuals. This suggests that individual identity might be coded in both digital and analog form. The chemical composition of different AGS samples from the same pandas consistently displayed a minimum cluster distance, much smaller than that between samples from different individuals in a hierarchical linkage cluster (average linkage) dendrogram. Our results indicate that the AGS might contain an "odor fingerprint." Although putative sex pheromones such as squalene and erucic acid should be assessed further by bioassay, our study suggests that synthetic chemosignals might be useful in modulating the behavior and physiology of giant pandas.

Analysis of the major histocompatibility complex in graft rejection revisited by gene expression profiles.

The precise role of major histocompatibility complex (MHC) molecules in graft rejection remains incompletely understood. The important role of foreign peptides in the alloimmune response was recently recognized. We performed a comparative study of the functions of minor antigens Class I, Class II, and CD1 in murine cardiac allograft rejection by investigating the expression of a large panel of immune and inflammatory genes. To investigate the role of MHC Class II and I, our protocol analyzed allograft recipients deficient in MHC Class II and b2 microglobulin (b2-M), a critical component of the Class I heterodimer. We also included CD1 deficient recipients to differentiate effects in the beta2-M deficient strain due to CD1 deficiency versus the combined inactivation of CD1 and Class I. The serum cytokines tumor necrosis factor (TNF)-alpha interleukin (IL)-6, interferon (IFN)-gamma and IL-1beta were evaluated posttransplant by ELISA. The intragraft expression of 55 chemokines, chemokine receptors, and CD markers were measured by ribonuclease protection assay. The data were analyzed through hierarchical clustering dendrograms and self-organizing maps. The analysis indicates that each gene deficiency induces both the upregulation and the downregulation of distinct subsets of genes and that similar kinetics of rejection can be attributed to different molecular mechanisms. The study provides novel insights into the role of classical and non-classical MHC molecules in graft rejection.

Expression profiles in the progression of ductal carcinoma in the breast

An understanding of the multi-step nature of cancer as it is in the breast, as a series of pivotal genetic/epigenetic modifications is irrefutably a milestone in diagnostics, prognostics and eventually providing a cure. Here we have utilised a variant of analysis of variance (ANOVA) as a model for the identification and tracking of specific mRNA species whose transcription has been significantly altered at each grade in the progression of ductal carcinoma, making it possible to correlate histological progression with the genetic events underlying breast cancer. We show that in the progression of ductal carcinomas, from grade 1 to 3, there is a reduction in the actual number of mRNA species, which are significantly over or under expressed. We also show that this technique can be employed to generate differential gene expression patterns, whereby the combined expression profile of the tailored spectra of genes in the comparison of each ductal grade is sufficient to render them on clearly separate arms of an array-wise hierarchical cluster dendrogram.