Energy Trade-Off and Four Extreme Human Body Types

BACKGROUND

Resource trade-off theory suggests that increased performance on a given trait comes at the cost of decreased performance on other traits.

METHODS

Growth data from 1889 subjects (996 girls) were used from the GrowUp1974 Gothenburg study. Energy Trade-Off (ETO) between height and weight for individuals with extreme body types was characterized using a novel ETO-Score (ETOS). Four extreme body types were defined based on height and ETOI at early adulthood: tall-slender, short-stout, short-slender, and tall-stout; their growth trajectories assessed from ages 0.5-17.5 years.A GWAS using UK BioBank data was conducted to identify gene variants associated with height, BMI, and for the first time with ETOS.

RESULTS

Height and ETOS trajectories show a two-hit pattern with profound changes during early infancy and at puberty for tall-slender and short-stout body types.Several loci (including FTO, ADCY3, GDF5, ) and pathways were identified by GWAS as being highly associated with ETOS. The most strongly associated pathways were related to 'extracellular matrix', 'signal transduction', 'chromatin organization', and 'energy metabolism'.

CONCLUSIONS

ETOS represents a novel anthropometric trait with utility in describing body types. We discovered the multiple genomic loci and pathways probably involved in energy trade-off.

Personalized approach to childhood obesity: Lessons from gut microbiota and omics studies. Narrative review and insights from the 29th European childhood obesity congress

The traditional approach to childhood obesity prevention and treatment should fit most patients, but misdiagnosis and treatment failure could be observed in some cases that lie away from average as part of individual variation or misclassification. Here, we reflect on the contributions that high-throughput technologies such as next-generation sequencing, mass spectrometry-based metabolomics and microbiome analysis make towards a personalized medicine approach to childhood obesity. We hypothesize that diagnosing a child as someone with obesity captures only part of the phenotype; and that metabolomics, genomics, transcriptomics and analyses of the gut microbiome, could add precision to the term "obese," providing novel corresponding biomarkers. Identifying a cluster -omic signature in a given child can thus facilitate the development of personalized prognostic, diagnostic, and therapeutic approaches. It can also be applied to the monitoring of symptoms/signs evolution, treatment choices and efficacy, predisposition to drug-related side effects and potential relapse. This article is a narrative review of the literature and summary of the main observations, conclusions and perspectives raised during the annual meeting of the European Childhood Obesity Group. Authors discuss some recent advances and future perspectives on utilizing a systems approach to understanding and managing childhood obesity in the context of the existing omics data.

Prediction of Adult Height by Machine Learning Technique

CONTEXT

Prediction of AH is frequently undertaken in the clinical setting. The commonly used methods are based on the assessment of skeletal maturation. Predictive algorithms generated by machine learning, which can already automatically drive cars and recognize spoken language, are the keys to unlocking data that can precisely inform the pediatrician for real-time decision making.

OBJECTIVE

To use machine learning (ML) to predict adult height (AH) based on growth measurements until age 6 years.

METHODS

Growth data from 1596 subjects (798 boys) aged 0-20 years from the longitudinal GrowUp 1974 Gothenburg cohort were utilized to train multiple ML regressors. Of these, 100 were used for model comparison, the rest was used for 5-fold cross-validation. The winning model, random forest (RF), was first validated on 684 additional subjects from the 1974 cohort. It was additionally validated using 1890 subjects from the GrowUp 1990 Gothenburg cohort and 145 subjects from the Edinburgh Longitudinal Growth Study cohort.

RESULTS

RF with 51 regression trees produced the most accurate predictions. The best predicting features were sex and height at age 3.4-6.0 years. Observed and predicted AHs were 173.9 ± 8.9 cm and 173.9 ± 7.7 cm, respectively, with prediction average error of -0.4 ± 4.0 cm. Validation of prediction for 684 GrowUp 1974 children showed prediction accuracy r = 0.87 between predicted and observed AH (R2 = 0.75). When validated on the 1990 Gothenburg and Edinburgh cohorts (completely unseen by the learned RF model), the prediction accuracy was r = 0.88 in both cases (R2 = 0.77). AH in short children was overpredicted and AH in tall children was underpredicted. Prediction absolute error correlated negatively with AH (P < .0001).

CONCLUSION

We show successful, validated ML of AH using growth measurements before age 6 years. The most important features for prediction were sex, and height at age 3.4-6.0. Prediction errors result in over- or underestimates of AH for short and tall subjects, respectively. Prediction by ML can be generalized to other cohorts.

Steroid Metabolomic Signature of Insulin Resistance in Childhood Obesity

OBJECTIVE

On the basis of urinary steroidal gas chromatography-mass spectrometry (GC-MS), we previously defined a novel concept of a disease-specific "steroid metabolomic signature" and reclassified childhood obesity into five groups with distinctive signatures. The objective of the current study was to delineate the steroidal signature of insulin resistance (IR) in obese children.

RESEARCH DESIGN AND METHODS

Urinary samples of 87 children (44 girls) aged 8.5-17.9 years with obesity (BMI >97th percentile) were quantified for 31 steroid metabolites by GC-MS. Defined as HOMA-IR >95th percentile and fasting glucose-to-insulin ratio >0.3, IR was diagnosed in 20 (of 87 [23%]) of the examined patients. The steroidal fingerprints of subjects with IR were compared with those of obese children without IR (non-IR). The steroidal signature of IR was created from the product of IR - non-IR for each of the 31 steroids.

RESULTS

IR and non-IR groups of children had comparable mean age (13.7 ± 1.9 and 14.6 ± 2.4 years, respectively) and z score BMI (2.7 ± 0.5 and 2.7 ± 0.5, respectively). The steroidal signature of IR was characterized by high adrenal androgens, glucocorticoids, and mineralocorticoid metabolites; higher 5α-reductase (An/Et) (P = 0.007) and 21-hydroxylase [(THE + THF + αTHF)/PT] activity (P = 0.006); and lower 11βHSD1 [(THF + αTHF)/THE] activity (P = 0.012).

CONCLUSIONS

The steroidal metabolomic signature of IR in obese children is characterized by enhanced secretion of steroids from all three adrenal pathways. As only the fasciculata and reticularis are stimulated by ACTH, these findings suggest that IR directly affects the adrenals. We suggest a vicious cycle model, whereby glucocorticoids induce IR, which could further stimulate steroidogenesis, even directly. We do not know whether obese children with IR and the new signature may benefit from amelioration of their hyperadrenalism.

Steroid metabolomic signature of liver disease in nonsyndromic childhood obesity

OBJECTIVE

Analysis of steroids by gas chromatography-mass spectrometry (GC-MS) defines a subject's steroidal fingerprint. Here, we compare the steroidal fingerprints of obese children with or without liver disease to identify the 'steroid metabolomic signature' of childhood nonalcoholic fatty liver disease.

METHODS

Urinary samples of 85 children aged 8.5-18.0 years with BMI >97% were quantified for 31 steroid metabolites by GC-MS. The fingerprints of 21 children with liver disease (L1) as assessed by sonographic steatosis (L1L), elevated alanine aminotransferases (L1A) or both (L1AL), were compared to 64 children without markers of liver disease (L0). The steroidal signature of the liver disease was generated as the difference in profiles of L1 against L0 groups.

RESULTS

L1 comparing to L0 presented higher fasting triglycerides (P = 0.004), insulin (P = 0.002), INS/GLU (P = 0.003), HOMA-IR (P = 0.002), GGTP (P = 0.006), AST/SGOT (P = 0.002), postprandial glucose (P = 0.001) and insulin (P = 0.011). L1AL showed highest level of T-cholesterol and triglycerides (P = 0.029; P = 0.044). Fasting insulin, postprandial glucose, INS/GLU and HOMA-IR were highest in L1L and L1AL (P = 0.001; P = 0.017; P = 0.001; P = 0.001). The liver disease steroidal signature was marked by lower DHEA and its metabolites, higher glucocorticoids (mostly tetrahydrocortisone) and lower mineralocorticoid metabolites than L0. L1 patients showed higher 5α-reductase and 21-hydroxylase activity (the highest in L1A and L1AL) and lower activity of 11βHSD1 than L0 (P = 0.041, P = 0.009, P = 0.019).

CONCLUSIONS

The 'steroid metabolomic signature' of liver disease in childhood obesity provides a new approach to the diagnosis and further understanding of its metabolic consequences. It reflects the derangements of steroid metabolism in NAFLD that includes enhanced glucocorticoids and deranged androgens and mineralocorticoids.

Outcomes of pubertal development in girls as a function of pubertal onset age

BACKGROUND

The relationship between pubertal onset and tempo and pubertal growth is controversial. We hypothesized that the age at onset of girls' puberty predicts pubertal tempo and the rate of pubertal progression.

METHODS

We analysed the data of 380 girls from the prospective Study of Early Child Care and Youth Development (SECCYD), who were recruited in the USA from 1991-2006 and followed from birth to age 15.5 years. We used the following indicators: thelarche age (Tanner stage B2), pubarche age (P2), menarche age (M), the age when breast (B5) and pubic hair (P5) became fully mature, pubertal growth, pubertal duration (time from B2 to B5), pubertal progression (time from B2 to M). We clustered the girls according to B2 age into early onset (EO;<9.4 years), intermediate (IO;9.4-10.5 years), late onset (LO;>10.5 years).

RESULTS

All indicators of pubertal onset and conclusion occurred earlier in the EOs than in the LO; yet, the differences in the age at main pubertal milestones lessened as puberty progressed: two years for B2; -1.4 years for M; - one year for B5. In EO, puberty was one year (average) longer than in LO. Although EO grew 7 cm (average) more than LO, their heights at B5 were comparable. There was a significant relationship between the thelarche age and puberty tempo (r=0.23, P<0.0001).

CONCLUSIONS

The study highlights the predictive nature of variation in the onset age of puberty on its progression and duration. These results are reassuring in this context and will add to clinicians' and parental understanding of the expected milestones of puberty.

High abundance of ArfGAP1 found in the mossy fibers in hilus of the dentate gyrus region of the mouse brain

The Arf GTPase-activating protein ArfGAP1 and its brain-specific isoform ArfGAP1^B play an important role in neurotransmission. Here we analyzed the distribution of ArfGAP1 in the mouse brain. We found high levels of ArfGAP1 in the mouse dentate gyrus where it displayed especially elevated level in the polymorph layer (hilus). Importantly, the ArfGAP1 signal follows the pathway of the granular cell axons so-called mossy fibers which extend from the dentate gyrus to CA3 via stratum lucidum and partially stratum oriens. Additionally, we identified differential expression of ArfGAP1 in the isocortex. Thus, staining with anti-ArfGAP1 antibodies allows distinction between cortical cell layers 1, 2, 3 and 5 from 4 and 6. Taken together, our data suggest that ArfGAP1 can be used as a specific marker of the dentate mossy fibers and as for visualization of cortical layers in immunohistochemical studies.

Steroid Metabolomic Disease Signature of Nonsyndromic Childhood Obesity

CONTEXT

The profile of urinary steroids as measured by gas chromatography-mass spectrometry defines a subject's "steroidal fingerprint."

OBJECTIVE

Here, we clustered steroidal fingerprints to characterize patients with nonsyndromic childhood obesity by "steroid metabolomic signatures."

HYPOTHESIS

Nonsyndromic obesity is a symptom of different diseases and conditions, some of them will have their own signature.

DESIGN

A total of 31 steroid metabolites were quantified by gas chromatography-mass spectrometry, and their excretion rates were z-transformed. Using MetaboAnalyst 3.0, we divided the subjects into 5 distinctive groups by k-means clustering. Steroidal fingerprints and clinical/biochemical data of patients in each cluster were analyzed.

PATIENTS

A total of 87 obese children (44 females), aged 8.5-17.9 years, were clinically characterized, and their 24-hour urine was collected.

RESULTS

Cluster 1 (n = 39, 21 females) had normal steroid profile. Cluster 2 (n = 20, 11 females) showed mild, nonspecific elevation of C19 and C21 steroids, females' resistance to polycystic ovary morphology, and hirsutism. Cluster 3 (n = 7 female), with relative 21-hydroxylase insufficiency, was characterized by partial or full polycystic ovary syndrome. Cluster 4 (n = 4 males), showed markedly elevated C21 steroids and imbalance in the 11β-hydroxysteroid dehydrogenase system, higher insulin, increased frequency of glucose/insulin index more than 0.3, γ-glutamyl transpeptidase activity, systolic blood pressure, and tendency to liver steatosis. Cluster 5 (n = 17, 5 females) had elevated dehydroepiandrosterone and 17-OH-pregnenolone metabolites, suggesting 3β-hydroxysteroid dehydrogenase insufficiency but no clinically unique phenotype. Z-score body mass index values were not significantly different between the clusters.

CONCLUSIONS

We defined a novel concept of disease-specific steroid metabolomic signature based on urinary steroidal gas chromatography-mass spectrometry. Clustering by software designed for metabolic data analysis reclassified childhood obesity into 5 groups with distinctive signatures; groups require further definition and may require cluster-specific therapeutic strategies.

Pheromone-encoding mRNA is transported to the yeast mating projection by specific RNP granules

In response to mating pheromone, the yeast MFA2 mRNA is transported to the tip of the mating projection as an RNP granule and translated; integrity of the granules is required for normal mRNA transport and for the mating process.

Association of messenger RNAs with large complexes such as processing bodies (PBs) plays a pivotal role in regulating their translation and decay. Little is known about other possible functions of these assemblies. Exposure of haploid yeast cells, carrying mating type “a,” to “α pheromone” stimulates polarized growth resulting in a “shmoo” projection; it also induces synthesis of “a pheromone,” encoded by MFA2. In this paper, we show that, in response to α pheromone, MFA2 mRNA is assembled with two types of granules; both contain some canonical PB proteins, yet they differ in size, localization, motility, and sensitivity to cycloheximide. Remarkably, one type is involved in mRNA transport to the tip of the shmoo, whereas the other—in local translation in the shmoo. Normal assembly of these granules is critical for their movement, localization, and for mating. Thus, MFA2 mRNAs are transported to the shmoo tip, in complex with PB-like particles, where they are locally translated.

Environmental rather than genetic factors determine the variation in the age of the infancy to childhood transition: a twins study

OBJECTIVE

Using a twins study, we sought to assess the contribution of genetic against environmental factor as they affect the age at transition from infancy to childhood (ICT).

STUDY DESIGN

The subjects were 56 pairs of monozygotic twins, 106 pairs of dizygotic twins, and 106 pairs of regular siblings (SBs), for a total of 536 children. Their ICT was determined, and a variance component analysis was implemented to estimate components of the familial variance, with simultaneous adjustment for potential covariates.

RESULTS

We found substantial contribution of the common environment shared by all types of SBs that explained 27.7% of the total variance in ICT, whereas the common twin environment explained 9.2% of the variance, gestational age 3.5%, and birth weight 1.8%. In addition, 8.7% was attributable to sex difference, but we found no detectable contribution of genetic factors to inter-individual variation in ICT age.

CONCLUSIONS

Developmental plasticity impacts much of human growth. Here we show that of the ∼50% of the variance provided to adult height by the ICT, 42.2% is attributable to adaptive cues represented by shared twin and SB environment, with no detectable genetic involvement.

Genome-wide SNP-genotyping array to study the evolution of the human pathogen Vibrio vulnificus biotype 3

Vibrio vulnificus is an aquatic bacterium and an important human pathogen. Strains of V. vulnificus are classified into three different biotypes. The newly emerged biotype 3 has been found to be clonal and restricted to Israel. In the family Vibrionaceae, horizontal gene transfer is the main mechanism responsible for the emergence of new pathogen groups. To better understand the evolution of the bacterium, and in particular to trace the evolution of biotype 3, we performed genome-wide SNP genotyping of 254 clinical and environmental V. vulnificus isolates with worldwide distribution recovered over a 30-year period, representing all phylogeny groups. A custom single-nucleotide polymorphism (SNP) array implemented on the Illumina GoldenGate platform was developed based on 570 SNPs randomly distributed throughout the genome. In general, the genotyping results divided the V. vulnificus species into three main phylogenetic lineages and an additional subgroup, clade B, consisting of environmental and clinical isolates from Israel. Data analysis suggested that 69% of biotype 3 SNPs are similar to SNPs from clade B, indicating that biotype 3 and clade B have a common ancestor. The rest of the biotype 3 SNPs were scattered along the biotype 3 genome, probably representing multiple chromosomal segments that may have been horizontally inserted into the clade B recipient core genome from other phylogroups or bacterial species sharing the same ecological niche. Results emphasize the continuous evolution of V. vulnificus and support the emergence of new pathogenic groups within this species as a recurrent phenomenon. Our findings contribute to a broader understanding of the evolution of this human pathogen.

Peer group normalization and urine to blood context in steroid metabolomics: the case of CAH and obesity

Traditional interpretation of GC-MS output involved the semi-quantitative estimation of outstanding low or high specific metabolites and the ratio between metabolites. Here, we utilize a systems biology approach to steroid metabolomics of a complex steroid-related disorder, using an all-inclusive analysis of the steroidal pathway in the form of a subject steroidal fingerprint and disease signature, providing novel methods of normalization and visualization. The study compares 324 normal children to pure enzymatic deficiency in 27 untreated 21-hydroxylase CAH patients and to complex disease in 70 children with obesity. Steroid profiles were created by quantitative data generated by GC-MS analyses. A novel peer-group normalization method defined each individual subject's control group in a multi-dimensional space of metadata parameters. Classical steroid pathway visualization was enhanced by adding urinary end-product sub-nodes and by color coding of semi-quantitative metabolic concentrations and enzymatic activities. Unbiased automated data analysis confirmed the common knowledge for CAH - the inferred 17-hydroxyprogesterone was up-regulated and the inferred 21-hydroxylase enzyme activity was down-regulated. In childhood obesity, we observe a general decrease of both glucocorticoid and mineralocorticoid metabolites, increased androgens, up-regulation of 17,20-lyase, 17-OHase and 11β-HSD1 activity and down-regulation of 21-OHase enzymatic activity. Our study proved novel normalization and visualization techniques are to be useful in identifying subject fingerprint and disease signature in enzymatic deficiency and insufficiency, while demonstrating hypothesis generation in a complex disease such as childhood obesity.

GeneCards Version 3: the human gene integrator

GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73 000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards’ unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene’s functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite.

Database URL:www.genecards.org

Alterations in micro-ribonucleic acid expression profiles reveal a novel pathway for estrogen regulation

Estrogens are steroid hormones that have been implicated in a variety of cellular and physiological processes in the development of diseases such as cancer and are also known to be associated with the effects of endocrine disrupting chemicals. Here we show that 17beta-estradiol (E(2)) alters microRNA (miRNA) expression profiles in the adult zebrafish (Danio rerio). An association between E(2) and the expression of 25 miRNAs was found 12 h after treatment. Among the most up-regulated miRNAs were miR-196b and let-7h, and the most down-regulated miRNAs included miR-130c and miR-101a. Tissue-specific changes in the transcripts levels of estrogen receptors (Esr1, Esr2a, and Esr2b) and miRNAs were found after hormone treatment. The most up-regulated miR-196b and its precursors are highly expressed in the skin and showed similar tissue-specific expression patterns after treatment, indicating a common pattern of regulation by E(2). MiR-196b was shown to fine-tune the expression of its target gene Hoxb8a after treatment in whole-body homogenates. Taken together, our results suggest a novel pathway for the multifunctional and pleiotropic effects of estrogens and open new directions for future investigations of their association with miRNAs involved in estrogen-regulated physiological processes and diseases.

Novel definition files for human GeneChips based on GeneAnnot

BACKGROUND

Improvements in genome sequence annotation revealed discrepancies in the original probeset/gene assignment in Affymetrix microarray and the existence of differences between annotations and effective alignments of probes and transcription products. In the current generation of Affymetrix human GeneChips, most probesets include probes matching transcripts from more than one gene and probes which do not match any transcribed sequence.

RESULTS

We developed a novel set of custom Chip Definition Files (CDF) and the corresponding Bioconductor libraries for Affymetrix human GeneChips, based on the information contained in the GeneAnnot database. GeneAnnot-based CDFs are composed of unique custom-probesets, including only probes matching a single gene.

CONCLUSION

GeneAnnot-based custom CDFs solve the problem of a reliable reconstruction of expression levels and eliminate the existence of more than one probeset per gene, which often leads to discordant expression signals for the same transcript when gene differential expression is the focus of the analysis. GeneAnnot CDFs are freely distributed and fully compliant with Affymetrix standards and all available software for gene expression analysis. The CDF libraries are available from http://www.xlab.unimo.it/GA_CDF, along with supplementary information (CDF libraries, installation guidelines and R code, CDF statistics, and analysis results).

High-resolution physical and functional mapping of the template adjacent DNA binding site in catalytically active telomerase

Telomerase is a cellular reverse transcriptase, which utilizes an integral RNA template to extend single-stranded telomeric DNA. We used site-specific photocrosslinking to map interactions between DNA primers and the catalytic protein subunit (tTERT) of Tetrahymena thermophila telomerase in functional enzyme complexes. Our assays reveal contact of the single-stranded DNA adjacent to the primer-template hybrid and tTERT residue W187 at the periphery of the N-terminal domain. This contact was detected in complexes with three different registers of template in the active site, suggesting that it is maintained throughout synthesis of a complete telomeric repeat. Substitution of nearby residue Q168, but not W187, alters the K(m) for primer elongation, implying that it plays a role in the DNA recognition. These findings are the first to directly demonstrate the physical location of TERT-DNA contacts in catalytically active telomerase and to identify amino acid determinants of DNA binding affinity. Our data also suggest a movement of the TERT active site relative to the template-adjacent single-stranded DNA binding site within a cycle of repeat synthesis.

An integrative method for accurate comparative genome mapping

We present MAGIC, an integrative and accurate method for comparative genome mapping. Our method consists of two phases: preprocessing for identifying "maximal similar segments," and mapping for clustering and classifying these segments. MAGIC's main novelty lies in its biologically intuitive clustering approach, which aims towards both calculating reorder-free segments and identifying orthologous segments. In the process, MAGIC efficiently handles ambiguities resulting from duplications that occurred before the speciation of the considered organisms from their most recent common ancestor. We demonstrate both MAGIC's robustness and scalability: the former is asserted with respect to its initial input and with respect to its parameters' values. The latter is asserted by applying MAGIC to distantly related organisms and to large genomes. We compare MAGIC to other comparative mapping methods and provide detailed analysis of the differences between them. Our improvements allow a comprehensive study of the diversity of genetic repertoires resulting from large-scale mutations, such as indels and duplications, including explicitly transposable and phagic elements. The strength of our method is demonstrated by detailed statistics computed for each type of these large-scale mutations. MAGIC enabled us to conduct a comprehensive analysis of the different forces shaping prokaryotic genomes from different clades, and to quantify the importance of novel gene content introduced by horizontal gene transfer relative to gene duplication in bacterial genome evolution. We use these results to investigate the breakpoint distribution in several prokaryotic genomes.

Potential photosynthesis gene recombination between Prochlorococcus and Synechococcus via viral intermediates

Genes (psbA and psbD) encoding for photosynthetically important proteins were recently found in a number of cultured cyanophage genomes. This phenomenon may be a beneficial trait to the viruses or their photosynthetic cyanobacterial hosts, or may represent an untapped pool of genes involved in the formation of the photosynthetic apparatus that are prone to lateral gene transfer. Here we show analyses of psbA genes from uncultured environmental viruses and prophage populations. We observe a statistically significant separation between viral genes and their potential Synechococcus hosts' genes, and statistical analyses under models of codon evolution indicate that the psbA genes of viruses are evolving under levels of purifying selection that are virtually indistinguishable from their hosts. Furthermore, our data also indicate the possible exchange and reshuffling of psbA genes between Synechococcus and Prochlorococcus via phage intermediates. Overall, these observations raise the possibility that marine viruses serve as a potential genetic pool in shaping the evolution of cyanobacterial photosynthesis.

Annotation of androgen dependence to human prostate cancer-associated genes by microarray analysis of mouse prostate

In silico methods and array technologies have identified genes differentially expressed in prostate cancer. Biological functions of the identified genes are often unclear. Considering the biological significance of androgens in prostate cancer, we profiled the prostate transcripts of congenital androgen-deficient mice with or without androgen replacement in vivo using murine gene expression array. In parallel genes differentially expressed in human prostate cancer were identified by Digital Differential Display and the Serial Analysis of Gene Expression. Androgen dependence of the identified genes was then determined by the steady-state mRNA levels of the murine orthologs in response to androgen treatment. The annotation is supported by the finding that some of the androgen target genes have been reported previously with independent experiments.

GeneTide--Terra Incognita Discovery Endeavor: a new transcriptome focused member of the GeneCards/GeneNote suite of databases

GeneCards® is an automatically mined database of human genes that strives to create, along with its auxiliary databases—GeneLoc, GeneNote and GeneAnnot—the most inclusive resource of gene-centered information of the human genome. GeneTide, the Gene Terra Incognita Discovery Endeavor (http://genecards.weizmann.ac.il/genetide/), the newest addition to this family, is a transcriptome-focused database which aims to enhance GeneCards with additional expressed sequence tag (EST)-based genes. This is achieved by comprehensively mapping >85% of the ∼5.6 million human ESTs currently available at dbEST to known genes by means of data mining and integration of genomic resources including UniGene, DoTS, AceView and in-house resources. GeneTide thus creates comprehensive links between ESTs and GeneCards genes. Furthermore, groups of unassociated transcripts serve as a basis for defining novel EST-based GeneCards Candidates (EGCs). These EGCs, nearly 25 000 of which were defined in version 0.3 of GeneTide, are further annotated with various parameters, including splicing evidence and expression data extracted from the GeneNote database, to determine their validity as possible de novo genes.

Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification

MOTIVATION

Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression.

RESULTS

To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index tau, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15< tau<0.85 were found to constitute >50% of all expression patterns. We developed a binary classification, indicating for every gene the I(B) tissues in which it is overly expressed, and the 12-I(B) tissues in which it shows low expression. The 85 dominant midrange patterns with I(B)=2-11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny.

AVAILABILITY

All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803.

CONTACT

doron.lancet@weizmann.ac.il

SUPPLEMENTARY INFORMATION

Four tables available at the above site.

GeneAnnot: interfacing GeneCards with high-throughput gene expression compendia

The interpretation of microarray expression results often includes extensive efforts to identify and annotate the gene representatives immobilised on the arrays. In this paper we describe the usage of our automatic GeneAnnot system, which links between Affymetrix arrays and the rich human gene annotations available in GeneCards. We explain GeneCards search options and results display; elaborate on the presentation of expression information in GeneCards, including both our whole-genome GeneNote project and external expression resources; describe the various parameters and displays used by GeneAnnot to assess the annotation quality and probeset specificity; and show how to search GeneAnnot and GeneNote websites directly.

GeneNote: whole genome expression profiles in normal human tissues

A novel data set, GeneNote (Gene Normal Tissue Expression), was produced to portray complete gene expression profiles in healthy human tissues using the Affymetrix GeneChip HG-U95 set, which includes 62 839 probe-sets. The hybridization intensities of two replicates were processed and analyzed to yield the complete transcriptome for twelve human tissues. Abundant novel information on tissue specificity provides a baseline for past and future expression studies related to diseases. The data is posted in GeneNote (http://genecards.weizmann.ac.il/genenote/), a widely used compendium of human genes (http://bioinfo.weizmann.ac.il/genecards).

GeneAnnot: comprehensive two-way linking between oligonucleotide array probesets and GeneCards genes

MOTIVATION

High density oligonucleotide arrays are usually annotated in a one-to-one fashion, with each probeset assigned to one gene. However, in reality, subsets of oligonucleotides in a probeset may match sequences within more than one gene, potentially leading to misinterpretations. Moreover, a gene is often represented by more than one probeset, and analyzing probe matches at the mRNA level can help one deduce whether these probesets are derived from the same or different splice variants.

RESULTS

The GeneAnnot system comprehensively documents the many-to-many relationship between oligonucleotide array probesets and annotated genes in GeneCards. It performs pairwise alignments between the probe sequences and gene transcripts, and assigns sensitivity and specificity scores to each probeset/gene pair.

AVAILABILITY

http://genecards.weizmann.ac.il/geneannot/

SUPPLEMENTARY INFORMATION

Program description and statistics http://genecards.weizmann.ac.il/geneannot/DOC/index.html

Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE

Recent enhancements and current research in the GeneCards (GC) (http://bioinfo.weizmann.ac.il/cards/) project are described, including the addition of gene expression profiles and integrated gene locations. Also highlighted are the contributions of specialized associated human gene-centric databases developed at the Weizmann Institute. These include the Unified Database (UDB) (http://bioinfo.weizmann.ac.il/udb) for human genome mapping, the human Chromosome 21 database at the Weizmann Insti-tute (CroW 21) (http://bioinfo.weizmann.ac.il/crow21), and the Human Olfactory Receptor Data Explora-torium (HORDE) (http://bioinfo.weizmann.ac.il/HORDE). The synergistic relationships amongst these efforts have positively impacted the quality, quantity and usefulness of the GeneCards gene compendium.