A Genome-Wide Association Study Reveals Loci Influencing Height and Other Conformation Traits in Horses

The molecular analysis of genes influencing human height has been notoriously difficult. Genome-wide association studies (GWAS) for height in humans based on tens of thousands to hundreds of thousands of samples so far revealed ∼200 loci for human height explaining only 20% of the heritability. In domestic animals isolated populations with a greatly reduced genetic heterogeneity facilitate a more efficient analysis of complex traits. We performed a genome-wide association study on 1,077 Franches-Montagnes (FM) horses using ∼40,000 SNPs. Our study revealed two QTL for height at withers on chromosomes 3 and 9. The association signal on chromosome 3 is close to the LCORL/NCAPG genes. The association signal on chromosome 9 is close to the ZFAT gene. Both loci have already been shown to influence height in humans. Interestingly, there are very large intergenic regions at the association signals. The two detected QTL together explain ∼18.2% of the heritable variation of height in horses. However, another large fraction of the variance for height in horses results from ECA 1 (11.0%), although the association analysis did not reveal significantly associated SNPs on this chromosome. The QTL region on ECA 3 associated with height at withers was also significantly associated with wither height, conformation of legs, ventral border of mandible, correctness of gaits, and expression of the head. The region on ECA 9 associated with height at withers was also associated with wither height, length of croup and length of back. In addition to these two QTL regions on ECA 3 and ECA 9 we detected another QTL on ECA 6 for correctness of gaits. Our study highlights the value of domestic animal populations for the genetic analysis of complex traits.

Mutations upstream of fabI in triclosan resistant Staphylococcus aureus strains are associated with elevated fabI gene expression

Background The enoyl-acyl carrier protein (ACP) reductase enzyme (FabI) is the target for a series of antimicrobial agents including novel compounds in clinical trial and the biocide triclosan. Mutations in fabI and heterodiploidy for fabI have been shown to confer resistance in S. aureus strains in a previous study. Here we further determined the fabI upstream sequence of a selection of these strains and the gene expression levels in strains with promoter region mutations. Results Mutations in the fabI promoter were found in 18% of triclosan resistant clinical isolates, regardless the previously identified molecular mechanism conferring resistance. Although not significant, a higher rate of promoter mutations were found in strains without previously described mechanisms of resistance. Some of the mutations identified in the clinical isolates were also detected in a series of laboratory mutants. Microarray analysis of selected laboratory mutants with fabI promoter region mutations, grown in the absence of triclosan, revealed increased fabI expression in three out of four tested strains. In two of these strains, only few genes other than fabI were upregulated. Consistently with these data, whole genome sequencing of in vitro selected mutants identified only few mutations except the upstream and coding regions of fabI, with the promoter mutation as the most probable cause of fabI overexpression. Importantly the gene expression profiling of clinical isolates containing similar mutations in the fabI promoter also showed, when compared to unrelated non-mutated isolates, a significant up-regulation of fabI. Conclusions In conclusion, we have demonstrated the presence of C34T, T109G, and A101C mutations in the fabI promoter region of strains with fabI up-regulation, both in clinical isolates and/or laboratory mutants. These data provide further observations linking mutations upstream fabI with up-regulated expression of the fabI gene.

Cluster analysis and display of genome-wide expression patterns

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Virus resistance and gene silencing in plants can be induced by simultaneous expression of sense and antisense RNA

Many examples of extreme virus resistance and posttranscriptional gene silencing of endogenous or reporter genes have been described in transgenic plants containing sense or antisense transgenes. In these cases of either cosuppression or antisense suppression, there appears to be induction of a surveillance system within the plant that specifically degrades both the transgene and target RNAs. We show that transforming plants with virus or reporter gene constructs that produce RNAs capable of duplex formation confer virus immunity or gene silencing on the plants. This was accomplished by using transcripts from one sense gene and one antisense gene colocated in the plant genome, a single transcript that has self-complementarity, or sense and antisense transcripts from genes brought together by crossing. A model is presented that is consistent with our data and those of other workers, describing the processes of induction and execution of posttranscriptional gene silencing.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

GenEST, a powerful bidirectional link between cDNA sequence data and gene expression profiles generated by cDNA-AFLP

The release of vast quantities of DNA sequence data by large-scale genome and expressed sequence tag (EST) projects underlines the necessity for the development of efficient and inexpensive ways to link sequence databases with temporal and spatial expression profiles. Here we demonstrate the power of linking cDNA sequence data (including EST sequences) with transcript profiles revealed by cDNA-AFLP, a highly reproducible differential display method based on restriction enzyme digests and selective amplification under high stringency conditions. We have developed a computer program (GenEST) that predicts the sizes of virtual transcript-derived fragments (TDFs) of in silico-digested cDNA sequences retrieved from databases. The vast majority of the resulting virtual TDFs could be traced back among the thousands of TDFs displayed on cDNA-AFLP gels. Sequencing of the corresponding bands excised from cDNA-AFLP gels revealed no inconsistencies. As a consequence, cDNA sequence databases can be screened very efficiently to identify genes with relevant expression profiles. The other way round, it is possible to switch from cDNA-AFLP gels to sequences in the databases. Using the restriction enzyme recognition sites, the primer extensions and the estimated TDF size as identifiers, the DNA sequence(s) corresponding to a TDF with an interesting expression pattern can be identified. In this paper we show examples in both directions by analyzing the plant parasitic nematode Globodera rostochiensis. Various novel pathogenicity factors were identified by combining ESTs from the infective stage juveniles with expression profiles of ∼4000 genes in five developmental stages produced by cDNA-AFLP.

Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer

The biological significance of DNA amplification in cancer is thought to be due to the selection of increased expression of a single or few important genes. However, systematic surveys of the copy number and expression of all genes within an amplified region of the genome have not been performed. Here we have used a combination of molecular, genomic, and microarray technologies to identify target genes for 17q23, a common region of amplification in breast cancers with poor prognosis. Construction of a 4-Mb genomic contig made it possible to define two common regions of amplification in breast cancer cell lines. Analysis of 184 primary breast tumors by fluorescence in situ hybridization on tissue microarrays validated these results with the highest amplification frequency (12.5%) observed for the distal region. Based on GeneMap'99 information, 17 known genes and 26 expressed sequence tags were localized to the contig. Analysis of genomic sequence identified 77 additional transcripts. A comprehensive analysis of expression levels of these transcripts in six breast cancer cell lines was carried out by using complementary DNA microarrays. The expression patterns varied from one cell line to another, and several overexpressed genes were identified. Of these, RPS6KB1, MUL, APPBP2, and TRAP240 as well as one uncharacterized expressed sequence tag were located in the two common amplified regions. In summary, comprehensive analysis of the 17q23 amplicon revealed a limited number of highly expressed genes that may contribute to the more aggressive clinical course observed in breast cancer patients with 17q23-amplified tumors.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

Genome-wide gene expression profiles of the developing mouse hippocampus

We have analyzed the developmental molecular programs of the mouse hippocampus, a cortical structure critical for learning and memory, by means of large-scale DNA microarray techniques. Of 11,000 genes and expressed sequence tags examined, 1,926 showed dynamic changes during hippocampal development from embryonic day 16 to postnatal day 30. Gene-cluster analysis was used to group these genes into 16 distinct clusters with striking patterns that appear to correlate with major developmental hallmarks and cellular events. These include genes involved in neuronal proliferation, differentiation, and synapse formation. A complete list of the transcriptional changes has been compiled into a comprehensive gene profile database (http://BrainGenomics.Princeton.edu), which should prove valuable in advancing our understanding of the molecular and genetic programs underlying both the development and the functions of the mammalian brain.

Human cytomegalovirus latent gene expression in granulocyte-macrophage progenitors in culture and in seropositive individuals.

Following infection with cytomegalovirus, human granulocyte-macrophage progenitors carry the viral genome but fail to support productive replication. Viral transcripts arise from a region encompassing the major regulatory gene locus; however, their structure differs significantly from productive phase transcripts. One class, sense transcripts, is encoded in the same direction as productive phase transcripts but uses two novel start sites in the ie1/ie2 promoter/enhancer region. These transcripts have the potential to encode a novel 94 aa protein. The other class, antisense transcript, is unspliced and complimentary to ie1 exons 2-4, and has the potential to encode novel 154 and 152 aa proteins. Consistent with a role in latency, these transcripts are present in bone marrow aspirates from naturally infected, healthy seropositive donors but are not present in seronegative controls. Sense latent transcripts are present in a majority of seropositive individuals. Consistent with the expression of latent transcripts, antibody to the 94 aa and 152 aa proteins is detectable in the serum of seropositive individuals. Thus, latent infection by cytomegalovirus is accompanied by the presence of latency-associated transcripts and expression of immunogenic proteins. Overall, these results suggest that bone marrow-derived myeloid progenitors are an important natural site of viral latency.

Production of infectious human respiratory syncytial virus from cloned cDNA confirms an essential role for the transcription elongation factor from the 5' proximal open reading frame of the M2 mRNA in gene expression and provides a capability for vaccine development.

Infectious human respiratory syncytial virus (RSV) was produced by the intracellular coexpression of five plasmid-borne cDNAs. One cDNA encoded a complete positive-sense version of the RSV genome (corresponding to the replicative intermediate RNA or antigenome), and each of the other four encoded a separate RSV protein, namely, the major nucleocapsid N protein, the nucleocapsid P phosphoprotein, the major polymerase L protein, or the protein from the 5' proximal open reading frame of the M2 mRNA [M2(ORF1)]. RSV was not produced if any of the five plasmids was omitted. The requirement for the M2(ORF1) protein is consistent with its recent identification as a transcription elongation factor and confirms its importance for RSV gene expression. It should thus be possible to introduce defined changes into infectious RSV. This should be useful for basic studies of RSV molecular biology and pathogenesis; in addition, there are immediate applications to the development of live attenuated vaccine strains bearing predetermined defined attenuating mutations.

Origin and diversity of the Sox transcription factor gene family: genome-wide analysis in Fugu rubripes

The SOX family of transcription factors are found throughout the animal kingdom and are important in a variety of developmental contexts. Genome analysis has identified 20 Sox genes in human and mouse, which can be subdivided into 8 groups, based on sequence comparison and intron-exon structure. Most of the SOX groups identified in mammals are represented by a single SOX sequence in invertebrate model organisms, suggesting a duplication and divergence mechanism has operated during vertebrate evolution. We have now analysed the Sox gene complement in the pufferfish, Fugu rubripes, in order to shed further light on the diversity and origins of the Sox gene family. Major differences were found between the Sox family in Fugu and those in humans and mice. In particular, Fugu does not have orthologues of Sry, Sox,15 and Sox30, which appear to be specific to mammals, while Sox19, found in Fugu and zebrafish but absent in mammals, seems to be specific to fishes. Six mammalian Sox genes are represented by two copies each in Fugu, indicating a large-scale gene duplication in the fish lineage. These findings point to recent Sox gene loss, duplication and divergence occurring during the evolution of tetrapod and teleost lineages, and provide further evidence for large-scale segmental or a whole-genome duplication occurring early in the radiation of teleosts. (C) 2004 Elsevier B.V. All rights reserved.

Repressor- and activator-type ethylene response factors functioning in jasmonate signaling and disease resistance identified via a genome-wide screen of Arabidopsis transcription factor gene expression

To identify transcription factors (TFs) involved in jasmonate (JA) signaling and plant defense, we screened 1,534 Arabidopsis (Arabidopsis thaliana) TFs by real-time quantitative reverse transcription-PCR for their altered transcript at 6 h following either methyl JA treatment or inoculation with the incompatible pathogen Alternaria brassicicola. We identified 134 TFs that showed a significant change in expression, including many APETALA2/ethylene response factor (AP2/ERF), MYB, WRKY, and NACTF genes with unknown functions. Twenty TF genes were induced by both the pathogen and methyl JA and these included 10 members of the AP2/ERF TF family, primarily from the B1a and B3 subclusters. Functional analysis of the B1a TF AtERF4 revealed that AtERF4 acts as a novel negative regulator of JA-responsive defense gene expression and resistance to the necrotrophic fungal pathogen Fusarium oxysporum and antagonizes JA inhibition of root elongation. In contrast, functional analysis of the B3 TF AtERF2 showed that AtERF2 is a positive regulator of JA-responsive defense genes and resistance to F. oxysporum and enhances JA inhibition of root elongation. Our results suggest that plants coordinately express multiple repressor-and activator-type AP2/ERFs during pathogen challenge to modulate defense gene expression and disease resistance.

Differential gene expression in the developing mouse ureter

In many instances, kidney dysgenesis results as a secondary consequence to defects in the development of the ureter. Through the use of mouse genetics a number of genes associated with such malformations have been identified, however, the cause of many other abnormalities remain unknown. In order to identify novel genes involved in ureter development we compared gene expression in embryonic day (E) 12.5, E15.5 and postnatal day (P) 75 ureters using the Compugen mouse long oligo microarrays. A total of 248 genes were dynamically upregulated and 208 downregulated between E12.5 and P75. At E12.5, when the mouse ureter is comprised of a simple cuboidal epithelium surrounded by ureteric mesenchyme, genes previously reported to be expressed in the ureteric mesenchyme, foxC1 and foxC2 were upregulated. By E15.5 the epithelial layer develops into urothelium, impermeable to urine, and smooth muscle develops for the peristaltic movement of urine towards the bladder. The development of these two cell types coincided with the upregulation of UPIIIa, RAB27b and PPAR gamma reported to be expressed in the urothelium, and several muscle genes, Acta1, Tnnt2, Myocd, and Tpm2. In situ hybridization identified several novel genes with spatial expression within the smooth muscle, Acta1; ureteric mesenchyme and smooth muscle, Thbs2 and Co15a2; and urothelium, Kcnj8 and Adh1. This study marks the first known report defining global gene expression of the developing mouse ureter and will provide insight into the molecular mechanisms underlying kidney and lower urinary tract malformations. (c) 2005 Elsevier B.V. All rights reserved.

Whole Genome Analysis of Gene Expression Reveals Coordinated Activation of Signaling and Metabolic Pathways during Pollen-Pistil Interactions in Arabidopsis

Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.