Sequence diversity in 36 candidate genes for cardiovascular disorders.

Two strategies involving whole-genome association studies have been proposed for the identification of genes involved in complex diseases. The first one seeks to characterize all common variants of human genes and to test their association with disease. The second one seeks to develop dense maps of single-nucleotide polymorphisms (SNPs) and to detect susceptibility genes through linkage disequilibrium. We performed a molecular screening of the coding and/or flanking regions of 36 candidate genes for cardiovascular diseases. All polymorphisms identified by this screening were further genotyped in 750 subjects of European descent. In the whole set of genes, the lengths explored spanned 53.8 kb in the 5' regions, 68.4 kb in exonic regions, and 13 kb in the 3' regions. The strength of linkage disequilibrium within candidate regions suggests that genomewide maps of SNPs might be efficient ways to identify new disease-susceptibility genes, provided that the maps are sufficiently dense. However, the relatively large number of polymorphisms within coding and regulatory regions of candidate genes raises the possibility that several of them might be functional and that the pattern of genotype-phenotype association might be more complex than initially envisaged, as actually has been observed in some well-characterized genes. These results argue in favor of both genomewide association studies and detailed studies of the overall sequence variation of candidate genes, as complementary approaches.     

Identification of candidate disease genes in patients with common variable immunodeficiency

Background: Common variable immunodeficiency (CVID), the most prevalent form of primary immunodeficiency (PID), is characterized by hypogammaglobulinemia and recurrent infections. Understanding protein-protein interaction (PPI) networks of CVID genes and identifying candidate CVID genes are critical steps in facilitating the early diagnosis of CVID. Here, the aim was to investigate PPI networks of CVID genes and identify candidate CVID genes using computation techniques. Methods: Network density and biological distance were used to study PPI data for CVID and PID genes obtained from the STRING database. Gene expression data of patients with CVID were obtained from the Gene Expression Omnibus, and then Pearson’s correlation coefficient, a PPI database, and Kyoto Encyclopedia of Genes and Genomes were used to identify candidate CVID genes. We then evaluated our predictions and identified differentially expressed CVID genes. Results: The majority of CVID genes are characterized by a high network density and small biological distance, whereas most PID genes are characterized by a low network density and large biological distance, indicating that CVID genes are more functionally similar to each other and closely interact with one other compared with PID genes. Subsequently, we identified 172 CVID candidate genes that have similar biological functions to known CVID genes, and eight genes were recently reported as CVID-related genes. MYC, a candidate gene, was down-regulated in CVID duodenal biopsies, but up-regulated in blood samples compared with levels in healthy controls. Conclusion: Our findings will aid in a better understanding of the complex of CVID genes, possibly further facilitating the early diagnosis of CVID.     

Towards the adaptation of grapevine varieties to climate change: QTLs and candidate genes for developmental stages

The genetic determinism of developmental stages in grapevine was studied in the progeny of a cross between grapevine cultivars Riesling and Gewurztraminer by combining ecophysiological modelling, genetic analysis and data mining of the grapevine whole genome sequence. The dates of three phenological stages, budbreak, flowering and veraison, were recorded during four successive years for 120 genotypes in the vineyard. The phenotypic data analysed were the duration of three periods expressed in thermal time (degree-days): 15 February to budbreak (Bud), budbreak to flowering (Flo) and flowering to veraison (Ver). Parental and consensus genetic maps were built using 153 microsatellite markers on 188 individuals. Six independent quantitative trait loci (QTLs) were detected for the three phases. They were located on chromosomes 4 and 19 for Bud, chromosomes 7 and 14 for Flo and chromosomes 16 and 18 for Ver. Interactions were detected between loci and also between alleles at the same locus. Using the available grapevine whole-genome sequences, candidate genes underlying the QTLs were identified. VvFT, on chromosome 7, and a CONSTANS-like gene, on chromosome 14, were found to colocalise with the QTLs for flowering time. Genes related to the abscisic acid response and to sugar metabolism were detected within the confidence intervals of QTLs for veraison time. Their possible roles in the developmental process are discussed. These results raise new hypotheses for a better understanding of the physiological processes governing grapevine phenology and provide a framework for breeding new varieties adapted to the future predicted climatic conditions.     

Selective sweeps reveal candidate genes for adaptation to drought and salt tolerance in common sunflower, Helianthus annuus

Here we report the results of an analysis of variation at 128 EST-based microsatellites in wild Helianthus annuus, using populations from the species' typical plains habitat in Kansas and Colorado, as well as two arid desert and two distinct brackish marsh areas in Utah. The test statistics lnRV and lnRH were used to find regions of the genome that were significantly less variable in one population relative to the others and thus are likely to contain genes under selection. A small but detectable percentage (1.5-6%) of genes showed evidence for selection from both statistics in any particular environment, and a total of 17 loci showed evidence of selection in at least one environment. Distance-based measures provided additional evidence of selection for 15 of the 17 loci. Global F(ST)-values were significantly higher for candidate loci, as expected under divergent selection. However, pairwise F(ST)-values were lower for populations that shared a selective sweep. Moreover, while spatially separated populations undergoing similar selective pressures showed evidence of divergence at some loci, they evolved in concert at other loci. Thus, this study illustrates how selective sweeps might contribute both to the integration of conspecific populations and to the differentiation of races or species.     

Association between common variation in 120 candidate genes and breast cancer risk

Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran–Armitage trend test (p-trend) and a two-degrees of freedom χ² test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10⁻⁵) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty.     

From QTLs for enzyme activity to candidate genes in maize

In order to facilitate the search for genes underlying QTLs (Quantitative Trait Loci), the activities of key enzymes of the carbohydrate metabolism in maize, and the concentration of their substrates or products were used as quantitative traits. For each of the chosen enzyme, i.e. ADPglucose pyrophosphorylase, sucrose-phosphate-synthase and invertases, the corresponding cDNA was available. Since biochemical traits are more closely related to gene expression than agronomic traits, co-locations could be expected between an enzyme structural gene and a QTL for its enzyme activity, and/or the corresponding product or substrate content. This approach was applied using recombinant inbred lines on leaves at 3- or 4-leaf stage, under control and water stress conditions and on grain, at maturity. Several QTLs were detected for each trait, particularly for two enzyme activities measured in mature leaves. Apparent co-locations between QTL for activity and structural locus were observed for sucrose-phosphate-synthase (chromosome 8) and acid-soluble invertase (chromosome 2 and 5). Leaf acid-soluble (vacuolar) invertase provided an interesting case since QTL, on chromosome 5, explaining 17% of variability was apparently co-located with the Ivr2 gene encoding a vacuolar invertase protein which was strongly water-stress inducible. Similarly, in grain, an amylose QTL co-located with the Sh2 gene of ADPglucose pyrophosphorylase. The reliability of this candidate was further tested through the examination of Sh2 DNA polymorphism in 46 genetically unrelated lines. A correlation was obtained between this polymorphism and kernel starch content, which further validated Sh2 as a candidate. Some improvements or alternatives to this strategy are briefly discussed.      

Screening for candidate genes involved in tolerance to organic solvents in yeast

Saccharomyces cerevisiae mutant strain, KK-211, isolated from serial culture in medium containing isooctane showed an extremely higher tolerance to the hydrophobic organic-solvents, which are toxic to yeast cells compared to the wild-type parent strain, DY-1. To detect genes that are related to this tolerance, a DNA microarray analysis was performed using mRNAs isolated from strains DY-1 and KK-211. Fourteen genes were identified as being related to the tolerance. The expression of 12 genes including ICT1, YNL190W, and PRY3, was induced while the expression of two genes including PHO84 was repressed in strain KK-211. Two genes, ICT1 and YNL190W showed the same profile in the DNA microarray analysis and a differential display-polymerase chain reaction analysis. But, there is no detectable difference in the expression profile of KK-211 cells cultured with or without isooctane. The results suggest that change in expression levels of multiple genes that confer the modification function of the cell surface, not by a single gene, might be required for yeast cell tolerance to organic solvents.     

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes

Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes), a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short). The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.     

QTL and candidate genes for fecundity in sows

Fecundity in pigs is a trait of major economic interest but low heritability. For the improvement of fecundity, genetic markers for selection are desirable and therefore, several searches for genetic variation influencing fecundity have been performed. The aim of this review is to compare and to evaluate all published QTL analyses and candidate gene approaches concerning reproductive traits in sows. For this purpose, we present a comprehensive cytogenetic map comprising 54 QTL and 11 candidate genes with influence on reproductive traits. The evaluation and comparison of the results showed similarities, but also marked differences among studies. Reasons for different results are multicausal and are due to differences between resource populations, number of evaluated animals, mating systems, measured phenotypical traits and environmental influences. We could show that chromosome 8 and to a lower extend chromosome 7 are the most important chromosomes with regard to reproductive traits in pigs. For further research, fine mapping of the identified QTL regions is necessary in order to confirm and to narrow the most likely chromosomal intervals. Although difficult to perform, an advance would be a standardization of the experimental setup in particular, in respect to the collection of phenotypic data. Furthermore, we suggest to publish the information on further identified QTL and candidate genes as comprehensive and accurate as possible in order to allow a more transparent comparison and collation of the results.     

Breakthroughs in the search for dyslexia candidate genes

Four genes have recently been proposed as candidates for dyslexia: dyslexia susceptibility 1 candidate 1 (DYX1C1), roundabout Drosophila homolog 1 (ROBO1), doublecortin domain-containing protein 2 (DCDC2) and KIAA0319. Each gene is implicated in global brain-development processes such as neural migration and axonal guidance, with the exception of DYX1C1, the function of which is still unknown. The most immediate clinical prospect of the discovery of these genes is the possibility of early identification of dyslexia via genetic screening. However, research efforts have yet to identify a functional mutation in any of these genes. When causal variants are identified, they will need to be considered within a multifactorial framework, which is likely to involve gene-gene and gene-environment interactions, to make accurate predictions of diagnostic status.     

Development of candidate gene markers associated to common bacterial blight resistance in common bean

Common bacterial blight (CBB), caused by Xanthomonas axonopodis pv. phaseoli (Xap), is a major yield-limiting factor of common bean (Phaseolus vulgaris L.) production around the world. Two major CBB-resistant quantitative trait loci (QTL), linked to the sequence characterized amplified region markers BC420 and SU91, are located at chromosomes 6 and 8, respectively. Using map-based cloning approach, four bacterial artificial chromosome (BAC) clones from the BC420-QTL locus and one BAC clone containing SU91 were sequenced by Roche 454 technique and subsequently assembled using merged assemblies from three different programs. Based on the quality of the assembly, only the sequences of BAC 32H6 and 4K7 were used for candidate gene marker (CGM) development and candidate gene (CG) selection. For the BC420-QTL locus, 21 novel genes were predicted in silico by FGENESH using Medicago gene model, whereas 16 genes were identified in the SU91-QTL locus. For each putative gene, one or more primer pairs were designed and tested in the contrasting near isogenic lines. Overall, six and nine polymorphic markers were found in the SU91- and BC420-QTL loci, respectively. Afterwards, association mapping was conducted in a breeding population of 395 dry bean lines to discover marker-trait associations. Two CGMs per each locus showed better association with CBB resistance than the BC420 and SU91 markers, which include BC420-CG10B and BC420-CG14 for BC420_QTL locus, and SU91-CG10 and SU91-CG11 for SU91_QTL locus. The strong associations between CBB resistance and the CGs 10 and 14 from BC420_QTL locus and the CGs 10 and 11 from SU91_QTL locus indicate that the genes 10 and 14 from the BC420 locus are potential CGs underlying the BC420_QTL locus, whereas the genes 10 and 11 from the SU91 locus are potential CGs underlying the SU91_QTL locus. The superiority of SU91-CG11 was further validated in a recombinant inbred line population Sanilac?×?OAC 09-3. Thus, co-dominant CGMs, BC420-CG14 and SU91-CG11, are recommended to replace BC420 and SU91 for marker-assisted selection of common bean with resistance to CBB.     

A guide to web tools to prioritize candidate genes

Finding the most promising genes among large lists of candidate genes has been defined as the gene prioritization problem. It is a recurrent problem in genetics in which genetic conditions are reported to be associated with chromosomal regions. In the last decade, several different computational approaches have been developed to tackle this challenging task. In this study, we review 19 computational solutions for human gene prioritization that are freely accessible as web tools and illustrate their differences. We summarize the various biological problems to which they have been successfully applied. Ultimately, we describe several research directions that could increase the quality and applicability of the tools. In addition we developed a website (http://www.esat.kuleuven.be/gpp) containing detailed information about these and other tools, which is regularly updated. This review and the associated website constitute together a guide to help users select a gene prioritization strategy that suits best their needs.     

Differentiation in neutral genes and a candidate gene in the pied flycatcher: using biological archives to track global climate change

Global climate change is one of the major driving forces for adaptive shifts in migration and breeding phenology and possibly impacts demographic changes if a species fails to adapt sufficiently. In Western Europe, pied flycatchers (Ficedula hypoleuca) have insufficiently adapted their breeding phenology to the ongoing advance of food peaks within their breeding area and consequently suffered local population declines. We address the question whether this population decline led to a loss of genetic variation, using two neutral marker sets (mitochondrial control region and microsatellites), and one potentially selectively non‐neutral marker (avian Clock gene). We report temporal changes in genetic diversity in extant populations and biological archives over more than a century, using samples from sites differing in the extent of climate change. Comparing genetic differentiation over this period revealed that only the recent Dutch population, which underwent population declines, showed slightly lower genetic variation than the historic Dutch population. As that loss of variation was only moderate and not observed in all markers, current gene flow across Western and Central European populations might have compensated local loss of variation over the last decades. A comparison of genetic differentiation in neutral loci versus the Clock gene locus provided evidence for stabilizing selection. Furthermore, in all genetic markers, we found a greater genetic differentiation in space than in time. This pattern suggests that local adaptation or historic processes might have a stronger effect on the population structure and genetic variation in the pied flycatcher than recent global climate changes.     

Analysis of candidate genes for prostate cancer

Considerable evidence demonstrates that genetic factors are important in the development and aggressiveness of prostate cancer. To identify genetic variants that predispose to prostate cancer we tested candidate SNPs from genomic regions that show linkage to prostate cancer susceptibility and/or aggressiveness, as well as genes that show a significant difference in mRNA expression level between tumor and normal tissue. Cases had histologically verified prostate cancer. Controls were at least 65 years old, never registered a PSA above 2.5 ng/ml, always had digital rectal examinations that were not suspicious for cancer, and have no known family history of prostate cancer. Thirty-nine coding SNPs and nine non-coding SNPs were tested in up to 590 cases and 556 controls resulting in over 40,000 SNP genotypes. Significant differences in allele frequencies between cases and controls were observed for ID3 (inhibitor of DNA binding), p = 0.05, HPN (hepsin), p = 0.009, BCAS1 (breast carcinoma amplified sequence 1), p = 0.007, CAV2 (caveolin 2), p = 0.007, EMP3 (epithelial membrane protein 3), p < 0.0001, and MLH1 (mutL homolog 1), p < 0.0001. SNPs in three of these genes (BCAS1, EMP3 and MLH1) remained significant in an age-matched subsample.