The genomics of gene expression

Synergistic response to climate stressors in coral is associated with genotypic variation in baseline expression

As environments are rapidly reshaped due to climate change, phenotypic plasticity plays an important role in the ability of organisms to persist and is considered an especially important acclimatization mechanism for long-lived sessile organisms such as reef-building corals. Often, this ability of a single genotype to display multiple phenotypes depending on the environment is modulated by changes in gene expression, which can vary in response to environmental changes via two mechanisms: baseline expression and expression plasticity. We used transcriptome-wide expression profiling of eleven genotypes of common-gardened Acropora cervicornis to explore genotypic variation in the expression response to thermal and acidification stress, both individually and in combination. We show that the combination of these two stressors elicits a synergistic gene expression response, and that both baseline expression and expression plasticity in response to stress show genotypic variation. Additionally, we demonstrate that frontloading of a large module of coexpressed genes is associated with greater retention of algal symbionts under combined stress. These results illustrate that variation in the gene expression response of individuals to climate change stressors can persist even when individuals have shared environmental histories, affecting their performance under future climate change scenarios.

Gene expression differentials driven by mass rearing and artificial selection in black soldier fly colonies

The micro-evolutionary forces that shape genetic diversity during domestication have been assessed in many plant and animal systems. However, the impact of these processes on gene expression, and consequent functional adaptation to artificial environments, remains under-investigated. In this study, whole-transcriptome dynamics associated with the early stages of domestication of the black soldier fly (BSF), Hermetia illucens, were assessed. Differential gene expression (DGE) was evaluated in relation to (i) generational time within the cultured environment (F2 vs. F3), and (ii) two selection strategies [no artificial selective pressure (NS); and selection for greater larval mass (SEL)]. RNA-seq was conducted on 5th instar BSF larvae (n = 36), representing equal proportions of the NS (F2 = 9; F3 = 9) and SEL (F2 = 9; F3 = 9) groups. A multidimensional scaling plot revealed greater gene expression variability within the NS and F2 subgroups, while the SEL group clustered separately with lower levels of variation. Comparisons between generations revealed 898 differentially expressed genes (DEGs; FDR-corrected p < 0.05), while between selection strategies, 213 DEGs were observed (FDR-corrected p < 0.05). Enrichment analyses revealed that metabolic, developmental, and defence response processes were over-expressed in the comparison between F2 and F3 larvae, while metabolic processes were the main differentiating factor between NS and SEL lines. This illustrates the functional adaptations that occur in BSF colonies across generations due to mass rearing; as well as highlighting genic dynamics associated with artificial selection for production traits that might inform future selective breeding strategies.

Genome-Wide Genotype-Expression Relationships Reveal Both Copy Number and Single Nucleotide Differentiation Contribute to Differential Gene Expression between Stickleback Ecotypes

Repeated and independent emergence of trait divergence that matches habitat differences is a sign of parallel evolution by natural selection. Yet, the molecular underpinnings that are targeted by adaptive evolution often remain elusive. We investigate this question by combining genome-wide analyses of copy number variants (CNVs), single nucleotide polymorphisms (SNPs), and gene expression across four pairs of lake and river populations of the three-spined stickleback (Gasterosteus aculeatus). We tested whether CNVs that span entire genes and SNPs occurring in putative cis-regulatory regions contribute to gene expression differences between sticklebacks from lake and river origins. We found 135 gene CNVs that showed a significant positive association between gene copy number and gene expression, suggesting that CNVs result in dosage effects that can fuel phenotypic variation and serve as substrates for habitat-specific selection. Copy number differentiation between lake and river sticklebacks also contributed to expression differences of two immune-related genes in immune tissues, cathepsin A and GIMAP7. In addition, we identified SNPs in cis-regulatory regions (eSNPs) associated with the expression of 1,865 genes, including one eSNP upstream of a carboxypeptidase gene where both the SNP alleles differentiated and the gene was differentially expressed between lake and river populations. Our study highlights two types of mutations as important sources of genetic variation involved in the evolution of gene expression and in potentially facilitating repeated adaptation to novel environments.

Poplar CBF1 functions specifically in an integrated cold regulatory network

The C-repeat binding factors (CBFs), also termed dehydration-responsive element-binding protein 1 (DREB1) family members, play crucial roles in the acquisition of stress tolerance, but in trees, the underlying mechanisms of stress tolerance remain elusive. To gain insight into these mechanisms, we isolated five CBF1 orthologs from four poplar sections (Populus spp.) and assessed their expression under drought, cold, heat and salt stress conditions. Globally induced expression in response to cold suggested a correlation between poplar CBF1 expression and the acquisition of cold tolerance. Responses that varied between sections may reflect section-specific stress tolerance mechanisms, suggesting an effect of ecological context on the development of CBF1-mediated stress tolerance in poplar. We then used a genome-wide search strategy in Populus trichocarpa to predict 2263 putative CBF target genes; the identified genes participate in multiple biological processes and pathways. Almost all of the putative target genes contained multiple cis-acting elements that mediate responses to various environmental and endogenous signals, consistent with an important role of CBF1s in an integrated cold regulatory network. Finally, analysis of an association population of 528 individuals of Populus simonii identified six single-nucleotide polymorphisms (false discovery rate Q < 0.10) significantly (P < 0.005) associated with malondialdehyde production and electrolyte leakage, suggesting the potential importance of PsCBF1 in the regulation of some membrane-related functions. Our findings provide new insights into the function of PsCBF1 and shed light on the CBF-mediated regulatory network in poplar.

Divergence along the gonadal steroidogenic pathway: Implications for hormone-mediated phenotypic evolution

Across a range of taxa, hormones regulate suites of traits that influence survival and reproductive success; however, the mechanisms by which hormone-mediated traits evolve are still unclear. We hypothesized that phenotypic divergence might follow from differential regulation of genes encoding key steps in hormone biosynthesis and thus the rate of hormone production. We tested this hypothesis in relation to the steroid hormone testosterone by comparing two subspecies of junco (Junco hyemalis) in the wild and in captivity. These subspecies have diverged over the last 10-15kyears in multiple testosterone-mediated traits, including aggression, ornamentation, and body size. We show that variation in gonadal gene expression along the steroid biosynthetic pathway predicts phenotypic divergence within and among subspecies, and that the more androgenized subspecies exhibits a more prolonged time-course of elevated testosterone following exogenous stimulation. Our results point to specific genes that fulfill key conditions for phenotypic evolution because they vary functionally in their expression among individuals and between populations, and they map onto population variation in phenotype in a common garden. Our findings therefore build an important bridge between hormones, genes, and phenotypic evolution.

Differential responses to environmental challenge by common carp Cyprinus carpio highlight the importance of coping style in integrative physiology

Common carp Cyprinus carpio displaying proactive or reactive stress coping styles were acclimated to two environmental regimes (low oxygen and low temperature), and selected groups were tested for response to an inflammatory challenge (Escherichia coli lipopolysaccharide, LPS). Plasma glucose and lactate levels were measured, as were selected C. carpio-specific messenger (m)RNA transcript abundance, including cortisol receptor (CR), enolase (ENO), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and interleukin-1-beta (IL1β) was measured in individual whole brain samples. Basal levels (in sham injected fish held in normoxic conditions at 25° C) of plasma lactate and glucose differed between coping styles, being significantly lower in proactive individuals. Both variables increased in response to LPS challenge, with the exception of plasma glucose in reactive fish held in hypoxia. Baseline levels of gene expression under control conditions were significantly different for GAPDH between behavioural phenotypes. The responses to experimental challenge were sometimes diametrically opposed between stress-coping styles in a transcript-specific manner. For CR and GAPDH, for example, the response to LPS injection in hypoxia were opposite between proactive and reactive animals. Proactive fish showed decreased CR and increased GAPDH, whereas reactive showed the opposite response. These results further highlight that screening for stress-coping styles prior to experiments in adaptive physiology can significantly affect the interpretation of data obtained. Further, this leads to a more finely tuned analytical output providing an improved understanding of variation in individual responses to both environmental and inflammatory challenge.

Transcriptome profiling of immune tissues reveals habitat-specific gene expression between lake and river sticklebacks

The observation of habitat-specific phenotypes suggests the action of natural selection. The three-spined stickleback (Gasterosteus aculeatus) has repeatedly colonized and adapted to diverse freshwater habitats across the northern hemisphere since the last glaciation, while giving rise to recurring phenotypes associated with specific habitats. Parapatric lake and river populations of sticklebacks harbour distinct parasite communities, a factor proposed to contribute to adaptive differentiation between these ecotypes. However, little is known about the transcriptional response to the distinct parasite pressure of those fish in a natural setting. Here, we sampled wild-caught sticklebacks across four geographical locations from lake and river habitats differing in their parasite load. We compared gene expression profiles between lake and river populations using 77 whole-transcriptome libraries from two immune-relevant tissues, the head kidney and the spleen. Differential expression analyses revealed 139 genes with habitat-specific expression patterns across the sampled population pairs. Among the 139 differentially expressed genes, eight are annotated with an immune function and 42 have been identified as differentially expressed in previous experimental studies in which fish have been immune challenged. Together, these findings reinforce the hypothesis that parasites contribute to adaptation of sticklebacks in lake and river habitats.

Fine-mapping nicotine resistance loci in Drosophila using a multiparent advanced generation inter-cross population

Animals in nature are frequently challenged by toxic compounds, from those that occur naturally in plants as a defense against herbivory, to pesticides used to protect crops. On exposure to such xenobiotic substances, animals mount a transcriptional response, generating detoxification enzymes and transporters that metabolize and remove the toxin. Genetic variation in this response can lead to variation in the susceptibility of different genotypes to the toxic effects of a given xenobiotic. Here we use Drosophila melanogaster to dissect the genetic basis of larval resistance to nicotine, a common plant defense chemical and widely used addictive drug in humans. We identified quantitative trait loci (QTL) for the trait using the DSPR (Drosophila Synthetic Population Resource), a panel of multiparental advanced intercross lines. Mapped QTL collectively explain 68.4% of the broad-sense heritability for nicotine resistance. The two largest-effect loci-contributing 50.3 and 8.5% to the genetic variation-map to short regions encompassing members of classic detoxification gene families. The largest QTL resides over a cluster of ten UDP-glucuronosyltransferase (UGT) genes, while the next largest QTL harbors a pair of cytochrome P450 genes. Using RNAseq we measured gene expression in a pair of DSPR founders predicted to harbor different alleles at both QTL and showed that Ugt86Dd, Cyp28d1, and Cyp28d2 had significantly higher expression in the founder carrying the allele conferring greater resistance. These genes are very strong candidates to harbor causative, regulatory polymorphisms that explain a large fraction of the genetic variation in larval nicotine resistance in the DSPR.

PDEGEM: Modeling non-uniform read distribution in RNA-Seq data

Background

RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts. Although many methods have been introduced and much progress has been made, a satisfactory solution remains be elusive.

Results

In this article, we borrow the idea from the Positional Dependent Nearest Neighborhood (PDNN) model, originally developed for analyzing microarray data, to model the non-uniformity of read distribution in RNA-seq data. We propose a robust nonlinear regression model named PDEGEM, a Positional Dependent Energy Guided Expression Model to estimate the abundance of transcripts. Using real data, we find that the PDEGEM fits the data better than mseq in all three real datasets we tested. We also find that the expression measure obtained using PDEGEM showed higher correlation with that obtained from alterative assays for quantifying gene and isoform expressions.

Conclusions

Based on these results, we believe that our PDEGEM can improve the accuracy in modeling and estimating the transcript abundance and isoform expression in RNA-Seq data. Additionally, although the stacking energy and positional weight of the PDEGEM are relatively related to sequencing platforms and species, they share some common trends, which indicates that the PDEGEM could partly reflect the mechanism of DNA binding between the template strain and the new synthesized read.

The PDEGEM model can be freely downloaded at: http://www.math.pku.edu.cn/teachers/dengmh/PDEGEM.

Genome-wide identification of allele-specific expression in response to Streptococcus suis 2 infection in two differentially susceptible pig breeds

Although allele expression imbalance has been recognized in many species, and strongly linked to diseases, no whole transcriptome allele imbalance has been detected in pigs during pathogen infections. The pathogen Streptococcus suis 2 (SS2) causes serious zoonotic disease. Different pig breeds show differential susceptibility/resistance to pathogen infection, but the biological insight is little known. Here we analyzed allele-specific expression (ASE) using the spleen transcriptome of four pigs belonging to two phenotypically different breeds after SS2 infection. The comparative analysis of allele specific SNPs between control and infected animals revealed 882 and 1096 statistically significant differentially expressed allele SNPs (criteria: ratio ≧ 2 or ≦ 0.5) in Landrace and Enshi black pig, respectively. Twenty nine allelically imbalanced SNPs were further verified by Sanger sequencing, and later six SNPs were quantified by pyrosequencing assay. The pyrosequencing results are in agreement with the RNA-seq results, except two SNPs. Looking at the role of ASE in predisposition to diseases, the discovery of causative variants by ASE analysis might help the pig industry in long term to design breeding programs for improving SS2 resistance.

Key regulators in prostate cancer identified by co-expression module analysis

Background

Prostate cancer (PrCa) is the most commonly diagnosed cancer in men in the world. Despite the fact that a large number of its genes have been investigated, its etiology remains poorly understood. Furthermore, most PrCa candidate genes have not been rigorously replicated, and the methods by which they biologically function in PrCa remain largely unknown.

Results

Aiming to identify key players in the complex prostate cancer system, we reconstructed PrCa co-expressed modules within functional gene sets defined by the Gene Ontology (GO) annotation (biological process, GO_BP). We primarily identified 118 GO_BP terms that were well-preserved between two independent gene expression datasets and a consequent 55 conserved co-expression modules within them. Five modules were then found to be significantly enriched with PrCa candidate genes collected from expression Quantitative Trait Loci (eQTL), somatic copy number alteration (SCNA), somatic mutation data, or prognostic analyses. Specifically, two transcription factors (TFs) (NFAT and SP1) and three microRNAs (hsa-miR-19a, hsa-miR-15a, and hsa-miR-200b) regulating these five candidate modules were found to be critical to the development of PrCa.

Conclusions

Collectively, our results indicated that genes with similar functions may play important roles in disease through co-expression, and modules with different functions could be regulated by similar genetic components, such as TFs and microRNAs, in a synergistic manner.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1015) contains supplementary material, which is available to authorized users.

A genetic variant in the LDLR promoter is responsible for part of the LDL-cholesterol variability in primary hypercholesterolemia

BACKGROUND

GWAS have consistently revealed that LDLR locus variability influences LDL-cholesterol in general population. Severe LDLR mutations are responsible for familial hypercholesterolemia (FH). However, most primary hypercholesterolemias are polygenic diseases. Although Cis-regulatory regions might be the cause of LDL-cholesterol variability; an extensive analysis of the LDLR distal promoter has not yet been performed. We hypothesized that genetic variants in this region are responsible for the LDLR association with LDL-cholesterol found in GWAS.

METHODS

Four-hundred seventy-seven unrelated subjects with polygenic hypercholesterolemia (PH) and without causative FH-mutations and 525 normolipemic subjects were selected. A 3103 pb from LDLR (-625 to +2468) was sequenced in 125 subjects with PH. All subjects were genotyped for 4 SNPs (rs17242346, rs17242739, rs17248720 and rs17249120) predicted to be potentially involved in transcription regulation by in silico analysis. EMSA and luciferase assays were carried out for the rs17248720 variant. Multivariable linear regression analysis using LDL-cholesterol levels as the dependent variable were done in order to find out the variables that were independently associated with LDL-cholesterol.

RESULTS

The sequencing of the 125 PH subjects did not show variants with minor allele frequency ≥ 10%. The T-allele from g.3131C > T (rs17248720) had frequencies of 9% (PH) and 16.4% (normolipemic), p < 0.00001. Studies of this variant with EMSA and luciferase assays showed a higher affinity for transcription factors and an increase of 2.5 times in LDLR transcriptional activity (T-allele vs C-allele). At multivariate analysis, this polymorphism with the lipoprotein(a) and age explained ≈ 10% of LDL-cholesterol variability.

CONCLUSION

Our results suggest that the T-allele at the g.3131 T > C SNP is associated with LDL-cholesterol levels, and explains part of the LDL-cholesterol variability. As a plausible cause, the T-allele produces an increase in LDLR transcriptional activity and lower LDL-cholesterol levels.

Evidence of allelic imbalance in the schizophrenia susceptibility gene ZNF804A in human dorsolateral prefrontal cortex

The rs1344706, an intronic SNP within the zinc-finger protein 804A gene (ZNF804A), was identified as one of the most compelling risk SNPs for schizophrenia (SZ) and bipolar disorder (BD). It is however not clear by which molecular mechanisms ZNF804A increases disease risk. We evaluated the role of ZNF804A in SZ and BD by genotyping the originally associated rs1344706 SNP and an exonic SNP (rs12476147) located in exon four of ZNF804A in a sample of 422 SZ, 382 BD, and 507 controls from the isolated population of the Costa Rica Central Valley. We also investigated the rs1344706 SNP for allelic specific expression (ASE) imbalance in the dorsolateral prefrontal cortex (DLPFC) of 46 heterozygous postmortem brains. While no significant association between rs1344706 and SZ or BD was observed in the Costa Rica sample, we observed an increased risk of SZ for the minor allele (A) of the exonic rs12476147 SNP (p=0.026). Our ASE assay detected a significant over-expression of the rs12476147 A allele in DLPFC of rs1344706 heterozygous subjects. Interestingly, cDNA allele ratios were significantly different according to the intronic rs1344706 genotypes (p-value=0.03), with the rs1344706 A allele associated with increased ZNF804A rs12476147 A allele expression (average 1.06, p-value=0.02, for heterozygous subjects vs. genomic DNA). In conclusion, we have demonstrated a significant association of rs12476147 with SZ, and using a powerful within-subject design, an allelic expression imbalance of ZNF804A exonic SNP rs12476147 in the DLPFC. Although this data does not preclude the possibility of other functional variants in ZNF804A, it provides evidence that the rs1344706 SZ risk allele is the cis-regulatory variant directly responsible for this allelic expression imbalance in adult cortex.

Combining animal personalities with transcriptomics resolves individual variation within a wild-type zebrafish population and identifies underpinning molecular differences in brain function

Resolving phenotype variation within a population in response to environmental perturbation is central to understanding biological adaptation. Relating meaningful adaptive changes at the level of the transcriptome requires the identification of processes that have a functional significance for the individual. This remains a major objective towards understanding the complex interactions between environmental demand and an individual's capacity to respond to such demands. The interpretation of such interactions and the significance of biological variation between individuals from the same or different populations remain a difficult and under-addressed question. Here, we provide evidence that variation in gene expression between individuals in a zebrafish population can be partially resolved by a priori screening for animal personality and accounts for >9% of observed variation in the brain transcriptome. Proactive and reactive individuals within a wild-type population exhibit consistent behavioural responses over time and context that relates to underlying differences in regulated gene networks and predicted protein-protein interactions. These differences can be mapped to distinct regions of the brain and provide a foundation towards understanding the coordination of underpinning adaptive molecular events within populations.

Exploiting gene expression variation to capture gene-environment interactions for disease

Gene-environment interactions have long been recognized as a fundamental concept in evolutionary, quantitative, and medical genetics. In the genomics era, study of how environment and genome interact to shape gene expression variation is relevant to understanding the genetic architecture of complex phenotypes. While genetic analysis of gene expression variation focused on main effects, little is known about the extent of interaction effects implicating regulatory variants and their consequences on transcriptional variation. Here we survey the current state of the concept of transcriptional gene-environment interactions and discuss its utility for mapping disease phenotypes in light of the insights gained from genome-wide association studies of gene expression.

Comparison and contrast of genes and biological pathways responding to Marek's disease virus infection using allele-specific expression and differential expression in broiler and layer chickens

BACKGROUND

Marek's disease (MD) is a commercially important neoplastic disease of chickens caused by the Marek's disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Enhancing MD genetic resistance is desirable to augment current vaccines and other MD control measures. High throughput sequencing was used to profile splenic transcriptomes from individual F1 progeny infected with MDV at 4 days of age from both outbred broilers (meat-type) and inbred layer (egg-type) chicken lines that differed in MD genetic resistance. The resulting information was used to identify SNPs, genes, and biological pathways exhibiting allele-specific expression (ASE) in response to MDV infection in each type of chicken. In addition, we compared and contrasted the results of pathway analyses (ASE and differential expression (DE)) between chicken types to help inform on the biological response to MDV infection.

RESULTS

With 7 individuals per line and treatment group providing high power, we identified 6,132 single nucleotide polymorphisms (SNPs) in 4,768 genes and 4,528 SNPs in 3,718 genes in broilers and layers, respectively, that exhibited ASE in response to MDV infection. Furthermore, 548 and 434 genes in broilers and layers, respectively, were found to show DE following MDV infection. Comparing the datasets, only 72 SNPs and 850 genes for ASE and 20 genes for DE were common between the two bird types. Although the chicken types used in this study were genetically different, at the pathway level, both TLR receptor and JAK/STAT signaling pathways were enriched as well as exhibiting a high proportion of ASE genes, especially at the beginning of both above mentioned regulatory pathways.

CONCLUSIONS

RNA sequencing with adequate biological replicates is a powerful approach to identify high confidence SNPs, genes, and pathways that are associated with transcriptional response to MDV infection. In addition, the SNPs exhibiting ASE in response to MDV infection provide a strong foundation for determining the extent to which variation in expression influences MD incidence plus yield genetic markers for genomic selection. However, given the paucity of overlap among ASE SNP sets (broilers vs. layers), it is likely that separate screens need to be incorporated for each population. Finally, comparison of gene lists obtained between these two diverse chicken types indicate the TLR and JAK/STAT signaling are conserved when responding to MDV infection and may be altered by selection of genes exhibiting ASE found at the start of each pathway.

Neural sensitivity to sex steroids predicts individual differences in aggression: implications for behavioural evolution

Testosterone (T) regulates many traits related to fitness, including aggression. However, individual variation in aggressiveness does not always relate to circulating T, suggesting that behavioural variation may be more closely related to neural sensitivity to steroids, though this issue remains unresolved. To assess the relative importance of circulating T and neural steroid sensitivity in predicting behaviour, we measured aggressiveness during staged intrusions in free-living male and female dark-eyed juncos (Junco hyemalis). We compared aggressiveness to plasma T levels and to the abundance of androgen receptor (AR), aromatase (AROM) and oestrogen receptor alpha (ORα) mRNA in behaviourally relevant brain areas (avian medial amygdala, hypothalamus and song control regions). We also asked whether patterns of covariation among behaviour and endocrine parameters differed in males and females, anticipating that circulating T may be a better predictor of behaviour in males than in females. We found that circulating T related to aggressiveness only in males, but that gene expression for ORα, AR and AROM covaried with individual differences in aggressiveness in both sexes. These findings are among the first to show that individual variation in neural gene expression for three major sex steroid-processing molecules predicts individual variation in aggressiveness in both sexes in nature. The results have broad implications for our understanding of the mechanisms by which aggressive behaviour may evolve.

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

Genetic-epidemiological studies on monozygotic (MZ) twins have been used for decades to tease out the relative contributions of genes and the environment to a trait. Phenotypic discordance in MZ twins has traditionally been ascribed to non-shared environmental factors acting after birth, however recent data indicate that this explanation is far too simple. In this paper, we review other reasons for discordance, including differences in the in utero environment, genetic mosaicism, and stochastic factors, focusing particularly on epigenetic discordance. Epigenetic differences are gaining increasing recognition. Although it is clear that in specific cases epigenetic alterations provide a causal factor in disease etiology, the overall significance of epigenetics in twin discordance remains unclear. It is also challenging to determine the causality and relative contributions of environmental, genetic, and stochastic factors to epigenetic variability. Epigenomic profiling studies have recently shed more light on the dynamics of temporal methylation change and methylome heritability, yet have not given a definite answer regarding their relevance to disease, because of limitations in establishing causality. Here, we explore the subject of epigenetics as another component in human phenotypic variability and its links to disease focusing particularly on evidence from MZ twin studies.

Differential allelic expression of IL13 and CSF2 genes associated with asthma

An important area of genetic research is the identification of functional mechanisms in polymorphisms associated with diseases. A highly relevant functional mechanism is the influence of polymorphisms on gene expression levels (differential allelic expression, DAE). The coding single nucleotide polymorphisms (SNPs) CSF2^rs25882 and IL13^rs20541 have been associated with asthma. In this work, we investigated whether the mRNA expression levels of CSF2 or IL13 were correlated with these SNPs. Samples were analyzed by mass spectrometry-based quantification of gene expression. Both SNPs influenced gene expression levels (CSF2^rs25882: p_overall = 0.008 and p_{DAE samples} = 0.00006; IL13^rs20541: p_overall = 0.059 and p_{DAE samples} = 0.036). For CSF2, the expression level was increased by 27.4% (95% CI: 18.5%–35.4%) in samples with significant DAE in the presence of one copy of risk variant CSF2^rs25882-T. The average expression level of IL13 was increased by 29.8% (95% CI: 3.1%–63.4%) in samples with significant DAE in the presence of one copy of risk variant IL13^rs20541-A. Enhanced expression of CSF2 could stimulate macrophages and neutrophils during inflammation and may be related to the etiology of asthma. For IL-13, higher expression could enhance the functional activity of the asthma-associated isoform. Overall, the analysis of DAE provides an efficient approach for identifying possible functional mechanisms that link disease-associated variants with altered gene expression levels.

Chicks and single-nucleotide polymorphisms: an entrée into identifying genes conferring disease resistance in chicken

Marek’s disease (MD) is one of the most serious chronic infectious disease threats to the poultry industry worldwide. Selecting for increased genetic resistance to MD is a control strategy that can augment current vaccinal control measures. Although our previous efforts integrating various genomic screens successfully identified three resistance genes, the main limitation was mapping precision, which hindered our ability to identify and further evaluate high-confidence candidate genes. Towards identifying the remaining genes of this complex trait, we incorporated three additional approaches made substantially more powerful through next-generation sequencing and that exploit the growing importance of expression variation. First, we screened for allele-specific expression (ASE) in response to Marek’s disease virus (MDV) infection, which, when allelic imbalance was identified, is sufficient to indicate a cis-acting element for a specific gene. Second, sequencing of genomic regions enriched by chromatin immunoprecipitation (ChIP) combined with transcript profiling identified motifs bound and genes directly regulated by MDV Meq, a bZIP transcription factor and the viral oncogene. Finally, analysis of genomic sequences from two experimental lines divergently selected for MD genetic resistance allowed inference about regions under selection as well as potential causative polymorphisms. These new combined approaches have resulted in a large number of high-confidence genes conferring MD resistance reflecting the multigenic basis of this trait, which expands our biological knowledge and provides corresponding single-nucleotide polymorhpisms (SNPs) that can be directly evaluated for their genetic contribution towards disease resistance.

Partitioning transcript variation in Drosophila: abundance, isoforms, and alleles

Multilevel analysis of transcription is facilitated by a new array design that includes modules for assessment of differential expression, isoform usage, and allelic imbalance in Drosophila. The ∼2.5 million feature chip incorporates a large number of controls, and it contains 18,769 3' expression probe sets and 61,919 exon probe sets with probe sequences from Drosophila melanogaster and 60,118 SNP probe sets focused on Drosophila simulans. An experiment in D. simulans identified genes differentially expressed between males and females (34% in the 3' expression module; 32% in the exon module). These proportions are consistent with previous reports, and there was good agreement (κ = 0.63) between the modules. Alternative isoform usage between the sexes was identified for 164 genes. The SNP module was verified with resequencing data. Concordance between resequencing and the chip design was greater than 99%. The design also proved apt in separating alleles based upon hybridization intensity. Concordance between the highest hybridization signals and the expected alleles in the genotype was greater than 96%. Intriguingly, allelic imbalance was detected for 37% of 6579 probe sets examined that contained heterozygous SNP loci. The large number of probes and multiple probe sets per gene in the 3' expression and exon modules allows the array to be used in D. melanogaster and in closely related species. The SNP module can be used for allele specific expression and genotyping of D. simulans.

Differential allelic expression of c.1568C > A at UGT2B15 is due to variation in a novel cis-regulatory element in the 3'UTR

Differential allelic expression (DAE) is a powerful tool to identify cis-regulatory elements for gene expression. The UDP-glucuronosyltransferase 2 family, polypeptide B15 (UGT2B15), is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In the present study, we measured the relative expression of two alleles at SNP c.1568C>A (rs4148269) in this gene, which causes an amino acid substitution (T523K). An excess of the C over the A allele was consistently observed in both liver (P=0.0021) and breast (P=0.012) samples, suggesting that SNP(s) in strong linkage disequilibrium (LD) with c.1568C>A can regulate UGT2B15 expression in both tissues. By resequencing, one such SNP, c.1761T>C (rs3100) in 3' untranslated region (UTR), was identified. Reporter gene assays showed that the 1761T allele results in a significantly higher gene expression level than the 1761C allele in HepG2, MCF-7, LNCaP, and Caco-2 cell lines (all P<0.001), thus indicating that this variation can regulate UGT2B15 gene expression in liver, breast, colon, and prostate tissues. Considering its location, we postulated that this SNP is within an unknown microRNA binding site and can influence microRNA targeting. Considering the importance of UGT2B15 in metabolism, we proposed that this SNP might contribute to multiple cancer risk and variability in drug response.

Developmental and genetic origins of murine long bone length variation

If we wish to understand whether development influences the rate or direction of morphological evolution, we must first understand the developmental bases of morphological variation within species. However, quantitative variation in adult morphology is the product of molecular and cellular processes unfolding from embryonic development through juvenile growth to maturity. The Atchley-Hall model provides a useful framework for dissecting complex morphologies into their component parts as a way of determining which developmental processes contribute to variation in adult form. We have examined differences in postnatal allometry and the patterns of genetic correlation between age-specific traits for ten recombinant inbred strains of mice generated from an intercross of LG/J and SM/J. Long bone length is closely tied to body size, but variation in adult morphology is more closely tied to differences in growth rate between 3 and 5 weeks of age. These analyses show that variation generated during early development is overridden by variation generated later in life. To more precisely determine the cellular processes generating this variation we then examined the cellular dynamics of long bone growth plates at the time of maximum elongation rate differences in the parent strains. Our analyses revealed that variation in long bone length is the result of faster elongation rates of the LG/J stain. The developmental bases for these differences in growth rate involve the rate of cell division and chondrocyte hypertrophy in the growth plate.

DeltaN133p53 expression levels in relation to haplotypes of the TP53 internal promoter region

The transcription of the DeltaN133p53 isoform of the TP53 gene is controlled by an internal promoter region (IPR) containing eight polymorphisms in 11 common haplotypes, following a resequencing of 47 Caucasians. We assayed the functional effects of the commonest six haplotypes on the promoter activity with a luciferase reporter system, in HeLa and 293T cells. These studies showed that different IPR haplotypes are associated with differences in the promoter activity resulting in marked variation in the baseline expression of DeltaN133p53. In vivo quantitative-polymerase chain reaction (PCR) on human tissues confirmed that the baseline levels of DeltaN133p53 showed haplotype specific differences that paralleled those seen in vitro. When cell lines were treated with camptothecin, the fold-increase in DeltaN133p53 levels was dose-dependent but haplotype-independent (i.e., similar for all the haplotypes). Finally, we used an electrophoretic mobility shift assay to analyze the rs1794287 polymorphism and found changes in the pattern of protein binding. This partially confirmed our in silico analysis showing that the polymorphism rs1794287 can affect the function of the internal promoter by changing its affinity for several transcription factors. Thus, we showed that the expression of DeltaN133p53 is under genetic control, and suggested the presence of interindividual differences underlying this mechanism.

Expression quantitative trait loci analysis in plants

An expression Quantitative Trait Locus or eQTL is a chromosomal region that accounts for a proportion of the variation in abundance of a mRNA transcript observed between individuals in a genetic mapping population. A single gene can have one or multiple eQTLs. Large scale mRNA profiling technologies advanced genome-wide eQTL mapping in a diverse range of organisms allowing thousands of eQTLs to be detected in a single experiment. When combined with classical or trait QTLs, correlation analyses can directly suggest candidates for genes underlying these traits. Furthermore, eQTL mapping data enables genetic regulatory networks to be modelled and potentially provide a better understanding of the underlying phenotypic variation. The mRNA profiling data sets can also be used to infer the chromosomal positions of thousands of genes, an outcome that is particularly valuable for species with unsequenced genomes where the chromosomal location of the majority of genes remains unknown. In this review we focus on eQTL studies in plants, addressing conceptual and technical aspects that include experimental design, genetic polymorphism prediction and candidate gene identification.

Allelic imbalance (AI) identifies novel tissue-specific cis-regulatory variation for human UGT2B15

Allelic imbalance (AI) is a powerful tool to identify cis-regulatory variation for gene expression. UGT2B15 is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In this study, we measured the relative expression of two alleles at this gene by using SNP rs1902023:G>T. An excess of the G over the T allele was consistently observed in liver (P<0.001), but not in breast (P=0.06) samples, suggesting that SNPs in strong linkage disequilibrium with G253T regulate UGT2B15 expression in liver. Seven such SNPs were identified by resequencing the promoter and exon 1, which define two distinct haplotypes. Reporter gene assays confirmed that one haplotype displayed approximately 20% higher promoter activity compared to the other major haplotype in liver HepG2 (P<0.001), but not in breast MCF-7 (P=0.540) cells. Reporter gene assays with additional constructs pointed to rs34010522:G>T and rs35513228:C>T as the cis-regulatory variants; both SNPs were also evaluated in LNCaP and Caco-2 cells. By ChIP, we showed that the transcription factor Nrf2 binds to the region spanning rs34010522:G>T in all four cell lines. Our results provide a good example for how AI can be used to identify cis-regulatory variation and gain insights into the tissue specific regulation of gene expression.

Allele-specific expression assays using Solexa

Background

Allele-specific expression (ASE) assays can be used to identify cis, trans, and cis-by-trans regulatory variation. Understanding the source of expression variation has important implications for disease susceptibility, phenotypic diversity, and adaptation. While ASE is commonly measured via relative fluorescence at a SNP, next generation sequencing provides an opportunity to measure ASE in an accurate and high-throughput manner using read counts.

Results

We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell. In brief, transcripts of interest, which contain a known SNP, are PCR enriched and barcoded to enable multiplexing. Then high-throughput sequencing is used to estimate allele-specific expression using sequencing counts. To validate this method, we measured the allelic bias in a dilution series and found high correlations between measured and expected values (r>0.9, p < 0.001). We applied this method to a set of 5 genes in a Drosophila simulans parental mix, F1 and introgression and found that for these genes the majority of expression divergence can be explained by cis-regulatory variation.

Conclusion

We present a new method with the capacity to measure ASE for large numbers of assays using as little as one lane of a Solexa flowcell. This will be a valuable technique for molecular and population genetic studies, as well as for verification of genome-wide data sets.

Studying genetic variations in cancer prognosis (and risk): a primer for clinicians

Rare, high-penetrance genetic variations account for a small portion of genetic cancer syndromes. In contrast, most cancers develop from a combination of minor genetic influences and environmental factors. There are numerous publications on cancer susceptibility. In contrast, genetic studies in treatment response and outcome analyses are a rapidly emerging field. Approaches used in disease susceptibility can be adapted for genetic outcome studies. In this review, we summarize the current knowledge on how candidate genes and genetic variations are selected to evaluate gene-outcome, gene-prognosis, and gene-treatment response relationships as applicable to the practicing oncologist.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Reverse engineering the genotype-phenotype map with natural genetic variation

The genetic variation that occurs naturally in a population is a powerful resource for studying how genotype affects phenotype. Each allele is a perturbation of the biological system, and genetic crosses, through the processes of recombination and segregation, randomize the distribution of these alleles among the progeny of a cross. The randomized genetic perturbations affect traits directly and indirectly, and the similarities and differences between traits in their responses to common perturbations allow inferences about whether variation in a trait is a cause of a phenotype (such as disease) or whether the trait variation is, instead, an effect of that phenotype. It is then possible to use this information about causes and effects to build models of probabilistic 'causal networks'. These networks are beginning to define the outlines of the 'genotype-phenotype map'.

Tissue-dependent limited pleiotropy affects gene expression in barley

Non-synonymous coding mutations in a gene change the resulting protein, no matter where it is expressed, but the effects of cis-regulatory mutations could be spatially or temporally limited - a phenomenon termed limited pleiotropy. Here, we report the genome-wide occurrence of limited pleiotropy of cis-regulatory mutations in barley (Hordeum vulgare L.) using Affymetrix analysis of 22,840 genes in a population of 139 doubled haploid lines derived from a cross between the cultivars Steptoe (St) and Morex (Mx). We identified robust cis-acting expression regulators that segregate as major genes in two successive ontogenetic stages: germinating embryo tissues and seedling leaves from the embryonic axis. We show that these polymorphisms may be consistent in both tissues or may cause a dramatic change in transcript abundance in one tissue but not in another. We also show that the parental allele that increases expression can vary with the tissue, suggesting nucleotide polymorphism in enhancer sequences. Because of the limited pleiotropy of cis-regulating mutations, the number of cis expression quantitative trait loci (cis-eQTLs) discovered by 'genetical genomics' is strongly affected by the particular tissue or developmental stage studied. Given that limited pleiotropy is a common feature of cis-regulatory mutations in barley, we predict that the phenomenon would be relevant to developmental and/or tissue-specific interactions across wide taxonomic boundaries in both plants and animals.

Mixture modeling of transcript abundance classes in natural populations

Expression profiling of Drosophila melanogaster adult female heads for 108 nearly isogenic lines from two different populations, and of CEPH lymphoblastoid lines, shows that differential expression of transcripts among individuals is due to a complex interplay of cis- and trans-acting factors.

Background

Populations diverge in genotype and phenotype under the influence of such evolutionary processes as genetic drift, mutation accumulation, and natural selection. Because genotype maps onto phenotype by way of transcription, it is of interest to evaluate how these evolutionary factors influence the structure of variation at the level of transcription. Here, we explore the distributions of cis-acting and trans-acting factors and their relative contributions to expression of transcripts that exhibit two or more classes of abundance among individuals within populations.

Results

Expression profiling using cDNA microarrays was conducted in Drosophila melanogaster adult female heads for 58 nearly isogenic lines from a North Carolina population and 50 from a California population. Using a mixture modeling approach, transcripts were identified that exhibit more than one mode of transcript abundance across the samples. Power studies indicate that sample sizes of 50 individuals will generally be sufficient to detect divergent transcript abundance classes. The distribution of transcript abundance classes is skewed toward low frequency minor classes, which is reminiscent of the typical skew in genotype frequencies. Similar results are observed in reported data on gene expression in human lymphoblast cell lines, in which analysis of association with linked polymorphisms implies that cis-acting single nucleotide polymorphisms make only a modest contribution to bimodal distributions of transcript abundance.

Conclusion

Population surveys of gene expression may complement genetical genomics as a general approach to quantifying sources of transcriptional variation. Differential expression of transcripts among individuals is due to a complex interplay of cis-acting and trans-acting factors.

The role of heritability in mapping expression quantitative trait loci

Gene expression, as a heritable complex trait, has recently been used in many genome-wide linkage studies. The estimated overall heritability of each trait may be considered as evidence of a genetic contribution to the total phenotypic variation, which implies the possibility of mapping genome regions responsible for the gene expression variation via linkage analysis. However, heritability has been found to be an inconsistent predictor of significant linkage signals. To investigate this issue in human studies, we performed genome-wide linkage analysis on the 3554 gene expression traits of 194 Centre d'Etude du Polymorphisme Humain individuals provided by Genetic Analysis Workshop 15. Out of the 422 expression traits with significant linkage signals identified (LOD > 5.3), 89 traits have low estimated heritability (h² < 10%), among which 23 traits have an estimated heritability equal to 0. The linkage analysis on individual pedigree shows that the overall LOD scores may result from a few pedigrees with strong linkage signals. Screening gene expressions before linkage analysis using a relatively low heritability (h² < 20%) may result in a loss of significant linkage signals, especially for trans-acting expression quantitative trait loci (49%).

Co-regulation and multilocus determinants of gene expression in humans

BACKGROUND

The regulation of gene expression is an emerging area of investigation. Increased knowledge can deepen our understanding of the genetic contributions to variations in complex traits. The purpose of this study is to explore the feasibility of detecting regulatory elements of gene expression with multivariate analyses.

METHODS

Peripheral blood lymphocyte expression levels of 30 genes on chromosome 5 and a single gene, DEAD, on chromosome 22 were analyzed in single-point variance-component linkage analyses in multiplex families to identify putative regulatory regions. To explore the possibility of regulatory regions having individual relationships with the expression levels of a single gene, we utilized stepwise regression. To explore the possibility of pleiotropy of a single regulatory locus for multiple genes, bivariate linkage analysis was applied.

RESULTS

Twenty-one loci were linked to five expression levels. The two most significant were for the known region on chromosome 22 (LOD = 4.62). On chromosome 5 a LOD of 4.57 was found for the gene leukocyte-derived arginine aminopeptidase (LRAP) with a single-nucleotide polymorphism (SNP) within 5 Mb. Both genes showed evidence of linkage to multiple SNPs. When 194 family members were treated as independent, stepwise regression identified fewer single-nucleotide polymorphisms with significant predictive values (p < 0.05), providing evidence for multiple regulatory regions of unequal effect. However, when corrections for non-independence were applied these results could no longer be detected.

CONCLUSION

The complex nature of gene regulation can be explored by linkage analysis with single-nucleotide polymorphisms followed by multivariate methods to explore co-regulation.

Variable sexually dimorphic gene expression in laboratory strains of Drosophila melanogaster

BACKGROUND

Wild-type laboratory strains of model organisms are typically kept in isolation for many years, with the action of genetic drift and selection on mutational variation causing lineages to diverge with time. Natural populations from which such strains are established, show that gender-specific interactions in particular drive many aspects of sequence level and transcriptional level variation. Here, our goal was to identify genes that display transcriptional variation between laboratory strains of Drosophila melanogaster, and to explore evidence of gender-biased interactions underlying that variability.

RESULTS

Transcriptional variation among the laboratory genotypes studied occurs more frequently in males than in females. Qualitative differences are also apparent to suggest that genes within particular functional classes disproportionately display variation in gene expression. Our analysis indicates that genes with reproductive functions are most often divergent between genotypes in both sexes, however a large proportion of female variation can also be attributed to genes without expression in the ovaries.

CONCLUSION

The present study clearly shows that transcriptional variation between common laboratory strains of Drosophila can differ dramatically due to sexual dimorphism. Much of this variation reflects sex-specific challenges associated with divergent physiological trade-offs, morphology and regulatory pathways operating within males and females.

Fundulus as the premier teleost model in environmental biology: opportunities for new insights using genomics

A strong foundation of basic and applied research documents that the estuarine fish Fundulus heteroclitus and related species are unique laboratory and field models for understanding how individuals and populations interact with their environment. In this paper we summarize an extensive body of work examining the adaptive responses of Fundulus species to environmental conditions, and describe how this research has contributed importantly to our understanding of physiology, gene regulation, toxicology, and ecological and evolutionary genetics of teleosts and other vertebrates. These explorations have reached a critical juncture at which advancement is hindered by the lack of genomic resources for these species. We suggest that a more complete genomics toolbox for F. heteroclitus and related species will permit researchers to exploit the power of this model organism to rapidly advance our understanding of fundamental biological and pathological mechanisms among vertebrates, as well as ecological strategies and evolutionary processes common to all living organisms.

Genomewide identification of genes under directional selection: gene transcription Q(ST) scan in diverging Atlantic salmon subpopulations

Evolutionary genomics has benefited from methods that allow identifying evolutionarily important genomic regions on a genomewide scale, including genome scans and QTL mapping. Recently, genomewide scanning by means of microarrays has permitted assessing gene transcription differences among species or populations. However, the identification of differentially transcribed genes does not in itself suffice to measure the role of selection in driving evolutionary changes in gene transcription. Here, we propose and apply a "transcriptome scan" approach to investigating the role of selection in shaping differential profiles of gene transcription among populations. We compared the genomewide transcription levels between two Atlantic salmon subpopulations that have been diverging for only six generations. Following assessment of normality and unimodality on a gene-per-gene basis, the additive genetic basis of gene transcription was estimated using the animal model. Gene transcription h(2) estimates were significant for 1044 (16%) of all detected cDNA clones. In an approach analogous to that of genome scans, we used the distribution of the Q(ST) values estimated from intra- and intersubpopulation additive genetic components of the transcription profiles to identify 16 outlier genes (average Q(ST) estimate = 0.11) whose transcription levels are likely to have evolved under the influence of directional selection within six generations only. Overall, this study contributes both empirically and methodologically to the quantitative genetic exploration of gene transcription data.

Nonlinear regulation enhances the phenotypic expression of trans-acting genetic polymorphisms

BACKGROUND

Genetic variation explains a considerable part of observed phenotypic variation in gene expression networks. This variation has been shown to be located both locally (cis) and distally (trans) to the genes being measured. Here we explore to which degree the phenotypic manifestation of local and distant polymorphisms is a dynamic feature of regulatory design.

RESULTS

By combining mathematical models of gene expression networks with genetic maps and linkage analysis we find that very different network structures and regulatory motifs give similar cis/trans linkage patterns. However, when the shape of the cis-regulatory input functions is more nonlinear or threshold-like, we observe for all networks a dramatic increase in the phenotypic expression of distant compared to local polymorphisms under otherwise equal conditions.

CONCLUSION

Our findings indicate that genetic variation affecting the form of cis-regulatory input functions may reshape the genotype-phenotype map by changing the relative importance of cis and trans variation. Our approach combining nonlinear dynamic models with statistical genetics opens up for a systematic investigation of how functional genetic variation is translated into phenotypic variation under various systemic conditions.

Unravelling the world of cis-regulatory elements

Genome-wide comparisons indicate that only studying the coding regions will not be enough for explaining the biological complexity of an organism, while the genetic variants and the epigenetic differences of cis-regulatory elements are crucial to elucidate many complicated biological phenomena. Their various regulatory functions also play indispensable roles in forming organismal polymorphism. Recent studies showed that the cis-regulatory elements can regulate gene expression as nuclear organizers, and involve in functional noncoding transcription and produce regulatory noncoding RNA molecules. Novel high-throughput strategies and in silico analysis make a great amount data of cis-regulatory elements available. Particularly, the computational methods could help to combine reductionist studies with network biomedical investigations, and begin the era to understand organismal regulatory events at systems biology level.

Merging mouse transcriptome analyses with Parkinson's disease linkage studies

The hallmark of Parkinson's disease (PD OMIM #168600) is the degeneration of the nigral dopaminergic system affecting approximately 1% of the human population older than 65. In pursuit of genetic factors contributing to PD, linkage and association studies identified several susceptibility genes. The majority of these genes are expressed by the dopamine-producing neurons in the substantia nigra. We, therefore, propose expression by these neurons as a selection criterion, to narrow down, in a rational manner, the number of candidate genes in orphan PD loci, where no mutation has been associated thus far. We determined the corresponding human chromosome locations of 1435 murine cDNA fragments obtained from murine expression analyses of nigral dopaminergic neurons and combined these data with human linkage studies. These fragments represent 19 genes within orphan OMIM PD loci. We used the same approach for independent association studies and determined the genes in neighborhood to the peaks with the highest LOD score value. Our approach did not make any assumptions about disease mechanisms, but it, nevertheless, revealed α-synuclein, NR4A2 (Nurr1), and the tau genes, which had previously been associated to PD. Furthermore, our transcriptome analysis identified several classes of candidate genes for PD mutations and may also provide insight into the molecular pathways active in nigral dopaminergic neurons.

The biological importance of measuring individual variation

Functional genomics research using Fundulus heteroclitus has focused on variation among individuals because of the evolutionary importance and value of Fundulus in explaining the human condition (why individual humans are different and are affected differently by stress,disease and drugs). Among different populations and species of Fundulus, there are evolutionarily adaptive differences in gene expression. This natural variation in gene expression seems to affect cardiac metabolism because up to 81% of the variation in glucose utilization observed in isolated heart ventricles is related to specific patterns of gene expression. The surprising result from this research is that among different groups of individuals, the expression of mRNA from different metabolic pathways explains substrate-specific metabolism. For example, variation in oxidative phosphorylation mRNAs explains glucose metabolism for one group of individuals but expression of glucose metabolism genes explains this metabolism in a different group of individuals. This variation among individuals has important implications for studies using inbred strains:conclusions based on one individual or one strain will not necessarily reflect a generalized conclusion for a population or species. Finally, there are surprisingly strong positive and negative correlations among metabolic genes,both within and between pathways. These data suggest that measures of mRNA expression are meaningful, yet there is a complexity in how gene expression is related to physiological processes.

Functional domains of the BACE1 and BACE2 promoters and mechanisms of transcriptional suppression of the BACE2 promoter in normal neuronal cells

The beta-amyloid (Abeta) protein present in the neuritic plaques of Alzheimer's disease is cleaved from Abeta precursor protein (APP) by beta- and gamma-secretases. Following identification of beta-APP cleaving enzyme (BACE1) as the beta-secretase, a homologous beta-secretase 2 (BACE2) was described. Our goal is to characterize the regulatory region of the BACE genes. We compare functional domains within the BACE1 and BACE2 regulatory regions. Both BACE genes lack canonical TATAand CAAT boxes, but they contain distinguishing transcription start sites and transcription factor-binding sites. The BACE1 sequence contains more repetitive elements than does BACE2 (no elements). Regulatory domains do not overlap strongly between the two promoter regions. The BACE1upstream sequence contains both negative and positive domains, separated from the transcription seat by a long neutral domain. The corresponding BACE2sequence consists of a weakly positive domain directly upstream of a strongly positive domain, near a functionally active domain. DNA-protein interaction was corroborated by functional data. In primary rat cortical cultures, BACE1-driven reporter protein's expression was twice that of BACE2- driven reporter. The BACE2 gene promoter relatively reduced function in neuronal cells compared with BACE1. The BACE1 gene might operate through a single transcriptional control site. BACE2 operates through dual transcriptional control sites. Two (or more) regulatory pathways might control transcription in BACE2. Thus, BACE2 is partially suppressed in normal neuronal cells and likely to be a highly regulated gene expressed in a particularly tissue-specific fashion.

Survey of polymorphic sequence variation in the immediate 5' region of human DNA repair genes

Systematic screens have revealed extensive DNA sequence variation existing in the human population. Studies of the role of polymorphic genetic variants in explaining the association of family history with risk of common disease have generally focused on variants predicted to disrupt protein structure and activity. Recent studies have identified genetic variation in the level of expression of many genes, variation that is potentially biologically relevant in explaining individual variation in disease risk. In a survey of data available for 108 DNA repair genes that have been systematically screened for sequence variation, an average of 3.3 SNPs per gene were found to exist at a variant allele frequency of at least 0.02 in the region 2kb upstream from the 5'-untranslated region. One-third of the genes harbored a SNP with an allele frequency of at least 0.02 within a predicted promotor element. These variants are distributed among promoter elements that average 20 elements per gene. The frequency of polymorphic SNPs in CpG islands was 0.8 per gene, while the frequency of SNPs in the 5'-UTR was 0.7 per gene. The recognition of extensive genetic variation with potential to impact levels of gene expression, and thereby exacerbate the impact of amino acid substitution variants on the activity of proteins, increases the complexity of analyses required to explain the molecular genetic basis for the familial contribution to the sporadic incidence of common disease.