A strategy for the integration of QTL, gene expression, and sequence analyses

Atp1a2 and Kcnj9 Are Candidate Genes Underlying Sensitivity to Oxycodone-Induced Locomotor Activation and Withdrawal-Induced Anxiety-Like Behaviors in C57BL/6 Substrains

Opioid use disorder is heritable, yet its genetic etiology is largely unknown. C57BL/6J and C57BL/6NJ mouse substrains exhibit phenotypic diversity in the context of limited genetic diversity which together can facilitate genetic discovery. Here, we found C57BL/6NJ mice were less sensitive to oxycodone (OXY)-induced locomotor activation versus C57BL/6J mice in a conditioned place preference paradigm. Narrow-sense heritability of OXY-induced locomotor activity traits ranged from 0.22 to 0.31, implicating suitability for genetic analysis. Quantitative trait locus (QTL) mapping in an F2 cross identified a chromosome 1 QTL explaining 7%-12% of the variance in OXY locomotion and anxiety-like withdrawal in the elevated plus maze. A second QTL for EPM withdrawal behavior on chromosome 5 near Gabra2 (alpha-2 subunit of GABA-A receptor) explained 9% of the variance. To narrow the chromosome 1 locus, we generated recombinant lines spanning 163-181 Mb, captured the QTL for OXY locomotor traits and withdrawal, and fine-mapped a 2.45-Mb region (170.16-172.61 Mb). Transcriptome analysis identified five, localized striatal cis-eQTL transcripts and two were confirmed at the protein level (KCNJ9, ATP1A2). Kcnj9 codes for a potassium channel (GIRK3) that is a major effector of mu opioid receptor signaling. Atp1a2 codes for a subunit of a Na+/K+ ATPase enzyme that regulates neuronal excitability and shows functional adaptations following chronic opioid administration. To summarize, we identified two candidate genes underlying the physiological and behavioral properties of opioids, with direct preclinical relevance to investigators employing these widely used substrains and clinical relevance to human genetic studies of opioid use disorder.

An integration analysis based on genomic, transcriptomic and QTX information reveals credible candidate genes for fat-related traits in pigs

Meat quality improvement is of great interest to researchers in pig breeding and many researchers have identified abundant associated quantitative trait loci, genes and polymorphisms (QTXs) for fat-related traits. However, it is challenging to determine credible candidate genes from a mass of associations. The efficiency of identification of credible candidate genes in these QTXs is restricted by limited integration analyses of data from multiple omics. In this study, we constructed a 'candidate gene map' of fat-related traits in pigs based on published literature and the latest genome. In total, 6,861 QTXs, which covered 9,323 genes on the pig genome, were used. Combining the QTX hotspots and pathway analysis, we identified 180 candidate genes that may regulate the fat-related traits, and choose PNPLA2, PPARG, SREBF1, ACACA, PPARD and PPARA as credible candidate genes. In addition, we discussed the importance of incorporating transcriptome data and genomic data in causal gene identification, and the multi-omics information can effectively improve the credibility of identified candidate genes.

Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development

Plant developmental dynamics can be heritable, genetically correlated with fitness and yield, and undergo selection. Therefore, characterizing the mechanistic connections between the genetic architecture governing plant development and the resulting ontogenetic dynamics of plants in field settings is critically important for agricultural production and evolutionary ecology. We use hierarchical Bayesian Function-Valued Trait (FVT) models to estimate Brassica rapa growth curves throughout ontogeny, across two treatments, and in two growing seasons. We find genetic variation for plasticity of growth rates and final sizes, but not the inflection point (transition from accelerating to decelerating growth) of growth curves. There are trade-offs between growth rate and duration, indicating that selection for maximum yields at early harvest dates may come at the expense of late harvest yields and vice versa. We generate eigengene modules and determine which are co-expressed with FVT traits using a Weighted Gene Co-expression Analysis. Independently, we seed a Mutual Rank co-expression network model with FVT traits to identify specific genes and gene networks related to FVT. GO-analyses of eigengene modules indicate roles for actin/cytoskeletal genes, herbivore resistance/wounding responses, and cell division, while MR networks demonstrate a close association between metabolic regulation and plant growth. We determine that combining FVT Quantitative Trait Loci (QTL) and MR genes/WGCNA eigengene expression profiles better characterizes phenotypic variation than any single data type (i.e. QTL, gene, or eigengene alone). Our network analysis allows us to employ a targeted eQTL analysis, which we use to identify regulatory hotspots for FVT. We examine cis vs. trans eQTL that mechanistically link FVT QTL with structural trait variation. Colocalization of FVT, gene, and eigengene eQTL provide strong evidence for candidate genes influencing plant height. The study is the first to explore eQTL for FVT, and specifically do so in agroecologically relevant field settings.

We estimate the developmental dynamics of plant growth using mathematical functions to fit continuous functions to discrete plant height data collected throughout growth, and we use the parameters defining these mathematical functions as data. We identify genomic regions controlling plant growth and filter a novel transcriptomic data set using network reconstruction models to identify the genes and eigengenes associated with plant height. We combine these genomic and transcriptomic data to predict variation in plant height, and we use quantitative genetics to mechanistically connect plant genetics, transcriptomics, and development. Our approach demonstrates two powerful methods for the type of data reduction (FVT modeling and gene expression network reconstruction for targeted eQTL analyses) and data integration that will be necessary for driving forward the field of genetics in the post-genomic era. To the best of our knowledge, we are the first to apply these techniques to continuous models of plant development, and the first to do so in agroecologically relevant field settings.

Cross-species molecular dissection across alcohol behavioral domains

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.

Effect of crossing C57BL/6 and FVB mouse strains on basal cytokine expression

C57BL/6 is the most often used laboratory mouse strain. However, sometimes it is beneficial to cross the transgenic mice on the C57BL/6 background to the other strain, such as FVB. Although this is a common strategy, the influence of crossing these different strains on homeostatic expression of cytokines is not known. Here we have investigated the differences in the expression of selected cytokines between C57BL/6J and C57BL/6JxFVB mice in serum and skeletal muscle. We have found that only few cytokines were altered by crossing of the strains. Concentrations of IL5, IL7, LIF, MIP-2, and IP-10 were higher in serum of C57BL/6J mice than in C57BL/6JxFVB mice, whereas concentration of G-CSF was lower in C57BL/6J. In the skeletal muscle only the concentration of VEGF was higher in C57BL/6J mice than in C57BL/6JxFVB mice. Concluding, the differences in cytokine expression upon crossing C57BL/6 and FVB strain in basal conditions are not profound.

Microarray expression analysis of the main inflorescence in Brassica napus

The effect of the number of pods on the main inflorescence (NPMI) on seed yield in Brassica napus plants grown at high density is a topic of great economic and scientific interest. Here, we sought to identify patterns of gene expression that determine the NPMI during inflorescence differentiation. We monitored gene expression profiles in the main inflorescence of two B. napus F₆ RIL pools, each composed of nine lines with a low or high NPMI, and their parental lines, Zhongshuang 11 (ZS11) and 73290, using a Brassica 90K elements oligonucleotide array. We identified 4,805 genes that were differentially expressed (≥1.5 fold-change) between the low- and high-NPMI samples. Of these, 82.8% had been annotated and 17.2% shared no significant homology with any known genes. About 31 enriched GO clusters were identified amongst the differentially expressed genes (DEGs), including those involved in hormone responses, development regulation, carbohydrate metabolism, signal transduction, and transcription regulation. Furthermore, 92.8% of the DEGs mapped to chromosomes that originated from B. rapa and B. oleracea, and 1.6% of the DEGs co-localized with two QTL intervals (PMI10 and PMI11) known to be associated with the NPMI. Overexpression of BnTPI, which co-localized with PMI10, in Arabidopsis suggested that this gene increases the NPMI. This study provides insight into the molecular factors underlying inflorescence architecture, NPMI determination and, consequently, seed yield in B. napus.

Identification of a QTL in Mus musculus for alcohol preference, withdrawal, and Ap3m2 expression using integrative functional genomics and precision genetics

Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits.

Identification of candidate genes associated with positive and negative heterosis in rice

To identify the genes responsible for yield related traits, and heterosis, massively parallel signature sequencing (MPSS) libraries were constructed from leaves, roots and meristem tissues from the two parents, 'Nipponbare' and '93-11', and their F1 hybrid. From the MPSS libraries, 1-3 million signatures were obtained. Using cluster analysis, commonly and specifically expressed genes in the parents and their F1 hybrid were identified. To understand heterosis in the F1 hybrid, the differentially expressed genes in the F1 hybrid were mapped to yield related quantitative trait loci (QTL) regions using a linkage map constructed from 131 polymorphic simple sequence repeat markers with 266 recombinant inbred lines derived from a cross between Nipponbare and 93-11. QTLs were identified for yield related traits including days to heading, plant height, plant type, number of tillers, main panicle length, number of primary branches per main panicle, number of kernels per main panicle, total kernel weight per main panicle, 1000 grain weight and total grain yield per plant. Seventy one QTLs for these traits were mapped, of which 3 QTLs were novel. Many highly expressed chromatin-related genes in the F1 hybrid encoding histone demethylases, histone deacetylases, argonaute-like proteins and polycomb proteins were located in these yield QTL regions. A total of 336 highly expressed transcription factor (TF) genes belonging to 50 TF families were identified in the yield QTL intervals. These findings provide the starting genomic materials to elucidate the molecular basis of yield related traits and heterosis in rice.

Genetic determinants of voluntary exercise

Variation in voluntary exercise behavior is an important determinant of long-term human health. Increased physical activity is used as a preventative measure or therapeutic intervention for disease, and a sedentary lifestyle has generally been viewed as unhealthy. Predisposition to engage in voluntary activity is heritable and induces protective metabolic changes, but its complex genetic/genomic architecture has only recently begun to emerge. We first present a brief historical perspective and summary of the known benefits of voluntary exercise. Second, we describe human and mouse model studies using genomic and transcriptomic approaches to reveal the genetic architecture of exercise. Third, we discuss the merging of genomic information and physiological observations, revealing systems and networks that lead to a more complete mechanistic understanding of how exercise protects against disease pathogenesis. Finally, we explore potential regulation of physical activity through epigenetic mechanisms, including those that persist across multiple generations.

An interval of the obesity QTL Nob3.38 within a QTL hotspot on chromosome 1 modulates behavioral phenotypes

A region on mouse distal chromosome 1 (Chr. 1) that is highly enriched in quantitative trait loci (QTLs) controlling neural and behavioral phenotypes overlaps with the peak region of a major obesity QTL (Nob3.38), which we identified in an intercross of New Zealand Obese (NZO) mice with C57BL/6J (B6). By positional cloning we recently identified a microdeletion within this locus causing the disruption of Ifi202b that protects from adiposity by suppressing expression of 11β-Hsd1. Here we show that the Nob3.38 segment also corresponds with the QTL rich region (Qrr1) on Chr. 1 and associates with increased voluntary running wheel activity, Rota-rod performance, decreased grip strength, and anxiety-related traits. The characterization of a subcongenic line carrying 14.2 Mbp of Nob3.38 with a polymorphic region of 4.4 Mbp indicates that the microdeletion and/or other polymorphisms in its proximity alter body weight, voluntary activity, and exploration. Since 27 out of 32 QTL were identified in crosses with B6, we hypothesized that the microdeletion and or adjacent SNPs are unique for B6 mice and responsible for some of the complex Qrr1-mediated effects. Indeed, a phylogenic study of 28 mouse strains revealed a NZO-like genotype for 22 and a B6-like genotype for NZW/LacJ and 4 other C57BL strains. Thus, we suggest that a Nob3.38 interval (173.0-177.4 Mbp) does not only modify adiposity but also neurobehavioral traits by a haplotype segregating with C57BL strains.

Genetic control of a central pattern generator: rhythmic oromotor movement in mice is controlled by a major locus near Atp1a2

Fluid licking in mice is a rhythmic behavior that is controlled by a central pattern generator (CPG) located in a complex of brainstem nuclei. C57BL/6J (B6) and DBA/2J (D2) strains differ significantly in water-restricted licking, with a highly heritable difference in rates (h(2)≥0.62) and a corresponding 20% difference in interlick interval (mean ± SEM = 116.3±1 vs 95.4±1.1 ms). We systematically quantified motor output in these strains, their F(1) hybrids, and a set of 64 BXD progeny strains. The mean primary interlick interval (MPI) varied continuously among progeny strains. We detected a significant quantitative trait locus (QTL) for a CPG controlling lick rate on Chr 1 (Lick1), and a suggestive locus on Chr 10 (Lick10). Linkage was verified by testing of B6.D2-1D congenic stock in which a segment of Chr 1 of the D2 strain was introgressed onto the B6 parent. The Lick1 interval on distal Chr 1 contains several strong candidate genes. One of these is a sodium/potassium pump subunit (Atp1a2) with widespread expression in astrocytes, as well as in a restricted population of neurons. Both this subunit and the entire Na(+)/K(+)-ATPase molecule have been implicated in rhythmogenesis for respiration and locomotion. Sequence variants in or near Apt1a2 strongly modulate expression of the cognate mRNA in multiple brain regions. This gene region has recently been sequenced exhaustively and we have cataloged over 300 non-coding and synonymous mutations segregating among BXD strains, one or more of which is likely to contribute to differences in central pattern generator tempo.

Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos

Background

In the field of mouse genetics the advent of technologies like microarray based expression profiling dramatically increased data availability and sensitivity, yet these advanced methods are often vulnerable to the unavoidable heterogeneity of in vivo material and might therefore reflect differentially expressed genes between mouse strains of no relevance to a targeted experiment. The aim of this study was not to elaborate on the usefulness of microarray analysis in general, but to expand our knowledge regarding this potential “background noise” for the widely used Illumina microarray platform surpassing existing data which focused primarily on the adult sensory and nervous system, by analyzing patterns of gene expression at different embryonic stages using wild type strains and modern transgenic models of often non-isogenic backgrounds.

Results

Wild type embryos of 11 mouse strains commonly used in transgenic and molecular genetic studies at three developmental time points were subjected to Illumina microarray expression profiling in a strain-by-strain comparison. Our data robustly reflects known gene expression patterns during mid-gestation development. Decreasing diversity of the input tissue and/or increasing strain diversity raised the sensitivity of the array towards the genetic background. Consistent strain sensitivity of some probes was attributed to genetic polymorphisms or probe design related artifacts.

Conclusion

Our study provides an extensive reference list of gene expression profiling background noise of value to anyone in the field of developmental biology and transgenic research performing microarray expression profiling with the widely used Illumina microarray platform. Probes identified as strain specific background noise further allow for microarray expression profiling on its own to be a valuable tool for establishing genealogies of mouse inbred strains.

Systems genetic analysis of the effects of iron deficiency in mouse brain

Iron regulation in the brain is both necessary and highly complex. Too little or too much iron can compromise neurological function, yet we still do not know all of the regulatory processes. In our research, we seek to identify genes and gene networks underlying individual differences in brain iron regulation. To this end, we fed mice from 20+ inbred strains a diet low in iron from weaning to 4 months of age. At sacrifice, we measured iron content in the ventral midbrain (VMB). The VMB contains the substantia nigra, a region particularly vulnerable to iron imbalance. The results showed high, inter-strain variability in dietary iron reduction, from almost no loss to more than 40 % vs. control. When we performed quantitative trait loci (QTL) analysis, we observed a significant area on chromosome 2. Within this QTL, we selected glial high-affinity glutamate transporter 1 (Glt1) as the leading candidate. Expression of this gene is both correlated with VMB iron and is also cis-modulated by local sequence variants that segregate in the BXD family. VMB expression differences of Glt1 in six strains covary with differential susceptibility to VMB iron loss.

Cancer evolution and individual susceptibility

Cancer susceptibility is due to interactions between inherited genetic factors and exposure to environmental carcinogens. The genetic component is constituted mainly by weakly acting low-penetrance genetic variants that interact among themselves, as well as with the environment. These low susceptibility genes can be categorized into two main groups: one includes those that control intrinsic tumor cell activities (i.e. apoptosis, proliferation or DNA repair), and the other contains those that modulate the function of extrinsic tumor cell compartments (i.e. stroma, angiogenesis, or endocrine and immune systems). Genome-Wide Association Studies (GWAS) of human populations have identified numerous genetic loci linked with cancer risk and behavior, but nevertheless the major component of cancer heritability remains to be explained. One reason may be that GWAS cannot readily capture gene-gene or gene-environment interactions. Mouse model approaches offer an alternative or complementary strategy, because of our ability to control both the genetic and environmental components of risk. Recently developed genetic tools, including high-throughput technologies such as SNP, CGH and gene expression microarrays, have led to more powerful strategies for refining quantitative trait loci (QTL) and identifying the critical genes. In particular, the cross-species approaches will help to refine locations of QTLs, and reveal their genetic and environmental interactions. The identification of human tumor susceptibility genes and discovery of their roles in carcinogenesis will ultimately be important for the development of methods for prediction of risk, diagnosis, prevention and therapy for human cancers.

Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays

C57BL/6J (B6) and DBA/2J (D2) are two of the most commonly used inbred mouse strains in neuroscience research. However, the only currently available mouse genome is based entirely on the B6 strain sequence. Subsequently, oligonucleotide microarray probes are based solely on this B6 reference sequence, making their application for gene expression profiling comparisons across mouse strains dubious due to their allelic sequence differences, including single nucleotide polymorphisms (SNPs). The emergence of next-generation sequencing (NGS) and the RNA-Seq application provides a clear alternative to oligonucleotide arrays for detecting differential gene expression without the problems inherent to hybridization-based technologies. Using RNA-Seq, an average of 22 million short sequencing reads were generated per sample for 21 samples (10 B6 and 11 D2), and these reads were aligned to the mouse reference genome, allowing 16,183 Ensembl genes to be queried in striatum for both strains. To determine differential expression, ‘digital mRNA counting’ is applied based on reads that map to exons. The current study compares RNA-Seq (Illumina GA IIx) with two microarray platforms (Illumina MouseRef-8 v2.0 and Affymetrix MOE 430 2.0) to detect differential striatal gene expression between the B6 and D2 inbred mouse strains. We show that by using stringent data processing requirements differential expression as determined by RNA-Seq is concordant with both the Affymetrix and Illumina platforms in more instances than it is concordant with only a single platform, and that instances of discordance with respect to direction of fold change were rare. Finally, we show that additional information is gained from RNA-Seq compared to hybridization-based techniques as RNA-Seq detects more genes than either microarray platform. The majority of genes differentially expressed in RNA-Seq were only detected as present in RNA-Seq, which is important for studies with smaller effect sizes where the sensitivity of hybridization-based techniques could bias interpretation.

Genetic dissection of intermale aggressive behavior in BALB/cJ and A/J mice

Aggressive behaviors are disabling, treatment refractory, and sometimes lethal symptoms of several neuropsychiatric disorders. However, currently available treatments for patients are inadequate, and the underlying genetics and neurobiology of aggression is only beginning to be elucidated. Inbred mouse strains are useful for identifying genomic regions, and ultimately the relevant gene variants (alleles) in these regions, that affect mammalian aggressive behaviors, which, in turn, may help to identify neurobiological pathways that mediate aggression. The BALB/cJ inbred mouse strain exhibits relatively high levels of intermale aggressive behaviors and shows multiple brain and behavioral phenotypes relevant to neuropsychiatric syndromes associated with aggression. The A/J strain shows very low levels of aggression. We hypothesized that a cross between BALB/cJ and A/J inbred strains would reveal genomic loci that influence the tendency to initiate intermale aggressive behavior. To identify such loci, we conducted a genomewide scan in an F2 population of 660 male mice bred from BALB/cJ and A/J inbred mouse strains. Three significant loci on chromosomes 5, 10 and 15 that influence aggression were identified. The chromosome 5 and 15 loci are completely novel, and the chromosome 10 locus overlaps an aggression locus mapped in our previous study that used NZB/B1NJ and A/J as progenitor strains. Haplotype analysis of BALB/cJ, NZB/B1NJ and A/J strains showed three positional candidate genes in the chromosome 10 locus. Future studies involving fine genetic mapping of these loci as well as additional candidate gene analysis may lead to an improved biological understanding of mammalian aggressive behaviors.

Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse

BACKGROUND

The current study focused on the extent genetic diversity within a species (Mus musculus) affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS) formed from the same eight inbred strains that have been used to create the collaborative cross (CC). The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6) × DBA/2J (D2) F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum) gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA).

RESULTS

Genes reliably detected as expressed were similar in all three data sets as was the variability of expression. As measured by the WGCNA, the modular structure of the transcriptome networks was also preserved both on the basis of module assignment and from the perspective of the topological overlap maps. Details of the HS-CC gene modules are provided; essentially identical results were obtained for the HS4 and F2 modules. Gene ontology annotation of the modules revealed a significant overrepresentation in some modules for neuronal processes, e.g., central nervous system development. Integration with known protein-protein interactions data indicated significant enrichment among co-expressed genes. We also noted significant overlap with markers of central nervous system cell types (neurons, oligodendrocytes and astrocytes). Using the Allen Brain Atlas, we found evidence of spatial co-localization within the striatum for several modules. Finally, for some modules it was possible to detect an enrichment of transcription binding sites. The binding site for Wt1, which is associated with neurodegeneration, was the most significantly overrepresented.

CONCLUSIONS

Despite the marked differences in genetic diversity, the transcriptome structure was remarkably similar for the F2, HS4 and HS-CC. These data suggest that it should be possible to integrate network data from simple and complex crosses. A careful examination of the HS-CC transcriptome revealed the expected structure for striatal gene expression. Importantly, we demonstrate the integration of anatomical and network expression data.

Genetic architecture of voluntary exercise in an advanced intercross line of mice

Exercise is essential for health, yet the amount, duration, and intensity that individuals engage in are strikingly variable, even under prescription. Our focus was to identify the locations and effects of quantitative trait loci (QTL) controlling genetic predisposition for exercise-related traits, utilizing a large advanced intercross line (AIL) of mice. This AIL (G(4)) population originated from a reciprocal cross between mice with genetic propensity for increased voluntary exercise [high-runner (HR) line, selectively bred for increased wheel running] and the inbred strain C57BL/6J. After adjusting for family structure, we detected 32 significant and 13 suggestive QTL representing both daily running traits (distance, duration, average speed, and maximum speed) and the mean of these traits on days 5 and 6 (the selection criteria for HR) of a 6-day test conducted at 8 wk of age, with many co-localizing to similar genomic regions. Additionally, seven significant and five suggestive QTL were observed for the slope and intercept of a linear regression across all 6 days of running, some representing a combination of the daily traits. We also observed two significant and two suggestive QTL for body mass before exercise. These results, from a well-defined animal model, reinforce a genetic basis for the predisposition to engage in voluntary exercise, dissect this predisposition into daily segments across a continuous time period, and present unique QTL that may provide insight into the initiation, continuation, and temporal pattern of voluntary activity in mammals.

High throughput sequencing in mice: a platform comparison identifies a preponderance of cryptic SNPs

Background

Allelic variation is the cornerstone of genetically determined differences in gene expression, gene product structure, physiology, and behavior. However, allelic variation, particularly cryptic (unknown or not annotated) variation, is problematic for follow up analyses. Polymorphisms result in a high incidence of false positive and false negative results in hybridization based analyses and hinder the identification of the true variation underlying genetically determined differences in physiology and behavior. Given the proliferation of mouse genetic models (e.g., knockout models, selectively bred lines, heterogeneous stocks derived from standard inbred strains and wild mice) and the wealth of gene expression microarray and phenotypic studies using genetic models, the impact of naturally-occurring polymorphisms on these data is critical. With the advent of next-generation, high-throughput sequencing, we are now in a position to determine to what extent polymorphisms are currently cryptic in such models and their impact on downstream analyses.

Results

We sequenced the two most commonly used inbred mouse strains, DBA/2J and C57BL/6J, across a region of chromosome 1 (171.6 – 174.6 megabases) using two next generation high-throughput sequencing platforms: Applied Biosystems (SOLiD) and Illumina (Genome Analyzer). Using the same templates on both platforms, we compared realignments and single nucleotide polymorphism (SNP) detection with an 80 fold average read depth across platforms and samples. While public datasets currently annotate 4,527 SNPs between the two strains in this interval, thorough high-throughput sequencing identified a total of 11,824 SNPs in the interval, including 7,663 new SNPs. Furthermore, we confirmed 40 missense SNPs and discovered 36 new missense SNPs.

Conclusion

Comparisons utilizing even two of the best characterized mouse genetic models, DBA/2J and C57BL/6J, indicate that more than half of naturally-occurring SNPs remain cryptic. The magnitude of this problem is compounded when using more divergent or poorly annotated genetic models. This warrants full genomic sequencing of the mouse strains used as genetic models.

QTL analyses of temporal and intensity components of home-cage activity in KJR and C57BL/6J strains

BACKGROUND

A variety of mouse strains exhibit diversity in spontaneous activity consistent with an important genetic contribution. To date, many studies have defined spontaneous home-cage activity as total distance or total counts of activity within a test period. However, spontaneous activity is, in fact, a composite of elements of 'temporal' and 'intensity' that is similar to 'velocity'. Here, we report on quantitative trait loci for different components of spontaneous activity, an important step towards dissection of the underlying genetic mechanisms.

RESULTS

In the analysis of total home-cage activity (THA) after habituation in female mice, KJR strain exhibit higher activity than C57BL/6J (B6). In this study, THA was partitioned into two components: active time (AT) was an index of the 'temporal element' of THA, average activity during active time (AA) was an index of 'intensity'. Correlation analysis using B6xKJR F2 female mice indicated that AA is a major component of THA, whereas AA and AT were associated to a lesser degree. To explore the genetic basis of the activity differences, we conducted quantitative trait loci (QTL) analysis on data of THA and its components, AT and AA. Three significant QTL affecting variation of different components of home cage activity were identified, two linked QTL Hylaq1 and Hylaq2 on Chr 2, and Hylaq3 on Chr 10. Chromosomal positions of these QTL were previously implicated in locomotor activity (Chr 2) or open-field ambulation (Chr 10). The results indicated that Hylaq1 influences AT, Hylaq2, AA, while Hylaq3 is associated with both AA and AT.

CONCLUSION

Through this study, we found that variation in total home cage activity over a 3 day period is affected by variation in active time and intensity of activity. The latter two variables are distinct components of home cage activity with only partially overlapping genetic architecture.

Detection of reciprocal quantitative trait loci for acute ethanol withdrawal and ethanol consumption in heterogeneous stock mice

RATIONALE

Previous studies have suggested that there is an inverse genetic relationship between ethanol consumption (two-bottle choice, continuous access) and ethanol withdrawal (e.g., Metten et al., Behav Brain Res 95:113-122, 1998a).

OBJECTIVES

The current study used short-term selective breeding from heterogeneous stock (HS) animals to examine this relationship. The primary goal of the current study was to determine if reciprocal quantitative trait loci (QTLs) could be found in the selectively bred lines. The advantage of detecting QTLs in HS animals is that it is possible to extract a haplotype signature for the QTL, which in turn can be used to narrow the number of candidate genes generated from gene expression and sequence databases (see, e.g., Hitzemann et al., Mamm Genome 14:733-747, 2003).

RESULTS

Seven reciprocal QTLs were detected on chromosomes (Chr) 1 (two), 3, 6, 11, 16, and 17 that exceeded the nominal LOD threshold of 10; genetic drift, which occurs during selection, dramatically increases the LOD threshold. The proximal Chr 1 QTL was examined in some detail. The haplotype structure of the QTL was such that the LP/J allele was associated with low withdrawal and high consumption. The QTL appears to be located in a gene-poor region between 170 and 173 Mbp. Based on available sequence data, two plausible candidate genes emerge-Nos1ap and Atf6alpha.

CONCLUSIONS

The data presented here confirm some aspects of the negative genetic relationship between acute ethanol withdrawal and ethanol consumption. The QTL data point to the potential involvement of NO signaling and/or the unfolded protein response.

The future of mouse QTL mapping to diagnose disease in mice in the age of whole-genome association studies

Genome-wide association analysis is emerging as a powerful tool to define novel genes and molecular pathways involved in susceptibility to human complex disorders. However, in spite of recent successes, this approach is not without its limitations, the most notable of which is inconsistent phenotype penetrance due to varied environmental exposures. Mouse models do, however, circumvent some of these drawbacks by allowing for a much higher degree of control over genetic variation and environmental exposure, and although their application to human complex genetics is not always straightforward, they do serve as a powerful means of complementing observations in human populations. Mouse quantitative trait locus mapping has proven a successful, yet technically demanding method for defining trait susceptibility. In this review, we focus upon recent advances that are both reducing the technical burden traditionally associated with quantitative trait locus mapping, and enhancing the applicability of these approaches to human disease.

A systematic strategy for the discovery of candidate genes responsible for phenotypic variation

It is increasingly common to combine genome-wide expression data with quantitative trait mapping data to aid in the search for sequence polymorphisms responsible for phenotypic variation. By joining these complex but different data types at the level of the biological pathway, we can take advantage of existing biological knowledge to systematically identify possible mechanisms of genotype-phenotype interaction. With the development of web services and workflows, this process can be made rapid and systematic. Our methodology was applied to a use case of resistance to African trypanosomiasis in mice. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://www.myexperiment.org/users/43/workflows .

Evidence for epigenetic interactions for loci on mouse chromosome 1 regulating open field activity

The expression of motor activity levels in response to novel situations is under complex genetic and environmental control. Several genetic loci have been implicated in the regulation of this behavioral phenotype, but their relationship to epigenetic and epistatic interactions is relatively unknown. Here, we report on a quantitative trait locus (QTL) on mouse chromosome 1 for novelty-induced motor activity in the open field, using chromosome substitution strains derived from a high active host strain (C57BL/6J) and a low active donor strain (A/J). The QTL for open field (horizontal distance moved) peaked at the location of Kcnj9, however, QTL detection was initially masked by an interplay of both grandparent genetic origin and genetic co-factors influencing behavior on chromosome 1. Our findings indicate that epigenetic interactions can play an important role in the identification of behavioral QTLs and must be taken into consideration when applying behavioral genetic strategies.

Dissection of a QTL hotspot on mouse distal chromosome 1 that modulates neurobehavioral phenotypes and gene expression

A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 (Chr 1) that corresponds to human Chr 1q21-q23. This region is highly enriched in quantitative trait loci (QTLs) that control neural and behavioral phenotypes, including motor behavior, escape latency, emotionality, seizure susceptibility (Szs1), and responses to ethanol, caffeine, pentobarbital, and haloperidol. This region also controls the expression of a remarkably large number of genes, including genes that are associated with some of the classical traits that map to distal Chr 1 (e.g., seizure susceptibility). Here, we ask whether this QTL-rich region on Chr 1 (Qrr1) consists of a single master locus or a mixture of linked, but functionally unrelated, QTLs. To answer this question and to evaluate candidate genes, we generated and analyzed several gene expression, haplotype, and sequence datasets. We exploited six complementary mouse crosses, and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1. Qrr1 can be broadly divided into a proximal part (Qrr1p) and a distal part (Qrr1d), each associated with the expression of distinct subsets of genes. Qrr1d controls RNA metabolism and protein synthesis, including the expression of approximately 20 aminoacyl-tRNA synthetases. Qrr1d contains a tRNA cluster, and this is a functionally pertinent candidate for the tRNA synthetases. Rgs7 and Fmn2 are other strong candidates in Qrr1d. FMN2 protein has pronounced expression in neurons, including in the dendrites, and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d. Our analysis revealed a highly complex gene expression regulatory interval in Qrr1, composed of multiple loci modulating the expression of functionally cognate sets of genes.

High-resolution genetic mapping of mammalian motor activity levels in mice

The generation of motor activity levels is under tight neural control to execute essential behaviors, such as movement toward food or for social interaction. To identify novel neurobiological mechanisms underlying motor activity levels, we studied a panel of chromosome substitution (CS) strains derived from mice with high (C57BL/6J strain) or low motor activity levels (A/J strain) using automated home cage behavioral registration. In this study, we genetically mapped the expression of baseline motor activity levels (horizontal distance moved) to mouse chromosome 1. Further genetic mapping of this trait revealed an 8.3-Mb quantitative trait locus (QTL) interval. This locus is distinct from the QTL interval for open-field anxiety-related motor behavior on this chromosome. By data mining, an existing phenotypic and genotypic data set of 2445 genetically heterogeneous mice (http://gscan.well.ox.ac.uk/), we confirmed linkage to the peak marker at 79 970 253 bp and refined the QTL to a 312-kb interval containing a single gene (A830043J08Rik). Sequence analysis showed a nucleotide deletion in the 3' untranslated region of the Riken gene. Genome-wide microarray gene expression profiling in brains of discordant F(2) individuals from CS strain 1 showed a significant upregulation of Epha4 in low-active F(2) individuals. Inclusion of a genetic marker for Epha4 confirmed that this gene is located outside of the QTL interval. Both Epha4 and A830043J08Rik are expressed in brain motor circuits, and similar to Epha4 mutants, we found linkage between reduced motor neurons number and A/J chromosome 1. Our findings provide a novel QTL and a potential downstream target underlying motor circuitry development and the expression of physical activity levels.

Systematic analysis of emotionality in consomic mouse strains established from C57BL/6J and wild-derived MSM/Ms

Consomic strains have recently attracted attention as an advantageous method to screen for genes related to developmental, physiological, and behavioral phenotypes. Recently, a new set of consomic strains was established from the Japanese wild-derived mouse strain MSM/Ms and C57BL/6JJcl. By analyzing the entire consomic panel, we were able to identify a number of chromosomes associated with anxiety-like behaviors in the open-field (OF) test, a light-dark box and an elevated plus maze. Detailed observation of the OF behavior allowed us to identify chromosomes associated with those ethological traits, such as stretch attend, rearing, and jumping. Repeated OF test trials have different meanings for animals, and we found that some chromosomes responded to only the first or second trial, while others were consistent across both trials. By examining both male and female mice, sex-dependent effects were found in several measurements. Principal component analysis of anxiety-like behaviors extracted five factors: 'general locomotor activity', 'thigmotaxis', 'risk assessment', 'open-arm exploration' and 'autonomic emotionality'. We mapped chromosomes associated with these five factors of emotionality.

Gene expression profiling of Hfe-/- liver and duodenum in mouse strains with differing susceptibilities to iron loading: identification of transcriptional regulatory targets of Hfe and potential hemochromatosis modifiers

Background

Hfe disruption in mouse leads to experimental hemochromatosis by a mechanism that remains elusive. Affymetrix GeneChip^® Mouse Genome 430 2.0 microarrays and bioinformatics tools were used to characterize patterns of gene expression in the liver and the duodenum of wild-type and Hfe-deficient B6 and D2 mice (two inbred mouse strains with divergent iron loading severity in response to Hfe disruption), to clarify the mechanisms of Hfe action, and to identify potential modifier genes.

Results

We identified 1,343 transcripts that were upregulated or downregulated in liver and 370 in duodenum of Hfe^-/- mice, as compared to wild-type mice of the same genetic background. In liver, Hfe disruption upregulated genes involved in antioxidant defense, reflecting mechanisms of hepatoprotection activated by iron overload. Hfe disruption also downregulated the expression of genes involved in fatty acid β-oxidation and cholesterol catabolism, and of genes participating in mitochondrial iron traffic, suggesting a link between Hfe and the mitochondrion in regulation of iron homeostasis. These latter alterations may contribute to the inappropriate iron deficiency signal sensed by the duodenal enterocytes of these mice, and the subsequent upregulation of the genes encoding the ferrireductase Dcytb and several iron transporters or facilitators of iron transport in the duodenum. In addition, for several genes differentially expressed between B6 and D2 mice, expression was regulated by loci overlapping with previously mapped Hfe-modifier loci.

Conclusion

The expression patterns identified in this study contribute novel insights into the mechanisms of Hfe action and potential candidate genes for iron loading severity.

Quantitative genetics in the age of omics

The use of natural variation in the genetic dissection of quantitative traits has a long-standing tradition. Recent advances in high-throughput technologies for the quantification of biological molecules have shifted the focus in quantitative genetics from single traits to comprehensive large-scale analyses. So-called omic technologies now enable geneticists to take a look in the black box that translates genetic information into biological function. These processes include transcriptional and (post) translational regulation as well as metabolic signaling pathways. The progress made in analytical and statistical techniques now allows the construction of regulatory networks that integrate the different levels of the biological information flow from gene-to-function.

Behavioural analysis of congenic mouse strains confirms stress-responsive Loci on chromosomes 1 and 12

The way in which animals respond to stressful environments correlates with anxiety-related behaviour. To begin identifying the genetic factors that influence anxiety, we have studied the stress-responsiveness of inbred mouse strains using a modified form of the open field activity test (OFA), termed the elevated (e) OFA. In particular, two strains show high (DBA/2J) or low (C57BL/6J) stress-responsiveness in the eOFA. Genetic studies of an F(2) intercross between these two strains previously identified two regions, on chromosomes (Chr) 1 and 12, linked to anxiety-related behaviour. To confirm that these regions contain loci for stress-responsiveness, we established separate congenic mouse strains for the linked Chr1 and Chr12 regions. Each congenic strain harbours a DBA/2J-derived interval encompassing the linked region on the C57BL/6J genetic background: the congenic intervals are between, but not including approximately 48.6 Mb and approximately 194.8 Mb on Chr1, and approximately 36.2 Mb and the distal end of Chr12. Cohorts of DBA/2J, C57BL/6J and congenic mice were analysed for a series of stress-responsive phenotypes using the eOFA test. Both congenic strains had significantly different stress-responsive phenotypes compared to the low-stress C57BL/6J parental strain, but the DBA/2J-derived Chr12 interval had a greater genetic effect than the DBA/2J-derived Chr1 interval for changing the behavioral phenotype of the parental C57BL/6J mouse strain. These results confirmed the presence of stress-responsive loci on Chr1 and Chr12. New stress-related phenotypes were also identified, which aided in comparing and differentiating DBA/2J, C57BL/6J and congenic mice.

Fine mapping of mouse QTLs for fatness using SNP data

Quantitative trait loci (QTLs), as determined in crossbred studies, are a valuable resource to identify genes responsible for the corresponding phenotypic variances. Due to their broad chromosomal extension of some dozens of megabases, further steps are necessary to bring the number of candidate genes that underlie the detected effects to a reasonable order of magnitude. We use a set of 13,370 SNPs to identify informative haplotype blocks in 22 mouse QTLs for fatness. About half of the genes in a typical QTL overlap with haplotype blocks, which are different for the two base mouse lines, and which, thus, qualify for further analysis. For these genes we collect four more pieces of evidence for association with fat accumulation, namely (1) homology to genes identified in a Caenorhabditis elegans knock-out experiment as fat decreasing or fat increasing, (2) the overexpression of the genes in mouse fat, liver, muscle, or hypothalamus tissues, (3) the occurrence of a gene in several independently found QTLs, and (4) the information provided by gene ontology, to achieve a ranked list of 131 candidate genes. Ten genes fulfill three or four of the above sketched criteria and are discussed briefly, 121 further genes fulfilling two criteria are provided as on-line material. Viewing the genomic region of fatness-related QTLs under several different aspects is appropriate to assess the many thousands of genes that reside in such QTLs and to produce lists of more robust candidate genes.

A simple method for combining genetic mapping data from multiple crosses and experimental designs

Background

Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs.

Methodology/Principal Findings

We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fisher's combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values.

Conclusions/Significance

Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results.

Genetic determinants of emotionality and stress response in AcB/BcA recombinant congenic mice and in silico evidence of convergence with cardiovascular candidate genes

Genomic loci bearing stress-related phenotypes were dissected in recombinant congenic strains (RCS) of mice with C57BL/6J (B6) and A/J progenitors. Adult male mice from 14 A/J and 22 B6 background lines were evaluated for emotional reactivity in open-field (OF) and elevated plus-maze tests. Core temperature was monitored by radio telemetry during immobilization and on standard as well as salt-enriched diets. In addition, urinary electrolytes were measured. Genome-wide linkage analysis of the parameters revealed over 20 significant quantitative trait loci (QTL). The highest logarithm of odds (LOD) scores were within the previously-reported OF emotionality locus on Chr 1 (LOD = 4.6), in the dopa decarboxylase region on Chr 11 for the plus-maze (LOD = 4.7), and within a novel region of calmodulin 1 on Chr 12 for Ca++ excretion after a 24-h salt load (LOD = 4.6). RCS stress QTL overlapped with several candidate loci for cardiovascular (CV) disease. In silico evidence of functional polymorphisms by comparative sequence analysis of progenitor strains assisted to ascertain this convergence. The anxious BcA70 strain showed down regulation of Atp1a2 gene expression in the heart (P < 0.001) and brain (P < 0.05) compared with its parental B6 strain, compatible with the enhanced emotionality described in knock out animals for this gene, also involved in the salt-sensitive component of hypertension. Functional polymorphisms in regulatory elements of candidate genes of the CV/inflammatory/immune systems support the hypothesis of genetically-altered environmental susceptibility in CV disease development.

Characterization of the quantitative trait locus for haloperidol-induced catalepsy on distal mouse chromosome 1

We report here the confirmation of the quantitative trait locus for haloperidol-induced catalepsy on distal chromosome (Chr) 1. We determined that this quantitative trait locus was captured in the B6.D2-Mtv7a/Ty congenic mouse strain, whose introgressed genomic interval extends from approximately 169.1 to 191.3 Mb. We then constructed a group of overlapping interval-specific congenic strains to further break up the interval and remapped the locus between 177.5 and 183.4 Mb. We next queried single nucleotide polymorphism (SNP) data sets and identified three genes with nonsynonymous coding SNPs in the quantitative trait locus. We also queried two brain gene expression data sets and found five known genes in this 5.9-Mb interval that are differentially expressed in both whole brain and striatum. Three of the candidate quantitative trait genes were differentially expressed using quantitative real-time polymerase chain reaction analyses. Overall, the current study illustrates how multiple approaches, including congenic fine mapping, SNP analysis and microarray gene expression screens, can be integrated both to reduce the quantitative trait locus interval significantly and to detect promising candidate quantitative trait genes.

Genetical genomics: combining gene expression with marker genotypes in poultry

Microarrays have been widely implemented across the life sciences, although there is still debate on the most effective uses of such transcriptomics approaches. In genetical genomics, gene expression measurements are treated as quantitative traits, and genome regions affecting expression levels are denoted as expression QTL (eQTL). The detected eQTL can represent a locus that lies close to the gene that is being controlled (cis-acting) or one or more loci that are unlinked to the gene that is being controlled (trans-acting). One powerful outcome of genetical genomics is the reconstruction of genetic pathways underlying complex trait variation. Because of the modest size of experiments to date, genetical genomics may fall short of its promise to unravel genetic networks. We propose to combine expression studies with fine mapping of functional trait loci. This synergistic approach facilitates the implementation of genetical genomics for species without inbred resources but is equally applicable to model species. Among livestock species, poultry is well placed to embrace this technology with the availability of the chicken genome sequence, microarrays for various platforms, as well as experimental populations in which QTL have been mapped. In the buildup toward full-blown eQTL studies, we can study the effects of known candidate genes or marked QTL at the gene expression level in more focused studies. To demonstrate the potential of genetical genomics, we have identified the cis and trans effects for a functional BW QTL on chicken chromosome 4 in breast tissue samples from chickens with contrasting QTL genotypes.

A genome-wide set of congenic mouse strains derived from CAST/Ei on a C57BL/6 background

We previously reported the construction of two sets of heterozygous congenic strains spanning the mouse genome. For both sets, C57BL/6J was employed as the background strain while DNA from either DBA/2 or CAST/Ei was introgressed to form the congenic region. We have subsequently bred most of these strains to produce homozygous breeding stocks. Here, we report the characterization of the strain set based on CAST/Ei. CAST/Ei is the most genetically distant strain within the Mus mus species and many trait variations relevant to common diseases have been identified in CAST/Ei mice. Despite breeding difficulties for some congenic regions, presumably due to incompatible allelic variations between CAST/Ei and C57BL/6, the resulting congenic strains cover about 80% of the autosomal chromosomes and will be useful as a resource for the further analysis of quantitative trait loci between the strains.

Further studies on using multiple-cross mapping (MCM) to map quantitative trait loci

We have completed whole-genome scans for quantitative trait loci (QTLs) associated with acute ethanol-induced activation in the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2) , BALB/cJ (C), and LP/J (LP) inbred strains. The goal was to test the hypothesis that given the relatively simple structure of the laboratory mouse genome, the same QTLs will be detected in multiple crosses which in turn will provide support for the strategy of multiple-cross mapping (MCM). QTLs with LOD scores greater than 4 were detected on Chrs 1, 2, 3, 8, 9, 13, 14, and 16. Only for the QTL on distal Chr 1 was there convincing evidence that the same or at least a very similar QTL was detected in multiple crosses. We also mapped the Chr 2 QTL directly in heterogeneous stock (HS) animals derived from the four inbred strains. At G(19) the QTL was mapped to an approximately 3-Mbp interval and this interval was associated with a haplotype block with a largely biallelic structure: B6-L:C-D2. We conclude that mapping in HS animals not only provides significantly greater QTL resolution, at least in some cases it provides significantly more information about the QTL haplotype structure.

Heterosis and polymorphisms of gene expression in an elite rice hybrid as revealed by a microarray analysis of 9198 unique ESTs

Despite the significant contributions of utilizing heterosis to crop productivity worldwide, the biological mechanisms of heterosis remained largely uncharacterized. In this study, we analyzed gene expression profiles of an elite rice hybrid and the parents at three stages of young panicle development, using a cDNA microarray consisting of 9198 expressed sequence tags (ESTs), with the objective to reveal patterns of gene expression that may be associated with heterosis in yield. A total of 8422 sequences showed hybridization signals in all three genotypes in at least one stage and 5771 sequences produced detectable signals in all slides. Significant differences in expression level were detected for 438 sequences among the three genotypes in at least one of the three stages, as determined by ANOVA validated with 100 permutations at P < 0.05. Significant mid-parent heterosis was detected for 141 sequences, which demonstrated the following features: a much larger number of sequences showed negative heterosis than ones showing positive heterosis; genes functioning in DNA replication and repair tended to show positive heterosis; genes functioning in carbohydrate metabolism, lipid metabolism, energy metabolism, translation, protein degradation, and cellular information processing showed negative heterosis; both positive and negative heterosis were observed for genes in amino acid metabolism, transcription, signal transduction, plant defense and transportation. The results are indicative of the biochemical and physiological activities taking place in the hybrid relative to the parents. Identification of genes showing expression polymorphisms among different genotypes and heterotic expression in the hybrid may provide new avenues for exploring the biological mechanisms underlying heterosis.

An integrative approach for the identification of quantitative trait loci

The genetic dissection of complex traits is one of the most difficult and most important challenges facing science today. We discuss here an integrative approach to quantitative trait loci (QTL) mapping in mice. This approach makes use of the wealth of genetic tools available in mice, as well as the recent advances in genome sequence data already available for a number of inbred mouse strains. We have developed mapping strategies that allow a stepwise narrowing of a QTL mapping interval, prioritizing candidate genes for further analysis with the potential of identifying the most probable candidate gene for the given trait. This approach integrates traditional mapping tools, fine mapping tools, sequence-based analysis, bioinformatics and gene expression.

Inheritance patterns of transcript levels in F1 hybrid mice

Genetic analysis of transcriptional regulation is a rapidly emerging field of investigation that promises to shed light on the regulatory networks that control gene expression. Although a number of such studies have been carried out, the nature and extent of the heritability of gene expression traits have not been well established. We describe the inheritance of transcript levels in liver tissue in the first filial (F1) generation of mice obtained from reciprocal crosses between the common inbred strains A/J and C57BL/6J. We obtain estimates of genetic and technical variance components from these data and demonstrate that shrinkage estimators can increase detectable heritability. Estimates of heritability vary widely from transcript to transcript, with one-third of transcripts showing essentially no heritability (<0.01) and one-quarter showing very high heritability (>0.50). Roughly half of all transcripts are differentially expressed between the two parental strains. Most transcripts show an additive pattern of inheritance. Dominance effects were observed for 20% of transcripts and a small number of transcripts were identified as showing an overdominance mode of inheritance. In addition, we identified 314 transcripts with expression levels that differ between the reciprocal F1 animals. These genes may be related to maternal effect.

Gene expression profiling in the striatum of inbred mouse strains with distinct opioid-related phenotypes

Background

Mouse strains with a contrasting response to morphine provide a unique model for studying the genetically determined diversity of sensitivity to opioid reward, tolerance and dependence. Four inbred strains selected for this study exhibit the most distinct opioid-related phenotypes. C57BL/6J and DBA/2J mice show remarkable differences in morphine-induced antinociception, self-administration and locomotor activity. 129P3/J mice display low morphine tolerance and dependence in contrast to high sensitivity to precipitated withdrawal observed in SWR/J and C57BL/6J strains. In this study, we attempted to investigate the relationships between genetic background and basal gene expression profile in the striatum, a brain region involved in the mechanism of opioid action.

Results

Gene expression was studied by Affymetrix Mouse Genome 430v2.0 arrays with probes for over 39.000 transcripts. Analysis of variance with the control for false discovery rate (q < 0.01) revealed inter-strain variation in the expression of ~3% of the analyzed transcripts. A combination of three methods of array pre-processing was used to compile a list of ranked transcripts covered by 1528 probe-sets significantly different between the mouse strains under comparison. Using Gene Ontology analysis, over-represented patterns of genes associated with cytoskeleton and involved in synaptic transmission were identified. Differential expression of several genes with relevant neurobiological function (e.g. GABA-A receptor alpha subunits) was validated by quantitative RT-PCR. Analysis of correlations between gene expression and behavioural data revealed connection between the level of mRNA for K homology domain containing, RNA binding, signal transduction associated 1 (Khdrbs1) and ATPase Na+/K+ alpha2 subunit (Atp1a2) with morphine self-administration and analgesic effects, respectively. Finally, the examination of transcript structure demonstrated a possible inter-strain variability of expressed mRNA forms as for example the catechol-O-methyltransferase (Comt) gene.

Conclusion

The presented study led to the recognition of differences in the gene expression that may account for distinct phenotypes. Moreover, results indicate strong contribution of genetic background to differences in gene transcription in the mouse striatum. The genes identified in this work constitute promising candidates for further animal studies and for translational genetic studies in the field of addictive and analgesic properties of opioids.

Pooled analysis of data from multiple quantitative trait locus mapping populations

Quantitative trait locus (QTL) analysis on pooled data from multiple populations (pooled analysis) provides a means for evaluating, as a whole, evidence for existence of a QTL from different studies and examining differences in gene effect of a QTL among different populations. Objectives of this study were to: (1) develop a method for pooled analysis and (2) conduct pooled analysis on data from two soybean mapping populations. Least square interval mapping was extended for pooled analysis by inclusion of populations and cofactor markers as indicator variables and covariate variables separately in the multiple linear models. The general linear test approach was applied for detecting a QTL. Single population-based and pooled analyses were conducted on data from two F(2:3) mapping populations, Hamilton (susceptible) x PI 90763 (resistant) and Magellan (susceptible) x PI 404198A (resistant), for resistance to soybean cyst nematode (SCN) in soybean. It was demonstrated that where a QTL was shared among populations, pooled analysis showed increased LOD values on the QTL candidate region over single population analyses. Where a QTL was not shared among populations, however, the pooled analysis showed decreased LOD values on the QTL candidate region over single population analyses. Pooled analysis on data from genetically similar populations may have higher power of QTL detection than single population-based analyses. QTLs were identified by pooled analysis on linkage groups (LGs) G, B1 and J for resistance to SCN race 2 whereas QTLs on LGs G, B1 and E for resistance to SCN race 5 in soybean PI 90763 and PI 404198A. QTLs on LG G and B1 were identified in both PI 90763 and PI 404198A whereas QTLs on LG E and J were identified in PI 90763 only. QTLs on LGs G and B1 for resistance to race 2 may be the same or closely linked with QTLs on LG G and B1 for resistance to race 5, respectively. It was further demonstrated that QTLs on G and B1 carried by PI 90763 were not significantly different in gene effect from QTLs on LGs G and B1 in PI 404198A, respectively.

Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice

Activation of the mesolimbic dopamine reward pathway by acute ethanol produces reinforcement and changes in gene expression that appear to be crucial to the molecular basis for adaptive behaviors and addiction. The inbred mouse strains DBA/2J and C57BL/6J exhibit contrasting acute behavioral responses to ethanol. We used oligonucleotide microarrays and bioinformatics methods to characterize patterns of gene expression in three brain regions of the mesolimbic reward pathway of these strains. Expression profiling included examination of both differences in gene expression 4 h after saline injection or acute ethanol (2 g/kg). Using a rigorous stepwise method for microarray analysis, we identified 788 genes differentially expressed in control DBA/2J versus C57BL/6J mice and 307 ethanol-regulated genes in the nucleus accumbens, prefrontal cortex, and ventral tegmental area. There were strikingly divergent patterns of ethanol-responsive gene expression in the two strains. Ethanol-responsive genes also showed clustering at discrete chromosomal regions, suggesting local chromatin effects in regulation. Ethanol-regulated genes were generally related to neuroplasticity, but regulation of discrete functional groups and pathways was brain region specific: glucocorticoid signaling, neurogenesis, and myelination in the prefrontal cortex; neuropeptide signaling and developmental genes, including factor Bdnf, in the nucleus accumbens; and retinoic acid signaling in the ventral tegmental area. Bioinformatics analysis identified several potential candidate genes for quantitative trait loci linked to ethanol behaviors, further supporting a role for expression profiling in identifying genes for complex traits. Brain region-specific changes in signaling and neuronal plasticity may be critical components in development of lasting ethanol behavioral phenotypes such as dependence, sensitization, and craving.

Natural variation and genetic covariance in adult hippocampal neurogenesis

Adult hippocampal neurogenesis is highly variable and heritable among laboratory strains of mice. Adult neurogenesis is also remarkably plastic and can be modulated by environment and activity. Here, we provide a systematic quantitative analysis of adult hippocampal neurogenesis in two large genetic reference panels of recombinant inbred strains (BXD and AXB/BXA, n = 52 strains). We combined data on variation in neurogenesis with a new transcriptome database to extract a set of 190 genes with expression patterns that are also highly variable and that covary with rates of (i) cell proliferation, (ii) cell survival, or the numbers of surviving (iii) new neurons, and (iv) astrocytes. Expression of a subset of these neurogenesis-associated transcripts was controlled in cis across the BXD set. These self-modulating genes are particularly interesting candidates to control neurogenesis. Among these were musashi (Msi1h) and prominin1/CD133 (Prom1), both of which are linked to stem-cell maintenance and division. Twelve neurogenesis-associated transcripts had significant cis-acting quantitative trait loci, and, of these, six had plausible biological association with adult neurogenesis (Prom1, Ssbp2, Kcnq2, Ndufs2, Camk4, and Kcnj9). Only one cis-acting candidate was linked to both neurogenesis and gliogenesis, Rapgef6, a downstream target of ras signaling. The use of genetic reference panels coupled with phenotyping and global transcriptome profiling thus allowed insight into the complexity of the genetic control of adult neurogenesis.

Gene expression profiling of arthritis using a QTL chip reveals a complex gene regulation of the Cia5 region in mice

One of the major quantitative trait loci (QTLs) associated with arthritis in crosses between B10.RIII and RIIIS/J mice is the Cia5 on chromosome 3. Early in the congenic mapping process it was clear that the locus was complex, consisting of several subloci with small effects. Therefore, we developed two novel strategies to dissect a QTL: the partial advanced inter-cross (PAI) strategy, with which we recently found the Cia5 region to consist of three loci, Cia5, Cia21 and Cia22, and now we introduce the QTL-chip strategy, where we have combined congenic mapping with a QTL-restricted expression profiling using a novel microarray design. The expression of QTL genes was compared between parental and congenic mice in lymph node, spleen and paw samples in five biological replicates and in dye-swapped experiments at three time points during the induction phase of arthritis. The QTL chip approach revealed 4 genes located in Cia21, differently expressed in lymph nodes, and 14 genes in Cia22, located within two clusters. One cluster contains six genes, differently expressed in spleen, and the second cluster contains eight genes, differently expressed in paws. We conclude the QTL-chip strategy to be valuable in the selection of candidate genes to be prioritized for further investigation.

Gene expression differences in mice divergently selected for methamphetamine sensitivity

In an effort to identify genes that may be important for drug-abuse liability, we mapped behavioral quantitative trait loci (bQTL) for sensitivity to the locomotor stimulant effect of methamphetamine (MA) using two mouse lines that were selectively bred for high MA-induced activity (HMACT) or low MA-induced activity (LMACT). We then examined gene expression differences between these lines in the nucleus accumbens, using 20 U74Av2 Affymetrix microarrays and quantitative polymerase chain reaction (qPCR). Expression differences were detected for several genes, including Casein Kinase 1 Epsilon (Csnkle), glutamate receptor, ionotropic, AMPA1 (GluR1), GABA B1 receptor (Gabbr1), and dopamine- and cAMP-regulated phosphoprotein of 32 kDa (Darpp-32). We used the www.WebQTL.org database to identify QTL that regulate the expression of the genes identified by the microarrays (expression QTL; eQTL). This approach identified an eQTL for Csnkle on Chromosome 15 (LOD = 3.8) that comapped with a bQTL for the MA stimulation phenotype (LOD = 4.5), suggesting that a single allele may cause both traits. The chromosomal region containing this QTL has previously been associated with sensitivity to the stimulant effects of cocaine. These results suggest that selection was associated with (and likely caused) altered gene expression that is partially attributable to different frequencies of gene expression polymorphisms. Combining classical genetics with analysis of whole-genome gene expression and bioinformatic resources provides a powerful method for provisionally identifying genes that influence complex traits. The identified genes provide excellent candidates for future hypothesis-driven studies, translational genetic studies, and pharmacological interventions.