Variation in the Large-Scale Organization of Gene Expression Levels in the Hippocampus Relates to Stable Epigenetic Variability in Behavior

Despite sharing the same genes, identical twins demonstrate substantial variability in behavioral traits and in their risk for disease. Epigenetic factors-DNA and chromatin modifications that affect levels of gene expression without affecting the DNA sequence-are thought to be important in establishing this variability. Epigenetically-mediated differences in the levels of gene expression that are associated with individual variability traditionally are thought to occur only in a gene-specific manner. We challenge this idea by exploring the large-scale organizational patterns of gene expression in an epigenetic model of behavioral variability.To study the effects of epigenetic influences on behavioral variability, we examine gene expression in genetically identical mice. Using a novel approach to microarray analysis, we show that variability in the large-scale organization of gene expression levels, rather than differences in the expression levels of specific genes, is associated with individual differences in behavior. Specifically, increased activity in the open field is associated with increased variance of log-transformed measures of gene expression in the hippocampus, a brain region involved in open field activity. Early life experience that increases adult activity in the open field also similarly modifies the variance of gene expression levels. The same association of the variance of gene expression levels with behavioral variability is found with levels of gene expression in the hippocampus of genetically heterogeneous outbred populations of mice, suggesting that variation in the large-scale organization of gene expression levels may also be relevant to phenotypic differences in outbred populations such as humans. We find that the increased variance in gene expression levels is attributable to an increasing separation of several large, log-normally distributed families of gene expression levels. We also show that the presence of these multiple log-normal distributions of gene expression levels is a universal characteristic of gene expression in eurkaryotes. We use data from the MicroArray Quality Control Project (MAQC) to demonstrate that our method is robust and that it reliably detects biological differences in the large-scale organization of gene expression levels.Our results contrast with the traditional belief that epigenetic effects on gene expression occur only at the level of specific genes and suggest instead that the large-scale organization of gene expression levels provides important insights into the relationship of gene expression with behavioral variability. Understanding the epigenetic, genetic, and environmental factors that regulate the large-scale organization of gene expression levels, and how changes in this large-scale organization influences brain development and behavior will be a major future challenge in the field of behavioral genomics

Consistency Analysis of Redundant Probe Sets on Affymetrix Three-Prime Expression Arrays and Applications to Differential mRNA Processing

Affymetrix three-prime expression microarrays contain thousands of redundant probe sets that interrogate different regions of the same gene. Differential expression analysis methods rarely consider probe redundancy, which can lead to inaccurate inference about overall gene expression or cause investigators to overlook potentially valuable information about differential regulation of variant mRNA products. We investigated the behaviour and consistency of redundant probe sets in a publicly-available data set containing samples from mouse brain amygdala and hippocampus and asked how applying filtering methods to the data affected consistency of results obtained from redundant probe sets. A genome-based filter that screens and groups probe sets according to their overlapping genomic alignments significantly improved redundant probe set consistency. Screening based on qualitative Present-Absent calls from MAS5 also improved consistency. However, even after applying these filters, many redundant probe sets showed significant fold-change differences relative to each other, suggesting differential regulation of alternative transcript production. Visual inspection of these loci using an interactive genome visualization tool (igb.bioviz.org) exposed thirty putative examples of differential regulation of alternative splicing or polyadenylation across brain regions in mouse. This work demonstrates how P/A-call and genome-based filtering can improve consistency among redundant probe sets while at the same time exposing possible differential regulation of RNA processing pathways across sample types

A mathematical and computational review of Hartree-Fock SCF methods in Quantum Chemistry

We present here a review of the fundamental topics of Hartree-Fock theory in Quantum Chemistry. From the molecular Hamiltonian, using and discussing the Born-Oppenheimer approximation, we arrive to the Hartree and Hartree-Fock equations for the electronic problem. Special emphasis is placed in the most relevant mathematical aspects of the theoretical derivation of the final equations, as well as in the results regarding the existence and uniqueness of their solutions. All Hartree-Fock versions with different spin restrictions are systematically extracted from the general case, thus providing a unifying framework. Then, the discretization of the one-electron orbitals space is reviewed and the Roothaan-Hall formalism introduced. This leads to a exposition of the basic underlying concepts related to the construction and selection of Gaussian basis sets, focusing in algorithmic efficiency issues. Finally, we close the review with a section in which the most relevant modern developments (specially those related to the design of linear-scaling methods) are commented and linked to the issues discussed. The whole work is intentionally introductory and rather self-contained, so that it may be useful for non experts that aim to use quantum chemical methods in interdisciplinary applications. Moreover, much material that is found scattered in the literature has been put together here to facilitate comprehension and to serve as a handy reference.Comment: 64 pages, 3 figures, tMPH2e.cls style file, doublesp, mathbbol and subeqn package

Specific bottom–up effects of arbuscular mycorrhizal fungi across a plant–herbivore–parasitoid system

The majority of plants are involved in symbioses with arbuscular mycorrhizal fungi (AMF), and these associations are known to have a strong influence on the performance of both plants and insect herbivores. Little is known about the impact of AMF on complex trophic chains, although such effects are conceivable. In a greenhouse study we examined the effects of two AMF species, Glomus intraradices and G. mosseae on trophic interactions between the grass Phleum pratense, the aphid Rhopalosiphum padi, and the parasitic wasp Aphidius rhopalosiphi. Inoculation with AMF in our study system generally enhanced plant biomass (+5.2%) and decreased aphid population growth (−47%), but there were no fungal species-specific effects. When plants were infested with G. intraradices, the rate of parasitism in aphids increased by 140% relative to the G. mosseae and control treatment. When plants were associated with AMF, the developmental time of the parasitoids decreased by 4.3% and weight at eclosion increased by 23.8%. There were no clear effects of AMF on the concentration of nitrogen and phosphorus in plant foliage. Our study demonstrates that the effects of AMF go beyond a simple amelioration of the plants’ nutritional status and involve rather more complex species-specific cascading effects of AMF in the food chain that have a strong impact not only on the performance of plants but also on higher trophic levels, such as herbivores and parasitoids

In Silico and In Vitro Investigations of the Mutability of Disease-Causing Missense Mutation Sites in Spermine Synthase

Spermine synthase (SMS) is a key enzyme controlling the concentration of spermidine and spermine in the cell. The importance of SMS is manifested by the fact that single missense mutations were found to cause Snyder-Robinson Syndrome (SRS). At the same time, currently there are no non-synonymous single nucleoside polymorphisms, nsSNPs (harmless mutations), found in SMS, which may imply that the SMS does not tolerate amino acid substitutions, i.e. is not mutable.To investigate the mutability of the SMS, we carried out in silico analysis and in vitro experiments of the effects of amino acid substitutions at the missense mutation sites (G56, V132 and I150) that have been shown to cause SRS. Our investigation showed that the mutation sites have different degree of mutability depending on their structural micro-environment and involvement in the function and structural integrity of the SMS. It was found that the I150 site does not tolerate any mutation, while V132, despite its key position at the interface of SMS dimer, is quite mutable. The G56 site is in the middle of the spectra, but still quite sensitive to charge residue replacement.The performed analysis showed that mutability depends on the detail of the structural and functional factors and cannot be predicted based on conservation of wild type properties alone. Also, harmless nsSNPs can be expected to occur even at sites at which missense mutations were found to cause diseases

Placental 11-Beta Hydroxysteroid Dehydrogenase Methylation Is Associated with Newborn Growth and a Measure of Neurobehavioral Outcome

Background: There is growing evidence that the intrauterine environment can impact the neurodevelopment of the fetus through alterations in the functional epigenome of the placenta. In the placenta, the HSD11B2 gene encoding the 11-beta hydroxysteroid dehydrogenase enzyme, which is responsible for the inactivation of maternal cortisol, is regulated by DNA methylation, and has been shown to be susceptible to stressors from the maternal environment. Methodology/Principal Findings: We examined the association between DNA methylation of the HSD11B2 promoter region in the placenta of 185 healthy newborn infants and infant and maternal characteristics, as well as the association between this epigenetic variability and newborn neurobehavioral outcome assessed with the NICU Network Neurobehavioral Scales. Controlling for confounders, HSD11B2 methylation extent is greatest in infants with the lowest birthweights (P = 0.04), and this increasing methylation was associated with reduced scores of quality of movement (P = 0.04). Conclusions/Significance: These results suggest that factors in the intrauterine environment which contribute to birth outcome may be associated with placental methylation of the HSD11B2 gene and that this epigenetic alteration is in turn associated with a prospectively predictive early neurobehavioral outcome, suggesting in some part a mechanism for th

Modulation of Tcf7l2 Expression Alters Behavior in Mice

The comorbidity of type 2 diabetes (T2D) with several psychiatric diseases is well established. While environmental factors may partially account for these co-occurrences, common genetic susceptibilities could also be implicated in the confluence of these diseases. In support of shared genetic burdens, TCF7L2, the strongest genetic determinant for T2D risk in the human population, has been recently implicated in schizophrenia (SCZ) risk, suggesting that this may be one of many loci that pleiotropically influence both diseases. To investigate whether Tcf7l2 is involved in behavioral phenotypes in addition to its roles in glucose metabolism, we conducted several behavioral tests in mice with null alleles of Tcf7l2 or overexpressing Tcf7l2. We identified a role for Tcf7l2 in anxiety-like behavior and a dose-dependent effect of Tcf7l2 alleles on fear learning. None of the mutant mice showed differences in prepulse inhibition (PPI), which is a well-established endophenotype for SCZ. These results show that Tcf7l2 alters behavior in mice. Importantly, these differences are observed prior to the onset of detectable glucose metabolism abnormalities. Whether these differences are related to human anxiety-disorders or schizophrenia remains to be determined. These animal models have the potential to elucidate the molecular basis of psychiatric comorbidities in diabetes and should therefore be studied further

Genetic Mapping of Social Interaction Behavior in B6/MSM Consomic Mouse Strains

Genetic studies are indispensable for understanding the mechanisms by which individuals develop differences in social behavior. We report genetic mapping of social interaction behavior using inter-subspecific consomic strains established from MSM/Ms (MSM) and C57BL/6J (B6) mice. Two animals of the same strain and sex, aged 10 weeks, were introduced into a novel open-field for 10 min. Social contact was detected by an automated system when the distance between the centers of the two animals became less than ~12 cm. In addition, detailed behavioral observations were made of the males. The wild-derived mouse strain MSM showed significantly longer social contact as compared to B6. Analysis of the consomic panel identified two chromosomes (Chr 6 and Chr 17) with quantitative trait loci (QTL) responsible for lengthened social contact in MSM mice and two chromosomes (Chr 9 and Chr X) with QTL that inhibited social contact. Detailed behavioral analysis of males identified four additional chromosomes associated with social interaction behavior. B6 mice that contained Chr 13 from MSM showed more genital grooming and following than the parental B6 strain, whereas the presence of Chr 8 and Chr 12 from MSM resulted in a reduction of those behaviors. Longer social sniffing was observed in Chr 4 consomic strain than in B6 mice. Although the frequency was low, aggressive behavior was observed in a few pairs from consomic strains for Chrs 4, 13, 15 and 17, as well as from MSM. The social interaction test has been used as a model to measure anxiety, but genetic correlation analysis suggested that social interaction involves different aspects of anxiety than are measured by open-field test

Finding the needle in the haystack: why high-throughput screening is good for your health

High-throughput screening is an essential component of the toolbox of modern technologies that improve speed and efficiency in contemporary cancer drug development. This is particularly important as we seek to exploit, for maximum therapeutic benefit, the large number of new molecular targets emerging from the Human Genome Project and cancer genomics. Screening of diverse collections of low molecular weight compounds plays a key role in providing chemical starting points for iterative optimisation by medicinal chemistry. Examples of successful drug discovery programmes based on high-throughput screening are described, and these offer potential in the treatment of breast cancer and other malignancies