Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes

Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development

Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation

The R2R3-MYB Transcription Factor Gene Family in Maize

MYB proteins comprise a large family of plant transcription factors, members of which perform a variety of functions in plant biological processes. To date, no genome-wide characterization of this gene family has been conducted in maize (Zea mays). In the present study, we performed a comprehensive computational analysis, to yield a complete overview of the R2R3-MYB gene family in maize, including the phylogeny, expression patterns, and also its structural and functional characteristics. The MYB gene structure in maize and Arabidopsis were highly conserved, indicating that they were originally compact in size. Subgroup-specific conserved motifs outside the MYB domain may reflect functional conservation. The genome distribution strongly supports the hypothesis that segmental and tandem duplication contribute to the expansion of maize MYB genes. We also performed an updated and comprehensive classification of the R2R3-MYB gene families in maize and other plant species. The result revealed that the functions were conserved between maize MYB genes and their putative orthologs, demonstrating the origin and evolutionary diversification of plant MYB genes. Species-specific groups/subgroups may evolve or be lost during evolution, resulting in functional divergence. Expression profile study indicated that maize R2R3-MYB genes exhibit a variety of expression patterns, suggesting diverse functions. Furthermore, computational prediction potential targets of maize microRNAs (miRNAs) revealed that miR159, miR319, and miR160 may be implicated in regulating maize R2R3-MYB genes, suggesting roles of these miRNAs in post-transcriptional regulation and transcription networks. Our comparative analysis of R2R3-MYB genes in maize confirm and extend the sequence and functional characteristics of this gene family, and will facilitate future functional analysis of the MYB gene family in maize

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = −0.71 to −1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = −0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10⁻⁶, 1.7 × 10⁻⁹, 3.5 × 10⁻¹² and 1.0 × 10⁻⁴, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes

Investigation of the genetic interaction between BDNF and DRD3 genes in suicidical behaviour in psychiatric disorders

Objectives. Suicide is a serious public health concern, and it is partly genetic. The brain-derived neurotrophic factor (BDNF) gene has been a strong candidate in genetic studies of suicide (Dwivedi et al., Arch Gen Psychiatry 2010;60:804-815; Zai et al., Prog Neuropsychopharmacol Biol Psychiatry 2012;34:1412-1418) and BDNF regulates the expression of the dopamine D3 receptor. Objective. We examined the role of the BDNF and DRD3 genes in suicide. Methods. We analysed four tag single-nucleotide polymorphisms (SNPs) in BDNF and 15 SNPs in the D3 receptor gene DRD3 for possible association with suicide attempt history in our Canadian sample of Schizophrenia (SCZ) patients of European ancestry (N = 188). Results. In this sample, we found a possible interaction between the BDNF Val66Met and DRD3 Ser9Gly SNPs in increasing the risk of suicide attempt(s) in our SCZ sample. Specifically, a larger proportion of SCZ patients who were carrying at least one copy of the minor allele at each of the Val66Met and Ser9Gly functional markers have attempted suicides compared to patients with other genotypes (Bonferroni P < 0.05). However, we could not replicate this finding in samples from other psychiatric populations. Conclusions. Taken together, the results from the present study suggest that an interaction between BDNF and DRD3 may not play a major role in the risk for suicide attempt, though further studies, especially in SCZ, are required