Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques.

Integrative genomics and genetics approaches have proven to be a useful tool in elucidating the complex relationships often found in gene regulatory networks. More importantly, a number of studies have provided the necessary experimental evidence confirming the validity of the causal relationships inferred using such an approach. By integrating messenger RNA (mRNA) expression data with microRNA (miRNA) (i.e. small non-coding RNA with well-established regulatory roles in a myriad of biological processes) expression data, we show how integrative genomics approaches can be used to characterize the role played by approximately a third of registered mouse miRNAs within the context of a liver gene regulatory network. Our analysis reveals that the transcript abundances of miRNAs are subject to regulatory control by many more loci than previously observed for mRNA expression. Moreover, our results indicate that miRNAs exist as highly connected hub-nodes and function as key sensors within the transcriptional network. We also provide evidence supporting the hypothesis that miRNAs can act cooperatively or redundantly to regulate a given pathway and that miRNAs play a subtle role by dampening expression of their target gene through the use of feedback loops.

Niche adaptation by expansion and reprogramming of general transcription factors.

Numerous lineage-specific expansions of the transcription factor B (TFB) family in archaea suggests an important role for expanded TFBs in encoding environment-specific gene regulatory programs. Given the characteristics of hypersaline lakes, the unusually large numbers of TFBs in halophilic archaea further suggests that they might be especially important in rapid adaptation to the challenges of a dynamically changing environment. Motivated by these observations, we have investigated the implications of TFB expansions by correlating sequence variations, regulation, and physical interactions of all seven TFBs in Halobacterium salinarum NRC-1 to their fitness landscapes, functional hierarchies, and genetic interactions across 2488 experiments covering combinatorial variations in salt, pH, temperature, and Cu stress. This systems analysis has revealed an elegant scheme in which completely novel fitness landscapes are generated by gene conversion events that introduce subtle changes to the regulation or physical interactions of duplicated TFBs. Based on these insights, we have introduced a synthetically redesigned TFB and altered the regulation of existing TFBs to illustrate how archaea can rapidly generate novel phenotypes by simply reprogramming their TFB regulatory network.

Assessing the prospects of genome-wide association studies performed in inbred mice.

The remarkable success in mapping genes linked to a number of disease traits using genome-wide association studies (GWAS) in human cohorts has renewed interest in applying this same technique in model organisms such as inbred laboratory mice. Unlike humans, however, the limited genetic diversity in the ancestry of laboratory mice combined with selection pressure over the past decades have yielded an intricate population genetic structure that can complicate the results obtained from association studies. This problem is further exacerbated by the small number of strains typically used in such studies where multiple spurious associations arise as a result of random chance. We sought to empirically assess the viability of GWAS in inbred mice using hundreds of expression traits for which the true location of the expression quantitative trait locus was known a priori. We then measured transcript abundance levels for these expression traits in 16 classical and 3 wild-derived inbred strains and carried out a genome-wide association scan, demonstrating the low statistical power of such studies and empirically estimating the large extent to which allelic association of transcripts gives rise to spurious associations. We provide evidence illustrating that in a large fraction of cases, the marker with the most significant p values fails to map to the location of the true eQTL. Finally, we provide experimental support for hundreds of traits, and that combining linkage analysis with association mapping provides significant increases in statistical power over a stand-alone GWAS as well as significantly higher mapping resolution than either study alone.

Exon and junction microarrays detect widespread mouse strain- and sex-bias expression differences.

BACKGROUND: Studies have shown that genetic and sex differences strongly influence gene expression in mice. Given the diversity and complexity of transcripts produced by alternative splicing, we sought to use microarrays to establish the extent of variation found in mouse strains and genders. Here, we surveyed the effect of strain and sex on liver gene and exon expression using male and female mice from three different inbred strains. RESULTS: 71 liver RNA samples from three mouse strains - DBA/2J, C57BL/6J and C3H/HeJ - were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons ("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. CONCLUSION: Exon expression profiling identifies significantly more variation than both 3' gene expression profiling and whole-transcript gene expression profiling. A large percentage of genes that are not differentially expressed at the gene level demonstrate exon expression variation suggesting an influence of strain and sex on alternative splicing and a need to profile expression changes at sub-gene resolution.

Proteomic analyses of a Listeria monocytogenes mutant lacking sigmaB identify new components of the sigmaB regulon and highlight a role for sigmaB in the utilization of glycerol.

In Listeria monocytogenes the alternative sigma factor sigmaB plays important roles in both virulence and stress tolerance. In this study a proteomic approach was used to define components of the sigmaB regulon in L. monocytogenes 10403S (serotype 1/2a). Using two-dimensional gel electrophoresis and the recently developed isobaric tags for relative and absolute quantitation technique, the protein expression profiles of the wild type and an isogenic delta sigB deletion strain were compared. Overall, this study identified 38 proteins whose expression was sigmaB dependent; 17 of these proteins were found to require the presence of sigmaB for full expression, while 21 were expressed at a higher level in the delta sigB mutant background. The data obtained with the two proteomic approaches showed limited overlap (four proteins were identified by both methods), a finding that highlights the complementarity of the two technologies. Overall, the proteomic data reaffirmed a role for sigmaB in the general stress response and highlighted a probable role for sigmaB in metabolism, especially in the utilization of alternative carbon sources. Proteomic and physiological data revealed the involvement of sigmaB in glycerol metabolism. Five newly identified members of the sigmaB regulon were shown to be under direct regulation of sigmaB using reverse transcription-PCR (RT-PCR), while random amplification of cDNA ends-PCR was used to map four sigmaB-dependent promoters upstream from lmo0796, lmo1830, lmo2391, and lmo2695. Using RT-PCR analysis of known and newly identified sigmaB-dependent genes, as well as proteomic analyses, sigmaB was shown to play a major role in the stationary phase of growth in complex media.

DNA sequence-based subtyping and evolutionary analysis of selected Salmonella enterica serotypes.

While serotyping and phage typing have been used widely to characterize Salmonella isolates, sensitive subtyping methods that allow for evolutionary analyses are essential for examining Salmonella transmission, ecology, and evolution. A set of 25 Salmonella enterica isolates, representing five clinically relevant serotypes (serotypes Agona, Heidelberg, Schwarzengrund, Typhimurium, and Typhimurium var. Copenhagen) was initially used to develop a multilocus sequence typing (MLST) scheme for Salmonella targeting seven housekeeping and virulence genes (panB, fimA, aceK, mdh, icdA, manB, and spaN). A total of eight MLST types were found among the 25 isolates sequenced. A good correlation between MLST types and Salmonella serotypes was observed; only one serotype Typhimurium var. Copenhagen isolate displayed an MLST type otherwise typical for serotype Typhimurium isolates. Since manB, fimA, and mdh allowed for the highest subtype discrimination among the initial 25 isolates, we chose these three genes to perform DNA sequencing of an additional 41 Salmonella isolates representing a larger diversity of serotypes. This "three-gene sequence typing scheme" allowed discrimination of 25 sequence types (STs) among a total of 66 isolates; STs correlated well with serotypes and allowed within-serotype differentiation for 9 of the 12 serotypes characterized. Phylogenetic analyses showed that serotypes Kentucky and Newport could each be separated into two distinct, statistically well supported evolutionary lineages. Our results show that a three-gene sequence typing scheme allows for accurate serotype prediction and for limited subtype discrimination among clinically relevant serotypes of Salmonella. Three-gene sequence typing also supports the notion that Salmonella serotypes represent both monophyletic and polyphyletic lineages.