Identifying cis-regulatory elements by statistical analysis and phylogenetic footprinting and analyzing their coexistence and related gene ontology

Discovery of cis-regulatory elements in gene promoters is a highly challenging research issue in computational molecular biology. This paper presents a novel approach to searching putative cis-regulatory elements in human promoters by first finding 8-mer sequences of high statistical significance from gene promoters of humans, mice, and Drosophila melanogaster, respectively, and then identifying the most conserved ones across the three species (phylogenetic footprinting). In this study, a conservation analysis on both closely related species (humans and mice) and distantly related species (humans/mice and Drosophila) is conducted not only to examine more candidates but also to improve the prediction accuracy. We have found 124 putative cis-regulatory elements and grouped these into 20 clusters. The investigation on the coexistence of these clusters in human gene promoters reveals that SP1, EGR, and NRF-1 are the dominant clusters appearing in the combinatorial combination of up to five clusters. Gene Ontology (GO) analysis also shows that many GO categories of transcription factors binding to these cis-regulatory elements match the GO categories of genes whose promoters contain these elements. Compared with previous research, the contribution of this study lies not only in the finding of new cis-regulatory elements, but also in its pioneering exploration on the coexistence of discovered elements and the GO relationship between transcription factors and regulated genes. This exploration verifies the putative cis-regulatory elements that have been found from this study and also gives new insight on the regulation mechanisms of gene expression.

State-related alterations of gene expression in bipolar disorder : a systematic review

Objective:  Alterations in gene expression in bipolar disorder have been found in numerous studies. It is unclear whether such alterations are related to specific mood states. As a biphasic disorder, mood state-related alterations in gene expression have the potential to point to markers of disease activity, and trait-related alterations might indicate vulnerability pathways. This review therefore evaluated the evidence for whether gene expression in bipolar disorder is state or trait related.

Methods:  A systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline for reporting systematic reviews, based on comprehensive database searches for studies on gene expression in patients with bipolar disorder in specific mood states, was conducted. We searched Medline, Embase, PsycINFO, and The Cochrane Library, supplemented by manually searching reference lists from retrieved publications.

Results:  A total of 17 studies were included, comprising 565 patients and 418 control individuals. Six studies evaluated intraindividual alterations in gene expression across mood states. Two of five studies found evidence of intraindividual alterations in gene expression between a depressed state and a euthymic state. No studies evaluated intraindividual differences in gene expression between a manic state and a euthymic state, while only one case study evaluated differences between a manic state and a depressed state, finding altered expression in seven genes. No study investigated intraindividual variations in gene expression between a euthymic state and multiple states of various polarities (depressive, manic, hypomanic). Intraindividual alterations in expression of the same genes were not investigated across studies. Only one gene (the brain-derived neurotrophic factor gene; BDNF) was investigated across multiple studies, showing no alteration between bipolar disorder patients and control individuals.

Conclusions:  There is evidence of some genes exhibiting state-related alterations in expression in bipolar disorder; however, this finding is limited by the lack of replication across studies. Further prospective studies are warranted, measuring gene expression in various affective phases, allowing for assessment of intraindividual differences.