Translation regulation plays important roles in both normal physiological conditions and diseases states. This regulation requires cis-regulatory elements located mostly in 5′ and 3′ UTRs and trans-regulatory factors (e.g., RNA binding proteins (RBPs)) which recognize specific RNA features and interact with the translation machinery to modulate its activity. In this paper, we discuss important aspects of 5′ UTR-mediated regulation by providing an overview of the characteristics and the function of the main elements present in this region, like uORF (upstream open reading frame), secondary structures, and RBPs binding motifs and different mechanisms of translation regulation and the impact they have on gene expression and human health when deregulated.

Increasing evidence indicates that many, if not all, small genes encoding proteins ≤100 aa are missing in annotations of bacterial genomes currently available. To uncover unannotated small genes in the model bacterium Salmonella enterica Typhimurium 14028s, we used the genomic technique ribosome profiling, which provides a snapshot of all mRNAs being translated (translatome) in a given growth condition. For comprehensive identification of unannotated small genes, we obtained Salmonella translatomes from four different growth conditions: LB, MOPS rich defined medium, and two infection-relevant conditions low Mg2+ (10 µM) and low pH (5.8). To facilitate the identification of small genes, ribosome profiling data were analyzed in combination with in silico predicted putative open reading frames and transcriptome profiles. As a result, we uncovered 130 unannotated ORFs. Of them, 98% were small ORFs putatively encoding peptides/proteins ≤100 aa, and some of them were only expressed in the infection-relevant low Mg2+ and/or low pH condition. We validated the expression of 25 of these ORFs by western blot, including the smallest, which encodes a peptide of 7 aa residues. Our results suggest that many sequenced bacterial genomes are underannotated with regard to small genes and their gene annotations need to be revised.

Genome sequence analysis of Xanthomonas oryzae pv. oryzae KACC10331 provides insight into the X. oryzae gum gene cluster that is composed of 14 open-reading frames (ORFs), designated gumB, -C, -D, -E, -F, -G, -H, -I, -J, -K, -L, -M, XOO3167, and -N. We analyzed the transcriptional linkage of the X. oryzae gum gene cluster by using RT-PCR. Analyses of the gum gene cluster by RT-PCR with the wild-type and mutant strains, which carried a deletion of the promoter-like region upstream of gumB or an insertion of the rrnB transcriptional terminator into the gumF gene, revealed that the ORFs of this gene cluster were transcribed as polycistronic mRNA, from gumB to gumN, and the secondary promoter was located upstream of gumG. Taken together, these results suggest that the genes of this cluster constitute an operon expressed from overlapping transcripts.

Eukaryotic gene expression must be coordinated for the proper functioning of biological processes. This coordination can be achieved both at the transcriptional and post-transcriptional levels. In both cases, regulatory sequences placed at either promoter regions or on UTRs function as markers recognized by regulators that can then activate or repress different groups of genes according to necessity. While regulatory sequences involved in transcription are quite well documented, there is a lack of information on sequence elements involved in post-transcriptional regulation. We used a statistical over-representation method to identify novel regulatory elements located on UTRs. An exhaustive search approach was used to calculate the frequency of all possible n-mers (short nucleotide sequences) in 16,160 human genes of NCBI RefSeq sequences and to identify any peculiar usage of n-mers on UTRs. After a stringent filtering process, we identified 2,772 highly over-represented n-mers on 3' UTRs. We provide evidence that these n-mers are potentially involved in regulatory functions. Identified n-mers overlap with previously identified binding sites for HuR and TIA-1 and, ARE and GRE sequences. We determine also that n-mers overlap with predicted miRNA target sites. Finally, a method to cluster n-mer groups allowed the identification of putative gene networks.

Assembly of the functional tetrameric form of Mu transposase (MuA protein) at the two att ends of Mu depends on interaction of MuA with multiple att and enhancer sites on supercoiled DNA, and is stimulated by MuB protein. The N-terminal domain I of MuA harbours distinct regions for interaction with the att ends and enhancer; the C-terminal domain III contains separate regions essential for tetramer assembly and interaction with MuB protein (IIIalpha and IIIbeta, respectively). Although the central domain II (the 'DDE' domain) of MuA harbours the known catalytic DDE residues, a 26 amino acid peptide within IIIalpha also has a non-specific DNA binding and nuclease activity which has been implicated in catalysis. One model proposes that active sites for Mu transposition are assembled by sharing structural/catalytic residues between domains II and III present on separate MuA monomers within the MuA tetramer. We have used substrates with altered att sites and mixtures of MuA proteins with either wild-type or altered att DNA binding specificities, to create tetrameric arrangements wherein specific MuA subunits are nonfunctional in II, IIIalpha or IIIbeta domains. From the ability of these oriented tetramers to carry out DNA cleavage and strand transfer we conclude that domain IIIalpha or IIIbeta function is not unique to a specific subunit within the tetramer, indicative of a structural rather than a catalytic function for domain III in Mu transposition.

Microhomology-mediated end joining (MMEJ) anneals short, imperfect microhomologies flanking DNA breaks, producing repair products with deletions in a Ku- and RAD52-independent fashion. Puzzlingly, MMEJ preferentially selects certain microhomologies over others, even when multiple microhomologies are available. To define rules and parameters for microhomology selection, we altered the length, the position, and the level of mismatches to the microhomologies flanking homothallic switching (HO) endonuclease-induced breaks and assessed their effect on MMEJ frequency and the types of repair product formation. We found that microhomology of eight to 20 base pairs carrying no more than 20% mismatches efficiently induced MMEJ. Deletion of MSH6 did not impact MMEJ frequency. MMEJ preferentially chose a microhomology pair that was more proximal from the break. Interestingly, MMEJ events preferentially retained the centromere proximal side of the HO break, while the sequences proximal to the telomere were frequently deleted. The asymmetry in the deletional profile among MMEJ products was reduced when HO was induced on the circular chromosome. The results provide insight into how cells search and select microhomologies for MMEJ in budding yeast.

BackgroundScientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.ResultsSidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick.ConclusionsSidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that traditional single gene lists do not, particularly in areas such as interaction discovery.

Breast cancer (BCa) is the most common malignant disease in women in U.S. Nearly 20% of patients with advanced BCa is eventually diagnosed with brain lesions. The available treatment regimens are not capable of significantly treating the BCa-induced brain metastases due to their inability to penetrate the blood brain barrier. The exact molecular mechanism for metastases of BCa into brain is unknown. The current rodent model systems for BCa brain metastasis have limitations. Therefore, there is a need of efficient model system that can significantly contribute towards our understanding of different factors from both host and tumor leading to brain metastasis. Previously we reported estrogen-independent B6TC cell, derived from the stable spontaneous fusion of MDA-MB-231 and ZR-75-1 cells in mouse bone-marrow microenvironment, which has propensity to metastasize to brain when inoculated through intracardiac route, and express stem cell-like features. In this study using B6TC, we have developed an efficient and novel mouse model for studying BCa-induced brain metastasis and investigated the role of a potent pan-TGF-β inhibitor, BGERII, for blocking brain metastasis. We have generated three cell lines from B6TC through three successive rounds of inoculation in mouse and isolation of brain metastatic cells. Each round of selection enhanced the brain metastatic propensity. An initial microarray analysis identified genes implicated in metastasis regulation- MMP1, HB-EGF, ST3GAL1, PTGS2, ITGA3, and CXCR4, showing significant up-regulation in B6TC compared to its parental MDA-MB-231 and ZR-75-1 cells. Analyses of second round of RNA microarray, performed with three sub-lines of B6TC with successively enhanced brain metastatic propensity over generations, identified some molecular pathways, including TGF beta signaling pathway that are associated with enhanced brain metastasis. We next investigated whether metastatic tumor growth in the brain microenvironment can be inhibited by systemic administration of a potent pan-TGF-β inhibitor, BGERII- a recombinant fusion protein containing the endoglin domain of betaglycan (BGE) and the extracellular domain of RII. The animals were inoculated intracardically with N3LR, the most potent sub-line of highly metastatic B6TC cells and were then treated with vehicle or BGERII systemically via i.p. injection right after the inoculation. After three weeks, the BGERII treated group showed lower brain metastasis incidence and tumor burden as detected by whole mouse bioluminescence and GFP imaging. Further analyses to understand the underlying molecular and regulatory mechanism of brain metastasis and its intervention in our mouse model is underway for the discovery of novel molecularly targeted drugs to prevent and eradicate BCa metastasis initiation, progression and recurrence. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3390. doi:1538-7445.AM2012-3390