A comprehensive, domain-wide comparative analysis of genomic imprinting between mammals that imprint and those that do not can provide valuable information about how and why imprinting evolved. The ...imprinting status, DNA methylation, and genomic landscape of the Dlk1-Dio3 cluster were determined in eutherian, metatherian, and prototherian mammals including tammar wallaby and platypus. Imprinting across the whole domain evolved after the divergence of eutherian from marsupial mammals and in eutherians is under strong purifying selection. The marsupial locus at 1.6 megabases, is double that of eutherians due to the accumulation of LINE repeats. Comparative sequence analysis of the domain in seven vertebrates determined evolutionary conserved regions common to particular sub-groups and to all vertebrates. The emergence of Dlk1-Dio3 imprinting in eutherians has occurred on the maternally inherited chromosome and is associated with region-specific resistance to expansion by repetitive elements and the local introduction of noncoding transcripts including microRNAs and C/D small nucleolar RNAs. A recent mammal-specific retrotransposition event led to the formation of a completely new gene only in the eutherian domain, which may have driven imprinting at the cluster.
The exponential increase in the submission of nucleotide sequences to the nucleotide sequence database by genome sequencing centres has resulted in a need for rapid, automatic methods for ...classification of the resulting protein sequences. There are several signature and sequence cluster-based methods for protein classification, each resource having distinct areas of optimum application owing to the differences in the underlying analysis methods. In recognition of this, InterPro was developed as an integrated documentation resource for protein families, domains and functional sites, to rationalise the complementary efforts of the individual protein signature database projects. The member databases - PRINTS, PROSITE, Pfam, ProDom, SMART and TIGRFAMs - form the InterPro core. Related signatures from each member database are unified into single InterPro entries. Each InterPro entry includes a unique accession number, functional descriptions and literature references, and links are made back to the relevant member database(s). Release 4.0 of InterPro (November 2001) contains 4,691 entries, representing 3,532 families, 1,068 domains, 74 repeats and 15 sites of post-translational modification (PTMs) encoded by different regular expressions, profiles, fingerprints and hidden Markov models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (2,141,621 InterPro hits from 586,124 SWISS-PROT and TrEMBL protein sequences). The database is freely accessible for text- and sequence-based searches.
The exponential increase in the submission of nucleotide sequences to the nucleotide sequence database by genome sequencing centres has resulted in a need for rapid, automatic methods for ...classification of the resulting protein sequences. There are several signature and sequence cluster-based methods for protein classification, each resource having distinct areas of optimum application owing to the differences in the underlying analysis methods. In recognition of this, InterPro was developed as an integrated documentation resource for protein families, domains and functional sites, to rationalise the complementary efforts of the individual protein signature database projects. The member databases - PRINTS, PROSITE, Pfam, ProDom, SMART and TIGRFAMs - form the InterPro core. Related signatures from each member database are unified into single InterPro entries. Each InterPro entry includes a unique accession number, functional descriptions and literature references, and links are made back to the relevant member database(s). Release 4.0 of InterPro (November 2001) contains 4,691 entries, representing 3,532 families, 1,068 domains, 74 repeats and 15 sites of post-translational modification (PTMs) encoded by different regular expressions, profiles, fingerprints and hidden Markov models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (2,141,621 InterPro hits from 586,124 SWISS-PROT and TrEMBL protein sequences). The database is freely accessible for text- and sequence-based searches.
An estimated 4% to 7% of the population will develop a clinically significant thyroid nodule during their lifetime. In many cases, preoperative diagnoses by needle biopsy are inconclusive. Thus, ...there is a clear need for improved diagnostic tests to distinguish malignant from benign thyroid tumors. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers from numerous thyroid cancer expression profiling studies.
To address this challenge, we have carried out a comprehensive meta-review of thyroid cancer biomarkers from 21 published studies. A gene ranking system that considers the number of comparisons in agreement, total number of samples, average fold-change and direction of change was devised.
We have observed that genes are consistently reported by multiple studies at a highly significant rate (P < .05). Comparison with a meta-analysis of studies reprocessed from raw data showed strong concordance with our method.
Our approach represents a useful method for identifying consistent gene expression markers when raw data are unavailable. A review of the top 12 candidates revealed well known thyroid cancer markers such as MET, TFF3, SERPINA1, TIMP1, FN1, and TPO as well as relatively novel or uncharacterized genes such as TGFA, QPCT, CRABP1, FCGBP, EPS8 and PROS1. These candidates should help to develop a panel of markers with sufficient sensitivity and specificity for the diagnosis of thyroid tumors in a clinical setting.
Galectin-3 (Gal-3), which has received significant recent attention for its utility as a diagnostic marker for thyroid cancer, represents the most well-studied molecular candidate for thyroid cancer ...diagnosis. Gal-3 is a protein that binds to β-galactosidase residues on cell surface glycoproteins and has also been identified in the cytoplasmic and nuclear compartment. This marker has been implicated in regulation of normal cellular proliferation and apoptosis, as well as malignant transformation and the metastasis of cancer cells. We here present a mechanistic review of Gal-3 and its role in cancer development and progression. Gal-3 expression studies in thyroid tissue and cytologic tumor specimens and their methodological considerations are also discussed in this article. Despite great variance in their methodology, the majority of immunohistochemical studies found that Gal-3 was differentially expressed in thyroid carcinoma compared with benign and normal thyroid specimens, suggesting that Gal-3 is a good diagnostic marker for thyroid cancer. Recent studies have also demonstrated improved methodological reliability. On the other hand, Gal-3 genomic expression studies have shown inconsistent results for diagnostic utility and are not recommended. Overall, the development of Gal-3 as a diagnostic marker for thyroid cancer represents a promising avenue for future study, and its clinical application could significantly reduce the number of diagnostic thyroid operations performed for cases of indeterminant fine needle aspiration biopsy cytology, and thus positively impact the current management of thyroid nodular disease.
We describe Trans-ABySS, a de novo short-read transcriptome assembly and analysis pipeline that addresses variation in local read densities by assembling read substrings with varying stringencies and ...then merging the resulting contigs before analysis. Analyzing 7.4 gigabases of 50-base-pair paired-end Illumina reads from an adult mouse liver poly(A) RNA library, we identified known, new and alternative structures in expressed transcripts, and achieved high sensitivity and specificity relative to reference-based assembly methods.
Cell fate acquisition is heavily influenced by direct interactions between master regulators and tissue-specific enhancers. However, it remains unclear how lineage-specifying transcription factors, ...which are often expressed in both progenitor and mature cell populations, influence cell differentiation. Using in vivo mouse liver development as a model, we identified thousands of enhancers that are bound by the master regulators HNF4A and FOXA2 in a differentiation-dependent manner, subject to chromatin remodeling, and associated with differentially expressed target genes. Enhancers exclusively occupied in the embryo were found to be responsive to developmentally regulated TEAD2 and coactivator YAP1. Our data suggest that Hippo signaling may affect hepatocyte differentiation by influencing HNF4A and FOXA2 interactions with temporal enhancers. In summary, transcription factor-enhancer interactions are not only tissue specific but also differentiation dependent, which is an important consideration for researchers studying cancer biology or mammalian development and/or using transformed cell lines.
Rho/ROCK signaling and caveolin-1 (Cav1) are implicated in tumor cell migration and metastasis; however, the underlying molecular mechanisms remain poorly defined. Cav1 was found here to be an ...independent predictor of decreased survival in breast and rectal cancer and significantly associated with the presence of distant metastasis for colon cancer patients. Rho/ROCK signaling promotes tumor cell migration by regulating focal adhesion (FA) dynamics through tyrosine (Y14) phosphorylation of Cav1. Phosphorylated Cav1 is localized to protrusive domains of tumor cells and Cav1 tyrosine phosphorylation is dependent on Src kinase and Rho/ROCK signaling. Increased levels of phosphorylated Cav1 were associated with elevated GTP-RhoA levels in metastatic tumor cells of various tissue origins. Stable expression and knockdown studies of Cav1 in tumor cells showed that phosphorylated Cav1 expression stimulates Rho activation, stabilizes FAK association with FAs, and promotes cell migration and invasion in a ROCK-dependent and Src-dependent manner. Tyrosine-phosphorylated Cav1, therefore, functions as an effector of Rho/ROCK signaling in the regulation of FA turnover and, thereby, tumor cell migration and invasion. These studies define a feedback loop between Rho/ROCK, Src, and phosphorylated Cav1 in tumor cell protrusions, identifying a novel function for Cav1 in tumor metastasis that may contribute to the poor prognosis of some Cav1-expressing tumors.
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