GC-compositional strand bias around transcription start sites in plants and fungi

BACKGROUND: A GC-compositional strand bias or GC-skew (=(C-G)/(C+G)), where C and G denote the numbers of cytosine and guanine residues, was recently reported near the transcription start sites (TSS) of Arabidopsis genes. However, it is unclear whether other eukaryotic species have equally prominent GC-skews, and the biological meaning of this trait remains unknown. RESULTS: Our study confirmed a significant GC-skew (C > G) in the TSS of Oryza sativa (rice) genes. The full-length cDNAs and genomic sequences from Arabidopsis and rice were compared using statistical analyses. Despite marked differences in the G+C content around the TSS in the two plants, the degrees of bias were almost identical. Although slight GC-skew peaks, including opposite skews (C < G), were detected around the TSS of genes in human and Drosophila, they were qualitatively and quantitatively different from those identified in plants. However, plant-like GC-skew in regions upstream of the translation initiation sites (TIS) in some fungi was identified following analyses of the expressed sequence tags and/or genomic sequences from other species. On the basis of our dataset, we estimated that >70 and 68% of Arabidopsis and rice genes, respectively, had a strong GC-skew (>0.33) in a 100-bp window (that is, the number of C residues was more than double the number of G residues in a +/-100-bp window around the TSS). The mean GC-skew value in the TSS of highly-expressed genes in Arabidopsis was significantly greater than that of genes with low expression levels. Many of the GC-skew peaks were preferentially located near the TSS, so we examined the potential value of GC-skew as an index for TSS identification. Our results confirm that the GC-skew can be used to assist the TSS prediction in plant genomes. CONCLUSION: The GC-skew (C > G) around the TSS is strictly conserved between monocot and eudicot plants (ie. angiosperms in general), and a similar skew has been observed in some fungi. Highly-expressed Arabidopsis genes had overall a more marked GC-skew in the TSS compared to genes with low expression levels. We therefore propose that the GC-skew around the TSS in some plants and fungi is related to transcription. It might be caused by mutations during transcription initiation or the frequent use of transcription factor-biding sites having a strand preference. In addition, GC-skew is a good candidate index for TSS prediction in plant genomes, where there is a lack of correlation among CpG islands and genes

Pediatric growing teratoma syndrome of the ovary A case report and review of the literature

Rationale: Growing teratoma syndrome is defined as an increase in tumor size during or after systemic chemotherapy for germ cell tumors. These cases involve normal tumor maker levels and histological features of only mature teratoma. We report a rare case of an ovarian immature teratoma in a Japanese child that was diagnosed as growing teratoma syndrome. Patient concerns: A 12-year-old girl presented a painful abdominal mass. She underwent left salpingo-oophorectomy for grade 1 immature teratoma in the left ovary. She did not undergo additional chemotherapy or radiotherapy. Four months later, she presented with grade 3 immature teratoma disseminated into the abdomen and pelvis. Chemotherapy resulted in the tumor maker levels returning to their normal ranges, although the tumors had grown slightly. Diagnosis: The specimens resected by laparotomy after the chemotherapy consisted of mature tissue predominantly, although primitive neuroepithelium was observed in a small part of the specimen. The pathological diagnosis was grade 1 immature teratoma, notwithstanding the clinical diagnosis was growing teratoma syndrome based on the clinical features and pathogenesis. Interventions: Laparotomy was performed at 7 months after the first operation, with resection of various tumors as well as the rectum, sigmoid colon, residual left fallopian duct, and a small part of the ileum and omentum. Some small tumors at the parietal peritoneum were ablated, although many tiny tumors around the uterus were left untreated. Outcomes: The patient has been free from recurrence for 5 years. Lessons: Growing teratoma syndrome can develop in children, and their tumor size is comparable to that in adolescents and adults. Furthermore, development of growing teratoma syndrome from a primary germ cell tumor is presumably faster in children than in adolescents and adults. Complete resection of all growing teratoma tissue is recommended, although fertility-sparing surgery should be considered when possible

Current Status and Future Development of Cell Transplantation Therapy for Periodontal Tissue Regeneration

It has been shown that stem cell transplantation can regenerate periodontal tissue, and several clinical trials involving transplantation of stem cells into human patients have already begun or are in preparation. However, stem cell transplantation therapy is a new technology, and the events following transplantation are poorly understood. Several studies have reported side effects and potential risks associated with stem cell transplantation therapy. To protect patients from such risks, governments have placed regulations on stem cell transplantation therapies. It is important for the clinicians to understand the relevant risks and governmental regulations. This paper describes the ongoing clinical studies, basic research, risks, and governmental controls related to stem cell transplantation therapy. Then, one clinical study is introduced as an example of a government-approved periodontal cell transplantation therapy

Characteristics and clustering of human ribosomal protein genes

BACKGROUND: The ribosome is a central player in the translation system, which in mammals consists of four RNA species and 79 ribosomal proteins (RPs). The control mechanisms of gene expression and the functions of RPs are believed to be identical. Most RP genes have common promoters and were therefore assumed to have a unified gene expression control mechanism. RESULTS: We systematically analyzed the homogeneity and heterogeneity of RP genes on the basis of their expression profiles, promoter structures, encoded amino acid compositions, and codon compositions. The results revealed that (1) most RP genes are coordinately expressed at the mRNA level, with higher signals in the spleen, lymph node dissection (LND), and fetal brain. However, 17 genes, including the P protein genes (RPLP0, RPLP1, RPLP2), are expressed in a tissue-specific manner. (2) Most promoters have GC boxes and possible binding sites for nuclear respiratory factor 2, Yin and Yang 1, and/or activator protein 1. However, they do not have canonical TATA boxes. (3) Analysis of the amino acid composition of the encoded proteins indicated a high lysine and arginine content. (4) The major RP genes exhibit a characteristic synonymous codon composition with high rates of G or C in the third-codon position and a high content of AAG, CAG, ATC, GAG, CAC, and CTG. CONCLUSION: Eleven of the RP genes are still identified as being unique and did not exhibit at least some of the above characteristics, indicating that they may have unknown functions not present in other RP genes. Furthermore, we found sequences conserved between human and mouse genes around the transcription start sites and in the intronic regions. This study suggests certain overall trends and characteristic features of human RP genes

DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model

Structural equation models and Bayesian networks have been widely used to analyze causal relations between continuous variables. In such frameworks, linear acyclic models are typically used to model the data-generating process of variables. Recently, it was shown that use of non-Gaussianity identifies the full structure of a linear acyclic model, i.e., a causal ordering of variables and their connection strengths, without using any prior knowledge on the network structure, which is not the case with conventional methods. However, existing estimation methods are based on iterative search algorithms and may not converge to a correct solution in a finite number of steps. In this paper, we propose a new direct method to estimate a causal ordering and connection strengths based on non-Gaussianity. In contrast to the previous methods, our algorithm requires no algorithmic parameters and is guaranteed to converge to the right solution within a small fixed number of steps if the data strictly follows the model

A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks

Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function

Identifying Potential Regulatory Sequences of Alternative Splicing

Introduction Alternative splicing is an important mechanism that contributes to expanding protein diversity by generating multiple protein isoforms from a single gene. We have previously reported computational approach to infer alternative splicing patterns from Mus musculus full-length cDNA clones and microarray data [4]. Although we have predicted a large number of unreported splice variants, general mechanisms that regulate those alternative splicing were yet to be understood. In the present study, we constructed datasets of putative alternatively spliced genes by use of full-length cDNA clones and genomic DNA sequences. Our putative datasets were then evaluated by comparing information contents of constitutive splice-sites and those of alternative splice-sites. Using phylogenetic footprinting approach, we identified the potential regulatory sequences of alternative splicing. 2 Method and Results 2.1 Detection of Putative Alternative Splicing Patterns We detected putative splic