The Prognostic Significance of PD1 and PDL1 Gene Expression in Lung Cancer: A Meta-Analysis.

BACKGROUND: Immune checkpoint blockade therapy represents an extraordinary advance in lung cancer treatment. It is important to determine the expression of immune checkpoint genes, such as programmed cell death 1 (PD1) and programmed cell death-ligand 1 (PDL1), to develop immunotherapeutic strategies. The aim of this study was to explore the association between PD1 and PDL1 gene expression and prognoses and outcomes in lung cancer. METHODS: This meta-analysis analyzed 1,251 patients from eight different microarray gene expression datasets and were evaluated for their prognostic implications and verified using another independent research. RESULTS: The mean expression levels of PDL1 in adenocarcinoma (AD) and squamous cell carcinoma (SC) were significantly higher in patients who died than in patients who did not. There was a trend toward incremental increases in PD1 and PDL1 expression significantly decreasing the risk of relapse and death among AD patients (HR = 0.69; 95% CI = 0.53 ~ 0.91; HR = 0.68; 95% CI = 0.54 ~ 0.84, respectively) and SC patients (HR = 0.53; 95% CI = 0.32 ~ 0.89; HR = 0.78; 95% CI = 0.57 ~ 1.00 respectively), as early-stage patients in this study were more likely to have high expression of both PD1 and PDL1 than late-stage patients (P-trend < 0.05). In contrast, late-stage SC patients expressing one or more of the genes at a high level had a significantly elevated risk of relapse (HR = 1.51; 95% CI = 1.07 ~ 2.11) and death (HR = 1.41; 95% CI = 1.08 ~ 1.84). This result was consistent with the validation data set. CONCLUSION: These findings indicate that high expression of PD1 and PDL1 is associated with superior outcome in early-stage lung cancer but an adverse outcome in late-stage lung cancer. The expression levels of PD1 and PDL1 individually or jointly are potential prognostic factors for predicting patient outcomes in lung cancer.

Three TF Co-expression Modules Regulate Pressure-Overload Cardiac Hypertrophy in Male Mice.

Pathological cardiac hypertrophy, a dynamic remodeling process, is a major risk factor for heart failure. Although a number of key regulators and related genes have been identified, how the transcription factors (TFs) dynamically regulate the associated genes and control the morphological and electrophysiological changes during the hypertrophic process are still largely unknown. In this study, we obtained the time-course transcriptomes at five time points in four weeks from male murine hearts subjected to transverse aorta banding surgery. From a series of computational analyses, we identified three major co-expression modules of TF genes that may regulate the gene expression changes during the development of cardiac hypertrophy in mice. After pressure overload, the TF genes in Module 1 were up-regulated before the occurrence of significant morphological changes and one week later were down-regulated gradually, while those in Modules 2 and 3 took over the regulation as the heart size increased. Our analyses revealed that the TF genes up-regulated at the early stages likely initiated the cascading regulation and most of the well-known cardiac miRNAs were up-regulated at later stages for suppression. In addition, the constructed time-dependent regulatory network reveals some TFs including Egr2 as new candidate key regulators of cardiovascular-associated (CV) genes.

Uncovering MicroRNA Regulatory Hubs that Modulate Plasma Cell Differentiation.

Using genome-wide approaches, we studied the microRNA (miRNA) expression profile during human plasma cell (PC) differentiation induced by stimulation of human blood B cells with T follicular helper cell-dependent signals. Combining the profiles of differentially expressed genes in PC differentiation with gene ontology (GO) analysis revealed that a significant group of genes involved in the transcription factor (TF) activity was preferentially changed. We thus focused on studying the effects of differentially expressed miRNAs on several key TFs in PC differentiation. Cohorts of differentially expressed miRNAs cooperating as miRNA hubs were predicted and validated to modulate key TFs, including a down-regulated miRNA hub containing miR-101-3p, -125b-5p, and -223-3p contributing to induction of PRDM1 as well as an up-regulated miRNA hub containing miR-34a-5p, -148a-3p, and -183-5p suppressing BCL6, BACH2, and FOXP1. Induced expression of NF-κB and PRDM1 during PC differentiation controlled the expression of up- and down-regulated miRNA hubs, respectively. Co-expression of miR-101-3p, -125b-5p, and -223-3p in stimulated B cells showed synergistic effects on inhibition of PC formation, which can be rescued by re-introduction of PRDM1. Together, we catalogue the complex roadmap of miRNAs and their functional interplay in collaboratively directing PC differentiation.

Transcriptome dynamics of developing maize leaves and genomewide prediction of cis elements and their cognate transcription factors.

Maize is a major crop and a model plant for studying C4 photosynthesis and leaf development. However, a genomewide regulatory network of leaf development is not yet available. This knowledge is useful for developing C3 crops to perform C4 photosynthesis for enhanced yields. Here, using 22 transcriptomes of developing maize leaves from dry seeds to 192 h post imbibition, we studied gene up- and down-regulation and functional transition during leaf development and inferred sets of strongly coexpressed genes. More significantly, we developed a method to predict transcription factor binding sites (TFBSs) and their cognate transcription factors (TFs) using genomic sequence and transcriptomic data. The method requires not only evolutionary conservation of candidate TFBSs and sets of strongly coexpressed genes but also that the genes in a gene set share the same Gene Ontology term so that they are involved in the same biological function. In addition, we developed another method to predict maize TF-TFBS pairs using known TF-TFBS pairs in Arabidopsis or rice. From these efforts, we predicted 1,340 novel TFBSs and 253 new TF-TFBS pairs in the maize genome, far exceeding the 30 TF-TFBS pairs currently known in maize. In most cases studied by both methods, the two methods gave similar predictions. In vitro tests of 12 predicted TF-TFBS interactions showed that our methods perform well. Our study has significantly expanded our knowledge on the regulatory network involved in maize leaf development.

The prognostic significance of RUNX2 and miR-10a/10b and their inter-relationship in breast cancer.

BACKGROUND: The major cancer related mortality is caused by metastasis and invasion. It is important to identify genes regulating metastasis and invasion in order to curtail metastatic spread of cancer cells. METHODS: This study investigated the association between RUNX2 and miR-10a/miR-10b and the risk of breast cancer relapse. Expression levels of RUNX2 and miR-10a/b in 108 pairs of tumor and non-tumor tissue of breast cancer were assayed by quantitative PCR analysis and evaluated for their prognostic implications. RESULTS: The median expression levels of RUNX2 and miR-10b in tumor tissue normalized using adjacent non-tumor tissue were significantly higher in relapsed patients than in relapse-free patients. Higher expression of these three genes were significantly correlated with the hazard ratio for breast cancer recurrence (RUNX2: 3.02, 95% CI = 1.50 ~ 6.07; miR-10a: 2.31, 95% CI = 1.00 ~ 5.32; miR-10b: 3.96, 95% CI = 1.21 ~ 12.98). The joint effect of higher expression of all three genes was associated with a hazard ratio of 12.37 (95% CI = 1.62 ~ 94.55) for relapse. In a breast cancer cell line, RUNX2 silencing reduced the expression of miR-10a/b and also impaired cell motility, while RUNX2 overexpression elicited opposite effects. CONCLUSIONS: These findings indicate that higher expression of RUNX2 and miR-10a/b was associated with adverse outcome of breast cancer. Expression levels of RUNX2 and miR-10a/b individually or jointly are potential prognostic factors for predicting breast cancer recurrence. Data from in vitro studies support the notion that RUNX2 promoted cell motility by upregulating miR-10a/b.

Assembler for de novo assembly of large genomes.

Assembling a large genome using next generation sequencing reads requires large computer memory and a long execution time. To reduce these requirements, we propose an extension-based assembler, called JR-Assembler, where J and R stand for "jumping" extension and read "remapping." First, it uses the read count to select good quality reads as seeds. Second, it extends each seed by a whole-read extension process, which expedites the extension process and can jump over short repeats. Third, it uses a dynamic back trimming process to avoid extension termination due to sequencing errors. Fourth, it remaps reads to each assembled sequence, and if an assembly error occurs by the presence of a repeat, it breaks the contig at the repeat boundaries. Fifth, it applies a less stringent extension criterion to connect low-coverage regions. Finally, it merges contigs by unused reads. An extensive comparison of JR-Assembler with current assemblers using datasets from small, medium, and large genomes shows that JR-Assembler achieves a better or comparable overall assembly quality and requires lower memory use and less central processing unit time, especially for large genomes. Finally, a simulation study shows that JR-Assembler achieves a superior performance on memory use and central processing unit time than most current assemblers when the read length is 150 bp or longer, indicating that the advantages of JR-Assembler over current assemblers will increase as the read length increases with advances in next generation sequencing technology.

Anatomical and transcriptional dynamics of maize embryonic leaves during seed germination.

Our anatomical analysis revealed that a dry maize seed contains four to five embryonic leaves at different developmental stages. Rudimentary kranz structure (KS) is apparent in the first leaf with a substantial density, but its density decreases toward younger leaves. Upon imbibition, leaf expansion occurs rapidly with new KSs initiated from the palisade-like ground meristem cells in the middle of the leaf. In parallel to the anatomical analysis, we obtained the time course transcriptomes for the embryonic leaves in dry and imbibed seeds every 6 h up to hour 72. Over this time course, the embryonic leaves exhibit transcripts of 30,255 genes at a level that can be regarded as "expressed." In dry seeds, ∼25,500 genes are expressed, showing functional enrichment in transcription, RNA processing, protein synthesis, primary metabolic pathways, and calcium transport. During the 72-h time course, ∼13,900 genes, including 590 transcription factor genes, are differentially expressed. Indeed, by 30 h postimbibition, ∼2,200 genes expressed in dry seeds are already down-regulated, and ∼2,000 are up-regulated. Moreover, the top 1% expressed genes at 54 h or later are very different from those before 30 h, reflecting important developmental and physiological transitions. Interestingly, clusters of genes involved in hormone metabolism, signaling, and responses are differentially expressed at various time points and TF gene expression is also modular and stage specific. Our dataset provides an opportunity for hypothesizing the timing of regulatory actions, particularly in the context of KS development.

Historical profiling of maize duplicate genes sheds light on the evolution of C4 photosynthesis in grasses.

C4 plants evolved from C3 plants through a series of complex evolutionary steps. On the basis of the evolution of key C4 enzyme genes, the evolution of C4 photosynthesis has been considered a story of gene/genome duplications and subsequent modifications of gene function. If whole-genome duplication has contributed to the evolution of C4 photosynthesis, other genes should have been duplicated together with these C4 genes. However, which genes were co-duplicated with C4 genes and whether they have also played a role in C4 evolution are largely unknown. In this study, we developed a simple method to characterize the historical profile of the paralogs of a gene by tracing back to the most recent common ancestor (MRCA) of the gene and its paralog(s) and then counting the number of paralogs at each MRCA. We clustered the genes into clusters with similar duplication profiles and inferred their functional enrichments. Applying our method to maize, a familiar C4 plant, we identified many genes that show similar duplication profiles with those of the key C4 enzyme genes and found that the functional preferences of the C4 gene clusters are not only similar to those identified by an experimental approach in a recent study but also highly consistent with the functions required for the C4 photosynthesis evolutionary model proposed by S.F. Sage. Some of these genes might have co-evolved with the key C4 enzyme genes to increase the strength of C4 photosynthesis. Moreover, our results suggested that most key C4 enzyme genes had different origins and have undergone a long evolutionary process before the emergence of C4 grasses (Andropogoneae), consistent with the conclusion proposed by previous authors.

Characterizing regulatory and functional differentiation between maize mesophyll and bundle sheath cells by transcriptomic analysis.

To study the regulatory and functional differentiation between the mesophyll (M) and bundle sheath (BS) cells of maize (Zea mays), we isolated large quantities of highly homogeneous M and BS cells from newly matured second leaves for transcriptome profiling by RNA sequencing. A total of 52,421 annotated genes with at least one read were found in the two transcriptomes. Defining a gene with more than one read per kilobase per million mapped reads as expressed, we identified 18,482 expressed genes; 14,972 were expressed in M cells, including 53 M-enriched transcription factor (TF) genes, whereas 17,269 were expressed in BS cells, including 214 BS-enriched TF genes. Interestingly, many TF gene families show a conspicuous BS preference in expression. Pathway analyses reveal differentiation between the two cell types in various functional categories, with the M cells playing more important roles in light reaction, protein synthesis and folding, tetrapyrrole synthesis, and RNA binding, while the BS cells specialize in transport, signaling, protein degradation and posttranslational modification, major carbon, hydrogen, and oxygen metabolism, cell division and organization, and development. Genes coding for several transporters involved in the shuttle of C(4) metabolites and BS cell wall development have been identified, to our knowledge, for the first time. This comprehensive data set will be useful for studying M/BS differentiation in regulation and function.

Revealing the anti-tumor effect of artificial miRNA p-27-5p on human breast carcinoma cell line T-47D.

microRNAs (miRNAs) cause mRNA degradation or translation suppression of their target genes. Previous studies have found direct involvement of miRNAs in cancer initiation and progression. Artificial miRNAs, designed to target single or multiple genes of interest, provide a new therapeutic strategy for cancer. This study investigates the anti-tumor effect of a novel artificial miRNA, miR P-27-5p, on breast cancer. In this study, we reveal that miR P-27-5p downregulates the differential gene expressions associated with the protein modification process and regulation of cell cycle in T-47D cells. Introduction of this novel artificial miRNA, miR P-27-5p, into breast cell lines inhibits cell proliferation and induces the first "gap" phase (G1) cell cycle arrest in cancer cell lines but does not affect normal breast cells. We further show that miR P-27-5p targets the 3'-untranslated mRNA region (3'-UTR) of cyclin-dependent kinase 4 (CDK4) and reduces both the mRNA and protein level of CDK4, which in turn, interferes with phosphorylation of the retinoblastoma protein (RB1). Overall, our data suggest that the effects of miR p-27-5p on cell proliferation and G1 cell cycle arrest are through the downregulation of CDK4 and the suppression of RB1 phosphorylation. This study opens avenues for future therapies targeting breast cancer.

Editing site analysis in a gymnosperm mitochondrial genome reveals similarities with angiosperm mitochondrial genomes.

Sequence analysis of organelle genomes and comprehensive analysis of C-to-U editing sites from flowering and non-flowering plants have provided extensive sequence information from diverse taxa. This study includes the first comprehensive analysis of RNA editing sites from a gymnosperm mitochondrial genome, and utilizes informatics analyses to determine conserved features in the RNA sequence context around editing sites. We have identified 565 editing sites in 21 full-length and 4 partial cDNAs of the 39 protein-coding genes identified from the mitochondrial genome of Cycas taitungensis. The information profiles and RNA sequence context of C-to-U editing sites in the Cycas genome exhibit similarity in the immediate flanking nucleotides. Relative entropy analyses indicate that similar regions in the 5' flanking 20 nucleotides have information content compared to angiosperm mitochondrial genomes. These results suggest that evolutionary constraints exist on the nucleotide sequences immediately adjacent to C-to-U editing sites, and similar regions are utilized in editing site recognition.

Uncovering small RNA-mediated responses to phosphate deficiency in Arabidopsis by deep sequencing.

Recent studies have demonstrated the important role of plant microRNAs (miRNAs) under nutrient deficiencies. In this study, deep sequencing of Arabidopsis (Arabidopsis thaliana) small RNAs was conducted to reveal miRNAs and other small RNAs that were differentially expressed in response to phosphate (Pi) deficiency. About 3.5 million sequence reads corresponding to 0.6 to 1.2 million unique sequence tags from each Pi-sufficient or Pi-deficient root or shoot sample were mapped to the Arabidopsis genome. We showed that upon Pi deprivation, the expression of miR156, miR399, miR778, miR827, and miR2111 was induced, whereas the expression of miR169, miR395, and miR398 was repressed. We found cross talk coordinated by these miRNAs under different nutrient deficiencies. In addition to miRNAs, we identified one Pi starvation-induced DICER-LIKE1-dependent small RNA derived from the long terminal repeat of a retrotransposon and a group of 19-nucleotide small RNAs corresponding to the 5' end of tRNA and expressed at a high level in Pi-starved roots. Importantly, we observed an increased abundance of TAS4-derived trans-acting small interfering RNAs (ta-siRNAs) in Pi-deficient shoots and uncovered an autoregulatory mechanism of PAP1/MYB75 via miR828 and TAS4-siR81(-) that regulates the biosynthesis of anthocyanin. This finding sheds light on the regulatory network between miRNA/ta-siRNA and its target gene. Of note, a substantial amount of miR399* accumulated under Pi deficiency. Like miR399, miR399* can move across the graft junction, implying a potential biological role for miR399*. This study represents a comprehensive expression profiling of Pi-responsive small RNAs and advances our understanding of the regulation of Pi homeostasis mediated by small RNAs.

GR-Aligner: an algorithm for aligning pairwise genomic sequences containing rearrangement events.

MOTIVATION: Homologous genomic sequences between species usually contain different rearrangement events. Whether some specific patterns existed in the breakpoint regions that caused such events to occur is still unclear. To resolve this question, it is necessary to determine the location of breakpoints at the nucleotide level. The availability of sequences near breakpoints would further facilitate the related studies. We thus need a tool that can identify breakpoints and align the neighboring sequences. Although local alignment tools can detect rearrangement events, they only report a set of discontinuous alignments, where the detailed alignments in the breakpoint regions are usually missing. Global alignment tools are even less appropriate for these tasks since most of them are designed to align the conserved regions between sequences in a consistent order, i.e. they do not consider rearrangement events. RESULTS: We propose an effective and efficient pairwise sequence alignment algorithm, called GR-Aligner (Genomic Rearrangement Aligner), which can find breakpoints of rearrangement events by integrating the forward and reverse alignments of the breakpoint regions flanked by homologously rearranged sequences. In addition, GR-Aligner also provides an option to view the alignments of sequences extended to the breakpoints. These outputs provide materials for studying possible evolutionary mechanisms and biological functionalities of the rearrangement.

Learning atomic human actions using variable-length Markov models.

Visual analysis of human behavior has generated considerable interest in the field of computer vision because of its wide spectrum of potential applications. Human behavior can be segmented into atomic actions, each of which indicates a basic and complete movement. Learning and recognizing atomic human actions are essential to human behavior analysis. In this paper, we propose a framework for handling this task using variable-length Markov models (VLMMs). The framework is comprised of the following two modules: a posture labeling module and a VLMM atomic action learning and recognition module. First, a posture template selection algorithm, based on a modified shape context matching technique, is developed. The selected posture templates form a codebook that is used to convert input posture sequences into discrete symbol sequences for subsequent processing. Then, the VLMM technique is applied to learn the training symbol sequences of atomic actions. Finally, the constructed VLMMs are transformed into hidden Markov models (HMMs) for recognizing input atomic actions. This approach combines the advantages of the excellent learning function of a VLMM and the fault-tolerant recognition ability of an HMM. Experiments on realistic data demonstrate the efficacy of the proposed system.

Prediction of human miRNAs using tissue-selective motifs in 3' UTRs.

MicroRNAs (miRNAs) play an important role in posttranscriptional regulation of genes. We developed a method to predict human miRNAs without requiring cross-species conservation. We first identified lowly/moderately expressed tissue-selective genes using EST data and then identified overrepresented motifs of seven nucleotides in the 3' UTRs of these genes. Using these motifs as potential target sites of miRNAs, we recovered more than two-thirds of the known human miRNAs. We then used those motifs that did not match any known human miRNA seed region to infer novel miRNAs. We predicted 36 new human miRNA genes with 44 mature forms and 4 novel alternative mature forms of 2 known miRNA genes when a stringent criterion was used and many more novel miRNAs when a less stringent criterion was used. We tested the expression of 11 predicted miRNAs in three human cell lines and found 5 of them expressed in all three cell lines and 1 expressed in one cell line. We selected 2 of them, P-2 and P-27-5p, to do functional validation, using their mimics and inhibitors and using both luciferase assay and Western blotting. These experiments provided strong evidence that both P-2 and P-27-5p are novel miRNAs and that CREB3L3, which encodes cAMP-responsive element binding protein 3-like 3, is a target gene of P-2, whereas LAMB3, which encodes laminin beta3, is a target gene of P-27-5p.

The mitochondrial genome of the gymnosperm Cycas taitungensis contains a novel family of short interspersed elements, Bpu sequences, and abundant RNA editing sites.

The mtDNA of Cycas taitungensis is a circular molecule of 414,903 bp, making it 2- to 6-fold larger than the known mtDNAs of charophytes and bryophytes, but similar to the average of 7 elucidated angiosperm mtDNAs. It is characterized by abundant RNA editing sites (1,084), more than twice the number found in the angiosperm mtDNAs. The A + T content of Cycas mtDNA is 53.1%, the lowest among known land plants. About 5% of the Cycas mtDNA is composed of a novel family of mobile elements, which we designated as "Bpu sequences." They share a consensus sequence of 36 bp with 2 terminal direct repeats (AAGG) and a recognition site for the Bpu 10I restriction endonuclease (CCTGAAGC). Comparison of the Cycas mtDNA with other plant mtDNAs revealed many new insights into the biology and evolution of land plant mtDNAs. For example, the noncoding sequences in mtDNAs have drastically expanded as land plants have evolved, with abrupt increases appearing in the bryophytes, and then in the seed plants. As a result, the genomic organizations of seed plant mtDNAs are much less compact than in other plants. Also, the Cycas mtDNA appears to have been exempted from the frequent gene loss observed in angiosperm mtDNAs. Similar to the angiosperms, the 3 Cycas genes nad1, nad2, and nad5 are disrupted by 5 group II intron squences, which have brought the genes into trans-splicing arrangements. The evolutionary origin and invasion/duplication mechanism of the Bpu sequences in Cycas mtDNA are hypothesized and discussed.

Transfer of chloroplast genomic DNA to mitochondrial genome occurred at least 300 MYA.

With the completion of the first gymnosperm mitochondrial genome (mtDNA) from Cycas taitungensis and the availability of more mtDNA taxa in the past 5 years, we have conducted a systematic analysis of DNA transfer from chloroplast genomes (cpDNAs) to mtDNAs (mtpts) in 11 plants, including 2 algae, 1 liverwort, 1 moss, 1 gymnosperm, 3 monocots, and 3 eudicots. By using shared gene order and boundaries between different mtpts as the criterion, the timing of cpDNA transfer during plant evolution was estimated from the phylogenetic tree reconstructed independently from concatenated protein-coding genes of 11 available mtDNAs. Several interesting findings emerged. First, frequent DNA transfer from cpDNA to mtDNA occurred at least as far back as the common ancestor of extant gymnosperms and angiosperms, about 300 MYA. The oldest mtpt is trnV(uac)-trnM(cau)-atpE-atpB-rbcL. Three other mtpts--psaA-psaB, rps19-trnH(gug)-rpl2-rpl23, and psbE-psbF--were dated to the common ancestor of extant angiosperms, at least 150 MYA. However, all protein-coding genes of mtpts have degenerated since their first transfer. Therefore, mtpts contribute nothing to the functioning of mtDNA but junk sequences. We discovered that the cpDNA transfers have occurred randomly at any positions of the cpDNAs. We provide strong evidence that the cp-derived tRNA-trnM(cau) is the only mtpt (1 out of 3 cp-derived tRNA shared by seed plants) truly transferred from cpDNA to mtDNA since the time of the common ancestor of extant gymnosperms and angiosperms. Our observations support the proposition of Richly and Leister (2004) that "primary insertions of organellar DNAs are large and then diverge and fragment over evolutionary time."

Simultaneous amino acid substitutions at antigenic sites drive influenza A hemagglutinin evolution.

The HA1 domain of HA, the major antigenic protein of influenza A viruses, contains all of the antigenic sites of HA and is under continual immune-driven selection. To resolve controversies on whether only a few or many residue sites of HA1 have undergone positive selection, whether positive selection at HA1 is continual or punctuated, and whether antigenic change is punctuated, we introduce an approach to analyze 2,248 HA1 sequences collected from 1968 to 2005. We identify 95 substitutions at 63 sites from 1968 to 2005 and show that each substitution occurred very rapidly. The rapid substitution and the fact that 57 of the 63 sites are antigenic sites indicate that hitchhiking plays a minor role and that most of these sites, many more than previously found, have undergone positive selection. Strikingly, 88 of the 95 substitutions occurred in groups, and multiple mutations at antigenic sites sped up the fixation process. Our results suggest that positive selection has been ongoing most of the time, not sporadic, and that multiple mutations at antigenic sites cumulatively enhance antigenic drift, indicating that antigenic change is less punctuated than recently proposed.

Phylo-mLogo: an interactive and hierarchical multiple-logo visualization tool for alignment of many sequences.

BACKGROUND: When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences. RESULTS: A multiple-logo alignment visualization tool, called Phylo-mLogo, is presented in this paper. Phylo-mLogo calculates the variabilities and homogeneities of alignment sequences by base frequencies or entropies. Different from the traditional representations of sequence logos, Phylo-mLogo not only displays the global logo patterns of the whole alignment of multiple sequences, but also demonstrates their local homologous logos for each clade hierarchically. In addition, Phylo-mLogo also allows the user to focus only on the analysis of some important, structurally or functionally constrained sites in the alignment selected by the user or by built-in automatic calculation. CONCLUSION: With Phylo-mLogo, the user can symbolically and hierarchically visualize hundreds of aligned sequences simultaneously and easily check the changes of their amino acid sites when analyzing many homologous/orthologous or influenza virus sequences. More information of Phylo-mLogo can be found at URL http://biocomp.iis.sinica.edu.tw/phylomlogo.

Influence of mRNA decay rates on the computational prediction of transcription rate profiles from gene expression profiles.

The abundance of an mRNA species depends not only on the transcription rate at which it is produced, but also on its decay rate,which determines how quickly it is degraded. Both transcription rate and decay rate are important factors in regulating gene expression. With the advance of the age of genomics, there are a considerable number of gene expression datasets, in which the expression profiles of tens of thousands of genes are often non-uniformly sampled. Recently,numerous studies have proposed to infer the regulatory networks from expression profiles. Nevertheless, how mRNA decay rates affect the computational prediction of transcription rate profiles from expression profiles has not been well studied. To understand the influences, we present a systematic method based on a gene dynamic regulation model by taking mRNA decay rates, expression profiles and transcription profiles into account. Generally speaking,an expression profile can be regarded as a representation of a biological condition. The rationale behind the concept is that the biological condition is reflected in the changing of gene expression profile. Basically,the biological condition is either associated to the cell cycle or associated to the environmental stresses. The expression profiles of genes that belong to the former, so-called cell cycle data, are characterized by periodicity, whereas the expression profiles of genes that belong to the latter, so-called condition-specific data, are characterized by a steep change after a specific time without periodicity. In this paper, we examine the systematic method on the simulated expression data as well as the real expression data including yeast cell cycle data and condition-specific data (glucose-limitation data). The results indicate that mRNA decay rates do not significantly influence the computational prediction of transcription-rate profiles for cell cycle data. On the contrary,the magnitudes and shapes of transcription-rate profiles for condition specific data are significantly affected by mRNA decay rates. This analysis provides an opportunity for researchers to conduct future research on inferring regulatory networks computationally with available expression profiles under different biological conditions.