Edward Wijaya

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress.

BackgroundThe transcriptional regulatory network involved in low temperature response leading to acclimation has been established in Arabidopsis. In japonica rice, which can only withstand transient exposure to milder cold stress (10°C), an oxidative-mediated network has been proposed to play a key role in configuring early responses and short-term defenses. The components, hierarchical organization and physiological consequences of this network were further dissected by a systems-level approach.ResultsRegulatory clusters responding directly to oxidative signals were prominent during the initial 6 to 12 hours at 10°C. Early events mirrored a typical oxidative response based on striking similarities of the transcriptome to disease, elicitor and wounding induced processes. Targets of oxidative-mediated mechanisms are likely regulated by several classes of bZIP factors acting on as1/ocs/TGA-like element enriched clusters, ERF factors acting on GCC-box/JAre-like element enriched clusters and R2R3-MYB factors acting on MYB2-like element enriched clusters.Temporal induction of several H2O2-induced bZIP, ERF and MYB genes coincided with the transient H2O2 spikes within the initial 6 to 12 hours. Oxidative-independent responses involve DREB/CBF, RAP2 and RAV1 factors acting on DRE/CRT/rav1-like enriched clusters and bZIP factors acting on ABRE-like enriched clusters. Oxidative-mediated clusters were activated earlier than ABA-mediated clusters.ConclusionGenome-wide, physiological and whole-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress and developmental responses leads to modulated growth and vigor maintenance contributing to a delay of plastic injuries.

Supra-optimal expression of the cold-regulated OsMyb4 transcription factor in transgenic rice changes the complexity of transcriptional network with major effects on stress tolerance and panicle development

The R2R3-type OsMyb4 transcription factor of rice has been shown to play a role in the regulation of osmotic adjustment in heterologous overexpression studies. However, the exact composition and organization of its underlying transcriptional network has not been established to be a robust tool for stress tolerance enhancement by regulon engineering. OsMyb4 network was dissected based on commonalities between the global chilling stress transcriptome and the transcriptome configured by OsMyb4 overexpression. OsMyb4 controls a hierarchical network comprised of several regulatory sub-clusters associated with cellular defense and rescue, metabolism and development. It regulates target genes either directly or indirectly through intermediary MYB, ERF, bZIP, NAC, ARF and CCAAT-HAP transcription factors. Regulatory sub-clusters have different combinations of MYB-like, GCC-box-like, ERD1-box-like, ABRE-like, G-box-like, as1/ocs/TGA-like, AuxRE-like, gibberellic acid response element (GARE)-like and JAre-like cis-elements. Cold-dependent network activity enhanced cellular antioxidant capacity through radical scavenging mechanisms and increased activities of phenylpropanoid and isoprenoid metabolic processes involving various abscisic acid (ABA), jasmonic acid (JA), salicylic acid (SA), ethylene and reactive oxygen species (ROS) responsive genes. OsMyb4 network is independent of drought response element binding protein/C-repeat binding factor (DREB/CBF) and its sub-regulons operate with possible co-regulators including nuclear factor-Y. Because of its upstream position in the network hierarchy, OsMyb4 functions quantitatively and pleiotrophically. Supra-optimal expression causes misexpression of alternative targets with costly trade-offs to panicle development.

Hydroxypropyl-β-Cyclodextrin Spikes Local Inflammation That Induces Th2 Cell and T Follicular Helper Cell Responses to the Coadministered Antigen

Cyclodextrins are commonly used as a safe excipient to enhance the solubility and bioavailability of hydrophobic pharmaceutical agents. Their efficacies and mechanisms as drug-delivery systems have been investigated for decades, but their immunological properties have not been examined. In this study, we reprofiled hydroxypropyl-β-cyclodextrin (HP-β-CD) as a vaccine adjuvant and found that it acts as a potent and unique adjuvant. HP-β-CD triggered the innate immune response at the injection site, was trapped by MARCO+ macrophages, increased Ag uptake by dendritic cells, and facilitated the generation of T follicular helper cells in the draining lymph nodes. It significantly enhanced Ag-specific Th2 and IgG Ab responses as potently as did the conventional adjuvant, aluminum salt (alum), whereas its ability to induce Ag-specific IgE was less than that of alum. At the injection site, HP-β-CD induced the temporary release of host dsDNA, a damage-associated molecular pattern. DNase-treated mice, MyD88-deficient mice, and TBK1-deficient mice showed significantly reduced Ab responses after immunization with this adjuvant. Finally, we demonstrated that HP-β-CD–adjuvanted influenza hemagglutinin split vaccine protected against a lethal challenge with a clinically isolated pandemic H1N1 influenza virus, and the adjuvant effect of HP-β-CD was demonstrated in cynomolgus macaques. Our results suggest that HP-β-CD acts as a potent MyD88- and TBK1-dependent T follicular helper cell adjuvant and is readily applicable to various vaccines.

RECOUNT: EXPECTATION MAXIMIZATION BASED ERROR CORRECTION TOOL FOR NEXT GENERATION SEQUENCING DATA

Next generation sequencing technologies enable rapid, large-scale production of sequence data sets. Unfortunately these technologies also have a non-neglible sequencing error rate, which biases their outputs by introducing false reads and reducing the quantity of the real reads. Although methods developed for SAGE data can reduce these false counts to a considerable degree, until now they have not been implemented in a scalable way. Recently, a program named FREC has been developed to address this problem for next generation sequencing data. In this paper, we introduce RECOUNT, our implementation of an Expectation Maximization algorithm for tag count correction and compare it to FREC. Using both the reference genome and simulated data, we find that RECOUNT performs as well or better than FREC, while using much less memory (e.g. 5GB vs. 75GB). Furthermore, we report the first analysis of tag count correction with real data in the context of gene expression analysis. Our results show that tag count correction not only increases the number of mappable tags, but can make a real difference in the biological interpretation of next generation sequencing data. RECOUNT is an open-source C++ program available at http://seq.cbrc.jp/recount.

Probabilistic alignments with quality scores

MOTIVATION Recent studies have revealed the importance of considering quality scores of reads generated by next-generation sequence (NGS) platforms in various downstream analyses. It is also known that probabilistic alignments based on marginal probabilities (e.g. aligned-column and/or gap probabilities) provide more accurate alignment than conventional maximum score-based alignment. There exists, however, no study about probabilistic alignment that considers quality scores explicitly, although the method is expected to be useful in SNP/indel callers and bisulfite mapping, because accurate estimation of aligned columns or gaps is important in those analyses. RESULTS In this study, we propose methods of probabilistic alignment that consider quality scores of (one of) the sequences as well as a usual score matrix. The method is based on posterior decoding techniques in which various marginal probabilities are computed from a probabilistic model of alignments with quality scores, and can arbitrarily trade-off sensitivity and positive predictive value (PPV) of prediction (aligned columns and gaps). The method is directly applicable to read mapping (alignment) toward accurate detection of SNPs and indels. Several computational experiments indicated that probabilistic alignments can estimate aligned columns and gaps accurately, compared with other mapping algorithms e.g. SHRiMP2, Stampy, BWA and Novoalign. The study also suggested that our approach yields favorable precision for SNP/indel calling.

Patterns of cis-element enrichment reveal potential regulatory modules involved in the transcriptional regulation of anoxia response of japonica rice

Unlike other cereal species, rice is able to germinate and elongate under anoxia. The regulatory mechanism that configures the transcriptome of rice during anaerobic germination is yet to be established. In this study, the major regulatory modules among anoxia-responsive genes in rice identified from published microarray data were predicted by ab initio analysis of cis-regulatory information content. Statistically overrepresented sequence motifs were detected from bona fide promoter sequences [-1000 to +200], revealing various patterns of cis-element enrichment that are highly correlated with bZIP, ERF and MYB types of transcription factors. As implied by the cis-element enrichment patterns, combinatorial mechanisms configure the overall changes in gene expression during anoxic germination and coleoptile elongation. High enrichment of cis-elements associated with ARF, bZIP, ERF, MYB and WRKY (SUSIBA2) transcription factors was also detected among the glycolytic and fermentative associated genes that were upregulated during anoxia. The patterns established from the global analysis of cis-element distribution for upregulated and downregulated genes and their associations with potential cognate regulatory transcription factors indicate the significant roles of ethylene and abscisic acid mediated signaling during coleoptile elongation under anoxia. In addition, the regulation of genes encoding enzymes in the glycolytic and fermentative metabolism could be associated with abscisic acid and auxin in rice coleoptiles to maintain sugar and ATP levels for longer survival.

Identification of salt gland-associated genes and characterization of a dehydrin from the salt secretor mangrove Avicennia officinalis

BackgroundSalt stress is a major challenge for growth and development of plants. The mangrove tree Avicennia officinalis has evolved salt tolerance mechanisms such as salt secretion through specialized glands on its leaves. Although a number of structural studies on salt glands have been done, the molecular mechanism of salt secretion is not clearly understood. Also, studies to identify salt gland-specific genes in mangroves have been scarce.ResultsBy subtractive hybridization (SH) of cDNA from salt gland-rich cell layers (tester) with mesophyll tissues as the driver, several Expressed Sequence Tags (ESTs) were identified. The major classes of ESTs identified include those known to be involved in regulating metabolic processes (37%), stress response (17%), transcription (17%), signal transduction (17%) and transport functions (12%). A visual interactive map generated based on predicted functional gene interactions of the identified ESTs suggested altered activities of hydrolase, transmembrane transport and kinases. Quantitative Real-Time PCR (qRT-PCR) was carried out to validate the expression specificity of the ESTs identified by SH. A Dehydrin gene was chosen for further experimental analysis, because it is significantly highly expressed in salt gland cells, and dehydrins are known to be involved in stress remediation in other plants. Full-length Avicennia officinalis Dehydrin1 (AoDHN1) cDNA was obtained by Rapid Amplification of cDNA Ends. Phylogenetic analysis and further characterization of this gene suggested that AoDHN1 belongs to group II Late Embryogenesis Abundant proteins. qRT-PCR analysis of Avicennia showed up-regulation of AoDHN1 in response to salt and drought treatments. Furthermore, some functional insights were obtained by growing E. coli cells expressing AoDHN1. Growth of E. coli cells expressing AoDHN1 was significantly higher than that of the control cells without AoDHN1 under salinity and drought stresses, suggesting that the mangrove dehydrin protein helps to mitigate the abiotic stresses.ConclusionsThirty-four ESTs were identified to be enriched in salt gland-rich tissues of A. officinalis leaves. qRT-PCR analysis showed that 10 of these were specifically enriched in the salt gland-rich tissues. Our data suggest that one of the selected genes, namely, AoDHN1 plays an important role to mitigate salt and drought stress responses.

Transcriptomics analysis of salt stress tolerance in the roots of the mangrove Avicennia officinalis

Salinity affects growth and development of plants, but mangroves exhibit exceptional salt tolerance. With direct exposure to salinity, mangrove roots possess specific adaptations to tolerate salt stress. Therefore, studying the early effects of salt on mangrove roots can help us better understand the tolerance mechanisms. Using two-month-old greenhouse-grown seedlings of the mangrove tree Avicennia officinalis subjected to NaCl treatment, we profiled gene expression changes in the roots by RNA-sequencing. Of the 6547 genes that were differentially regulated in response to salt treatment, 1404 and 5213 genes were significantly up- and down-regulated, respectively. By comparative genomics, 93 key salt tolerance-related genes were identified of which 47 were up-regulated. Upon placing all the differentially expressed genes (DEG) in known signaling pathways, it was evident that most of the DEGs involved in ethylene and auxin signaling were up-regulated while those involved in ABA signaling were down-regulated. These results imply that ABA-independent signaling pathways also play a major role in salt tolerance of A. officinalis. Further, ethylene response factors (ERFs) were abundantly expressed upon salt treatment and the Arabidopsis mutant aterf115, a homolog of AoERF114 is characterized. Overall, our results would help in understanding the possible molecular mechanism underlying salt tolerance in plants.

Reference-free prediction of rearrangement breakpoint reads

MOTIVATION Chromosome rearrangement events are triggered by atypical breaking and rejoining of DNA molecules, which are observed in many cancer-related diseases. The detection of rearrangement is typically done by using short reads generated by next-generation sequencing (NGS) and combining the reads with knowledge of a reference genome. Because structural variations and genomes differ from one person to another, intermediate comparison via a reference genome may lead to loss of information. RESULTS In this article, we propose a reference-free method for detecting clusters of breakpoints from the chromosomal rearrangements. This is done by directly comparing a set of NGS normal reads with another set that may be rearranged. Our method SlideSort-BPR (breakpoint reads) is based on a fast algorithm for all-against-all comparisons of short reads and theoretical analyses of the number of neighboring reads. When applied to a dataset with a sequencing depth of 100×, it finds ∼ 88% of the breakpoints correctly with no false-positive reads. Moreover, evaluation on a real prostate cancer dataset shows that the proposed method predicts more fusion transcripts correctly than previous approaches, and yet produces fewer false-positive reads. To our knowledge, this is the first method to detect breakpoint reads without using a reference genome. AVAILABILITY AND IMPLEMENTATION The source code of SlideSort-BPR can be freely downloaded from https://code.google.com/p/slidesort-bpr/.

Finding Protein-Coding Genes through Human Polymorphisms

Human gene catalogs are fundamental to the study of human biology and medicine. But they are all based on open reading frames (ORFs) in a reference genome sequence (with allowance for introns). Individual genomes, however, are polymorphic: their sequences are not identical. There has been much research on how polymorphism affects previously-identified genes, but no research has been done on how it affects gene identification itself. We computationally predict protein-coding genes in a straightforward manner, by finding long ORFs in mRNA sequences aligned to the reference genome. We systematically test the effect of known polymorphisms with this procedure. Polymorphisms can not only disrupt ORFs, they can also create long ORFs that do not exist in the reference sequence. We found 5,737 putative protein-coding genes that do not exist in the reference, whose protein-coding status is supported by homology to known proteins. On average 10% of these genes are located in the genomic regions devoid of annotated genes in 12 other catalogs. Our statistical analysis showed that these ORFs are unlikely to occur by chance.