Interferon-stimulated gene 15 polymorphisms are associated with spontaneous preterm birth in Taiwanese women.

PROBLEM: Immune and inflammatory responses are known to be major causes of preterm birth (PTB). The maternal genetic background plays an important role in the development of PTB. Interferon-stimulated gene 15 (ISG15) is an interferon-induced protein which can modulate immune cell activation and function. We aim to study if polymorphisms in the ISG15 gene are associated with spontaneous PTB (sPTB) risk in Taiwanese women. METHOD OF STUDY: ISG15 rs4615788 C/G, rs1921 G/A, and rs8997 A/G polymorphisms were genotyped in a hospital-based study of 112 women with sPTB and 1120 term controls. The plasma concentrations of ISG15 were determined by enzyme-linked immunosorbent assay. RESULTS: We found the ISG15 rs1921 G-rs8997 A haplotype was associated with decreased risk for PTB (χ2  = 6.26, p = .01, pc  = .04). The A/G genotype of ISG15 rs8997 polymorphism might have the potential to confer reduced risk of PTB women (χ2  = 4.09, p = .04, pc  = .08). Spontaneous PTB women displayed higher plasma ISG15 levels compared to term controls (p < .001). The plasma ISG15 levels among pregnant women with rs8997 A/G genotype were found significantly lower compared to G/G genotype (p = .03). CONCLUSIONS: Women with the ISG15 rs1921 G-rs8997 A haplotype may associate with spontaneous PTB. These findings provide new insights into the etiology of preterm birth.

Detection of Amyotrophic Lateral Sclerosis (ALS) Comorbidity Trajectories Based on Principal Tree Model Analytics.

The multifaceted nature and swift progression of Amyotrophic Lateral Sclerosis (ALS) pose considerable challenges to our understanding of its evolution and interplay with comorbid conditions. This study seeks to elucidate the temporal dynamics of ALS progression and its interaction with associated diseases. We employed a principal tree-based model to decipher patterns within clinical data derived from a population-based database in Taiwan. The disease progression was portrayed as branched trajectories, each path representing a series of distinct stages. Each stage embodied the cumulative occurrence of co-existing diseases, depicted as nodes on the tree, with edges symbolizing potential transitions between these linked nodes. Our model identified eight distinct ALS patient trajectories, unveiling unique patterns of disease associations at various stages of progression. These patterns may suggest underlying disease mechanisms or risk factors. This research re-conceptualizes ALS progression as a migration through diverse stages, instead of the perspective of a sequence of isolated events. This new approach illuminates patterns of disease association across different progression phases. The insights obtained from this study hold the potential to inform doctors regarding the development of personalized treatment strategies, ultimately enhancing patient prognosis and quality of life.

Progression to myocardial infarction short-term death based on interval sequential pattern mining.

BACKGROUND: Myocardial infarction (MI) is one of the significant cardiovascular diseases (CVDs). According to Taiwanese health record analysis, the hazard rate reaches a peak in the initial year after diagnosis of MI, drops to a relatively low value, and maintains stable for the following years. Therefore, identifying suspicious comorbidity patterns of short-term death before the diagnosis may help achieve prolonged survival for MI patients. METHODS: Interval sequential pattern mining was applied with odds ratio to the hospitalization records from the Taiwan National Health Insurance Research Database to evaluate the disease progression and identify potential subjects at the earliest possible stage. RESULTS: Our analysis resulted in five disease pathways, including "diabetes mellitus," "other disorders of the urethra and urinary tract," "essential hypertension," "hypertensive heart disease," and "other forms of chronic ischemic heart disease" that led to short-term death after MI diagnosis, and these pathways covered half of the cohort. CONCLUSION: We explored the possibility of establishing trajectory patterns to identify the high-risk population of early mortality after MI.

Distinctive microbial community and genome structure in coastal seawater from a human-made port and nearby offshore island in northern Taiwan facing the Northwestern Pacific Ocean.

Pollution in human-made fishing ports caused by petroleum from boats, dead fish, toxic chemicals, and effluent poses a challenge to the organisms in seawater. To decipher the impact of pollution on the microbiome, we collected surface water from a fishing port and a nearby offshore island in northern Taiwan facing the Northwestern Pacific Ocean. By employing 16S rRNA gene amplicon sequencing and whole-genome shotgun sequencing, we discovered that Rhodobacteraceae, Vibrionaceae, and Oceanospirillaceae emerged as the dominant species in the fishing port, where we found many genes harboring the functions of antibiotic resistance (ansamycin, nitroimidazole, and aminocoumarin), metal tolerance (copper, chromium, iron and multimetal), virulence factors (chemotaxis, flagella, T3SS1), carbohydrate metabolism (biofilm formation and remodeling of bacterial cell walls), nitrogen metabolism (denitrification, N2 fixation, and ammonium assimilation), and ABC transporters (phosphate, lipopolysaccharide, and branched-chain amino acids). The dominant bacteria at the nearby offshore island (Alteromonadaceae, Cryomorphaceae, Flavobacteriaceae, Litoricolaceae, and Rhodobacteraceae) were partly similar to those in the South China Sea and the East China Sea. Furthermore, we inferred that the microbial community network of the cooccurrence of dominant bacteria on the offshore island was connected to dominant bacteria in the fishing port by mutual exclusion. By examining the assembled microbial genomes collected from the coastal seawater of the fishing port, we revealed four genomic islands containing large gene-containing sequences, including phage integrase, DNA invertase, restriction enzyme, DNA gyrase inhibitor, and antitoxin HigA-1. In this study, we provided clues for the possibility of genomic islands as the units of horizontal transfer and as the tools of microbes for facilitating adaptation in a human-made port environment.

Deep-learning based breast cancer detection for cross-staining histopathology images.

Hematoxylin and eosin (H&E) staining is the gold standard for tissue characterization in routine pathological diagnoses. However, these visible light dyes do not exclusively label the nuclei and cytoplasm, making clear-cut segmentation of staining signals challenging. Currently, fluorescent staining technology is much more common in clinical research for analyzing tissue morphology and protein distribution owing to its advantages of channel independence, multiplex labeling, and the possibility of enabling 3D tissue labeling. Although both H&E and fluorescent dyes can stain the nucleus and cytoplasm for representative tissue morphology, color variation between these two staining technologies makes cross-analysis difficult, especially with computer-assisted artificial intelligence (AI) algorithms. In this study, we applied color normalization and nucleus extraction methods to overcome the variation between staining technologies. We also developed an available workflow for using an H&E-stained segmentation AI model in the analysis of fluorescent nucleic acid staining images in breast cancer tumor recognition, resulting in 89.6% and 80.5% accuracy in recognizing specific tumor features in H&E- and fluorescent-stained pathological images, respectively. The results show that the cross-staining inference maintained the same precision level as the proposed workflow, providing an opportunity for an expansion of the application of current pathology AI models.

Identification of fish species through tRNA-based primer design.

BACKGROUND: The correct establishment of the barcode classification system for fish can facilitate biotaxonomists to distinguish fish species, and it can help the government to verify the authenticity of the ingredients of fish products or identify unknown fish related samples. The Cytochrome c oxidation I (COI) gene sequence in the mitochondria of each species possesses unique characteristics, which has been widely used as barcodes in identifying species in recent years. Instead of using COI gene sequences for primer design, flanking tRNA segments of COI genes from 2618 complete fish mitochondrial genomes were analyzed to discover suitable primers for fish classification at taxonomic family level. The minimal number of primer sets is designed to effectively distinguish various clustered groups of fish species for identification applications. Sequence alignment analysis and cross tRNA segment comparisons were applied to check and ensure the primers for each cluster group are exclusive. RESULTS: Two approaches were applied to improve primer design and re-cluster fish species. The results have shown that exclusive primers for 2618 fish species were successfully discovered through in silico analysis. In addition, we applied sequence alignment analysis to confirm that each pair of primers can successfully identify all collected fish species at the taxonomic family levels. CONCLUSIONS: This study provided a practical strategy to discover unique primers for each fishery species and a comprehensive list of exclusive primers for extracting COI barcode sequences of all known fishery species. Various applications of verification of fish products or identification of unknown fish species could be effectively achieved.

Transcriptomic analysis reveals distinct mechanisms of adaptation of a polar picophytoplankter under ocean acidification conditions.

Human emissions of carbon dioxide are causing irreversible changes in our oceans and impacting marine phytoplankton, including a group of small green algae known as picochlorophytes. Picochlorophytes grown in natural phytoplankton communities under future predicted levels of carbon dioxide have been demonstrated to thrive, along with redistribution of the cellular metabolome that enhances growth rate and photosynthesis. Here, using next-generation sequencing technology, we measured levels of transcripts in a picochlorophyte Chlorella, isolated from the sub-Antarctic and acclimated under high and current ambient CO2 levels, to better understand the molecular mechanisms involved with its ability to acclimate to elevated CO2. Compared to other phytoplankton taxa that induce broad transcriptomic responses involving multiple parts of their cellular metabolism, the changes observed in Chlorella focused on activating gene regulation involved in different sets of pathways such as light harvesting complex binding proteins, amino acid synthesis and RNA modification, while carbon metabolism was largely unaffected. Triggering a specific set of genes could be a unique strategy of small green phytoplankton under high CO2 in polar oceans.

Comprehensive Linear Epitope Prediction System for Host Specificity in Nodaviridae.

BACKGROUND: Nodaviridae infection is one of the leading causes of death in commercial fish. Although many vaccines against this virus family have been developed, their efficacies are relatively low. Nodaviridae are categorized into three subfamilies: alphanodavirus (infects insects), betanodavirus (infects fish), and gammanodavirus (infects prawns). These three subfamilies possess host-specific characteristics that could be used to identify effective linear epitopes (LEs). METHODOLOGY: A multi-expert system using five existing LE prediction servers was established to obtain initial LE candidates. Based on the different clustered pathogen groups, both conserved and exclusive LEs among the Nodaviridae family could be identified. The advantages of undocumented cross infection among the different host species for the Nodaviridae family were applied to re-evaluate the impact of LE prediction. The surface structural characteristics of the identified conserved and unique LEs were confirmed through 3D structural analysis, and concepts of surface patches to analyze the spatial characteristics and physicochemical propensities of the predicted segments were proposed. In addition, an intelligent classifier based on the Immune Epitope Database (IEDB) dataset was utilized to review the predicted segments, and enzyme-linked immunosorbent assays (ELISAs) were performed to identify host-specific LEs. PRINCIPAL FINDINGS: We predicted 29 LEs for Nodaviridae. The analysis of the surface patches showed common tendencies regarding shape, curvedness, and PH features for the predicted LEs. Among them, five predicted exclusive LEs for fish species were selected and synthesized, and the corresponding ELISAs for antigenic feature analysis were examined. CONCLUSION: Five identified LEs possessed antigenicity and host specificity for grouper fish. We demonstrate that the proposed method provides an effective approach for in silico LE prediction prior to vaccine development and is especially powerful for analyzing antigen sequences with exclusive features among clustered antigen groups.

Comparative Transcriptome Analysis of Organ-Specific Adaptive Responses to Hypoxia Provides Insights to Human Diseases.

The common carp is a hypoxia-tolerant fish, and the understanding of its ability to live in low-oxygen environments has been applied to human health issues such as cancer and neuron degeneration. Here, we investigated differential gene expression changes during hypoxia in five common carp organs including the brain, the gill, the head kidney, the liver, and the intestine. Based on RNA sequencing, gene expression changes under hypoxic conditions were detected in over 1800 genes in common carp. The analysis of these genes further revealed that all five organs had high expression-specific properties. According to the results of the GO and KEGG, the pathways involved in the adaptation to hypoxia provided information on responses specific to each organ in low oxygen, such as glucose metabolism and energy usage, cholesterol synthesis, cell cycle, circadian rhythm, and dopamine activation. DisGeNET analysis showed that some human diseases such as cancer, diabetes, epilepsy, metabolism diseases, and social ability disorders were related to hypoxia-regulated genes. Our results suggested that common carp undergo various gene regulations in different organs under hypoxic conditions, and integrative bioinformatics may provide some potential targets for advancing disease research.

Using Comorbidity Pattern Analysis to Detect Reliable Methylated Genes in Colorectal Cancer Verified by Stool DNA Test.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide in 2020. Colonoscopy and the fecal immunochemical test (FIT) are commonly used as CRC screening tests, but both types of tests possess different limitations. Recently, liquid biopsy-based DNA methylation test has become a powerful tool for cancer screening, and the detection of abnormal DNA methylation in stool specimens is considered as an effective approach for CRC screening. The aim of this study was to develop a novel approach in biomarker selection based on integrating primary biomarkers from genome-wide methylation profiles and secondary biomarkers from CRC comorbidity analytics. A total of 125 differential methylated probes (DMPs) were identified as primary biomarkers from 352 genome-wide methylation profiles. Among them, 51 biomarkers, including 48 hypermethylated DMPs and 3 hypomethylated DMPs, were considered as suitable DMP candidates for CRC screening tests. After comparing with commercial kits, three genes (ADHFE1, SDC2, and PPP2R5C) were selected as candidate epigenetic biomarkers for CRC screening tests. Methylation levels of these three biomarkers were significantly higher for patients with CRC than normal subjects. The sensitivity and specificity of integrating methylated ADHFE1, SDC2, and PPP2R5C for CRC detection achieved 84.6% and 92.3%, respectively. Through an integrated approach using genome-wide DNA methylation profiles and electronic medical records, we could design a biomarker panel that allows for early and accurate noninvasive detection of CRC using stool samples.

Conformational epitope matching and prediction based on protein surface spiral features.

BACKGROUND: A conformational epitope (CE) is composed of neighboring amino acid residues located on an antigenic protein surface structure. CEs bind their complementary paratopes in B-cell receptors and/or antibodies. An effective and efficient prediction tool for CE analysis is critical for the development of immunology-related applications, such as vaccine design and disease diagnosis. RESULTS: We propose a novel method consisting of two sequential modules: matching and prediction. The matching module includes two main approaches. The first approach is a complete sequence search (CSS) that applies BLAST to align the sequence with all known antigen sequences. Fragments with high epitope sequence identities are identified and the predicted residues are annotated on the query structure. The second approach is a spiral vector search (SVS) that adopts a novel surface spiral feature vector for large-scale surface patch detection when queried against a comprehensive epitope database. The prediction module also contains two proposed subsystems. The first system is based on knowledge-based energy and geometrical neighboring residue contents, and the second system adopts combinatorial features, including amino acid contents and physicochemical characteristics, to formulate corresponding geometric spiral vectors and compare them with all spiral vectors from known CEs. An integrated testing dataset was generated for method evaluation, and our two searching methods effectively identified all epitope regions. The prediction results show that our proposed method outperforms previously published systems in terms of sensitivity, specificity, positive predictive value, and accuracy. CONCLUSIONS: The proposed method significantly improves the performance of traditional epitope prediction. Matching followed by prediction is an efficient and effective approach compared to predicting directly on specific surfaces containing antigenic characteristics.

Enhanced Over-Representation Analysis for the Differential Regulation of Birc5a and HIF2α-Knockdown Approaches.

Hypoxia-inducible factors (HIFs) and survivin (Birc5) genes are often considered important cancer drug targets for molecularly targeted therapy, as both genes play important roles in the cellular differentiation and development of neuronal cells. Pathway enrichment analysis is predominantly applied when interpreting the correlated behaviors of activated gene clusters. Traditional enrichment analysis is evaluated via p-values only, regardless of gene expression fold-change levels, gene locations, and possible hidden interactions within a pathway. Here, we combined these factors to retrieve significant pathways, as compared with traditional approaches. We performed RNA-seq analyses on Birc5a and HIF2α knocked down in zebrafish during the embryogenesis stage. Regarding Birc5a, two additional biological pathways, sphingolipid metabolism and herpes simplex infection, were identified; whereas for HIF2α, four biological pathways were re-identified, including ribosome biogenesis in eukaryotes, proteasome, purine metabolism, and complement and coagulation cascades. Our proposed approaches identified additional significant pathways directly related to cell differentiation or cancer, also providing comprehensive mechanisms for designing further biological experiments.

Integrated Hypoxia Signaling and Oxidative Stress in Developmental Neurotoxicity of Benzo[a]Pyrene in Zebrafish Embryos.

Benzo[a]pyrene (B[a]P) is a polycyclic aromatic hydrocarbon formed by the incomplete combustion of organic matter. Environmental B[a]P contamination poses a serious health risk to many organisms because the pollutant may negatively affect many physiological systems. As such, chronic exposure to B[a]P is known to lead to locomotor dysfunction and neurodegeneration in several organisms. In this study, we used the zebrafish model to delineate the acute toxic effects of B[a]P on the developing nervous system. We found that embryonic exposure of B[a]P downregulates shh and isl1, causing morphological hypoplasia in the telencephalon, ventral thalamus, hypothalamus, epiphysis and posterior commissure. Moreover, hypoxia-inducible factors (hif1a and hif2a) are repressed upon embryonic exposure of B[a]P, leading to reduced expression of the Hif-target genes, epo and survivin, which are associated with neural differentiation and maintenance. During normal embryogenesis, low-level oxidative stress regulates neuronal development and function. However, our experiments revealed that embryonic oxidative stress is greatly increased in B[a]P-treated embryos. The expression of catalase was decreased and sod1 expression increased in B[a]P-treated embryos. These transcriptional changes were coincident with increased embryonic levels of H2O2 and malondialdehyde, with the levels in B[a]P-treated fish similar to those in embryos treated with 120-µM H2O2. Together, our data suggest that reduced Hif signaling and increased oxidative stress are involved in B[a]P-induced acute neurotoxicity during embryogenesis.

Chimeric 6-methylsalicylic acid synthase with domains of acyl carrier protein and methyltransferase from Pseudallescheria boydii shows novel biosynthetic activity.

Polyketides are important secondary metabolites, many of which exhibit potent pharmacological applications. Biosynthesis of polyketides is carried out by a single polyketide synthase (PKS) or multiple PKSs in successive elongations of enzyme-bound intermediates related to fatty acid biosynthesis. The polyketide gene PKS306 from Pseudallescheria boydii NTOU2362 containing domains of ketosynthase (KS), acyltransferase (AT), dehydratase (DH), acyl carrier protein (ACP) and methyltransferase (MT) was cloned in an attempt to produce novel chemical compounds, and this PKS harbouring green fluorescent protein (GFP) was expressed in Saccharomyces cerevisiae. Although fluorescence of GFP and fusion protein analysed by anti-GFP antibody were observed, no novel compound was detected. 6-methylsalicylic acid synthase (6MSAS) was then used as a template and engineered with PKS306 by combinatorial fusion. The chimeric PKS containing domains of KS, AT, DH and ketoreductase (KR) from 6MSAS with ACP and MT from PKS306 demonstrated biosynthesis of a novel compound. The compound was identified with a deduced chemical formula of C7 H10 O3 , and the chemical structure was named as 2-hydroxy-2-(propan-2-yl) cyclobutane-1,3-dione. The novel compound synthesized by the chimeric PKS in this study demonstrates the feasibility of combinatorial fusion of PKS genes to produce novel polyketides.

A voting mechanism-based linear epitope prediction system for the host-specific Iridoviridae family.

BACKGROUND: The Iridoviridae family is categorized into five genera and clustered into two subfamilies: Alphairidovirinae includes Lymphocystivirus, Ranavirus (GIV), and Megalocystivirus (TGIV), which infect vertebrate hosts and Betairidovirinae includes Iridovirus and Chloriridovirus, which infect invertebrate hosts. Clustered Iridoviridae subfamilies possess host-specific characteristics, which can be considered as exclusive features for in-silico prediction of effective epitopes for vaccine development. A voting mechanism-based linear epitope (LE) prediction system was applied to identify and endorse LE candidates with a minimum length requirement for each clustered subfamily RESULTS: The experimental results showed that four conserved epitopes among the Iridovirideae family, one exclusive epitope for invertebrate subfamily and two exclusive epitopes for vertebrate family were predicted. These predicted LE candidates were further validated by ELISA assays for evaluating the strength of antigenicity and cross antigenicity. The conserved LEs for Iridoviridae family reflected high antigenicity responses for the two subfamilies, while exclusive LEs reflected high antigenicity responses only for the host-specific subfamily CONCLUSIONS: Host-specific characteristics are important features and constraints for effective epitope prediction. Our proposed voting mechanism based system provides a novel approach for in silico LE prediction prior to vaccine development, and it is especially powerful for analyzing antigen sequences with exclusive features between two clustered groups.

Multiple model species selection for transcriptomics analysis of non-model organisms.

BACKGROUND: Transcriptomic sequencing (RNA-seq) related applications allow for rapid explorations due to their high-throughput and relatively fast experimental capabilities, providing unprecedented progress in gene functional annotation, gene regulation analysis, and environmental factor verification. However, with increasing amounts of sequenced reads and reference model species, the selection of appropriate reference species for gene annotation has become a new challenge. METHODS: We proposed a novel approach for finding the most effective reference model species through taxonomic associations and ultra-conserved orthologous (UCO) gene comparisons among species. An online system for multiple species selection (MSS) for RNA-seq differential expression analysis was developed, and comprehensive genomic annotations from 291 reference model eukaryotic species were retrieved from the RefSeq, KEGG, and UniProt databases. RESULTS: Using the proposed MSS pipeline, gene ontology and biological pathway enrichment analysis can be efficiently achieved, especially in the case of transcriptomic analysis of non-model organisms. The results showed that the proposed method solved problems related to limitations in annotation information and provided a roughly twenty-fold reduction in computational time, resulting in more accurate results than those of traditional approaches of using a single model reference species or the large non-redundant reference database. CONCLUSIONS: Selection of appropriate reference model species helps to reduce missing annotation information, allowing for more comprehensive results than those obtained with a single model reference species. In addition, adequate model species selection reduces the computational time significantly while retaining the same order of accuracy. The proposed system indeed provides superior performance by selecting appropriate multiple species for transcriptomic analysis compared to traditional approaches.

Functional enrichment analysis based on long noncoding RNA associations.

BACKGROUND: Differential gene expression analysis using RNA-seq data is a popular approach for discovering specific regulation mechanisms under certain environmental settings. Both gene ontology (GO) and KEGG pathway enrichment analysis are major processes for investigating gene groups that participate in common biological responses or possess related functions. However, traditional approaches based on differentially expressed genes only detect a few significant GO terms and pathways, which are frequently insufficient to explain all-inclusive gene regulation mechanisms. METHODS: Transcriptomes of survivin (birc5) gene knock-down experimental and wild-type control zebrafish embryos were sequenced and assembled, and a differential expression (DE) gene list was obtained for traditional functional enrichment analysis. In addition to including DE genes with significant fold-change levels, we considered additional associated genes near or overlapped with differentially expressed long noncoding RNAs (DE lncRNAs), which may directly or indirectly activate or inhibit target genes and play important roles in regulation networks. Both the original DE gene list and the additional DE lncRNA-associated genes were combined to perform a comprehensive overrepresentation analysis. RESULTS: In this study, a total of 638 DE genes and 616 DE lncRNA-associated genes (lncGenes) were leveraged simultaneously in searching for significant GO terms and KEGG pathways. Compared to the traditional approach of only using a differential expression gene list, the proposed method of employing DE lncRNA-associated genes identified several additional important GO terms and KEGG pathways. In GO enrichment analysis, 60% more GO terms were obtained, and several neuron development functional terms were retrieved as complete annotations. We also observed that additional important pathways such as the FoxO and MAPK signaling pathways were retrieved, which were shown in previous reports to play important roles in apoptosis and neuron development functions regulated by the survivin gene. CONCLUSIONS: We demonstrated that incorporating genes near or overlapped with DE lncRNAs into the DE gene list outperformed the traditional enrichment analysis method for effective biological functional interpretations. These hidden interactions between lncRNAs and target genes could facilitate more comprehensive analyses.

Comparison of grouper infection with two different iridoviruses using transcriptome sequencing and multiple reference species selection.

Due to high-density aquafarming in Taiwan, groupers are commonly infected with two different iridoviruses: Megalocytivirus (grouper iridovirus of Taiwan, TGIV) and Ranavirus (grouper iridovirus, GIV). Iridoviral diseases cause mass mortality, and surviving fish retain these pathogens, which can then be horizontally transferred. These viruses have therefore become a major challenge for grouper aquaculture. In this study, comparisons of the biological responses of groupers to infection with these two different iridoviruses were performed. A novel approach for transcriptomic analysis was proposed to enhance the discovery of differentially expressed genes and associated biological pathways. In this method, suitable and available reference species are selected from the NCBI taxonomy tree and the Ensembl and KEGG databases instead of either choosing only one model species or adopting the NCBI non-redundant dataset as references. Our results show that selection of multiple appropriate model species as references increases the efficiency and performance of analyses compared to those of traditional approaches. Using this method, 17 shared pathways and 5 specific pathways were found to be significantly differentially expressed following infection with the two iridoviruses, among which 11 pathways were additionally identified based on the proposed method of multiple reference species selection. Among the pathways responsive to infection with a specific iridovirus, the spliceosomal pathway (ko03040; p-value = 0.0011) was exclusively associated with TGIV infection, while the glycolysis/gluconeogenesis pathway (ko00010; p-value = 0.0032) was associated with GIV infection. These findings and designed corresponding biological experiments may facilitate a deeper understanding of the mechanisms by which both TGIV and GIV cause fatal infections, as well as the ways in which they induce different pathologies and symptoms. We believe that the proposed novel mechanism for de novo transcriptomic analysis provides superior and comprehensive functional annotations and that the resulting shared and specific pathways identified may help immunologists develop specific vaccines against various types of iridovirus in the near future.

Complete chloroplast genome of Gracilaria firma (Gracilariaceae, Rhodophyta), with discussion on the use of chloroplast phylogenomics in the subclass Rhodymeniophycidae.

BACKGROUND: The chloroplast genome of Gracilaria firma was sequenced in view of its role as an economically important marine crop with wide industrial applications. To date, there are only 15 chloroplast genomes published for the Florideophyceae. Apart from presenting the complete chloroplast genome of G. firma, this study also assessed the utility of genome-scale data to address the phylogenetic relationships within the subclass Rhodymeniophycidae. The synteny and genome structure of the chloroplast genomes across the taxa of Eurhodophytina was also examined. RESULTS: The chloroplast genome of Gracilaria firma maps as a circular molecule of 187,001 bp and contains 252 genes, which are distributed on both strands and consist of 35 RNA genes (3 rRNAs, 30 tRNAs, tmRNA and a ribonuclease P RNA component) and 217 protein-coding genes, including the unidentified open reading frames. The chloroplast genome of G. firma is by far the largest reported for Gracilariaceae, featuring a unique intergenic region of about 7000 bp with discontinuous vestiges of red algal plasmid DNA sequences interspersed between the nblA and cpeB genes. This chloroplast genome shows similar gene content and order to other Florideophycean taxa. Phylogenomic analyses based on the concatenated amino acid sequences of 146 protein-coding genes confirmed the monophyly of the classes Bangiophyceae and Florideophyceae with full nodal support. Relationships within the subclass Rhodymeniophycidae in Florideophyceae received moderate to strong nodal support, and the monotypic family of Gracilariales were resolved with maximum support. CONCLUSIONS: Chloroplast genomes hold substantial information that can be tapped for resolving the phylogenetic relationships of difficult regions in the Rhodymeniophycidae, which are perceived to have experienced rapid radiation and thus received low nodal support, as exemplified in this study. The present study shows that chloroplast genome of G. firma could serve as a key link to the full resolution of Gracilaria sensu lato complex and recognition of Hydropuntia as a genus distinct from Gracilaria sensu stricto.