BLAST Sequence Alignment Research Articles

Molecular Identification of 'Candidatus Phytoplasma malaysianum'-Related Strains Associated with Areca catechu Palm Yellow Leaf Disease and Phylogenetic Diversity of the Phytoplasmas Within the 16SrXXXII Group.

Areca catechu palm is an important cash plant in Hainan Island of China and also in the tropical regions of the world. A. catechu palm yellow leaf (AcYL) disease caused by phytoplasmas is a devastating disease for plant production. In the study, the phytoplasmas associated with the AcYL disease were identified and characterized based on their conserved genes, and genetic variation and phylogenetic relationship of the phytoplasma strains in the 16SrXXXII group were demonstrated. The results indicated that A. catechu palm plants showing yellow leaf symptoms were infected by 'Candidatus Phytoplasma malaysianum'-related strains belonging to the 16SrXXXII-D subgroup. BLAST and multiple sequence alignment analysis based on 16S rRNA and secA genes showed that the AcYL phytoplasmas shared 100% sequence identity and 100% homology with the 'Ca. P. malaysianum'-related strains. Phylogenetic analysis indicated that the AcYL phytoplasmas and 'Ca. P. malaysianum'-related strains belonging to the 16SrXXXII group clustered into one clade with a 100% bootstrap value. Based on computer-simulated digestions, six kinds of restriction fragment length polymorphism patterns within the 16SrXXXII group were obtained, and a novel subgroup in the 16Sr group was recommended to propose and describe the relevant strains in this 16Sr subgroup. To our knowledge, this is the first study to report that A. catechu palm showing yellow leaf symptoms was infected by 'Ca. P. malaysianum'-related strains belonging to the 16SrXXXII group. A novel 16Sr subgroup, 16SrXXXII-F, was proposed based on the systematical analysis of genetic variation of all phytoplasmas within the 16SrXXXII group. The findings of this study will support references for monitoring the epidemiology and developing effective prevention strategies for AcYL disease.

Computational Analysis and NGS for Human LDHC Complexed with NAD+ and Ethylamino Acetic Acid (Lung Cancer)

Abstract: This study presents a multidimensional exploration of the structural and functional characteristics of the human Lactate Dehydrogenase C (LDHC) complexed with NAD+ and ethylamino acetic acid (EAA), focusing on its implications in lung cancer. Leveraging data from the Protein Data Bank (PDB) and Molecular Modeling Database (MMDB), a comprehensive analysis was conducted using various computational tools and resources. Structural insights were gained through PDBsum and RasMol, elucidating molecular interactions and identifying potential drug-target sites. Sequence analysis via BLAST and Multiple Sequence Alignment provided further understanding of conserved sequences and structural motifs. Visualization and manipulation of molecular structures were facilitated by PyMOL, enabling the identification of active drug-target sites. Proteinligand docking studies using the CB-Dock2 server assessed the efficiency of LDHC complexation with NAD+. Structural validation through the SAVES server ensured the reliability of the complex structure. Additionally, biological network analysis using the STRING database revealed associations with gene ontology and structural classification of the protein, offering insights into targeted interventions in the ancestry of the protein. This comprehensive approach provides valuable insights into LDHC's role in cancer biology and offers promising avenues for therapeutic development in lung cancer.

Antibody sequences assembly method based on weighted de Bruijn graph.

With the development of next-generation protein sequencing technologies, sequence assembly algorithm has become a key technology for de novo sequencing process. At present, the existing methods can address the assembly of an unknown single protein chain. However, for monoclonal antibodies with light and heavy chains, the assembly is still an unsolved question. To address this problem, we propose a new assembly method, DBAS, which integrates the quality scores and sequence alignment scores from de novo sequencing peptides into a weighted de Bruijn graph to assemble the final protein sequences. The established method is used to assembling sequences from two datasets with mixed light and heavy chains from antibodies. The results show that the DBAS can assemble long antibody sequences for both mixed light and heavy chains and single chains. In addition, DBAS is able to distinguish the light and heavy chains by using BLAST sequence alignment. The results show that the algorithm has good performance for both target sequence coverage and contig assembly accuracy.

In silico analysis and expression profiling of Expansin A4, BURP domain protein RD22-like and E6-like genes associated with fiber quality in cotton.

To supply high-quality cotton fibre for the textile industry, the development of long, strong and fine fibre cotton varieties is imperative. An interlinked approach was used to comprehend the role of fibre genes by analyzing interspecific progenies of cotton species. Wild Gossypium species and races are rich source of genetic polymorphism due to environmental dispersal and continuous natural selection. These genetic resources hold mass of outclass genes that can be used in cotton improvement breeding programs to exploit possible traits such as fibre quality, abiotic stress tolerance, and disease and insect resistance. Therefore, use of new molecular techniques such as genomics, transcriptomics and bioinformatics is very important to utilize the genetic potential of wild species in cotton improvement programs. Interspecific lines and Gossypium species used in the study were grown at Central Cotton Research Institute (CCRI), Multan. After retrieving DNA sequence of the genes from NCBI, the primers for gene expression and full-length gene sequence were designed. Expression profiling of Expansin A4, BURP Domain protein RD22-like and E6-like fibre genes was performed through Real Time PCR. BLAST and DNA sequence alignment was conducted for sequence comparison of interspecific lines and Gossypium species. Different in silico analysis were used for characterization of fibre genes and identification of cis acting promoter elements in promoter region. Variable expression of genes related to fibre development was observed at different stages. BLAST and DNA sequence alignment demonstrated resemblance of interspecific lines with G. hirsutum. In silico analysis on the sequence data also confirmed the role of Expansin A4, BURP Domain protein RD22-like and E6-like fibre genes in fibre development. Genetic engineering is also recommended by transferring E6-like, Expansin A4 and BURP Domain RD22-like genes in local cotton cultivars. Similarly, several stress tolerant and light responsive cis acting elements were identified through promotor analysis, which may contribute for fibre development in the breeding programs. Expansin A4, BURP Domain RD22-like and E6-like have positive role in fibre development with variable expression at fiber length and strength associated stages.

Transcriptome Analysis of Antennal Chemosensory Genes in Curculio Dieckmanni Faust. (Coleoptera: Curculionidae).

The olfactory system plays a key role in regulating insect behaviors, such as locating host plants, spawning sites, and mating partners and avoiding predators. Chemosensory genes are required for olfactory recognition in insects. Curculio dieckmanni Faust. (Coleoptera: Curculionidae) damages hazelnuts and causes severe economic losses. There are no effective control measures, but understanding the olfaction mechanisms of this insect could lead to a new approach for population management. However, the genes that perform chemosensory functions in C. dieckmanni are still unclear. Using high-throughput sequencing, we assembled the antennal transcriptome of C. dieckmanni and annotated the major chemosensory gene families. Of the chemosensory gene families, we found 23 odorant-binding proteins, 15 chemosensory proteins, 2 sensory neuron membrane proteins, 15 odorant receptors, 23 ionotropic receptors, and nine gustatory receptors. Using Blast sequence alignment and phylogenetic analysis, the sequences of these proteins were identified. Male- and female-specific chemosensory genes involved in odorant detection and recognition were validated by qRT-PCR. Among the chemosensory genes, we found significant differences in the expression of CdieOBP8, CdieOBP9, CdieOBP19, CdieOBP20, CdieOBP21, CdieCSP15, CdieOR13, and CdieOR15 between adult male and female C. dieckmanni. A total of 87 expressed chemosensory proteins were found in C. dieckmanni. Investigating these proteins will help reveal the molecular mechanism of odorant recognition in C. dieckmanni and may aid the development of novel control strategies for this species.

Transcriptome annotation in the cloud: complexity, best practices and cost

BACKGROUND The NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) initiative provides NIH-funded researchers cost-effective access to commercial cloud providers, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). These cloud providers represent an alternative for the execution of large computational biology experiments like transcriptome annotation, which is a complex analytical process that requires the interrogation of multiple biological databases with several advanced computational tools. The core components of annotation pipelines published since 2012 are BLAST sequence alignments using annotated databases of both nucleotide or protein sequences almost exclusively with networked on-premises compute systems. FINDINGS We compare multiple BLAST sequence alignments using AWS and GCP. We prepared several Jupyter Notebooks with all the code required to submit computing jobs to the batch system on each cloud provider. We consider the consequence of the number of query transcripts in input files and the effect on cost and processing time. We tested compute instances with 16, 32, and 64 vCPUs on each cloud provider. Four classes of timing results were collected: the total run time, the time for transferring the BLAST databases to the instance local solid-state disk drive, the time to execute the CWL script, and the time for the creation, set-up, and release of an instance. This study aims to establish an estimate of the cost and compute time needed for the execution of multiple BLAST runs in a cloud environment. CONCLUSIONS We demonstrate that public cloud providers are a practical alternative for the execution of advanced computational biology experiments at low cost. Using our cloud recipes, the BLAST alignments required to annotate a transcriptome with ∼500,000 transcripts can be processed in <2 hours with a compute cost of ∼$200-$250. In our opinion, for BLAST-based workflows, the choice of cloud platform is not dependent on the workflow but, rather, on the specific details and requirements of the cloud provider. These choices include the accessibility for institutional use, the technical knowledge required for effective use of the platform services, and the availability of open source frameworks such as APIs to deploy the workflow.

Transcriptome annotation in the cloud: complexity, best practices, and cost.

The NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) initiative provides NIH-funded researchers cost-effective access to commercial cloud providers, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). These cloud providers represent an alternative for the execution of large computational biology experiments like transcriptome annotation, which is a complex analytical process that requires the interrogation of multiple biological databases with several advanced computational tools. The core components of annotation pipelines published since 2012 are BLAST sequence alignments using annotated databases of both nucleotide or protein sequences almost exclusively with networked on-premises compute systems. We compare multiple BLAST sequence alignments using AWS and GCP. We prepared several Jupyter Notebooks with all the code required to submit computing jobs to the batch system on each cloud provider. We consider the consequence of the number of query transcripts in input files and the effect on cost and processing time. We tested compute instances with 16, 32, and 64 vCPUs on each cloud provider. Four classes of timing results were collected: the total run time, the time for transferring the BLAST databases to the instance local solid-state disk drive, the time to execute the CWL script, and the time for the creation, set-up, and release of an instance. This study aims to establish an estimate of the cost and compute time needed for the execution of multiple BLAST runs in a cloud environment. We demonstrate that public cloud providers are a practical alternative for the execution of advanced computational biology experiments at low cost. Using our cloud recipes, the BLAST alignments required to annotate a transcriptome with ∼500,000 transcripts can be processed in <2 hours with a compute cost of ∼$200-$250. In our opinion, for BLAST-based workflows, the choice of cloud platform is not dependent on the workflow but, rather, on the specific details and requirements of the cloud provider. These choices include the accessibility for institutional use, the technical knowledge required for effective use of the platform services, and the availability of open source frameworks such as APIs to deploy the workflow.

Neural Network and Random Forest Models in Protein Function Prediction.

Over the past decade, the demand for automated protein function prediction has increased due to the volume of newly sequenced proteins. In this paper, we address the function prediction task by developing an ensemble system automatically assigning Gene Ontology (GO) terms to the given input protein sequence. We develop an ensemble system which combines the GO predictions made by random forest (RF) and neural network (NN) classifiers. Both RF and NN models rely on features derived from BLAST sequence alignments, taxonomy and protein signature analysis tools. In addition, we report on experiments with a NN model that directly analyzes the amino acid sequence as its sole input, using a convolutional layer. The Swiss-Prot database is used as the training and evaluation data. In the CAFA3 evaluation, which relies on experimental verification of the functional predictions, our submitted ensemble model demonstrates competitive performance ranking among top-10 best-performing systems out of over 100 submitted systems. In this paper, we evaluate and further improve the CAFA3-submitted system. Our machine learning models together with the data pre-processing and feature generation tools are publicly available as an open source software at https://github.com/TurkuNLP/CAFA3.

Molecular cloning, characterization, and antioxidant function of catalase in Lymantria dispar asiatic (Lepidoptera: Lymantriidae) under avermectin stress

The critical antioxidant catalase (CAT) breaks down hydrogen peroxide induced by environmental stresses. Here we cloned full length catalase cDNA from Lymantria dispar asiatic (LdCAT). Bioinformatic analyses showed that open reading frames of LdCAT contains 1524 bp, encoding 507 amino acids with molecular weight of 126.99 kDa, theoretical pI of 5.00, aliphatic index of 29.92, grand average of hydropathicity of 0.764, and instability index (II) of 46.56. Protein BLAST and multiple sequence alignment indicated that LdCAT had high identity with CAT from other insects, especially lepidopterans. In a phylogenetic analysis, LdCAT was most similar to CAT from Spodoptera litura and S. exigua. Quantitative real-time polymerase chain reaction showed that LdCAT transcripts in all instar larvae and the five tissues tested, verifying the ubiquity of LdCAT in L. disapr. Moreover, LdCAT of third instar larvae was significantly upregulated after they fed on avermectin at sublethal and LC10 doses. The highest relative transcript levels were found 2 h after an avermectin spray at LC90, and in the cuticula, rather than heads, fat bodies, malpighian tubes, and midguts after a spray avermectin at a sublethal concentration. The expression level of LdCAT under pesticide stresses here suggested that CAT is an important antioxidant enzyme of L. disapr defensing against pesticide stress and may be a good target for controlling this pest.

DNA Barcoding of endangered Ceropegia odorata Nimmo ex J. Graham and Ceropegia hirsuta Wight & Arn. species of Gujarat

In the present study, DNA Barcoding was made for the endangered plants Ceropegia odorata Nimmo ex J. Graham and Ceropegia hirsuta Wight & Arn. DNA barcoding is used to authenticate their reliable identification, conservation, discrimination, similarities and evolutionary trend among them and with their related taxa for future use. Two species, viz., Ceropegia odorata Nimmo ex J. Graham and Ceropegia hirsuta Wight & Arn are reported from Gujarat Dediyapada. The identification of both the species depends on the knowledge which held by taxonomists. Non-specialist cannot cover all the knowledge of the species. To handle with these difficulties’ DNA Barcoding aims to develop a standardized, rapid, and inexpensive species identification method approachable to non- specialists and will become easy for taxonomist. DNA isolation from leaf samples of present study species was carried out by applying a modified CTAB method and good isolation was just for the species considered. Gradient PCR amplification was performed for the isolated DNA using rbcL gene and the primers rbcLF and rbcLR were used. The amplification success rate was 90-95%. PCR amplification was tested with 1 % agarose gel electrophoresis using ethidium bromide and the products were confirmed. The PCR products were further processed for DNA sequencing and sequences were good for the species with the success rate of 95 %. Pairwise sequence alignments were made with BLAST and multiple sequence alignments are made with ClustalW, and Neighbor joining method to study the phylogenetic aspects of the species studied and with their related taxa this study was to apply to support conservation efforts of Ceropegia Species in Gujarat and all over India. We used to recommend rbcL marker for both the sample. We specifically tested whether the markers could be used to solve taxonomic confusion concerning the Ceropegia species. This Barcoding system will be utilized specifically to identify and create phylogeny among the selected endangered species.

ILDR2 has a negligible role in hepatic steatosis.

We have previously reported that Ildr2 knockdown via adenovirally-delivered shRNA causes hepatic steatosis in mice. In the present study we investigated hepatic biochemical and anatomic phenotypes of Cre-mediated Ildr2 knock-out mice. Liver-specific Ildr2 knock-out mice were generated in C57BL/6J mice segregating for a floxed (exon 1) allele of Ildr2, using congenital and acute (10-13-week-old male mice) Cre expression. In addition, Ildr2 shRNA was administered to Ildr2 knock-out mice to test the effects of Ildr2 shRNA, per se, in the absence of Ildr2 expression. RNA sequencing was performed on livers of these knockdown and knockout mice. Congenital and acute liver-specific and hepatocyte-specific knockout mice did not develop hepatic steatosis. However, administration of Ildr2 shRNA to Ildr2 knock-out mice did cause hepatic steatosis, indicating that the Ildr2 shRNA had apparent “off-target” effects on gene(s) other than Ildr2. RNA sequencing and BLAST sequence alignment revealed Dgka as a candidate gene mediating these “off-target” effects. Ildr2 shRNA is 63% homologous to the Dgka gene, and Dgka expression decreased only in mice displaying hepatic steatosis. Dgka encodes diacylglycerol kinase (DGK) alpha, one of a family of DGKs which convert diacylglycerides to phosphatidic acid for second messenger signaling. Dgka knockdown mice would be expected to accumulate diacylglyceride, contributing to the observed hepatic steatosis. We conclude that ILDR2 plays a negligible role in hepatic steatosis. Rather, hepatic steatosis observed previously in Ildr2 knockdown mice was likely due to shRNA targeting of Dgka and/or other “off-target” genes. We propose that the gene candidates identified in this follow-up study may lead to identification of novel regulators of hepatic lipid metabolism.

CBIO-01. THE EARLY CHANGES IN PROTEIN EXPRESSION IN THE RHESUS OPTIC NERVES INJURED BY A SINGLE DOSE/FRACTIONATION STEREOTACTIC RADIOSURGERY

Radiation-induced optic neuropathy (RION) is a severe complication when we use stereotactic radiosurgery (SRS) to treat anterior visual disease. This study was designed to analyze the early changes in protein expression in rhesus optic nerves injured by SRS. The left side intraorbital optic nerves of 3 rhesus monkeys (6-8 years)were injured by gamma knife surgery (GKS) (marginal dose of 15 Gy, 50% isodose curve), while the contralateral optic nerves served as the control. The bilateral intraorbital optic nerves of 3 rhesus monkeys were dissected and performed a non-marker quantitative proteomic analysis at 72 hours after GKS. The differential expression protein information was obtained. The functional information of those proteins was obtained through the BLAST sequence alignment with the human proteomic. The result showed that 41 proteins fit the criteria for differential expression (change>2.0-fold, P value<0.05 or exclusive expression). 7 proteins were significantly down-regulated (change>2.0-fold, P value<0.05) at the injured optic nerves. 18 proteins were exclusively expressed in the contralateral optic nerves. And 16 proteins were exclusively expressed in the injured optic nerves. In general, this study indicated that the single dose of 15 Gy on a 50% isodose curve in the optic nerve had a significant impact on protein expression at 72 hours after GKS. Non-marker quantitative analysis based on high-resolution LCMS/MS can be used to detect the early protein expression change in RION. At 72h after GKS, The cell’s endocytosis and pinocytosis were declined and shown a significant inflammation and immunization. The proliferation of those cell were declined and the genetic transcription and translation were increased in the injury optic.

Studies on DNA barcoding of sacred plant - Ficus religiosa L.

In the present investigation, DNA barcoding were made for the sacred trees of Main (Big) Temples in Cuddalore district, namely Ficus religiosa, to document their reliable identification, discrimination, similarities and evolutionary trend among them and with their related taxa for future use. DNA isolation from leaf samples of present study species was carried out by using a modified CTAB method and good isolation was got for the species studied. Gradient PCR amplification was performed for the isolated DNA using matK gene and the primers matK472F &amp; matK1248R. The amplification success was 90-95%. PCR amplification was tested with 1 % agarose gel electrophoresis using ethidium bromide and the products were confirmed. The PCR products were sent to Xcelris Labs Ltd. Sydney House, Premchand Nagar Road, Bodakdev, Ahmedabad 380054, India, for DNA sequencing and sequences were got for the species with the success rate of 95 %. Pairwise sequence alignments were made with BLAST and multiple sequence alignments are made with ClustalW, and based on the sequence alignments, dentrograms were constructed using software Mega 5 and Neighbor joining method to study the phylogenetic aspects of the species studied and with their related taxa.

DNA Barcoding of Highly Threatened Sacred Plant - Aegle marmelos L.

DNA barcoding is a useful tool to define operational taxonomic units based on standardized DNA regions. In this study, the matK chloroplast gene was tested for species identification of highly threatened sacred plant Aegle marmelos L., to document their reliable identification, discrimination, similarities and evolutionary trend with their related taxa for future use. DNA isolation from leaf sample of Aegle marmelos was carried out by using a modified Cetyl Trimethyl Ammonium Bromide method (CTAB). Gradient PCR amplification was performed for the isolated DNA using matK gene and the primers, matK472F and matK1248R. Pairwise sequence alignments were made with BLAST and multiple sequence alignments were also made with ClustalW. Based on the sequence alignments, dendrograms were constructed using the software, Mega 5 and Neighbor Joining tree method was used to study the phylogenetic aspects of the species studied and with their related taxa. The success rate of PCR amplification was 90-95% and the success rate of DNA sequence was 95%. The maximum identity of the present study sample was 100% with Aegle marmelos and the similarity of other related species, Severinia buxifolia, Citrus trifoliata and Citrus reticulata was 97% respectively.

NCBI BLASTP on High-Performance Reconfigurable Computing Systems

The BLAST sequence alignment program is a central application in bioinformatics. The de facto standard version, NCBI BLAST, uses complex heuristics that make it challenging to simultaneously achieve both high performance and exact agreement. We propose a system that uses novel FPGA-based filters that reduce the input database by over 99.97% without loss of sensitivity. There are several contributions. First is design of the filters themselves, which perform two-hit seeding, exhaustive ungapped alignment, and exhaustive gapped alignments, respectively. Second is the coupling of the filters, especially the two-hit seeding and the ungapped alignment. Third is pipelining the filters in a single design, including maintaining load balancing as data are reduced by orders of magnitude at each stage. Fourth is the optimization required to maintain operating frequency for the resulting complex design. And finally, there is system integration both in hardware (the Convey HC1-EX) and software (NCBI BLASTP). We present results for various usage scenarios and find complete agreement and a factor of nearly 5x speedup over a fully parallel implementation of the reference code on a contemporaneous CPU. We believe that the resulting system is the leading per-socket-accelerated NCBI BLAST.

NCBI BLASTP on the convey HC1-EX

The BLAST sequence alignment program is a central application in bioinformatics. The de facto standard version, NCBI BLAST, uses complex heuristics which make it challenging to simultaneously achieve both high performance and exact agreement. In previous work, a system that used novel FPGA-based filters reduced the input database by over 99.97% without loss of sensitivity. In the present work we report experiences in getting from a prototype to a potential product for the Convey HC1-EX. There are several issues. The first is the efforts made to maintain timing for a highly complex configuration as it is optimized by including additional filter stages. This requires implementation and optimization of new interface logic as well as floor-planning. The second is the system-level tradeoffs necessary to maintain correctness. The issue here is preventing low frequency events, which necessarily cannot be mapped to the FPGA, from diluting the performance benefits without sacrificing sensitivity. We present results for various usage scenarios and find a factor of nearly 5x speed-up over a fully parallel implementation of the reference code on a contemporaneous CPU. We believe that the resulting system is the leading accelerated NCBI BLAST. The significance of this work is that, while such in-depth work is necessary to achieve highperformance for complex systems, these issues are rarely described nin the academic literature.

Bioinformatic Analysis of 302 Reactive Metabolite Target Proteins. Which Ones Are Important for Cell Death?

Many low molecular weight compounds undergo biotransformation to chemically reactive metabolites (CRMs) that covalently modify cellular proteins. However, the mechanisms by which this covalent binding leads to cytotoxicity are not understood. Prior analyses of lists of target proteins sorted by functional categories or hit frequency have not proven informative. In an attempt to move beyond covalent binding, we hypothesized that xenobiotic posttranslational modification of proteins might disrupt important protein-protein interactions (PPIs) and thereby direct cells from homeostasis into cell death pathways. To test this hypothesis, we analyzed a list of 302 proteins (66% rat, 26% mouse, 5% human) known to be targeted by 41 different cytotoxic CRMs. Human orthologs of rodent proteins were found by blast sequence alignment, and their interacting partners were found using the Human Protein Reference Database. The combined set of target orthologs and partners was sorted into KEGG pathways and Gene Ontology categories. Those most highly ranked based on sorting statistics and toxicological relevance were heavily involved with intracellular signaling pathways, protein folding, unfolded protein response, and regulation of apoptosis. Detailed examination revealed that many of the categories were flagged primarily by partner proteins rather than target proteins and that a majority of these partners interacted with just a small number of proteins in the CRM target set. A similar analysis performed without the partner proteins flagged very few categories as significant. These results support the hypothesis that disruption of important PPIs may be a major mechanism contributing to CRM-induced acute cytotoxicity.

Deciphering a Serum Peptide Activity Associated with Biologic Clock

Circadian rhythms have been widely observed in plants, animals, fungi and cyanobacteria. The periodic rhythm is roughly 24-hour cycle in biochemical, physiological, or behavioral processes in organisms. Although circadian rhythms are endogenously-driven, an organism's circadian clock is adjusted to the environmental stimuli and must maintain the periodicity of biologic rhythm despite the changing kinetics in cellular activities. Some cellular proteins are believed to be associated with circadian rhythms. In this study, deficiency of a serum protein in human subjects was detected in individuals diagnosed with sleep disorders. N-terminal sequence analysis of the short peptide with BLAST sequence alignment software on NCBI indicated that it might be related to the protein named Hlark (human lark protein). Lark is required for embryonic development, and is, in fact, RBM4, a splicing regulator. RBM4 is crucial for targeting to speckles. This finding is consistent with the potential existence of a novel sub-nuclear targeting pathway. RBM4 and Lark is probably the same protein and are localized in speckles and nucleoli, but can redistribute to peri-nucleolar clusters, consistent with a novel sub-nuclear pathway.

Ranking-aware integration and explorative search of distributed bio-data

Motivation and Objectives High-throughput production of both biomolecular data and their annotations is providing a rapidly increasing amount of very valuable information that can potentially help finding also long-searched answers to fundamental biomedical questions. Yet, such data deluge makes difficult to extract the information most reliable and most related to the increasingly complex biomedical questions to be answered, which can simultaneously regard many heterogeneous aspects of single or multiple organisms, biological tissues, cells or biomolecular entities. To address such complex questions, many bio-data about several heterogeneous topics, which are available but dispersed in different data sources, must be searched, extracted, integrated and comprehensively queried. Different approaches have been proposed to combine individual search services available on the Web in order to support such heterogeneous searches (Hull et al., 2006; Nekrutenko, 2010). Yet, they rarely rely on a general model of the services to be integrated and none considers, in the integration process, the often available partial rankings of the data to be integrated. Lately, Search Computing (Ceri et al., 2010) has been proposed as a new software framework to build answers to complex search queries by interacting with a collection of cooperating search services and using ranking and joining of results as the dominant factors for service composition. By leveraging the peculiar features of search services, it offers query approaches, execution plans, plan optimization techniques, query configuration tools, and exploratory user interfaces. Here, we report and discuss our work aimed at supporting the explorative search of heterogeneous distributed bio-data and the automatic integration and global ranking of their individual search results, also taking into account the partial rankings of individual searches. In so doing, we make a step towards the computational support required for complex biomedical question answering and biomedical knowledge discovery. Methods According to the Service Mart modeling approach of Search Computing (Ceri et al., 2010), we selected an initial set of typical biomolecular topics (i.e. Protein, Gene, Gene Expression and Biological Function) and modeled the Service Marts (i.e. the generalized and normalized conceptual description) of the bioinformatics services that provide data regarding such topics. We did so by identifying their main and common attributes and normalizing their names. We also defined the semantic Connection Patterns, i.e. the pair-wise coupling, between Service Marts of services that provide data about different topics. This was done by identifying pairs of normalized attributes of the connected Service Marts and defining their comparison predicates, as conjunctive Boolean expressions, that allow joining their values semantically. In so doing, we defined the Semantic Resource Framework (SRF) depicted in Figure 1, which constitutes the reference used by Search Computing to enable the exploration of the services registered in the framework and integrate the data that they provide (Ceri et al., 2010). Then, using available Search Computing tools, we registered in the Search Computing framework five bioinformatics search services that provide data about the topics and semantic associations described in the biomolecular

Tau class glutathione S-transferases candidates from Brassica rapa: Genetic mapping and sequence analysis

Glutathione S-transferases (GSTs) have medically and agriculturally important roles in plants such as herbicide detoxification, responses to biotic and abiotic stress and catalytic reaction of anticancer compounds. The fully sequenced Arabidopsis thaliana and rice (Oryza sativa) genome revealed identification of 52 and 61 members of GSTs, and 28 and 39 of those belong to the Tau class of GSTs (GSTUs), respectively. Based on the sequences of AtGSTUs, 14 BAC clones derived from Brassica rapa that contain similar sequences of AtGSTUs were identified and 17 unique sequences of open reading frames were detected in the 14 BAC clones using blast search and sequence alignment. Those sequences were designated the Tau class candidate of GST derived from B. rapa (BrGSTUs) and it is confirmed that BrGSTUs are also clustered in tandem as it has been known to be common feature in plant. They were mapped on BrR5, BrR7, BrR8, BrR9, or BrR10, and their nucleotide and amino acid sequences were highly similar to those of AtGSTUs. In addition, in silico analysis of BrGSTUs was performed using Korea Brassica Genome Project 24 K (KBGP-24K) oligochip and microarray database for cold, salt, and drought stresses. The results of this study will facilitate further researches for breeding of Chinese cabbage containing medically and agriculturally important traits.