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PubMed2000

Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective.

Cellular metabolism is most often described and interpreted in terms of the biochemical reactions that make up the metabolic network. Genomics is providing near complete information regarding the genes/gene products participating in cellular metabolism for a growing number of organisms. As the true functional units of metabolic systems are its pathways, the time has arrived to define metabolic pathways in the context of whole-cell metabolism for the analysis of the structural design and capabilities of the metabolic network. In this study, we present the theoretical foundations for the identification of the unique set of systemically independent biochemical pathways, termed extreme pathways, based on system stochiometry and limited thermodynamics. These pathways represent the edges of the steady-state flux cone derived from convex analysis, and they can be used to represent any flux distribution achievable by the metabolic network. An algorithm is presented to determine the set of extreme pathways for a system of any complexity and a classification scheme is introduced for the characterization of these pathways. The property of systemic independence is discussed along with its implications for issues related to metabolic regulation and the evolution of cellular metabolic networks. The underlying pathway structure that is determined from the set of extreme pathways now provides us with the ability to analyse, interpret, and perhaps predict metabolic function from a pathway-based perspective in addition to the traditional reaction-based perspective. The algorithm and classification scheme developed can be used to describe the pathway structure in annotated genomes to explore the capabilities of an organism.

Algorithms↗
PubMed2002

RIO: analyzing proteomes by automated phylogenomics using resampled inference of orthologs.

BACKGROUND: When analyzing protein sequences using sequence similarity searches, orthologous sequences (that diverged by speciation) are more reliable predictors of a new protein's function than paralogous sequences (that diverged by gene duplication). The utility of phylogenetic information in high-throughput genome annotation ("phylogenomics") is widely recognized, but existing approaches are either manual or not explicitly based on phylogenetic trees. RESULTS: Here we present RIO (Resampled Inference of Orthologs), a procedure for automated phylogenomics using explicit phylogenetic inference. RIO analyses are performed over bootstrap resampled phylogenetic trees to estimate the reliability of orthology assignments. We also introduce supplementary concepts that are helpful for functional inference. RIO has been implemented as Perl pipeline connecting several C and Java programs. It is available at http://www.genetics.wustl.edu/eddy/forester/. A web server is at http://www.rio.wustl.edu/. RIO was tested on the Arabidopsis thaliana and Caenorhabditis elegans proteomes. CONCLUSION: The RIO procedure is particularly useful for the automated detection of first representatives of novel protein subfamilies. We also describe how some orthologies can be misleading for functional inference.

Animals↗
PubMed2003

Identification of a unique IAHP (IcmF associated homologous proteins) cluster in Vibrio cholerae and other proteobacteria through in silico analysis.

Previously using global transcription profile approach, the icmF gene of V. cholerae was identified as an in vivo induced gene involved in the regulation of motility, adherence to intestinal epithelial cells. The present report shows that icmF has 27 homologues in the finished and unfinished microbial genome sequences available in the database and among them only Legionella pneumophila IcmF has been partially characterized. We first identified a gene cluster containing 15 genes surrounding IcmF and designated as IcmF associated homologous protein (IAHP), present in nine gram-negative proteo-bacteria that need an intimate contact with the eukaryotic host cells. Only in P. aeruginosa the cluster is present in three different regions of the genome. In Y. pestis CO92 the cluster is in the same orientation as that of V. cholerae. But in E. coli O157:H7 VT2 Sakai, E. coli O157:H7 EDL933 and Y. pestis KIM, the cluster is in the opposite orientation to that of V. cholerae though the relative position of respective ORFs are the same. In other proteobacteria like M. loti, A. tumefaciens, P. aeruginosa and S. typhimurum, the genes are reshuffled indicating the frequent rearrangement in microbial genomes. Annotation, motif and domain prediction suggested a role of the proteins of IAHP cluster in cell surface architecture or secretion. Phylogenetic analysis of each protein belonging to the cluster present in all the nine organisms showed that only E. coli O157:H7 VT2 Sakai, E. coli O157:H7 EDL933, Y. pestis KIM and Y. pestis CO92 are closer to the V. cholerae and this pattern was similar for all proteins in the cluster. Presence of low G + C regions before and after the gene cluster in V. cholerae and both of the E. coli O157: H7 strains provide possibility of transfer of the gene cluster from a foreign source. From our finding it can be speculated that both of the E. coli O157:H7 strains and V. cholerae has a common ancestor, but the other organism where the cluster is reshuffled has undergone a long term of evolution.

Amino Acid Sequence↗
PubMed2006

Identification and analysis of genes and pseudogenes within duplicated regions in the human and mouse genomes.

The identification and classification of genes and pseudogenes in duplicated regions still constitutes a challenge for standard automated genome annotation procedures. Using an integrated homology and orthology analysis independent of current gene annotation, we have identified 9,484 and 9,017 gene duplicates in human and mouse, respectively. On the basis of the integrity of their coding regions, we have classified them into functional and inactive duplicates, allowing us to define the first consistent and comprehensive collection of 1,811 human and 1,581 mouse unprocessed pseudogenes. Furthermore, of the total of 14,172 human and mouse duplicates predicted to be functional genes, as many as 420 are not included in current reference gene databases and therefore correspond to likely novel mammalian genes. Some of these correspond to partial duplicates with less than half of the length of the original source genes, yet they are conserved and syntenic among different mammalian lineages. The genes and unprocessed pseudogenes obtained here will enable further studies on the mechanisms involved in gene duplication as well as of the fate of duplicated genes.

Animals↗
PubMed2005

JIGSAW: integration of multiple sources of evidence for gene prediction.

MOTIVATION: Computational gene finding systems play an important role in finding new human genes, although no systems are yet accurate enough to predict all or even most protein-coding regions perfectly. Ab initio programs can be augmented by evidence such as expression data or protein sequence homology, which improves their performance. The amount of such evidence continues to grow, but computational methods continue to have difficulty predicting genes when the evidence is conflicting or incomplete. Genome annotation pipelines collect a variety of types of evidence about gene structure and synthesize the results, which can then be refined further through manual, expert curation of gene models. RESULTS: JIGSAW is a new gene finding system designed to automate the process of predicting gene structure from multiple sources of evidence, with results that often match the performance of human curators. JIGSAW computes the relative weight of different lines of evidence using statistics generated from a training set, and then combines the evidence using dynamic programming. Our results show that JIGSAW's performance is superior to ab initio gene finding methods and to other pipelines such as Ensembl. Even without evidence from alignment to known genes, JIGSAW can substantially improve gene prediction accuracy as compared with existing methods. AVAILABILITY: JIGSAW is available as an open source software package at http://cbcb.umd.edu/software/jigsaw.

Algorithms↗
PubMed1998

Prediction of locally optimal splice sites in plant pre-mRNA with applications to gene identification in Arabidopsis thaliana genomic DNA.

Prediction of splice site selection and efficiency from sequence inspection is of fundamental interest (testing the current knowledge of requisite sequence features) and practical importance (genome annotation, design of mutant or transgenic organisms). In plants, the dominant variables affecting splice site selection and efficiency include the degree of matching to the extended splice site consensus and the local gradient of U- and G+C-composition (introns being U-rich and exons G+C-rich). We present a novel method for splice site prediction, which was particularly trained for maize and Arabidopsis thaliana. The method extends our previous algorithm based on logitlinear models by considering three variables simultaneously: intrinsic splice site strength, local optimality and fit with respect to the overall splice pattern prediction. We show that the method considerably improves prediction specificity without compromising the high degree of sensitivity required in gene prediction algorithms. Applications to gene identification are illustrated for Arabidopsis and suggest that successful methods must combine scoring for splice sites, coding potential and similarity with potential homologs in non-trivial ways. A WWW version of the SplicePredictor program is available at http:/gnomic.stanford.edu/volker/SplicePredi ctor.html/

Algorithms↗
PubMed2025

ATAC-seq in Emerging Model Organisms: Challenges and Strategies.

The Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) is a versatile and widely utilized method for identifying potential regulatory regions, such as promoters and enhancers, within a genome. ATAC-seq has been successfully applied to a wide range of established and emerging model organisms. However, implementing this method in emerging model systems, such as arthropods, can be challenging due to several factors that influence data quality. These factors include the availability of a sufficient amount and quality of tissue or cells, the need for species- and tissue-specific protocol optimization, the completeness and accuracy of the reference genome, and the quality of the genome annotation. In this article, we emphasize the key steps in the ATAC-seq protocol that, based on our experience, have the greatest impact on data quality when adapting this method for emerging model organisms. Specifically, we discuss the importance of nuclei isolation, the incubation conditions of the Tn5 transposase, and PCR amplification of the library. Furthermore, we outline essential quality checkpoints during the bioinformatic analysis of ATAC-seq data to assist in assessing data integrity and consistency. Given that many emerging model organisms may not be readily available in laboratory cultures, we also emphasize the importance of evaluating how different preservation methods affect ATAC-seq data quality. Based on examples in one spider and one ant species, we demonstrate that replication and thorough quality controls at all steps of the protocol and data analysis are essential to assess the usability of ATAC-seq data. Our data highlights the importance of isolating the right number of intact nuclei, as well as ensuring optimal amplification conditions during library preparation to obtain good-quality sequence data for downstream analyses. We recommend using fresh tissue samples if possible because we show that direct cryopreservation of the tissue may affect chromatin integrity. This effect could be avoided or reduced by preserving the homogenate in cell culture medium. Overall, we explain the ATAC-seq protocol and downstream analyses in detail and give step-by-step advice to researchers who are new to the field and want to implement this method. With careful planning and validation, ATAC-seq can reveal the regulatory landscape of a genome and aid in identifying elements that govern gene expression.

Animals↗
PubMed2025

Chromosome scale genomes of two invasive Adelges species enable virtual screening for selective adelgicides.

Two invasive hemipteran adelgids are associated with widespread damage to several North American conifer species. Adelges tsugae, hemlock woolly adelgid, was introduced from Japan and reproduces parthenogenetically in North America, where it has rapidly decimated Tsuga canadensis and Tsuga caroliniana (the eastern and Carolina hemlocks, respectively). Adelges abietis, eastern spruce gall adelgid, introduced from Europe, forms distinctive pineapple-shaped galls on several native spruce species. While not considered a major forest pest, it weakens trees and increases susceptibility to additional stressors. Broad-spectrum insecticides that are often used to control adelgid populations can have off-target impacts on beneficial insects. Whole genome sequencing was performed on both species to aid in development of targeted solutions that may minimize ecological impact. Adelges abietis was sequenced using Illumina Linked-Read technology from 30 pooled individuals, with Hi-C scaffolding performed using data from a single individual collected from the same host plant. Adelges tsugae used Oxford Nanopore long-read sequencing from pooled nymphs. The assembled A. tsugae and A. abietis genomes, pooled from several parthenogenetic females, are 220.75 Mbp and 253.16 Mbp, respectively. Each consists of eight autosomal chromosomes, as well as two sex chromosomes (X1/X2), supporting the XX-XO sex determination system. The genomes are over 96% complete based on BUSCO assessment. Genome annotation identified 11,424 and 12,060 protein-coding genes in A. tsugae and A. abietis, respectively. Comparative analysis of proteins across 29 hemipteran species and 14 arthropod outgroups identified 31,666 putative gene families. Gene family evolution analysis with CAFE revealed lineage-specific expansions in immune-related aminopeptidases (ERAP1) and juvenile hormone binding proteins (JHBP), contractions in juvenile hormone acid methyltransferases (JHAMT), and conservation of nicotinic acetylcholine receptors (nAChR). These genes were explored as candidate families towards a long-term objective of developing adelgid-selective insecticides. Structural comparisons of proteins across seven focal species (Adelges tsugae, Adelges abietis, Adelges cooleyi, Rhopalosiphum maidis, Apis mellifera, Danaus plexippus, and Drosophila melanogaster) revealed high conservation of nAChR and ERAP1, while JHAMT exhibited species-specific structural divergence. The potential of JHAMT as a lineage-specific target for pest control was explored through virtual drug and pesticide screening.

adelgids↗
PubMed2004

Prediction of DtxR regulon: identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae.

BACKGROUND: The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. RESULT: Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. CONCLUSIONS: We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.

Bacterial Proteins↗
PubMed2025

Post-genome-wide association study dissects genetic vulnerability and risk gene expression of Sjögren's disease for cardiovascular disease.

OBJECTIVES: This study aims to clarify the genetic associations between Sjögren's Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibility genes. METHODS: We performed two-sample and multivariable Mendelian randomization (MR) analysis to investigate the association between SD and the risk of ischemic heart disease (IHD) and stroke. Linkage disequilibrium score regression (LDSC) and Bayesian co-localization analyses were employed to assess the genetic associations between traits. Cross-phenotype analyses were employed to identify shared variants and genes, followed by a Transcriptome-Wide Association Study (TWAS) and Multi-marker Analysis of Genomic Annotation (MAGMA) based on Multi-Trait Analysis of GWAS (MTAG) results. To validate the pleiotropic genes, we further analyzed tissue-specific differentially expressed genes (DEGs) related to SD using RNA sequencing data. RESULTS: The two-sample and multivariable MR analyses revealed that SD confers a genetic vulnerability to IHD and stroke. LDSC and co-localization analyses indicated a strong genetic linkage between SD and CVDs. Cross-phenotype analyses identified 38 and 37 pleiotropic single nucleotide polymorphisms (SNPs) for SD-Stroke and SD-IHD, respectively, primarily located within the MHC class region on 6p21.32:33 loci. Additionally, TWAS and MAGMA analyses identified pleiotropic genes located outside the MHC regions-seven associated with stroke (UHRF1BP1, SNRPC, BLK, FAM167A, ARHGAP27, C8orf12, and PLEKHM1) and two associated with IHD (UHRF1BP1 and SNRPC). Proxy variants within these genes in SD suggested an increased causal risk for stroke or IHD. Co-localization analysis further reinforced that SD and stroke share significant SNPs within the loci of FAM167A, BLK, C8orf12, SNRPC, and UHRF1BP1. DEG analysis revealed a significant up-regulation of the identified genes in SD-specific tissues. CONCLUSIONS: SD appears genetically predisposed to an increased risk of CVDs. Moreover, this research not only identified pleiotropic genes shared between SD and CVDs, but also, for the first time, detected key gene expressions that elevate CVD risk in SD patients-findings that may offer promising therapeutic targets for patient management.

Humans↗
PubMed2003

Improvement of the GenTHREADER method for genomic fold recognition.

MOTIVATION: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. RESULTS: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method. AVAILABILITY: http://www.psipred.net.

Amino Acid Sequence↗
PubMed2000

Assignment of enzyme substrate specificity by principal component analysis of aligned protein sequences: an experimental test using DNA glycosylase homologs.

We have studied the relationship between amino acid sequence and substrate specificity in a DNA glycosylase family by characterizing experimentally the specificity of four new members of the family. We show that principal component analysis (PCA) of the sequence family correctly predicts the substrate specificity of one of the novel homologs even though conventional sequence analysis methods fail to group this homolog with other sequences of the same specificity. PCA also suggested, correctly, that another homolog characterized previously differs in its specificity from those sequences with which it clusters by conventional criteria. These results suggest that principal component analysis of sequence families can be a useful tool in annotating genome sequences when there is ambiguity concerning which subfamily a new homolog belongs to. Published 2000 Wiley-Liss, Inc.

Amino Acid Sequence↗
PubMed2005

The paradox of functional heterochromatin.

Although heterochromatin has been studied for 80 years, its genetic function and molecular organization have remained elusive. In almost all organisms, heterochromatin has been regarded as genetically inactive chromosome regions. However, from genetic and genomic studies in Drosophila melanogaster and other organisms including humans, it is now clear that transcriptionally active domains are present within constitutive heterochromatin. These domains contain essential coding genes whose expression during development ensures the formation of the proper biochemical and morphological phenotypes, together with several gene models defined by genome annotation whose functions still need to be determined.

Animals↗
PubMed2006

Persistent biases in the amino acid composition of prokaryotic proteins.

Correspondence analysis of 28 proteomes selected to span the entire realm of prokaryotes revealed universal biases in the proteins' amino acid distribution. Integral Inner Membrane Proteins always form an individual cluster, which can then be used to predict protein localisation in unknown proteomes, independently of the organism's biotope or kingdom. Orphan proteins are consistently rich in aromatic residues. Another bias is also ubiquitous: the amino acid composition is driven by the G + C content of the first codon position. An unexpected bias is driven, in many proteomes, by the AAN box of the genetic code, suggesting some functional biochemical relationship between asparagine and lysine. Less-significant biases are driven by the rare amino acids, cysteine and tryptophan. Some allow identification of species-specific functions or localisation such as surface or exported proteins. Errors in genome annotations are also revealed by correspondence analysis, making it useful for quality control and correction.

Amino Acids↗
PubMed2005

A generalized affine gap model significantly improves protein sequence alignment accuracy.

Sequence alignment underpins common tasks in molecular biology, including genome annotation, molecular phylogenetics, and homology modeling. Fundamental to sequence alignment is the placement of gaps, which represent character insertions or deletions. We assessed the ability of a generalized affine gap cost model to reliably detect remote protein homology and to produce high-quality alignments. Generalized affine gap alignment with optimal gap parameters performed as well as the traditional affine gap model in remote homology detection. Evaluation of alignment quality showed that the generalized affine model aligns fewer residue pairs than the traditional affine model but achieves significantly higher per-residue accuracy. We conclude that generalized affine gap costs should be used when alignment accuracy carries more importance than aligned sequence length.

Algorithms↗
PubMed2006

Identifying cysteines and histidines in transition-metal-binding sites using support vector machines and neural networks.

Accurate predictions of metal-binding sites in proteins by using sequence as the only source of information can significantly help in the prediction of protein structure and function, genome annotation, and in the experimental determination of protein structure. Here, we introduce a method for identifying histidines and cysteines that participate in binding of several transition metals and iron complexes. The method predicts histidines as being in either of two states (free or metal bound) and cysteines in either of three states (free, metal bound, or in disulfide bridges). The method uses only sequence information by utilizing position-specific evolutionary profiles as well as more global descriptors such as protein length and amino acid composition. Our solution is based on a two-stage machine-learning approach. The first stage consists of a support vector machine trained to locally classify the binding state of single histidines and cysteines. The second stage consists of a bidirectional recurrent neural network trained to refine local predictions by taking into account dependencies among residues within the same protein. A simple finite state automaton is employed as a postprocessing in the second stage in order to enforce an even number of disulfide-bonded cysteines. We predict histidines and cysteines in transition-metal-binding sites at 73% precision and 61% recall. We observe significant differences in performance depending on the ligand (histidine or cysteine) and on the metal bound. We also predict cysteines participating in disulfide bridges at 86% precision and 87% recall. Results are compared to those that would be obtained by using expert information as represented by PROSITE motifs and, for disulfide bonds, to state-of-the-art methods.

Amino Acid Sequence↗
PubMed2002

The DNA damage response in filamentous fungi.

The mechanisms used by fungal cells to repair DNA damage have been subjects of intensive investigation for almost 50 years. As a result, the model yeasts Schizosaccharomyces pombe and Saccharomyces cerevisiae have led the way in yielding critical insights into the nature of the DNA damage response. At the same time, largely through the efforts of Etta Kafer, Hirokazu Inoue, and colleagues, a substantial collection of Aspergillus nidulans and Neurospora crassa DNA repair mutants has been identified and characterized in detail. As the analysis of these mutants continues and increasing amounts of annotated genome sequence become available, it is becoming readily apparent that the DNA damage response of filamentous fungi possesses several features that distinguish it from the model yeasts. These features are emphasized in this review, which describes the genes, regulatory networks, and processes that compose the fungal DNA damage response. Further characterization of this response will likely yield general insights that are applicable to animals and plants. Moreover, it may also become evident that the DNA damage response can be manipulated to control fungal growth.

Apoptosis↗
PubMed2001

Computational and experimental analyses reveal previously undetected coding exons of the KRIT1 (CCM1) gene.

A notable difficulty in annotating genomic sequence is identifying the correct start codon in a gene. An important such case has been found with KRIT1, the cerebral cavernous malformation type 1 (CCM1) gene. Analysis of human and mouse genomic sequence encompassing the region containing KRIT1/Krit1 using exon/gene-prediction and comparative alignment programs revealed putative exons upstream of the previously described first exon. These additional candidate exons show significant matches to mouse and human ESTs that are contiguous with and extend upstream from the previously designated 5' end of the KRIT1 cDNA sequence. RT-PCR and 5'RACE experiments confirm the presence of four additional upstream coding exons that encode an additional 207 amino acids. Importantly, a novel frameshift mutation in one of these newly identified KRIT1 exons has been found in a CCM1 family. These data establish the authentic KRIT1 amino acid sequence and suggest that the additional KRIT1 exons may harbor mutations in other CCM1 families. In addition, these results provide another example of the utility of rigorous computational and comparative sequence analysis for refining gene structure.

Alternative Splicing↗