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PubMed2025

Gene and pathway analysis of genome-wide genetic associations of bladder cancer.

BACKGROUND: Although genetic variants associated with bladder cancer (BCa) risk have been identified through hypothesis-driven and genome-wide association studies, a systematic understanding of BCa genetic susceptibility at the gene and pathway levels remains to be achieved. MATERIALS AND METHODS: In this 2-stage functional genomics study, we used 5 independent tools for genome-wide gene mapping and ranking based on BCa genome-wide association studies summary statistics, followed by a meta-analysis of gene-level significance p values, to obtain a consensus gene ranking in terms of association with BCa. Subsequently, we performed preranked gene-set enrichment analysis to identify the functional pathways involved in BCa genetic susceptibility. Joint analysis with gene-set enrichment analysis, based on somatic alteration frequency, was performed to explore the pathway-level relationships between genetic susceptibility and somatic alterations in BCa. RESULTS: Other than the well-known BCa genes (such as FGFR3, MYC, TERT, CCNE1, and TP63), we additionally prioritized a set of novel genes likely to be genetically implicated in BCa development, including SETD2, a possible tumor suppressor gene involved in chromatin remodeling. We further demonstrated convergence between genetic associations and somatic alterations at both the gene (eg, FGFR3 and TERT) and pathway levels (eg, cell cycle and chromatin modification), as well as functional ontologies specifically implicated in germline predisposition to BCa (eg, CD8/TCR signaling, immune checkpoints, and cytokine signaling). CONCLUSIONS: We identified several novel genes associated with BCa and demonstrated that genetic variants contribute to the development of BCa by affecting antitumor immunity, response to toxic exposure, and RNA and protein homeostasis and synergizing with somatic alterations in various cancer-related pathways.

Bladder cancer↗
PubMed2003

Gene expression in autumn leaves.

Two cDNA libraries were prepared, one from leaves of a field-grown aspen (Populus tremula) tree, harvested just before any visible sign of leaf senescence in the autumn, and one from young but fully expanded leaves of greenhouse-grown aspen (Populus tremula x tremuloides). Expressed sequence tags (ESTs; 5,128 and 4,841, respectively) were obtained from the two libraries. A semiautomatic method of annotation and functional classification of the ESTs, according to a modified Munich Institute of Protein Sequences classification scheme, was developed, utilizing information from three different databases. The patterns of gene expression in the two libraries were strikingly different. In the autumn leaf library, ESTs encoding metallothionein, early light-inducible proteins, and cysteine proteases were most abundant. Clones encoding other proteases and proteins involved in respiration and breakdown of lipids and pigments, as well as stress-related genes, were also well represented. We identified homologs to many known senescence-associated genes, as well as seven different genes encoding cysteine proteases, two encoding aspartic proteases, five encoding metallothioneins, and 35 additional genes that were up-regulated in autumn leaves. We also indirectly estimated the rate of plastid protein synthesis in the autumn leaves to be less that 10% of that in young leaves.

Arabidopsis Proteins↗
PubMed2002

A comparison of position-specific score matrices based on sequence and structure alignments.

Sequence comparison methods based on position-specific score matrices (PSSMs) have proven a useful tool for recognition of the divergent members of a protein family and for annotation of functional sites. Here we investigate one of the factors that affects overall performance of PSSMs in a PSI-BLAST search, the algorithm used to construct the seed alignment upon which the PSSM is based. We compare PSSMs based on alignments constructed by global sequence similarity (ClustalW and ClustalW-pairwise), local sequence similarity (BLAST), and local structure similarity (VAST). To assess performance with respect to identification of conserved functional or structural sites, we examine the accuracy of the three-dimensional molecular models predicted by PSSM-sequence alignments. Using the known structures of those sequences as the standard of truth, we find that model accuracy varies with the algorithm used for seed alignment construction in the pattern local-structure (VAST) > local-sequence (BLAST) > global-sequence (ClustalW). Using structural similarity of query and database proteins as the standard of truth, we find that PSSM recognition sensitivity depends primarily on the diversity of the sequences included in the alignment, with an optimum around 30-50% average pairwise identity. We discuss these observations, and suggest a strategy for constructing seed alignments that optimize PSSM-sequence alignment accuracy and recognition sensitivity.

Algorithms↗
PubMed2026

Moderate expression and activity of flocculins underlie the characteristic flocculation phenotype of Saccharomyces pastorianus.

Flocculation is a key technological trait in lager brewing, governing fermentation performance, yeast recovery, and beer quality. In the allo-aneuploid hybrid yeast Saccharomyces pastorianus, the genetic basis of flocculation remains poorly resolved due to its complex dual sub-genome architecture. Here, we systematically re-annotated and functionally characterized the complete FLO gene repertoire of the Group II strain CBS 1483. Thirteen FLO genes were identified, including allelic variants and a previously uncharacterized adhesin, Flo12, containing a Hyphal_reg_CWP domain instead of the canonical PA14 lectin-binding domain. Structural modeling revealed strong conservation of Ca²+-binding residues in PA14 domains, alongside repeat-region diversification likely contributing to functional variability. Using optogenetic expression in a FLO-null background, we demonstrated that SpcI-FLO9-1 and SpcI-FLO9-2_1 are the strongest drivers of flocculation, exhibiting NewFlo-like sugar sensitivity. Transcriptomic analysis during 17°P wort fermentation showed dynamic induction of these genes coinciding with flocculation onset. Surprisingly, deletion of both loci in CBS 1483 did not abolish but only delayed sedimentation in wort, accompanied by improved maltose utilization and attenuation. These findings reveal functional redundancy and compensatory mechanisms within the FLO network of lager yeast, highlighting the genetic complexity underlying flocculation, and providing a molecular framework to inform yeast selection, strain development, and optimization of the lager fermentation processes.IMPORTANCEFlocculation, the process by which yeast cells aggregate and settle, is essential for producing clear, high-quality lager beer, and for efficient yeast recovery during brewing. However, the genetic basis of this trait in lager yeast has remained poorly understood because these strains possess unusually complex hybrid genomes. In this study, we systematically identified and characterized the complete set of flocculation genes in the industrial lager yeast Saccharomyces pastorianus CBS 1483. We demonstrated that lager yeast flocculation is not controlled by a single dominant gene, but instead emerges from the combined action of several moderately active adhesion proteins that are expressed at low levels during fermentation. Surprisingly, deleting the two strongest candidate genes only delayed, rather than eliminated, sedimentation, revealing a robust compensatory network that preserves brewing performance. These findings refine the current understanding of yeast flocculation and provide a molecular framework for developing brewing strains with improved fermentation efficiency, product consistency, and flavor quality.

Saccharomyces pastorianus↗
PubMed2002

FunSpec: a web-based cluster interpreter for yeast.

BACKGROUND: For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time. RESULTS: We present here a web-based tool (FunSpec) for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations (e.g. functional roles, biochemical properties, localization). FunSpec is available online at http://funspec.med.utoronto.ca CONCLUSION: FunSpec is helpful for interpretation of any data type that generates groups of related genes and proteins, such as gene expression clustering and protein complexes, and is useful for predictive methods employing "guilt-by-association."

Cluster Analysis↗
PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗
PubMed2026

Genomic distribution characteristics and interspecific differences of microsatellite landscapes in Felidae.

BACKGROUND: Microsatellites within genomes play crucial roles in regulating gene expression, DNA replication, and chromosomal structure and function. Analyzing the composition and distribution patterns of microsatellites in closely related species not only reveals their evolutionary dynamics and adaptive mechanisms but also provides essential technical support for applications in genetic breeding, species conservation, and disease research. As one of the world's most captivating animal groups, the landscape patterns of microsatellites across feline genomes remain to be systematically characterized. RESULTS: This study utilized high-quality genomic data to conduct a systematic comparative analysis of microsatellite landscape distribution patterns across the genomes of 13 felid species. The findings revealed that microsatellite abundance and distribution exhibit species-specific characteristics, with a non-random genomic distribution and a negative correlation between microsatellite abundance and repeat length. The predominant distribution pattern followed the sequence: single > double > quadruple > triple > quintuple > sextuple nucleotide repeats. Microsatellite abundance peaked in intergenic regions, whereas trinucleotide repeats were more prevalent within exons. Coding regions showed a marked preference for trinucleotide and hexanucleotide repeats. Enrichment analysis of GO and KEGG pathways indicated that coding sequences containing microsatellites were primarily involved in transcription and translation processes. CONCLUSIONS: Our study elucidates the distribution patterns and characteristics of microsatellites across diverse feline species, providing significant insights into their evolutionary mechanisms and functional roles. Furthermore, these findings establish a valuable reference and foundational dataset for the future development of high-quality, species-specific microsatellite markers in felids.

Animals↗
PubMed2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

DNA methylation↗
PubMed2001

[Application of DNA chip technology to biomedical research].

The completion of Human Genome Project enabled us to access to the information on nucleotide sequences of whole human genome. One of the most valuable information on human genome would be the list of approximately 35,000 genes. Although 35% of them are still needed to annotate their functions, we can genome-widely approach to various conditions including disease states. To analyze bunch of information at once, we need high-throughput technology containing most of genes. DNA chip successfully provide a stable platform technology for the massive screening of genomes. Microarrays can be used to obtain genome-wide fingerprint on transcriptional changes in various physiological and pathological conditions, leading to the mining novel genes related to those specific states. We can check the multiple molecular markers for diagnosis, prediction or prognosis of specific diseases. Data from microarray will provide huge amounts of experssion profile, which might induce the transformation of biomedical research.

Base Sequence↗
PubMed2002

Gene3D: structural assignment for whole genes and genomes using the CATH domain structure database.

We present a novel web-based resource, Gene3D, of precalculated structural assignments to gene sequences and whole genomes. This resource assigns structural domains from the CATH database to whole genes and links these to their curated functional and structural annotations within the CATH domain structure database, the functional Dictionary of Homologous Superfamilies (DHS) and PDBsum. Currently Gene3D provides annotation for 36 complete genomes (two eukaryotes, six archaea, and 28 bacteria). On average, between 30% and 40% of the genes of a given genome can be structurally annotated. Matches to structural domains are found using the profile-based method (PSI-BLAST). and a novel protocol, DRange, is used to resolve conflicts in matches involving different homologous superfamilies.

Animals↗
PubMed2000

Re-annotating the Mycoplasma pneumoniae genome sequence: adding value, function and reading frames.

Four years after the original sequence submission, we have re-annotated the genome of Mycoplasma pneumoniae to incorporate novel data. The total number of ORFss has been increased from 677 to 688 (10 new proteins were predicted in intergenic regions, two further were newly identified by mass spectrometry and one protein ORF was dismissed) and the number of RNAs from 39 to 42 genes. For 19 of the now 35 tRNAs and for six other functional RNAs the exact genome positions were re-annotated and two new tRNA(Leu) and a small 200 nt RNA were identified. Sixteen protein reading frames were extended and eight shortened. For each ORF a consistent annotation vocabulary has been introduced. Annotation reasoning, annotation categories and comparisons to other published data on M.pneumoniae functional assignments are given. Experimental evidence includes 2-dimensional gel electrophoresis in combination with mass spectrometry as well as gene expression data from this study. Compared to the original annotation, we increased the number of proteins with predicted functional features from 349 to 458. The increase includes 36 new predictions and 73 protein assignments confirmed by the published literature. Furthermore, there are 23 reductions and 30 additions with respect to the previous annotation. mRNA expression data support transcription of 184 of the functionally unassigned reading frames.

Amino Acid Sequence↗
PubMed2001

A draft annotation and overview of the human genome.

BACKGROUND: The recent draft assembly of the human genome provides a unified basis for describing genomic structure and function. The draft is sufficiently accurate to provide useful annotation, enabling direct observations of previously inferred biological phenomena. RESULTS: We report here a functionally annotated human gene index placed directly on the genome. The index is based on the integration of public transcript, protein, and mapping information, supplemented with computational prediction. We describe numerous global features of the genome and examine the relationship of various genetic maps with the assembly. In addition, initial sequence analysis reveals highly ordered chromosomal landscapes associated with paralogous gene clusters and distinct functional compartments. Finally, these annotation data were synthesized to produce observations of gene density and number that accord well with historical estimates. Such a global approach had previously been described only for chromosomes 21 and 22, which together account for 2.2% of the genome. CONCLUSIONS: We estimate that the genome contains 65,000-75,000 transcriptional units, with exon sequences comprising 4%. The creation of a comprehensive gene index requires the synthesis of all available computational and experimental evidence.

Chromosome Mapping↗
PubMed2001

Strain-specific genes of Helicobacter pylori: distribution, function and dynamics.

Whole-genome clustering of the two available genome sequences of Helicobacter pylori strains 26695 and J99 allows the detection of 110 and 52 strain-specific genes, respectively. This set of strain-specific genes was compared with the sets obtained with other computational approaches of direct genome comparison as well as experimental data from microarray analysis. A considerable number of novel function assignments is possible using database-driven sequence annotation, although the function of the majority of the identified genes remains unknown. Using whole-genome clustering, it is also possible to detect species-specific genes by comparing the two H.pylori strains against the genome sequence of Campylobacter jejuni. It is interesting that the majority of strain-specific genes appear to be species specific. Finally, we introduce a novel approach to gene position analysis by employing measures from directional statistics. We show that although the two strains exhibit differences with respect to strain-specific gene distributions, this is due to the extensive genome rearrangements. If these are taken into account, a common pattern for the genome dynamics of the two Helicobacter strains emerges, suggestive of certain spatial constraints that may act as control mechanisms of gene flux.

Amino Acid Sequence↗
PubMed2002

MIPS: a database for genomes and protein sequences.

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

Amino Acid Sequence↗
PubMed2026

Shared genetic architecture of obesity and gastroesophageal reflux disease.

Obesity is identified as a risk factor of gastroesophageal reflux disease (GERD). This study aims to elucidate the shared genetic architecture of obesity-related phenotypes and GERD. Based on the publicly available genome-wide association studies' datasets, this genome-wide pleiotropic association study was conducted with various genetic approaches (including linkage disequilibrium score regression, high-definition likelihood inference for genetic correlations, pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis) sequentially to unravel the genetic associations from single-nucleotide polymorphism to gene levels, and to reveal the underlying shared genetic architecture between obesity-related phenotypes and GERD. This study discovered shared genetic mechanisms between GERD and several obesity-related phenotypes, including arm fat percentage (left), arm fat percentage (right), leg fat percentage (left), leg fat percentage (right), trunk fat percentage, waist-to-hip ratio, and body mass index. Significant genetic correlations were observed by linkage disequilibrium score regression and high-definition likelihood inference for genetic correlations, with multiple associated pleiotropic loci and their mapped genes identified by pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis. Additionally, several brain tissues were identified to be linked to both obesity and GERD by multi-marker analysis of genomic annotation. This research provided strong evidence of genetic correlations and brought novel insights into the underlying genetic connections and shared genetic architectures of obesity and GERD.

Humans↗
PubMed2026

META-DIFF: a k-mer-based pipeline that detects differentially abundant sequences in metagenomics whole genome sequencing.

Traditional case-control metagenomic studies are constrained by their dependence on taxonomic and functional databases. Because annotation occurs before differential analysis, they are limited to known elements and keep function and taxonomy separate. Although binning strategies have emerged to reconstruct genomes and mitigate this issue, they still require an assembly step, preventing the use of all available sequencing data. Here, we introduce META-DIFF, a pipeline based on differentially abundant k-mers independently of any prior annotation. From those k-mers, it reconstructs longer sequences and provides biological context, as well as the best set of unitigs to discriminate between conditions. Across both taxonomy-centric and functionally-centric benchmarks, it showed robust performance and displayed great reproducibility. It also behaved more conservatively than did other univariate methodologies, i.e. it maintained a high precision at the expense of recall, particularly in conditions of low fold-change and limited sequencing depth. The efficacy of META-DIFF was further validated through its application to a real-world colorectal cancer dataset, which produced both confirmatory and novel results compared with those of previous publications. The pipeline is able to exploit all reads and identify differentially abundant elements, including unknown DNA, prior to annotation. With the guidelines provided, META-DIFF provides users with great exploratory power to unravel microbiome changes.

Metagenomics↗
PubMed2001

Intrinsic errors in genome annotation.

Genome sequencing is usually followed by routine annotation of protein function based on the assumption that similar sequences will have similar functions. Here, we introduce a simple calculation to estimate the magnitude of any possible annotation errors. We counted the number of discrepancies in the annotation of well-established sets of similar proteins and extrapolated these values to the pairs of similar sequences used for the annotation of different microbial genomes. We conclude that the number of potential errors in the prediction of detailed functions is higher than is usually believed.

Binding Sites↗
PubMed2003

The Lipase Engineering Database: a navigation and analysis tool for protein families.

The Lipase Engineering Database (LED) (http://www.led.uni-stuttgart.de) integrates information on sequence, structure, and function of lipases, esterases, and related proteins. Sequence data on 806 protein entries are assigned to 38 homologous families, which are grouped into 16 superfamilies with no global sequence similarity between each other. For each family, multisequence alignments are provided with functionally relevant residues annotated. Pre-calculated phylogenetic trees allow navigation inside superfamilies. Experimental structures of 45 proteins are superposed and consistently annotated. The LED has been applied to systematically analyze sequence-structure-function relationships of this vast and diverse enzyme class. It is a useful tool to identify functionally relevant residues apart from the active site residues, and to design mutants with desired substrate specificity.

Amino Acid Sequence↗