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bioRxiv2022

Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor and investigating the immunorelated genes is of great significance. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, a immunoprognosis model was constructed to identify 4 hub genes with moderate predictive values for the prognosis of ccRCC patients. Interestingly, these 4 genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltrate and could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of 3 hub genes were associated with tumor progression (P<0.1). In conclusion, 4 genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

cancer biology↗

bioRxiv2022

ISCB RSG-Spain and highlights from the VIII Spanish Student Symposium in Bioinformatics and Computational Biology in 2021

The Regional Student Group of Spain is recognized by the Student Council and the International Society for Computational Biology. The objective of these institutions is to connect and share useful information among all professionals and students working in the field of bioinformatics and computational biology. In this article, we intend to present and publicize RSG-Spain, the Spanish ISCB regional student group, by relating its recent history of a growing community of students and young professionals and how it helps their development in the field. RSG-Spain, since its creation, has been involved in the organization of events with the aim of gathering bioinformaticians in the country and promoting research and collaboration in the field. Here the VIII Student Symposium held online in 2021 is presented, analyzing the output of the event and showing the main challenges found in its organization.

scientific communication and education↗

bioRxiv2022

Expression profiling of immune-response-genes common in SARS-CoV-1 and influenza A virus disease, viz-a-viz neutropenia disorder, using integrated bioinformatics tools

Viral diseases have proven to be an existential threat to man due to its fatality and its consistent emergence and re-emergence, so the need for novel ideas in combating this menace. Advances in genetic studies has proven to be indispensable in this fight as knowledge of organismal genetic variability has been useful in therapy development, as well as in mounting defense against the treacherous infectious agents. However, there are still fallow grounds needing to be explored in this war which informed this study, with focus on expression profiling of similar immune-responsegenes in SARS-COV-1 and influenza A virus (AIV) in respect to neutropenia (NP), using integrated bioinformatics techniques such as extraction of microarray dataset in the gene expression omnibus (GEO) database, generation of DEGs using GEO2R tool, construction of protein-protein interaction (PPI) network using string and Cytoscape software, Venn diagram analysis and then gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) for enrichment and pathway analysis respectively. Ten genes which includes ELANE, ITGA2B, CXCR1, CSF3R, SPI1, MS4A3, MMP8, CEACAM8, RNASE3, and DEFA4 were identified, with ELANE gene moreover identified as a key gene, which might be responsible in the regulation of immune response during viral infection, based on its characteristic feature in the PPI network.

genetics↗

bioRxiv2022

Bioinformatically predicted emulsifying peptides and potato protein hydrolysate improves the oxidative stability of microencapsulated fish oil

The aim of this study was to investigate the potential of potato proteins and peptides as emulsifiers in the microencapsulation of fish oil by spray-drying. Microcapsules were produced using a potato protein extract, and fractions enriched in patatin and protease inhibitors. Furthermore, bioinformatically predicted emulsifier peptides from abundant potato proteins and a hydrolysate, obtained through targeted proteolysis of the extract, were investigated. During 28 days of storage at 25{degrees}C, peptides and hydrolysate exhibited better emulsifying properties and higher encapsulation efficiencies compared to native proteins and sodium caseinate. Significant differences (p < 0.05) were observed in the peroxide value (PV) and secondary volatile oxidation products between the microcapsules produced with peptides and native proteins. Microcapsules produced with peptides and hydrolysate showed the highest oxidative stability, not exceeding a PV of 10 meq/kg oil, and with concentrations of volatiles below the odor threshold in oil for five of the six studied compounds. These results show the emulsifying potential of potato peptides and hydrolysate for use in microencapsulation of hydrophobic bioactive ingredients such as fish oil.

bioengineering↗

bioRxiv2023

Bioinformatics of cyanophycin metabolism genes and characterization of promiscuous isoaspartyl dipeptidases that catalyze the final step of cyanophycin degradation

Cyanophycin is a bacterial biopolymer used for storage of fixed nitrogen. It is composed of a backbone of L-aspartate residues with L-arginines attached to each of their side chains. Cyanophycin is produced by cyanophycin synthetase 1 (CphA1) using Arg, Asp and ATP, and is degraded in two steps. First, cyanophycinase breaks down the backbone peptide bonds, releasing {beta}-Asp-Arg dipeptides. Then, these dipeptides are broken down into free Asp and Arg by enzymes with isoaspartyl dipeptidase activity. Two bacterial enzymes are known to possess promiscuous isoaspartyl dipeptidase activity: isoaspartyl dipeptidase (IadA) and isoaspartyl aminopeptidase (IaaA). We performed a bioinformatic analysis to investigate whether genes for cyanophycin metabolism enzymes cluster together or are spread around the microbial genomes. Many genomes showed incomplete contingents of known cyanophycin metabolizing genes. Cyanophycin synthetase and cyanophycinase are usually clustered together when recognizable genes for each are found within a genome. Cyanophycinase and isoaspartyl dipeptidase genes typically cluster within genomes lacking cphA1. About one-third of genomes with genes for CphA1, cyanophycinase and IaaA show these genes clustered together, while the proportion is around one-sixth for CphA1, cyanophycinase and IadA. We used X-ray crystallography and biochemical studies to characterize an IadA and an IaaA from two such clusters. The enzymes retained their promiscuous nature, showing that being associated with cyanophycin-related genes did not make them specific for {beta}-Asp-Arg dipeptides derived from cyanophycin degradation.

biochemistry↗

bioRxiv2023

Bioinformatic analysis of the spike protein cleavage sites of coronaviruses in the mammalian order Eulipotyphla

The mammalian order Eulipotyphla, including hedgehogs and shrews, represent a poorly understood reservoir of coronaviruses with zoonotic potential. Here, we carried out a bioinformatic analyses of these viruses based on the viral spike protein--to illustrate the complexity of coronavirus evolutionary history and the diversity of viruses from these host species, with a focus on the presence of possible furin cleavage sites within the spike protein. We found no evidence for cleavage by furin itself; however, certain strains of Wencheng Sm Shrew coronavirus were shown to have a predicted cleavage site for other member of the proprotein convertases, which are furin family members-- suggesting their spillover potential. As the expanding urbanization and the trade of small mammals in the wet markets enhance the wildlife-human interactions, this may increase pathogen spillover risks. Therefore, we should implement broad wild animal surveillance and be vigilant of contact with these small wild mammals in light of one-health perspectives.

microbiology↗

bioRxiv2023

Bioinformatics-Guided Discovery of Biaryl-Tailored Lasso Peptides

Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) that feature an isopeptide bond and a distinct lariat fold. A growing number of secondary modifications have been described that further decorate lasso peptide scaffolds. Using genome mining, we have discovered a pair of lasso peptide biosynthetic gene clusters (BGCs) that include cytochrome P450 genes. Here, we report the structural characterization of two unique examples of (C-N) biaryl-containing lasso peptides. Nocapeptin A, from Nocardia terpenica, is tailored with Trp-Tyr crosslink while longipepetin A, from Longimycelium tulufanense, features Trp-Trp linkage. Besides the unusual bicyclic frame, longipepetin A receives an S-methylation by a new Met methyltransferase resulting in unprecedented sulfonium-bearing RiPP. Our bioinformatic survey revealed P450(s) and further maturating enzyme(s)-containing lasso BGCs awaiting future characterization.

biochemistry↗

bioRxiv2023

Bamboozle: A bioinformatic tool for identification and quantification of intraspecific barcodes

Evolutionary changes in populations of microbes, such as microalgae, cannot be traced using conventional metabarcoding loci as they lack intraspecific resolution. Consequently, selection and competition processes amongst strains of the same species cannot be resolved without elaborate isolation, culturing, and genotyping efforts. Bamboozle, a new bioinformatic tool introduced here, scans a species entire genome and identifies allele-rich barcodes that enable direct identification of different strains from a common population, and a single DNA sample, using amplicon sequencing. We demonstrate its usefulness by identifying hypervariable barcoding loci (<500 bp) from genomic data in two microalgal species, the diploid diatom Skeletonema marinoi, and the haploid chlorophyte Chlamydomonas reinhardtii. Across the genomes, only 26 loci capable of resolving all available strains genotypes were identified, all of which are within protein-coding genes of variable metabolic function. Single nucleotide polymorphisms (SNPs) provided the most reliable genetic markers, and amongst 55 strains of S. marinoi, three 500 bp loci contained, on average, 46 SNPs, 103 unique alleles, and displayed 100% heterozygosity. The prevalence of heterozygosity was identified as a novel opportunity to improve strain quantification and detect false positive artefacts during denoising of amplicon sequences. Finally, we illustrate how metabarcoding of a single genetic locus can be used to track strain abundances of 58 strains of S. marinoi in an artificial selection experiment. As future genomics datasets become available and DNA sequencing technologies develop, Bamboozle has flexible user settings enabling optimal barcodes to be designed for other species and applications.

evolutionary biology↗

bioRxiv2023

Beyond Structural Bioinformatics for Genomics with Dynamics Characterization of an Expanded KRAS Mutational Landscape

ABSTRACTCurrent capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation. Key PointsPlease provide 3 bullet points summarizing the manuscripts contribution to the field (100 characters max per point) 1) We functionally grouped 86 distinct KRAS mutations using MD scores, demonstrating scalability for genomics 2) MD-based groups explain experimental differences and mechanistic information about mutant proteins 3) Demonstrated added functional information from simulations for interpreting human genetic variation

genomics↗

bioRxiv2023

A large-scale bioinformatic study of graspimiditides and structural characterization of albusimiditide

Graspetides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) that exhibits an impressive diversity in patterns of side chain-to-side chain {omega}-ester or {omega}-amide linkages. Recent studies have uncovered a significant portion of graspetides to contain an additional post-translational modification involving aspartimidylation catalyzed by an O-methyltransferase, predominantly found in the genomes of Actinomycetota. Here, we present a comprehensive bioinformatic analysis focused on graspetides harboring aspartimide for which we propose the name graspimiditides. From Protein BLAST results of 5,000 methyltransferase sequences, we identified 962 unique putative graspimiditides, which we further classified into eight main clusters based on sequence similarity along with several smaller clusters and singletons. The previously studied graspimiditides, fuscimiditide and amycolimiditide, are identified in this analysis; fuscimiditide is a singleton while amycolimiditide is in the fifth largest cluster. Cluster 1, by far the largest cluster, contains 641 members, encoded almost exclusively in the Streptomyces genus. To characterize an example of a graspimiditide in Cluster 1, we conducted experimental studies on the peptide from Streptomyces albus J1074, which we named albusimiditide. By tandem mass spectrometry, hydrazinolysis, and amino acid substitution experiments, we elucidated the structure of albusimiditide to be a large tetracyclic peptide with four {omega}-ester linkages generating a stem-loop structure with one aspartimide. The ester crosslinks form 22-, 46-, 22-, and 44-atom macrocycles, last of which, the loop, contains the enzymatically installed aspartimide. Further in vitro experiments revealed that the aspartimide hydrolyzes in a 3:1 ratio of isoaspartate to aspartate residues. Overall, this study offers a comprehensive insight into the diversity and structural features of graspimiditides, paving the way for future investigations of this unique class of natural product. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/545981v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@bd68f2org.highwire.dtl.DTLVardef@1350705org.highwire.dtl.DTLVardef@5ff593org.highwire.dtl.DTLVardef@1f3c4a9_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2023

Genetic Association of SLC47A1 Gene Variant (17:19571562C >T) and Bioinformatics Analyses of MATE1 Protein in Chronic Kidney Disease Patients of Pakistani Origin

Chronic Kidney Disease (CKD) is a serious human threat worldwide which is associated with a number of environmental, clinical and genetic factors that affect serum creatinine (SCr) and glomerular filtration rate (eGFR). One of the best biochemical and genetic markers to study renal functioning is SLC47A1 which encodes MATE1 protein and can be a promising target to study its genetic causes, subject protein is a cationic transporter involved in the regulation of creatinine and urea levels in the blood which may cause toxicity and renal disorders. Hence, the current study focused to interrogate the putative association of SLC47A1 gene variant (17:19571562C>T) in 75 individuals (cases=50, controls=25) of Pakistani origin using ARMS-PCR genotyping, out of which 10 were found heterozygous, 57 homozygous wild-type and 08 homozygous mutants. PLINK data analysis toolset was used which manifested that sampled population complies the Hardy-Weinberg Equilibrium by {chi}2 (2, N = 75) =, p = 4.756 x 10-005, similarly the Chi-square statistics p = 0.03274 along with odds-ratio of 3.244 showing a significant genotypic association with the subject phenotype indicating that mutant allele is almost 3-times more prevalent in cases vs control cohorts with an alternative allele frequency of 0.22 and 0.08 in CKD patients and healthy controls respectively. Besides, few of the bioinformatics tools i.e., ProtParam, PsiPred, PDB-RCSB, Motif Scan, CTU-TMHMM-2.0, ScanProsite, PRmePRed, GPS PAIL2.0, NetOGlyc4.0, NetPhos3, SIFT, Polyphen-2 and STRING were also used for the prediction of different parameters of both the wild-type and mutant MATE1 proteins such as physiochemical properties, secondary structure prediction, 3-D structure, protein conserved domains, transmembrane structures, posttranslational modifications, SNP prediction/amino acid substitution, pathogenicity and protein-protein interaction networks. Current preliminary genotyping provided an insight into the association of the aforementioned genetic variant with CKD to estimate the genetic risks along with prediction of its functional effects in the system biology context which may be considered for developing new targeted drugs along with genetic counselling initiatives to evade this peril in the population.

genetics↗

bioRxiv2023

Genome-wide Bioinformatics Analysis of Human Protease Specificity Identified Potential Cathepsin L Cleavage Site at K790 Position of the SARS-CoV-2 Spike Glycoprotein

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) primarily enters the cell by binding the viruss spike (S) glycoprotein to the angiotensin-converting enzyme 2 (ACE2) receptor on the cell surface, followed by proteolytic cleavage by host proteases. Studies have identified furin and TMPRSS2 proteases in priming and triggering cleavages of the S glycoprotein, converting it into a fusion-competent form and initiating membrane fusion, respectively. Alternatively, SARS-CoV-2 can enter the cell through the endocytic pathway, where activation is triggered by lysosomal cathepsin L. However, other proteases are also suspected to be involved in both entry routes. In this study, we conducted a genome-wide bioinformatics analysis to explore the capacity of human proteases in hydrolyzing peptide bonds of the S glycoprotein. Predictive models of sequence specificity for 169 human proteases were constructed and applied to the S glycoprotein together with the method for predicting structural susceptibility to proteolysis of protein regions. After validating our approach on extensively studied S2 and S1/S2 cleavage sites, we applied our method to each peptide bond of the S glycoprotein across all 169 proteases. Our results indicate that various members of the PCSK, TTSP, and kallikrein families, as well as specific coagulation factors, are capable of cleaving S2 or S1/S2 sites. We have also identified a potential cleavage site of cathepsin L at the K790 position within the S2 loop. Structural analysis suggests that cleavage of this site induces conformational changes similar to the cleavage at the R815 (S2) position, leading to the exposure of the fusion peptide and subsequent fusion with the membrane. Other potential cleavage sites and the influence of mutations in common SARS-CoV-2 variants on proteolytic efficiency are discussed.

genomics↗

bioRxiv2023

Rapid and cost-effective epitope mapping using PURE ribosome display coupled with next-generation sequencing and bioinformatics

A novel, efficient and cost-effective approach for epitope identification of an antibody has been developed using a ribosome display platform. This platform, known as PURE ribosome display, utilizes an Escherichia coli-based reconstituted cell-free protein synthesis system (PURE system). It stabilizes the mRNA-ribosome-peptide complex via a ribosome-arrest peptide sequence. This system was complemented by next-generation sequencing (NGS) and an algorithm for analyzing binding epitopes. To showcase the effectiveness of this method, selection conditions were refined using the anti-PA tag monoclonal antibody with the PA tag peptide as a model. Subsequently, a random peptide library was constructed using 10 NNK triplet oligonucleotides via the PURE ribosome display. The resulting random peptide library-ribosome-mRNA complex was selected using a commercially available anti-HA (YPYDVPDYA) tag monoclonal antibody, followed by NGS and bioinformatic analysis. Our approach successfully identified the "DVPDY" sequence as an epitope within the hemagglutinin amino acid sequence, which was then experimentally validated. This platform provided a valuable tool for investigating continuous epitopes in antibodies.

bioengineering↗

bioRxiv2023

ChEC-seq2: an improved Chromatin Endogenous Cleavage sequencing method and bioinformatic analysis pipeline for mapping in vivo protein-DNA interactions

Defining the in vivo DNA binding specificity of transcription factors (TFs) has relied nearly exclusively on chromatin immunoprecipitation (ChIP). While ChIP reveals TF binding patterns, its resolution is low. Higher resolution methods employing nucleases such as ChIP-exo, chromatin endogenous cleavage (ChEC-seq) and CUT&RUN resolve both TF occupancy and binding site protection. ChEC-seq, in which an endogenous TF is fused to micrococcal nuclease, requires neither fixation nor antibodies. However, the specificity of DNA cleavage during ChEC has been suggested to be lower than the specificity of the peaks identified by ChIP or ChIP-exo, perhaps reflecting non-specific binding of transcription factors to DNA. We have simplified the ChEC-seq protocol to minimize nuclease digestion while increasing the yield of cleaved DNA. ChEC-seq2 cleavage patterns were highly reproducible between replicates and with published ChEC-seq data. Combined with DoubleChEC, a new bioinformatic pipeline that removes non-specific cleavage sites, ChEC-seq2 identified high-confidence cleavage sites for three different yeast TFs that are strongly enriched for their known binding sites and adjacent to known target genes.

genomics↗

bioRxiv2023

A novel bioinformatics pipeline for the identification of immune inhibitory receptors as potential therapeutic targets

Blocking inhibitory receptors like PD-1 and CTLA-4 has revolutionized cancer treatment in recent years. However, despite major successes in melanoma and lung cancer, the majority of cancer types are not responsive to these immunotherapies. As such, there is an ongoing need for the identification of novel inhibitory receptors as drug targets. Most inhibitory receptors signal via immunoreceptor tyrosine-based inhibitory motifs (ITIMs) and previous studies have estimated that our genome contains over 1600 ITIM- bearing transmembrane proteins. However, further testing and development of this large number of candidates requires increased understanding of their expression patterns and likelihood to function as inhibitory receptor. To assist in the selection of novel inhibitory receptor as therapeutic targets, we designed a novel bioinformatics pipeline integrating machine learning-guided structural predictions and sequence-based likelihood models to identify 51 known and 390 putative inhibitory receptors. Using publicly available transcriptomics data of immune cells, we determined the expression of these novel inhibitory receptors, and classified them into previously proposed functional categories. Known and putative inhibitory receptors were expressed across a wide variety of immune cells, and we found cell type-specific patterns in expression of these receptors. We used our pipeline to study inhibitory receptor expression patterns in single cell transcriptomics data of tumour infiltrating T cells. We determined that putative immune inhibitory receptors were expressed differentially in CD4+ and CD8+ T cell subsets, including exhausted CD8+ T cells and CD4+ memory T cells, which could allow for subset-specific targeting. In conclusion, we present an inhibitory receptor pipeline that identifies 51 known and 390 novel inhibitory receptors. This pipeline will support future drug target selection across diseases where therapeutic targeting of immune inhibitory receptors is warranted.

immunology↗

bioRxiv2024

IDENTIFICATION OF KEY GENES ASSOCIATED WITH PCOS (POLYCYSTIC OVARIAN SYNDROME) AND ENDOMETRIAL/OVARIAN CANCER THROUGH BIOINFORMATICS

BackgroundPCOS, a common endocrine disorder, is linked to increased risks of endometrial cancer (EC) and ovarian cancer (OC). Our study utilizes bioinformatics analysis to identify shared gene signatures and elucidate biological processes between EC/OC and PCOS. Materials and MethodsGene expression profiles for PCOS (GSE199225), endometrial cancer (GSE215413), and ovarian cancer (GSE174670) were obtained from the GEO database. Hub genes were identified through functional enrichment analysis and protein-protein interaction. Drug identification analyses were employed to find drugs targeting the hub genes. ResultKey hub genes linking PCOS and EC includes RECQL4, RAD54L, ATR, CHTF18, WDHD1, CDT1, PLK1, PKMYT1, RAD18, and RPL3; for PCOS and OC, they include HMOX1, TXNRD1, NQO1, GCLC, GSTP1, PRDX1, SOD1, GPX3, BOP1, and BYSL. Gene Ontology analysis revealed DNA Metabolic Processes in PCOS and EC, while in PCOS and OC, it identified the Removal of Superoxide Radicals. KEGG Pathway analysis highlighted Cell cycle in PCOS and EC and Hepatocellular carcinoma in PCOS and OC. Potential drugs for PCOS and EC include quercetin, calcitriol, and testosterone; for PCOS and OC, eugenol and 1-chloro-2,4-dinitrobenzene are identified. ConclusionThese findings offer insights into potential therapeutic targets and pathways linking PCOS with EC and OC, enhancing our understanding of the molecular mechanisms involved in these associations.

cancer biology↗

bioRxiv2024

Transcriptome sequencing and bioinformatics analysis of kidney tissue in a tree shrew model of calcium oxalate nephrolithiasis

BackgroundKidney stones, predominantly composed of calcium oxalate, are a prevalent and recurrent urological condition. Given their high incidence and recurrence rates, understanding their pathogenesis and identifying effective treatment strategies are imperative. MethodsIn this study, we established a calcium oxalate nephrolithiasis model using tree shrews, a primate-like animal species. When compared to commonly used rodent models (rats and mice), the tree shrew model demonstrated superior reproducibility and relevance. And leveraging transcriptome sequencing and comprehensive bioinformatics analysis. Resultswe identified 1,927 differentially expressed genes, including 1,450 upregulated and 476 downregulated genes. Furthermore, we annotated these genes to 41 KEGG enriched pathways and 1,413 GO enrichments, encompassing 1276 Biological Processes, 72 Cellular Components, and Molecular Functions. Notably, we prioritized the top 50 core genes that could potentially underlie the pathogenesis of calcium oxalate nephrolithiasis. ConclusionsOur findings establish the tree shrew as a relevant model for studying kidney stone formation and provide valuable insights into the underlying molecular mechanisms. These insights hold promise for the development of novel therapeutic strategies to address this significant health burden.

genomics↗

bioRxiv2024

GALEON: A Comprehensive Bioinformatic Tool to Analyse and Visualise Gene Clusters in Complete Genomes

MotivationGene clusters, defined as a set of genes encoding functionally-related proteins, are abundant in eukaryotic genomes. Despite the increasing availability of chromosome-level genomes, the comprehensive analysis of gene family evolution remains largely unexplored, particularly for large and highly dynamic gene families or those including very recent family members. These challenges stem from limitations in genome assembly contiguity, particularly in repetitive regions such as large gene clusters. Recent advancements in sequencing technology, such as long reads and chromatin contact mapping, hold promise in addressing these challenges. ResultsTo facilitate the identification, analysis, and visualisation of physically clustered gene family members within chromosome-level genomes, we introduce GALEON, a user-friendly bioinformatic tool. GALEON identifies gene clusters by studying the spatial distribution of pairwise physical distances among gene family members along with the genome-wide gene density. The pipeline also enables the simultaneous analysis and comparison of two gene families, and allows the exploration of the relationship between physical and evolutionary distances. This tool offers a novel approach for studying the origin and evolution of gene families. Availability and ImplementationGALEON is freely available from http://www.ub.edu/softevol/galeon, and from https://github.com/molevol-ub/galeon

genomics↗