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PubMed2002

Using genomic resources to guide research directions. The arabinogalactan protein gene family as a test case.

Arabinogalactan proteins (AGPs) are extracellular hydroxyproline-rich proteoglycans implicated in plant growth and development. The protein backbones of AGPs are rich in proline/hydroxyproline, serine, alanine, and threonine. Most family members have less than 40% similarity; therefore, finding family members using Basic Local Alignment Search Tool searches is difficult. As part of our systematic analysis of AGP function in Arabidopsis, we wanted to make sure that we had identified most of the members of the gene family. We used the biased amino acid composition of AGPs to identify AGPs and arabinogalactan (AG) peptides in the Arabidopsis genome. Different criteria were used to identify the fasciclin-like AGPs. In total, we have identified 13 classical AGPs, 10 AG-peptides, three basic AGPs that include a short lysine-rich region, and 21 fasciclin-like AGPs. To streamline the analysis of genomic resources to assist in the planning of targeted experimental approaches, we have adopted a flow chart to maximize the information that can be obtained about each gene. One of the key steps is the reformatting of the Arabidopsis Functional Genomics Consortium microarray data. This customized software program makes it possible to view the ratio data for all Arabidopsis Functional Genomics Consortium experiments and as many genes as desired in a single spreadsheet. The results for reciprocal experiments are grouped to simplify analysis and candidate AGPs involved in development or biotic and abiotic stress responses are readily identified. The microarray data support the suggestion that different AGPs have different functions.

Acids↗
PubMed1999

Why FRET over genomics?

Genetic information is being uncovered quickly and in vast amounts through the largely automated sequencing of genomes from all kinds of organisms. As this information becomes available, enormous challenges are emerging on three levels: first, functions will have to be assigned to individual gene products; second, factors that influence the expression level of these gene products will have to be identified; and third, allelic variants that act alone or in combination to give rise to complex traits will have to be characterized. Because of the sheer size of genomes, methods that can streamline or automate these processes are highly desirable. Fluorescence is an attractive readout for such high-throughput tasks because of the availability of equipment designed to detect light-emitting compounds with great speed and high capacity. The following is an overview of the achievements and potential of fluorescence resonance energy transfer (FRET) as applied in three areas of genomics: the identification of single-nucleotide polymorphisms, the detection of protein-protein interactions, and the genomewide analysis of regulatory sequences.

Animals↗
PubMed1998

High-throughput robotic system for sequencing of microbial genomes.

A high-throughput robotic workstation system was used for double-stranded plasmid DNA template preparation and sequencing reaction setup to streamline the sequencing process in genome projects. All 96-well miniprep kits that were tested provided high quality plasmid DNA suitable for fluorescent DNA sequencing. After quantitation in a 96-well UV spectrophotometer, the plasmid DNA was used as template to automatically set up sequencing reactions. The setup was controlled by spread sheets that were imported into the robotic system. We utilized this integrated system to prepare all necessary shotgun templates for our contributions to a number of large-scale genome projects as well as a full-length cDNA sequencing project.

Arabidopsis↗
PubMed2026

A streamlined protocol for small-scale protoplast generation and CRISPR/Cpf1-mediated genome editing in Fusarium oxysporum.

Fusarium oxysporum is a significant threat to agriculture and One Health, requiring advanced molecular tools for functional genomic analyses and biological control agent development. Existing gene-editing methods are hampered by costly protoplast preparation protocols and by CRISPR-Cas9 limitations, such as restricted protospacer adjacent motif (PAM) sequences and complex guide RNA requirements. We engineered an efficient CRISPR/Cpf1 system that overcomes these issues through three main innovations: small-scale protoplast generation using filter column-based methods that greatly reduce enzyme consumption while simplifying workflows, a CRISPR/Cpf1 system with shorter guide RNA design and staggered DNA cleavage to promote homologous recombination, and minimal homology arm strategies that significantly decrease cloning complexity. Extensive validation confirms successful gene targeting with molecular verification and functional analysis via standardized pathogenicity assays. This integrated platform offers affordable, accessible tools for systematic F. oxysporum research, enhancing fundamental understanding of plant-pathogen interactions and supporting high-throughput screening vital for agricultural biotechnology and biological agent development.

CRISPR/Cpf1↗
PubMed2026

Single-nucleotide transcription start sites profiling via Nascent Strand-Specific RNA sequencing uncovers IFN-γ-induced promoter dynamics.

Transcriptional regulation is a highly dynamic process in which nascent RNAs provide the most immediate readout of transcriptional activity. Precise mapping of transcription start sites (TSSs) is therefore critical for understanding promoter architecture and gene regulation, yet remains technically challenging. Here, we introduce Nascent Strand-Specific RNA sequencing (NSS-seq), a robust and streamlined method for genome-wide profiling of the capped 5' ends of nascent RNAs. By directly capturing transcription initiation events, NSS-seq overcomes the temporal delay inherent to conventional RNA-seq and enables time-resolved interrogation of transcriptional dynamics. Applied to interferon-γ (IFN-γ)-stimulation, NSS-seq uncovers previously unrecognized IFN-γ-responsive genes and transient transcription factor activation patterns underlying interferon-mediated tumor-suppressive functions. Together, NSS-seq provides a cost-effective and technically accessible platform for dissecting promoter-level regulatory dynamics during cellular responses.

Promoter Regions, Genetic↗
PubMed2005

Progress in modeling of protein structures and interactions.

The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.

Computer Simulation↗
PubMed2026

CREAT: A CRISPR-Based Genome Trimming Strategy for Systematic Identification of Dispensable Regions and Rapid Genome Reduction.

The construction of minimal-genome microbes offers an ideal platform for understanding fundamental biological processes and synthetic biology, yet the research is hindered by incomplete lists of essential genes in microbes and by multiple rounds of genome trimming with a trial-and-error nature. To address this, we introduce CREAT (CRISPR-based genome trimming with a multi-homology-arm template)-a streamlined approach that integrates CRISPR-targeted genome cleavage and homology arm walking to classify essential from non-essential genomic subregions, thus providing the basis for predicting essential genes in a given organism. These essential genes were then assembled into synthetic gene cassettes for one-step replacement of the targeted non-deletable genomic regions for further genome trimming. Eight consecutive rounds of CREAT genome trimming achieved a 20.8% reduction in genome size in Saccharolobus islandicus. Furthermore, Cas9-based CREAT genome trimming was developed for Bacillus subtilis and Escherichia coli, with efficiency greatly enhanced by the λ-Red recombinase in the latter. Together, this iterative application of CREAT provides a scalable and generally applicable strategy for rapidly constructing minimal genomes across diverse microorganisms.

CRISPR-Cas Systems↗
PubMed2006

Approaches to lipid metabolism gene identification and characterization in the postgenomic era.

The availability of genomic resources has already had a tremendous impact on biomedical research. In this review, we describe how whole genome sequence and high-throughput functional genomics projects have facilitated the identification and characterization of important genes in lipid metabolism and disease. We review key approaches and lipid genes identified in the first years of this century and discuss how genomic resources are likely to streamline gene identification and functional characterization in the future.

Animals↗
PubMed2003

Sequence-based alignment of sorghum chromosome 3 and rice chromosome 1 reveals extensive conservation of gene order and one major chromosomal rearrangement.

The completed rice genome sequence will accelerate progress on the identification and functional classification of biologically important genes and serve as an invaluable resource for the comparative analysis of grass genomes. In this study, methods were developed for sequence-based alignment of sorghum and rice chromosomes and for refining the sorghum genetic/physical map based on the rice genome sequence. A framework of 135 BAC contigs spanning approximately 33 Mbp was anchored to sorghum chromosome 3. A limited number of sequences were collected from 118 of the BACs and subjected to BLASTX analysis to identify putative genes and BLASTN analysis to identify sequence matches to the rice genome. Extensive conservation of gene content and order between sorghum chromosome 3 and the homeologous rice chromosome 1 was observed. One large-scale rearrangement was detected involving the inversion of an approximately 59 cM block of the short arm of sorghum chromosome 3. Several small-scale changes in gene collinearity were detected, indicating that single genes and/or small clusters of genes have moved since the divergence of sorghum and rice. Additionally, the alignment of the sorghum physical map to the rice genome sequence allowed sequence-assisted assembly of an approximately 1.6 Mbp sorghum BAC contig. This streamlined approach to high-resolution genome alignment and map building will yield important information about the relationships between rice and sorghum genes and genomic segments and ultimately enhance our understanding of cereal genome structure and evolution.

Base Sequence↗
PubMed2006

PET-Tool: a software suite for comprehensive processing and managing of Paired-End diTag (PET) sequence data.

BACKGROUND: We recently developed the Paired End diTag (PET) strategy for efficient characterization of mammalian transcriptomes and genomes. The paired end nature of short PET sequences derived from long DNA fragments raised a new set of bioinformatics challenges, including how to extract PETs from raw sequence reads, and correctly yet efficiently map PETs to reference genome sequences. To accommodate and streamline data analysis of the large volume PET sequences generated from each PET experiment, an automated PET data process pipeline is desirable. RESULTS: We designed an integrated computation program package, PET-Tool, to automatically process PET sequences and map them to the genome sequences. The Tool was implemented as a web-based application composed of four modules: the Extractor module for PET extraction; the Examiner module for analytic evaluation of PET sequence quality; the Mapper module for locating PET sequences in the genome sequences; and the Project Manager module for data organization. The performance of PET-Tool was evaluated through the analyses of 2.7 million PET sequences. It was demonstrated that PET-Tool is accurate and efficient in extracting PET sequences and removing artifacts from large volume dataset. Using optimized mapping criteria, over 70% of quality PET sequences were mapped specifically to the genome sequences. With a 2.4 GHz LINUX machine, it takes approximately six hours to process one million PETs from extraction to mapping. CONCLUSION: The speed, accuracy, and comprehensiveness have proved that PET-Tool is an important and useful component in PET experiments, and can be extended to accommodate other related analyses of paired-end sequences. The Tool also provides user-friendly functions for data quality check and system for multi-layer data management.

Animals↗
PubMed2006

Engineered bacteriophage-defence systems in bioprocessing.

Bacteriophages (phages) have the potential to interfere with any industry that produces bacteria as an end product or uses them as biocatalysts in the production of fermented products or bioactive molecules. Using microorganisms that drive food bioprocesses as an example, this review will describe a set of genetic tools that are useful in the engineering of customized phage-defence systems. Special focus will be given to the power of comparative genomics as a means of streamlining target selection, providing more widespread phage protection, and increasing the longevity of these industrially important bacteria in the bioprocessing environment.

Bacteria↗
PubMed2026

ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data.

MOTIVATION: Chemical genomics is a powerful high-throughput approach to systematically link phenotypes to genotypes. However, the vast datasets generated remain challenging to explore due to the lack of integrated, interactive tools for visualization and analysis. Existing workflows often require multiple independent software tools, limiting data accessibility and collaboration. Therefore, we created a user-friendly platform that enables efficient exploration and sharing of chemical genomics data. RESULTS: We developed ChemGenXplore, a web-based Shiny application designed to streamline the visualization and analysis of chemical genomic screens. It offers two primary functionalities: one for exploring pre-implemented datasets and another for analysing user-uploaded datasets. ChemGenXplore enables users to visualize phenotypic profiles, assess gene-gene and condition-condition correlations, perform GO and KEGG enrichment analysis, and generate customizable, interactive heatmaps. To further support collaborative research, ChemGenXplore also facilitates the comparative analysis of chemical genomic and other omics datasets. By consolidating these features into a single interactive and accessible tool, ChemGenXplore facilitates data sharing, enhances reproducibility, and promotes collaboration within the research community. AVAILABILITY AND IMPLEMENTATION: ChemGenXplore is freely accessible as a web application at https://chemgenxplore.kaust.edu.sa/. Source code and documentation, including instructions for local installation, are provided on GitHub (https://github.com/Hudaahmadd/ChemGenXplore). A Docker image is also available on DockerHub (https://hub.docker.com/r/hudaahmad/chemgenxplore) to ensure reproducibility and simplify installation.

Software↗
PubMed2004

Arabidopsis to rice. Applying knowledge from a weed to enhance our understanding of a crop species.

Although Arabidopsis is well established as the premiere model species in plant biology, rice (Oryza sativa) is moving up fast as the second-best model organism. In addition to the availability of large sets of genetic, molecular, and genomic resources, two features make rice attractive as a model species: it represents the taxonomically distinct monocots and is a crop species. Plant structural genomics was pioneered on a genome-scale in Arabidopsis and the lessons learned from these efforts were not lost on rice. Indeed, the sequence and annotation of the rice genome has been greatly accelerated by method improvements made in Arabidopsis. For example, the value of full-length cDNA clones and deep expressed sequence tag resources, obtained in Arabidopsis primarily after release of the complete genome, has been recognized by the rice genomics community. For rice >250,000 expressed sequence tags and 28,000 full-length cDNA sequences are available prior to the completion of the genome sequence. With respect to tools for Arabidopsis functional genomics, deep sequence-tagged lines, inexpensive spotted oligonucleotide arrays, and a near-complete whole genome Affymetrix array are publicly available. The development of similar functional genomics resources for rice is in progress that for the most part has been more streamlined based on lessons learned from Arabidopsis. Genomic resource development has been essential to set the stage for hypothesis-driven research, and Arabidopsis continues to provide paradigms for testing in rice to assess function across taxonomic divisions and in a crop species.

Arabidopsis↗
PubMed2025

insilicoSV: a flexible grammar-based framework for structural variant simulation and placement.

SUMMARY: Structural variants (SVs) are key drivers of genetic variation and disease in the genome. Their discovery remains challenging, however, in large part due to the scarcity of validated SV callsets and comprehensive benchmarks, which are essential for method development and evaluation. The growing number of data-driven learning-based approaches for SV discovery, in particular, requires large, diverse, and well-balanced training datasets to achieve reliable performance. To address this need, SV simulation has served as a key tool for assessing method performance and training SV models. However, existing SV simulators only support a fixed and limited set of SV classes and do not provide fine-grained control over the placement of SVs within specific contexts of the genome. Here we present insilicoSV, a versatile framework for SV simulation, which models SVs using a simple and flexible grammar, allowing users to easily define standard and custom arbitrary genome rearrangements, as well as encode genome placement constraints. This design allows insilicoSV to naturally support new and bespoke SV types, such as the complex rearrangements of cancer genomes. In addition to grammar-based modeling, insilicoSV provides built-in support for 26 predefined SV types, placement of user-provided SVs, small variant simulation, streamlined workflows for the simulation of genome evolution and genome mixtures, read simulation, alignment, and visualization. These features enable the creation of comprehensive genomic datasets for a variety of downstream applications, such as in-depth benchmarking of alignment and variant calling methods, as well as training of data-driven learning-based approaches for SV detection. AVAILABILITY AND IMPLEMENTATION: insilicoSV is available under the MIT license at https://github.com/PopicLab/insilicoSV and https://doi.org/10.5281/zenodo.17402009.

Software↗
PubMed1990

Differential intron loss and endosymbiotic transfer of chloroplast glyceraldehyde-3-phosphate dehydrogenase genes to the nucleus.

Chloroplast glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is composed of two different subunits, GAPA and GAPB, which are encoded in the nucleus by two related genes of eubacterial origin. In the present work the genes encoding chloroplast GAPA and GAPB from pea have been cloned and sequenced. The gene for GAPB is split by eight introns. Two introns interrupt the region encoding the transit peptide and six are found within the region encoding the mature subunit, four of which are in identical or similar positions relative to genes for cytosolic GAPDH of eukaryotic organisms. As opposed to this, the gene encoding pea GAPA has only two introns in the region encoding the mature subunit. These findings strongly support the "intron early" hypothesis and suggest that the low number of introns in the gene for chloroplast GAPA is due to differential loss of introns during the streamlining period of the chloroplast genome following the GAPB/GAPA separation. We deduce from this that eubacteria and chloroplasts contained GT-AG introns until relatively recently and that the duplication event leading to the genes encoding GAPB and GAPA and their respective transit peptides occurred in the chloroplast progenitor prior to the successive transfer and functional reintegration of these genes into the nuclear environment. These conclusions imply that GAPA/GAPB transit peptides are of eubacterial origin.

Amino Acid Sequence↗
PubMed2004

Genome reduction in prokaryotic obligatory intracellular parasites of humans: a comparative analysis.

Obligatory intracellular parasites have undergone significant genome reduction by gene loss over time in the context of their obligate associations with the host. The flux, streamlining and elimination of genes in these genomes constitute a selective and ongoing process. Comparative analyses of five completely sequenced obligatory intracellular parasite genomes reveal that these genomes display marked similarities in patterns of protein length and frequency distribution, with substantial sharing of a 'backbone genome'. From category distribution based on the database of cluster of orthologous groups of proteins (COG), it is clear that habitat is a major factor contributing to genome reduction. It is also observed that, in all five obligatory intracellular parasites, the reduction in number of genes/proteins is greater for proteins with lengths of 200-600 amino acids. These comparative analyses highlight that gene loss is function-dependent, but is independent of protein length. These comparisons enhance our knowledge of the forces that drive the extreme specialization of the bacteria and their association with the host.

Bacterial Proteins↗
PubMed1998

The evolutionary relationships between the two bacteria Escherichia coli and Haemophilus influenzae and their putative last common ancestor.

We have tried to approach the nature of the last common ancestor to Haemophilus influenzae and Escherichia coli and to determine how each bacterium could have diverged from this putative organism. The approach used was exhaustive analysis of the homologous proteins coded by genes present in these bacteria, using as criteria for sequence relatedness an alignment of at least 80 amino acid residues and a PAM distance (number of accepted point mutations per 100 residues separating two sequences) below 250. Evolutionarily significant similarities were found between 1,345 H. influenzae proteins (85% of the total genome) and 3,058 E. coli. proteins (75% of the total genome), many of them belonging to families of various sizes (from 666 doublets to 35 large groups of more than 10 members). Nearly all the genes found by this approach to be duplicated in both bacteria were already duplicated in their last common ancestor. This was deduced from (1) the comparison of the respective distributions of evolutionary distances between orthologs (genes separated only by speciation events) and paralogs (genes duplicated in the same genome) and (2) the analysis of the phylogenetic trees reconstructed for each family of paralogs containing at least two members belonging to each bacterium. The distributions of the different categories of homologs show a significant loss of paralogous genes in H. influenzae (reduction proportional to the genome size), of many sequences which are still present in one copy in E. coli, and of some entire gene families. Phylogenetic trees also confirmed this recent loss of paralogous genes in H. influenzae. Thus, the genome size of the last common ancestor of these two bacteria would have been close to that of present-day E. coli, and the evolution of H. influenzae toward a parasitic life led to an important decrease in its genome size by some mechanism of streamlining. During this recent evolution, the memory of the gene order present in the last common ancestor has been blurred, but a few short conserved chromosomal fragments can still be detected in present-day E. coli and H. influenzae.

Bacterial Proteins↗
PubMed2026

An open-source clinical bioinformatics pipeline for real-world NGS implementation: translating genomic variants into actionable treatment strategies in oncology.

BACKGROUND: Next-Generation Sequencing (NGS) has become a cornerstone technology in clinical practice, yet its adoption presents significant challenges. Physicians and oncologists must manage vast amounts of genome-scale data and transform it into actionable insights for complex decision-making. While commercial systems exist to synthesize data from NGS experiments into clinical reports, many are hindered by limitations such as closed-source designs that restrict transparency and customization. Additionally, some fail to leverage publicly available genomic databases, missing opportunities to integrate valuable external data. Furthermore, the rigidity of many tools in accommodating diverse NGS panels limits their applicability across varied clinical scenarios. METHODS: To address these limitations, we developed OncoReport, an open-source tool that generates comprehensive reports from NGS analyses. By integrating publicly accessible databases, OncoReport provides a robust, user-friendly environment equipped with essential tools for NGS analysis. This design aims to enhance data interpretation and support informed clinical decision-making. RESULTS: Rigorous testing has demonstrated OncoReport’s effectiveness in producing detailed, actionable reports that are clear and easy to use. By automating key aspects of the workflow, the tool significantly reduces manual effort and expedites the synthesis and interpretation of NGS results, making genomic insights more accessible to clinicians. CONCLUSION: OncoReport offers a transparent, flexible, and efficient framework for clinicians to analyze and apply genomic data in patient care. By streamlining workflows and leveraging open-source principles, it empowers healthcare professionals to make informed, data-driven decisions. OncoReport is freely available at https://oncoreport.atlas.dmi.unict.it, with source code and issue tracking on GitHub: https://github.com/knowmics-lab/oncoreport .

Humans↗