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Molecular processes during fat cell development revealed by gene expression profiling and functional annotation.

BACKGROUND: Large-scale transcription profiling of cell models and model organisms can identify novel molecular components involved in fat cell development. Detailed characterization of the sequences of identified gene products has not been done and global mechanisms have not been investigated. We evaluated the extent to which molecular processes can be revealed by expression profiling and functional annotation of genes that are differentially expressed during fat cell development. RESULTS: Mouse microarrays with more than 27,000 elements were developed, and transcriptional profiles of 3T3-L1 cells (pre-adipocyte cells) were monitored during differentiation. In total, 780 differentially expressed expressed sequence tags (ESTs) were subjected to in-depth bioinformatics analyses. The analysis of 3'-untranslated region sequences from 395 ESTs showed that 71% of the differentially expressed genes could be regulated by microRNAs. A molecular atlas of fat cell development was then constructed by de novo functional annotation on a sequence segment/domain-wise basis of 659 protein sequences, and subsequent mapping onto known pathways, possible cellular roles, and subcellular localizations. Key enzymes in 27 out of 36 investigated metabolic pathways were regulated at the transcriptional level, typically at the rate-limiting steps in these pathways. Also, coexpressed genes rarely shared consensus transcription-factor binding sites, and were typically not clustered in adjacent chromosomal regions, but were instead widely dispersed throughout the genome. CONCLUSIONS: Large-scale transcription profiling in conjunction with sophisticated bioinformatics analyses can provide not only a list of novel players in a particular setting but also a global view on biological processes and molecular networks.

3T3-L1 Cells↗

Screening and identification of the ncRNA-mRNA regulatory network associated with DNA methylation in goose embryonic myoblasts.

BACKGROUND: Local goose breeds Shitou and Wuzong exhibit distinct growth rates, implying divergent embryonic muscle development. This study used embryonic myoblasts from the Magang goose, an established model with superior growth traits, to explore the underlying common regulatory mechanisms. Extending our previous findings that 5-AZA (DNA methylation inhibitor) and BC339 (DNA hydroxylation inhibitor) oppositely affect myoblast proliferation and differentiation, we performed whole-transcriptome sequencing on inhibitor-treated goose embryonic myoblasts. This aimed to identify DNA methylation-mediated ncRNA-mRNA networks governing myoblast fate, with key interactions being functionally validated. RESULT: 5-AZA significantly promotes cell proliferation and differentiation by inhibiting DNA methyltransferase activity and reducing DNA methylation levels, whereas BC339 significantly suppresses cell proliferation and differentiation by inhibiting demethylation and increasing DNA methylation levels. Specifically, we identified 6,309 mRNAs, 579 lncRNAs, 194 miRNAs, and 825 circRNAs that were differentially expressed in response to 5-AZA and BC339 treatment. Based on GO and KEGG enrichment analyses, differentially expressed genes related to muscle development were selected to construct a ceRNA network. This network comprises 5 differentially expressed lncRNAs (DELs: MSTRG.17572.1, XR_001211738.1, MSTRG.1886.1, XR_001212555.1, MSTRG.8995.2), 2 differentially expressed circRNAs (DECs: novel_circ_029953, novel_circ_017636), 11 differentially expressed miRNAs (DEMs: miR-383-x, miR-10174-y, miR-191-x, miR-24-x, miR-9619-y, novel-m0303-5p, novel-m0105-3p, miR-204-x, miR-211-z, novel-m0075, miR-26-y), 5 differentially expressed genes (DEGs: KIF3A, CCND1, PPM1A, Table 2, TGFBR1), forming a total of 24 interactions. This study identified miR-9619-y as a critical negative regulator of goose embryonic myoblast development through targeted inhibition of CCND1. Dual-luciferase reporter assays confirmed the direct binding of miR-9619-y to the 3'-untranslated region of CCND1. Functional experiments demonstrated that overexpression of miR-9619-y significantly reduced the EdU-positive cell ratio and myotube area percentage, accompanied by cell cycle arrest at the G0/G1 phase. Conversely, inhibition of miR-9619-y promoted myoblast proliferation and differentiation while decreasing the proportion of cells in G0/G1 phase. During the proliferation stage, miR-9619-y overexpression significantly suppressed CCND1 expression at both mRNA and protein levels, down-regulated MyoD expression, and reduced Myf5 mRNA abundance; whereas miR-9619-y inhibition up-regulated these genes and their corresponding proteins. During the differentiation stage, overexpression of miR-9619-y similarly decreased the mRNA levels of CCND1, Myh1, and MyoG, as well as the protein levels of MyHC and CCND1, with inhibition producing the opposite effects. CONCLUSION: In this study, we predicted a ceRNA network based on bioinformatics analysis governing goose embryonic myoblast development, identifying key molecular components including mRNAs, miRNAs, lncRNAs, and circRNAs, along with 24 regulatory axes. Functional experiments further demonstrated that miR-9619-y arrests cell cycle progression and negatively regulates the proliferation and differentiation of goose embryonic myoblasts, as evidenced by its impact on both the mRNA and protein expression of key myogenic factors through targeted inhibition of CCND1. These findings, together with the bioinformatically predicted ceRNA network, suggest potential complex post-transcriptional regulatory mechanisms underlying myogenesis in geese and offer candidate molecular targets for genetic improvement of meat production performance in waterfowl breeding programs.

Animals↗

A novel frameshift variant in the TMPRSS3 gene causes nonsyndromic hearing loss in a consanguineous family.

BACKGROUND: Hearing Loss (HL) is the most common sensorineural condition in humans. Mutations in the TMPRSS3 gene (DNFB8/10 locus) have been linked to autosomal recessive non-syndromic hearing loss (ARNSHL). METHODS: Whole-exome sequencing (WES) was utilized to identify disease-causing variants in a proband from Iran with ARNSHL who presented clinically with sensorineural, bilateral, and prelingual HL. The pathogenicity and novelty of the identified variant were assessed using various databases. A co-segregation study was also performed to confirm the presence of the variant in the proband's parents. Additionally, the secondary and tertiary structures of the mutant TMPRSS3 protein were predicted using bioinformatics tools. Furthermore, a global mutational spectrum of TMPRSS3 was created and statistically analyzed. The Iranome database was also used to identify other putative mutations in the TMPRSS3 gene in the Iranian population. RESULTS: We identified a novel homozygous single nucleotide deletion in TMPRSS3 (c.297delA, p.Asp100ThrfsTer52) in the proband. This is the first report of this mutation in a patient with ARNSHL. Sanger sequencing confirmed that this variant co-segregated from the proband's parents. Bioinformatic tools classified this novel variant as likely pathogenic. Additionally, 49.55% of families with TMPRSS3-related HL patients were shown to have consanguinity, consistent with our study. The Iranome database also revealed the c.268G > A variant as a putative novel mutation in TMPRSS3. CONCLUSION: This research expanded the pool of evidence regarding the association between mutations in the TMPRSS3 gene and ARNSHL. The finding confirmed that a single nucleotide deletion caused HL in the proband, suggesting that genetic testing, such as WES, is a robust technique for diagnosing patients with this condition.

Humans↗

Discovering the interactome, functions, and clinical relevance of enhancer RNAs in kidney renal clear cell carcinoma.

Enhancer RNA (eRNA) has emerged as a key player in cancer biology, influencing various aspects of tumor development and progression. In this study, we investigated the role of eRNAs in kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma. Leveraging high-throughput sequencing data and bioinformatics analysis, we identified differentially expressed eRNAs in KIRC and constructed eRNA-centric regulatory networks. Our findings revealed that up-regulated eRNAs in KIRC potentially regulate immune response and hypoxia pathways, while down-regulated eRNAs may impact ion transport, cell cycle, and metabolism. Furthermore, we developed a diagnostic prediction model based on eRNA expression profiles, demonstrating its effectiveness in KIRC diagnosis. Finally, we elucidated the regulatory mechanism of an eRNA (ENSR00000305834) on the expression of SLC15A2, a potential prognostic biomarker in KIRC, through bioinformatics analysis and in vitro validation experiments. In summary, Our study highlights the clinical significance of eRNAs in KIRC and underscores their potential as therapeutic targets.

Carcinoma, Renal Cell↗

Comprehensive analysis of a novel LYST mutation in a Tunisian patient with Chediak-Higashi syndrome.

BACKGROUND: Chediak-Higashi Syndrome (CHS) is a rare autosomal recessive disorder characterized by oculocutaneous albinism, recurrent infections, bleeding tendencies, and progressive neurological impairment. The syndrome is caused by mutations in the LYST gene, which plays a crucial role in lysosomal trafficking. OBJECTIVE: This study aims to characterize the molecular basis of CHS in a Tunisian patient by identifying mutations in the LYST gene and analyzing their impact on the protein function, correlating these findings with the patient's clinical presentation. METHODS: A comprehensive clinical assessment was conducted on the patient, followed by biochemical, hematological, and microbiological analyses. Additionally, LYST protein levels were quantified in the patient and their parents using an ELISA assay. Genomic DNA was extracted from the patient's blood, and Whole Exome Sequencing (WES) was performed to identify mutations in the LYST gene. The findings were confirmed through Sanger sequencing, and bioinformatic tools were employed to predict the functional consequences of the detected mutations. RESULTS: The patient presented with classical symptoms of CHS, including silver hair, hypopigmented skin, recurrent infections, and neurological decline, with an unusually late onset at 18 years. ELISA results demonstrated significantly reduced LYST levels in the patient (1.8 ng/ml) compared to heterozygous parents (7.8 ng/ml and 8.1 ng/ml) and controls (9.2 ng/ml). Genetic analysis revealed a novel homozygous deletion, c.10269_10275del (p.Gly3424SerfsTer15), in the LYST gene, leading to a frameshift mutation and premature termination of the protein. Bioinformatic analysis demonstrated that this mutation leads to the deletion of five out of sven WD40 repeats in the protein's C-terminal region, which are critical for protein-protein interactions and lysosomal trafficking. CONCLUSION: The study identifies a novel LYST mutation in a Tunisian patient with CHS, expanding the spectrum of known genetic variants associated with the disease. The findings highlight the importance of genetic screening in populations with high consanguinity and underscore the need for targeted therapies to address the molecular defects in CHS.

Adolescent↗

FMRP promotes gastric cancer progression via m6A-dependent stabilization of DVL2 and activation of the Wnt/PCP-JNK pathway.

BACKGROUND: N6-methyladenosine (m6A) modification has emerged as a critical regulator in gastric cancer progression. Fragile X messenger ribonucleoprotein 1 (FMRP), an RNA-binding protein with tumorigenic potential, remains poorly characterized in gastric cancer. METHODS: FMRP expression in gastric cancer was assessed through bioinformatic analyses and tissue microarray-based immunohistochemistry. Its biological functions were examined through loss-of-function experiments in vitro and in vivo. Mechanistic investigations, including RNA interaction, m6A site mutation, and RNA stability analyses, were performed to identify downstream targets and pathways regulated by FMRP. RESULTS: Bioinformatic analyses and tissue microarray-based immunohistochemistry showed that FMRP was significantly upregulated in gastric cancer tissues. FMRP depletion suppressed tumor growth and metastasis. Subsequently, Dishevelled segment polarity protein 2 (DVL2) was identified as a candidate downstream target of FMRP. DVL2 was also significantly upregulated in gastric cancer tissues, and its expression positively correlated with FMRP expression. Mechanistically, FMRP bound to DVL2 mRNA and enhanced its stability in an m6A-dependent manner. Among the candidate sites tested, mutation of 1271A attenuated FMRP-mediated regulation of DVL2 reporter activity, supporting the involvement of this site. Functionally, FMRP promoted activation of the noncanonical Wnt/planar cell polarity (PCP) signaling pathway and enhanced the proliferative, migratory, and invasive capacities of gastric cancer cells via DVL2. CONCLUSIONS: These results define FMRP as an oncogenic driver in gastric cancer that operates via the DVL2/Wnt/PCP axis. Targeting this pathway may provide a potential therapeutic strategy for gastric cancer.

Stomach Neoplasms↗

A custom library construction method for super-resolution ribosome profiling in Arabidopsis.

BACKGROUND: Ribosome profiling, also known as Ribo-seq, is a powerful technique to study genome-wide mRNA translation. It reveals the precise positions and quantification of ribosomes on mRNAs through deep sequencing of ribosome footprints. We previously optimized the resolution of this technique in plants. However, several key reagents in our original method have been discontinued, and thus, there is an urgent need to establish an alternative protocol. RESULTS: Here we describe a step-by-step protocol that combines our optimized ribosome footprinting in plants with available custom library construction methods established in yeast and bacteria. We tested this protocol in 7-day-old Arabidopsis seedlings and evaluated the quality of the sequencing data regarding ribosome footprint length, mapped genomic features, and the periodic properties corresponding to actively translating ribosomes through open resource bioinformatic tools. We successfully generated high-quality Ribo-seq data comparable with our original method. CONCLUSIONS: We established a custom library construction method for super-resolution Ribo-seq in Arabidopsis. The experimental protocol and bioinformatic pipeline should be readily applicable to other plant tissues and species.

3-nt periodicity↗

Improved small volume lung cancer detection with computer-aided detection: database characteristics and imaging of response to breast cancer risk reduction strategies.

Computer-aided detection (CAD) and diagnosis (CADx) of in vivo imaging studies are important tools based on bioinformatics. Currently, there are two diseases for which the United States Food and Drug Administration (FDA) has given premarket approval (PMA): the detection of signs consistent with lung cancer on chest radiographs and breast cancer on mammograms. There are systems for other diseases and other types of images under development; however, this process depends on the availability of an accurate database. The author helped in the development of the databases for such systems and management of the clinical trial that resulted in the FDA-PMA of the system that detects findings consistent with lung cancer. The characteristics of the database used will be described. Further, a woman's risk of developing breast cancer differs from those of other women. Risk can be high, average, or low. There are now pharmaceuticals that decrease the risk that women, as a group, will develop breast cancer and it has been suggested that dietary changes could have similar effects. The pharmaceutical agents, though, have some associated side effects, and it is clinically important to determine whether these agents have decreased an individual woman's risk of breast cancer. In vivo imaging biomarkers of risk and successful risk reduction are therefore sought, but the information on possible in vivo imaging biomarkers is less mature than activities in CAD. Bioinformatics will be an important contributor to this in vivo imaging biomarker development.

Breast Neoplasms↗

New approaches for in silico identification of cytokine-modified beta cell gene networks.

Beta cell dysfunction and death in type 1 diabetes mellitus (T1DM) is caused by direct contact with activated macrophages and T lymphocytes and by exposure to soluble mediators secreted by these cells, such as cytokines and nitric oxide. Cytokine-induced apoptosis depends on the expression of pro- and anti-apoptotic genes that remain to be characterized. Using microarray analyses, we identified several transcription factor and "effector" gene networks regulated by interleukin-1beta and/or interferon-gamma in beta cells. This suggests that beta cell fate following exposure to cytokines is a complex and highly regulated process, depending on the duration and severity of perturbation of key gene networks. In order to draw correct conclusions from these massive amounts of data, we need to utilize novel bioinformatics and statistical tools. Thus, we are presently performing in silico analysis for the localization of binding sites for the transcription factor NF-kappaB (previously shown to be pivotal for beta cell apoptosis) in 15 temporally related gene clusters, identified by time-course microarray analysis. In silico analysis is based on a broad range of computational techniques used to detect motifs in a DNA sequence corresponding to the binding site of a transcription factor. These computer-based findings must be validated by use of positive and negative controls, and by "ChIP on chip" analysis. Moreover, new statistical approaches are required to decrease false positive findings. These novel approaches will constitute a "proof of principle" for the integrated use of bioinformatics and functional genomics in the characterization of relevant cytokine-regulated beta cell gene networks leading to beta cell apoptosis in T1DM.

Animals↗

The Nuclear Receptor Signaling Atlas: development of a functional atlas of nuclear receptors.

The Nuclear Receptor Signaling Atlas (NURSA) was developed by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute on Aging (NIA), and the National Cancer Institute (NCI) of the National Institutes of Health (NIH); the aim of NURSA is to utilize classical approaches to validate existing hypotheses and exploit new and emerging technologies to formulate and test new hypotheses that might elucidate the program of nuclear receptor (NR) structure, function, and role in disease. The means for carrying out this ambitious program required development of interactions among investigators and the combined application of new high-throughput technologies and existing approaches to allow for both mechanistic studies and accrual of large datasets in a discovery-based research effort, all leading to advances with implications for the missions of the NIDDK, NIA, and NCI. A team-based multidisciplinary approach has allowed for both objectives to proceed simultaneously, tied together via a central bioinformatics resource and one web-accessible venue (www.nursa.org). The ultimate goals for the NURSA consortium are to: 1) establish the mechanistic principles of NR function, 2) characterize NR-coregulator complex formation and regulation, 3) map protein-protein interactions for coregulators, 4) identify candidate downstream target genes of NR action, 5) identify target tissue expression of NRs, 6) understand the regulation of NR expression and, 7) integrate existing and emerging information through NURSA bioinformatics tools.

Animals↗

Mutation spectrum and predicted function of laforin in Lafora's progressive myoclonus epilepsy.

BACKGROUND: Lafora's disease is a progressive myoclonus epilepsy with pathognomonic inclusions (polyglucosan bodies) caused by mutations in the EPM2A gene. EPM2A codes for laforin, a protein with unknown function. Mutations have been reported in the last three of the gene's exons. To date, the first exon has not been determined conclusively. It has been predicted based on genomic DNA sequence analysis including comparison with the mouse homologue. OBJECTIVES: 1) To detect new mutations in exon 1 and establish the role of this exon in Lafora's disease. 2) To generate hypotheses about the biological function of laforin based on bioinformatic analyses. METHODS: 1) PCR conditions and components were refined to allow amplification and sequencing of the first exon of EPM2A. 2) Extensive bioinformatic analyses of the primary structure of laforin were completed. RESULTS: 1) Seven new mutations were identified in the putative exon 1. 2) Laforin is predicted not to localize to the cell membrane or any of the organelles. It contains all components of the catalytic active site of the family of dual-specificity phosphatases. It contains a sequence predicted to encode a carbohydrate binding domain (coded by exon 1) and two putative glucohydrolase catalytic sites. CONCLUSIONS: The identification of mutations in exon 1 of EPM2A establishes its role in the pathogenesis of Lafora's disease. The presence of potential carbohydrate binding and cleaving domains suggest a role for laforin in the prevention of accumulation of polyglucosans in healthy neurons.

Adolescent↗

AmpSeqR: an R package for amplicon deep sequencing data analysis.

Amplicon sequencing (AmpSeq) is a methodology that targets specific genomic regions of interest for polymerase chain reaction (PCR) amplification so that they can be sequenced to a high depth of coverage. Amplicons are typically chosen to be highly polymorphic, usually with several highly informative, high frequency single nucleotide polymorphisms (SNPs) segregating in an amplicon of 100-200 base pair (bp). This allows high sensitivity detection and quantification of the frequency of each sequence within each sample making it suitable for applications such as low frequency somatic mosaicism detection or minor clone detection in mixed samples. AmpSeq is being increasingly applied to both biological and medical studies, in applications such as cancer, infectious diseases and brain mosaicism studies. Current bioinformatics pipelines for AmpSeq data processing lack downstream analysis, have difficulty distinguishing between true sequences and PCR sequencing errors and artifacts, and often require bioinformatic expertise. We present a new R package: AmpSeqR, designed for the processing of deep short-read amplicon sequencing data, with a focus on infectious diseases. The pipeline integrates several existing R packages combining them with newly developed functions to perform optimal filtering of reads to remove noise and improve the accuracy of the detected sequences data, permitting detection of very low frequency clones in mixed samples. The package provides useful functions including data pre-processing, amplicon sequence variants (ASVs) estimation, data post-processing, data visualization, and automatically generates a comprehensive Rmarkdown report that contains all essential results facilitating easy inclusion into reports and publications. AmpSeqR is publicly available at https://github.com/bahlolab/AmpSeqR.

High-Throughput Nucleotide Sequencing↗

Toxicogenomics through the eyes of informatics: conference overview and recommendations.

Virginia Bioinformatics Institute, in conjunction with National Institutes of Environmental Health Sciences, hosted a conference, "Toxicogenomics through the Eyes of Informatics," in Bethesda, Maryland, USA, on 12-13 May 2003. Researchers around the world met to discuss how the application of bioinformatics tools, methodologies, and technologies will enhance our understanding of how cells and organisms respond to toxins. Conference topics included statistical methods, quantitative molecular data sets, computational algorithms for data analysis, computational modeling and simulation, challenges and opportunities in computational biology, and information technology infrastructure for data and tool management. This meeting report is a summary of conference presentations, survey results, current toxicogenomics concerns, and future directions of the toxicogenomics community. In conclusion this report discusses toxicogenomics as related to environmental agents, cell-chemical reactions, and gene-environment interactions.

Algorithms↗

Advanced molecular profiling in vivo detects novel function of dickkopf-3 in the regulation of bone formation.

UNLABELLED: A bioinformatics-based analysis of endochondral bone formation model detected several genes upregulated in this process. Among these genes the dickkopf homolog 3 (Dkk3) was upregulated and further studies showed that its expression affects in vitro and in vivo osteogenesis. This study indicates a possible role of Dkk3 in regulating bone formation. INTRODUCTION: Endochondral bone formation is a complex biological process involving numerous chondrogenic, osteogenic, and angiogenic proteins, only some of which have been well studied. Additional key genes may have important roles as well. We hypothesized that to identify key genes and signaling pathways crucial for bone formation, a comprehensive gene discovery strategy should be applied to an established in vivo model of osteogenesis. MATERIALS AND METHODS: We used in vivo implanted C3H10T1/2 cells that had been genetically engineered to express human bone morphogenetic protein-2 (BMP2) in a tetracycline-regulated system that controls osteogenic differentiation. Oligonucleotide microarray data from the implants (n = 4 repeats) was analyzed using coupled two-way clustering (CTWC) and statistical methods. For studying the effects of dickkopf homolog 3 (Dkk3) in chondrogenesis and osteogenesis, C3H10T1/2 mesenchymal progenitors were used. RESULTS: The CTWC revealed temporal expression of Dkk3 with other chondrogenesis-, osteogenesis-, and Wnt-related genes. Quantitative RT-PCR confirmed the expression of Dkk3 in the implants. C3H10T1/2 cells that expressed Dkk3 in the presence of BMP2 displayed lower levels of alkaline phosphatase and collagen I mRNA expression than control C3H10T1/2 cells that did not express Dkk3. Interestingly, the levels of collagen II mRNA expression, Alcian blue staining, and glucose aminoglycans (GAGs) production were not influenced by Dkk3 expression. In vivo microCT and bioluminescence imaging revealed that co-expression of Dkk3 and BMP2 by implanted C3H10T1/2 cells induced the formation of significantly lower quantities of bone than cells expressing only BMP2. CONCLUSIONS: A bioinformatics analysis enabled the identification of Dkk3 as a pivotal gene with a novel function in endochondral bone formation. Our results showed that Dkk3 might have inhibitory effects on osteogenesis, but no effect on chondrogenesis, indicating that Dkk3 plays a regulatory role in endochondral bone formation. Further mechanistic studies are required to reveal the mechanism of action of Dkk3 in endochondral bone formation.

Adaptor Proteins, Signal Transducing↗

Subcellular localization of CIAPIN1.

Cytokine-induced apoptosis inhibitor 1 (CIAPIN1) is a newly identified anti-apoptotic molecule. Our previous studies have demonstrated that CIAPIN1 is ubiquitously expressed in normal fetal and adult human tissues and confers multidrug resistance in gastric cancer cells, possibly by upregulating the expression of multidrug resistance gene 1 and multidrug resistance-related protein 1. However, fundamental biological functions of CIAPIN1 have not been elucidated. In this study, we first predicted the subcellular localization of CIAPIN1 with bioinformatic approaches and then characterized the intracellular localization of CIAPIN1 in both human and mouse cells by a combination of techniques including (a)immunohistochemistry and immunofluorescence, (b) His-tagged CIAPIN1 expression, and (c)subcellular fractionation and analysis of CIAPIN1 in the fractions by Western blotting. All methods produced consistent results; CIAPIN1 was localized in both the cytoplasm and the nucleus and was accumulated in the nucleolus. Bioinformatic prediction disclosed a putative nuclear localization signal and a putative nuclear export signal within both human and mouse CIAPIN1. These findings suggest that CIAPIN1 may undergo a cytoplasm-nucleus-nucleolus translocation.

Animals↗

Small serine recombinases are markers for antiphage defense system discovery.

Renewed interest in phage therapy has highlighted a need to understand how bacteria subvert phage infection through antiphage defense systems. Traditionally, strategies to identify antiphage defense systems lack throughput or have limitations for bacterial species where antiphage defense systems are understudied. Herein, we developed a bioinformatic pipeline that uses a small serine recombinase to identify known and unknown antiphage defense systems. Using this approach to query reference genomes and metagenomes, we show that small serine recombinase genes are genetically linked to antiphage defense systems and serve as bait for finding these systems across diverse bacterial phyla. Using co-transcription predictions and statistical analysis of protein domain abundances, we experimentally validated our bioinformatic approach by discovering that KAP P-loop NTPases are fused to putative antiphage domains and reinforce prokaryotic Schlafen proteins as a new class of antiphage defense. Our work shows that small serine recombinases are a reliable genetic marker for the discovery of antiphage defenses across diverse bacterial phyla.

Bacteriophages↗

Selection of target sites for mobile DNA integration in the human genome.

DNA sequences from retroviruses, retrotransposons, DNA transposons, and parvoviruses can all become integrated into the human genome. Accumulation of such sequences accounts for at least 40% of our genome today. These integrating elements are also of interest as gene-delivery vectors for human gene therapy. Here we present a comprehensive bioinformatic analysis of integration targeting by HIV, MLV, ASLV, SFV, L1, SB, and AAV. We used a mathematical method which allowed annotation of each base pair in the human genome for its likelihood of hosting an integration event by each type of element, taking advantage of more than 200 types of genomic annotation. This bioinformatic resource documents a wealth of new associations between genomic features and integration targeting. The study also revealed that the length of genomic intervals analyzed strongly affected the conclusions drawn--thus, answering the question "What genomic features affect integration?" requires carefully specifying the length scale of interest.

Binding Sites↗

The challenge of chromatin model comparison and validation: A project from the first international 4D Nucleome Hackathon.

The computational modeling of chromatin structure is highly complex due to the hierarchical organization of chromatin, which reflects its diverse biophysical principles, as well as inherent dynamism, which underlies its complexity. Chromatin structure modeling can be based on diverse approaches and assumptions, making it essential to determine how different methods influence the modeling outcomes. We conducted a project at the NIH-funded 4D Nucleome Hackathon on March 18-21, 2024, at The University of Washington in Seattle, USA. The hackathon provided an amazing opportunity to gather an international, multi-institutional and unbiased group of experts to discuss, understand and undertake the challenges of chromatin model comparison and validation. Here we give an overview of the current state of the 3D chromatin field and discuss our efforts to run and validate the models. We used distance matrices to represent chromatin models and we calculated Spearman correlation coefficients to estimate differences between models, as well as between models and experimental data. In addition, we discuss challenges in chromatin structure modeling that include: 1) different aspects of chromatin biophysics and scales complicate model comparisons, 2) large diversity of experimental data (e.g., population-based, single-cell, protein-specific) that differ in mathematical properties, heatmap smoothness, noise and resolutions complicates model validation, 3) expertise in biology, bioinformatics, and physics is necessary to conduct comprehensive research on chromatin structure, 4) bioinformatic software, which is often developed in academic settings, is characterized by insufficient support and documentation. We also emphasize the importance of establishing guidelines for software development and standardization.

Chromatin↗