Genome Browser Research Articles

PolyASite v3.0: a multi-species atlas of polyadenylation sites inferred from single-cell RNA-sequencing data

Abstract The broadly used 10X Genomics technology for single-cell RNA sequencing (scRNA-seq) captures RNA 3′ ends. Thus, some reads contain part of the non-templated polyadenosine tails, providing direct evidence for the sites of 3′ end cleavage and polyadenylation on the respective RNAs. Taking advantage of this property, we recently developed the SCINPAS workflow to infer polyadenylation sites (PASs) from scRNA-seq data. Here, we used this workflow to construct version 3.0 (v3.0, https://polyasite.unibas.ch/) of the PolyASite Atlas from a big compendium of publicly available human, mouse and worm scRNA-seq datasets obtained from healthy tissues. As the resolution of scRNA-seq was too low for robust detection of cell-level differences in PAS usage, we aggregated samples based on their tissue-of-origin to construct tissue-level catalogs of PASs. These provide qualitatively new information about PAS usage, in comparison to the previous PAS catalogs that were based on bulk 3′ end sequencing experiments primarily in cell lines. In the new version, we document stringency levels associated with each PAS so that users can balance sensitivity and specificity in their analysis. We also upgraded the integration with the UCSC Genome Browser and developed track hubs conveniently displaying pooled and tissue-specific expression of PASs.

Investigating the role of non-synonymous variant D67N of ADGRE2 in chronic myeloid leukemia

BackgroundChronic myeloid leukaemia (CML) is a type of blood cancer that begins in the hematopoietic stem cells. It is primarily characterized by a specific chromosomal aberration, the Philadelphia chromosome. While the fusion gene is a major contributor to CML, several other genes including ADGRE2, that are reported as highly expressed in hematopoietic stem cells and could be utilized as a therapeutic marker in leukemic patients are implicated in the disease’s progression. Until recently, little research had been conducted to identify single nucleotide polymorphisms (SNPs) associated with CML. Therefore, this study aims to investigate the influence of non-synonymous variants on the structure and function of the gene encoding adhesion G protein-coupled receptor E2, ADGRE2, and to evaluate their association with CML and its clinical and pathological characteristics.MethodsNon-synonymous SNPs of ADGRE2 were retrieved from the ENSEMBL, COSMIC, and gnomAD genome browsers, and the pathogenicity of deleterious variants was assessed using several established computational tools, including SIFT, CADD, REVEL, PolyPhen, and MetaLR.ResultsVarious in silico analyses explored the impact of damaging SNP on the function, stability, and structure of EGF-like modules containing mucin-like hormone receptor-like2 (EMR2) protein encoded by the ADGRE2 gene. Genotype analysis was performed on collected blood samples, revealing that altered genotype TT of variant rs765071211 (C/T) was associated significantly with CML patients compared to the control. Further in vitro and in vivo analyses suggest that this SNP holds potential for clinical translation.

The UCSC Genome Browser database: 2025 update.

The UCSC Genome Browser (https://genome.ucsc.edu) is a widely utilized web-based tool for visualization and analysis of genomic data, encompassing over 4000 assemblies from diverse organisms. Since its release in 2001, it has become an essential resource for genomics and bioinformatics research. Annotation data available on Genome Browser includes both internally created and maintained tracks as well as custom tracks and track hubs provided by the research community. This last year's updates include over 25 new annotation tracks such as the gnomAD 4.1 track on the human GRCh38/hg38 assembly, the addition of three new public hubs, and significant expansions to the Genome Archive[GenArk) system for interacting with the enormous variety of assemblies. We have also made improvements to our interface, including updates to the browser graphic page, such as a new popup dialog feature that now displays item details without requiring navigation away from the main Genome Browser page. GenePred tracks have been upgraded with right-click options for zooming and precise navigation, along with enhanced mouseOver functions. Additional improvements include a new grouping feature for track hubs and hub description info links. A new tutorial focusing on Clinical Genetics has also been added to the UCSC Genome Browser.

Generation and analysis of a mouse multitissue genome annotation atlas.

Generating an accurate and complete genome annotation for an organism is complex because the cells within each tissue can express a unique set of transcript isoforms from a unique set of genes. A comprehensive genome annotation should contain information on what tissues express what transcript isoforms at what level. This tissue-level isoform information can then inform a wide range of research questions as well as experiment designs. Long-read sequencing technology combined with advanced full-length cDNA library preparation methods has now achieved throughput and accuracy where generating these types of annotations is achievable. Here, we show this by generating a genome annotation of the mouse (Mus musculus). We used the nanopore-based R2C2 long-read sequencing method to generate 64 million highly accurate full-length cDNA consensus reads-averaging 5.4 million reads per tissue for a dozen tissues. Using the Mandalorion tool, we processed these reads to generate the Tissue-level Atlas of Mouse Isoforms which is available as a trackhub for the UCSC Genome Browser and contains at least one full-length isoform for the vast majority of expressed genes in each tissue.

The DoGA consortium expression atlas of promoters and genes in 100 canine tissues

The dog, Canis lupus familiaris, is an important model for studying human diseases. Unlike many model organisms, the dog genome has a comparatively poor functional annotation, which hampers gene discovery for development, morphology, disease, and behavior. To fill this gap, we established a comprehensive tissue biobank for both the dog and wolf samples. The biobank consists of 5485 samples representing 132 tissues from 13 dogs, 12 dog embryos, and 24 wolves. In a subset of 100 tissues from nine dogs and 12 embryos, we characterized gene expression activity for each promoter, including alternative and novel, i.e., previously not annotated, promoter regions, using the 5’ targeting RNA sequencing technology STRT2-seq. We identified over 100,000 promoter region candidates in the recent canine genome assembly, CanFam4, including over 45,000 highly reproducible sites with gene expression and respective tissue enrichment levels. We provide a promoter and gene expression atlas with interactive, open data resources, including a data coordination center and genome browser track hubs. We demonstrated the applicability of Dog Genome Annotation (DoGA) data and resources using multiple examples spanning canine embryonic development, morphology and behavior, and diseases across species.

MECOM Locus classical transcript isoforms affect tumor immune microenvironment and different targets in ovarian cancer

The MECOM locus is a gene frequently amplified in high-grade serous ovarian carcinoma (HGSOC). Nevertheless, the body of research examining the associations among MECOM transcripts, patient prognosis, and their role in modulating the tumor immune microenvironment (TIME) remains sparse, particularly in large cohorts. This study assessed the expression of MECOM transcripts in 352 HGSOC patients and 88 normal ovarian tissues from the combined GTEx/TCGA database. Using resources such as the UCSC Genome Browser, Ensembl, and NextProt, two transcripts corresponding to classical protein isoforms from MECOM were identified. Cox proportional hazards regression analysis, Kaplan-Meier survival curves, and a comprehensive TIME evaluation algorithm were employed to elucidate the connections between the expression levels of these transcripts and both patient prognosis and TIME status. Chromatin Immunoprecipitation sequencing (ChIP-seq) data for the two protein isoforms, as well as RNA sequencing data post-targeted silencing, were analyzed to identify potential regulatory targets of the different transcription factors. Elevated expression of the MECOM isoform transcripts was correlated with poorer survival in HGSOC patients, potentially through the modulation of cancer-associated fibroblasts (CAFs) and immunosuppressive cell populations. In contrast, higher levels of EVI1 isoform transcripts were linked to enhanced survival, possibly due to the regulation of CD8+ T cells, macrophages, and a reduction in the expression of JUN protein, or its DNA-binding activity on downstream genes. Diverse protein isoforms derived from MECOM were found to differentially affect the survival and tumor development in ovarian cancer patients through specific mechanisms. Investigating the molecular mechanisms underlying disease pathogenesis and identifying potential drug target proteins at the level of splice variant isoforms were deemed crucial.

ABCA3 c.838C>T (p.Arg280Cys, R280C) and c.697C>T (p.Gln233Ter, Q233X, Q233*) as Causative Variants for RDS: A Family Case Study and Literature Review.

Background: Respiratory distress syndrome (RDS) is the primary cause of respiratory failure in preterm infants, but it also affects 5-7% of term infants. Dysfunctions in pulmonary surfactant metabolism, resulting from mutations of the lung surfactant genes, are rare diseases, ranging from fatal neonatal RDS to interstitial lung disease, associated with increased morbidity and mortality. This study aims to clarify the clinical significance of ABCA3 variants found in a specific family case, as existing data in the literature are inconsistent. Material and Methods: A family case report was conducted; targeted panel genetic testing identified a variant of the SFTPB gene and two variants of ABCA3 genes. Comprehensive research involving a systematic review of PubMed, Google Scholar databases, and genome browsers was used to clarify the pathogenicity of the two ABCA3 variants found in the index patient. Advanced prediction tools were employed to assess the pathogenicity of the two ABCA3 variants, ensuring the validity and reliability of our findings. Results: The index case exhibited fatal neonatal RDS. Genetic testing revealed the presence of the SFTPB p.Val267Ile variant, which was not previously reported but is a benign variant based on family genetic testing and history. Additionally, two ABCA3 gene variants were identified: c.697C>T, not yet reported, and c.838C>T. These variants were found to affect ABCA3 protein function and were likely associated with neonatal RDS. Prediction tools and data from nine other cases in the literature supported this conclusion. Conclusions: Based on in silico predictors, an analysis of the presented family, and cases described in the literature, it is reasonable to consider reclassifying the two ABCA3 variants identified in the index case as pathogenic/pathogenic. Reclassification will improve genetic counseling accuracy and facilitate correct diagnosis.

6816 The Estrogen Environment Characteristic of Endometriotic Lesion May Attenuate the Receptor γ-Mediated Antiproliferative Activity of Retinoids

Abstract Disclosure: M. Izawa: None. Y. Azuma: None. F. Taniguchi: None. Background: Endometriosis has been accepted as an estrogen-dependent disease, and the estrogen environment in endometriotic lesions has been proposed as a major background of the pathophysiology. Although the hormonal therapy targeting the reduction of estrogen has been employed to reduce endometriosis-associated symptoms, the limitation of therapy has been well recognized. How to overcome the limitation remains an urgent subject to be explored. [Objective:]We focused on retinoids, which have been known to induce an antiproliferative activity in tumors. Based on the retinoic acid receptor (RAR) expression profile in endometriotic lesions, we evaluated the antiproliferative activity of retinoids using endometriotic cells. Finally, we examined the effect of estrogen on antiproliferative activity. Methods: Endometriotic tissue and cells: Institutional Review Boards approved this project. The chocolate cyst lining in the ovaries of patients with endometriosis was the source of endometriotic tissue. Stromal cells collected from endometriotic tissues were used as endometriotic cells. RAR expression: RNAs were prepared from endometriotic tissues and cells, and single-stranded cDNAs were subjected to RT-PCR. Primers were designed using the UCSF genome browser. Protein expression was examined by Western blotting. Cell proliferation assay: Cells were treated with all-trans retinoic acid (ATRA), selective RAR modulators (sRARMs), BMS753, CD2314 and CD437, RARγ antagonist MM11253 and 17β-estradiol (E2). Viable cells were estimated using WST-8 assay. RNA-seq analysis: Cells were treated with retinoids and E2. RNA samples were used for polyA+ selected library and the strand-specific RNA-seq. Differentially expressed genes with p-values < 0.05 and log2 fold changes > 1 were extracted as responsive genes. Results: RAR expression: Transcripts of wild-type RARα, RARβ, and RARγ were demonstrated in arbitrary 10 regions of patient tissue, and in endometriotic cells. The expression of these RARs was almost at a comparable level. Effect of retinoids and/or estrogen on cell proliferation: Cell proliferation rate was significantly decreased in the presence of ATRA. Among sRARMs tested, only CD437 reduced the cell proliferation. The antiproliferative activity of ATRA was attenuated either in the presence of MM11253 or E2, respectively. ATRA- and/or E2-responsive gene expressions To explore gene expressions in response to retinoids and E2, RNA-seq analysis was performed. The results suggest the diversity of ATRA- and E2-responsive genes in endometriotic lesions.[Conclusion:]Endometriotic cell proliferation was significantly suppressed in response to retinoids through RARγ. The observation that the antiproliferative activity was attenuated in the presence of E2 suggests a suppressive environment against the activity of retinois in endometriotic legions. Presentation: 6/2/2024

Long Non-coding RNA and Progression of Breast Cancer

Breast cancer is a major problem in the health sector worldwide. The prevalence of breast cancer incidence is on the rise in many countries despite efforts to eradicate it. The substantial efforts for the treatment of breast cancer are quite successful but the main hindrance is early detection which in turn is dependent on various factors i.e. genetic history, environmental exposures, hormonal causes, and sedentary lifestyle. In previous studies, lncRNAs were known to modulate the progression of many cancers like gastric, lung, ovarian, and colorectal cancers. This study was designed to find these lncRNAs role in breast cancer development. Bioinformatics tools were used for in silco analysis of these lncRNAs LINC01356, LINC01357, ARF4-AS1, and FAM83B. These lncRNAs were evaluated in GEPIA2 for subtype analysis and survival probability, Phylo CSF UCSC genome browser for conserved sequences and protein-coding potential, BcGenExMiner for correlation analysis and UALCAN for protein-coding gene expression. These above-mentioned lncRNAs showed high expression in the basal subtype of TNBC as compared with other subtypes and they showed poor survival rates in the basal subtype. LINC01356 and LINC01357 showed positive correlation with TAFA3 and SLC16A1. ARF4-AS1 positively correlated with ASB14 and FAM83B positively correlated with HCRTR2. These lncRNAs showing positive correlation with different genes have a role in breast cancer development and progression.

Identification of PPREs and PPRE associated genes in the human genome: insights into related kinases and disease implications.

"Peroxisome Proliferator-Activated Receptors" (PPARs) belong to the class of transcription factors (TF) identified as Nuclear Receptors (NR). Upon activation by peroxisome proliferators (PPs), PPARs modulate a diverse range of genes, consequently regulating intra-cellular lipid metabolism, glucose uptake, apoptosis, and cell proliferation. Subsequent to the heterodimerization of Retinoid X Receptors (RXR) with PPARs induced by the binding of activators to PPARs, facilitates the binding of the resulting complex to Peroxisome Proliferator-Activated Receptors Response Elements (PPRE), with a consensus sequence 5'AGGTCANAGGTCA-3', and regulate the transcription of the targeted genes. A comprehensive screening of PPRE within the whole human genome was performed using the Genome Workbench and UCSC Genome Browser to find the associated genes. Subsequently, the kinase subset was isolated from the extracted list of PPRE-related genes. Functional enrichment of the kinases was performed using FunRich, ToppGene, and ShinyGO. Network analysis and enrichment studies were then further performed using NDEx to elucidate these identified kinases' connections and significance. Additionally, the disease association of the PPRE kinases was analyzed using DisGeNET data in R studio and the COSMIC dataset. A comprehensive analysis of 1002 PPRE sequences within the human genome (T2T), yielded the identification of 660 associated genes, including 29 kinases. The engagement of these kinases in various biological pathways, such as apoptosis, platelet activation, and cytokine pathways, revealed from the functional enrichment analysis, illuminates the multifaceted role of PPAR in the regulation of cellular homeostasis and biological processes. Network analysis reveals the kinases interact with approximately 5.56% of the Human Integrated Protein-Protein Interaction rEference (HIPPIE) network. Disease association analysis using DisGeNET and COSMIC datasets revealed the significant roles of these kinases in cellular processes and disease modulation. This study elucidates the regulatory role of PPAR-associated genes and their association with numerous biological pathways. The involvement of the kinases with disease-related pathways highlights new potential for the development of therapeutic strategies designed for disease management and intervention.

A proteogenomic atlas of the human neural retina.

The human neural retina is a complex tissue with abundant alternative splicing and more than 10% of genetic variants linked to inherited retinal diseases (IRDs) alter splicing. Traditional short-read RNA-sequencing methods have been used for understanding retina-specific splicing but have limitations in detailing transcript isoforms. To address this, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass spectrometry and whole genome sequencing data of three healthy human neural retina samples. We identified nearly 60,000 transcript isoforms, of which approximately one-third are novel. Additionally, ten novel peptides confirmed novel transcript isoforms. For instance, we identified a novel IMPDH1 isoform with a novel combination of known exons that is supported by peptide evidence. Our research underscores the potential of in-depth tissue-specific transcriptomic analysis to enhance our grasp of tissue-specific alternative splicing. The data underlying the proteogenomic atlas are available via EGA with identifier EGAD50000000101, via ProteomeXchange with identifier PXD045187, and accessible through the UCSC genome browser.

Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites

BackgroundVariations in untranslated regions (UTR) alter regulatory pathways impacting phenotype, disease onset, and course of disease. Protein kinase C Zeta (PRKCZ), a serine-threonine kinase, is implicated in cardiovascular, neurological and oncological disorders. Due to limited research on PRKCZ, this study aimed to investigate the impact of UTR genetic variants’ on binding sites for transcription factors and miRNA. RNA secondary structure, eQTLs, and variation tolerance analysis were also part of the study.MethodsThe data related to PRKCZ gene variants was downloaded from the Ensembl genome browser, COSMIC and gnomAD. The RegulomeDB database was used to assess the functional impact of 5’ UTR and 3’UTR variants. The analysis of the transcription binding sites (TFBS) was done through the Alibaba tool, and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) was employed to identify pathways associated with PRKCZ. To predict the effect of variants on microRNA binding sites, PolymiRTS was utilized for 3’ UTR variants, and the SNPinfo tool was used for 5’ UTR variants.ResultsThe results obtained indicated that a total of 24 variants present in the 3’ UTR and 25 variants present in the 5’ UTR were most detrimental. TFBS analysis revealed that 5’ UTR variants added YY1, repressor, and Oct1, whereas 3’ UTR variants added AP-2alpha, AhR, Da, GR, and USF binding sites. The study predicted TFs that influenced PRKCZ expression. RNA secondary structure analysis showed that eight 5’ UTR and six 3’ UTR altered the RNA structure by either removal or addition of the stem-loop. The microRNA binding site analysis highlighted that seven 3’ UTR and one 5’ UTR variant altered the conserved site and also created new binding sites. eQTLs analysis showed that one variant was associated with PRKCZ expression in the lung and thyroid. The variation tolerance analysis revealed that PRKCZ was an intolerant gene.ConclusionThis study laid the groundwork for future studies aimed at targeting PRKCZ as a therapeutic target.

Abstract P367: Cross-Species Epigenomic Maps of Intergenic Loci for Hypertension and Blood Pressure

Many non-coding SNPs identified in Genome-Wide Association Studies (GWAS) likely affect BP-related gene expression through epigenetic mechanisms. This study analyzes the comparative genomic and epigenomic landscapes in human and rat kidney tissues, including kidney proximal tubule (PT) and medullary thick ascending limb (mTAL), focusing on the major challenge of identifying conserved regulatory elements in intergenic regions. The purpose of our study is to identify BP gene regulatory elements in intergenic regions that are conserved from human to rat for in vivo validation and mechanistic studies. Our ultimate goal is to generate high-resolution, genome-wide epigenomic maps of key BP-relevant tissues, using ATAC-seq, Hi-C, CUT&Tag, DNA methylation profiling and RNA-seq. We are creating visualization hubs for human and rat, integrating our data within the UCSC Genome Browser environment. UCSC contains extensive data for humans but very little for rats, particularly for the updated genome assemblies. To address this gap, we integrated our results with data from the Rat Genome Database (RGD). To date, we harmonized ATAC-seq data from human and rat PT and mTAL and displayed these data in RGD’s JBrowse2 genome browser for unique comparative genome views. Based on our initial analysis of data density and intensity, we are developing a novel pattern recognition algorithm to identify epigenomic marks that are conserved across rat and human genomes. Existing algorithms predominantly focus on the conservation of coding genes, gene families, and genomic sequences. Here, average normalized peak intensities for ATAC-seq data across tissues were subject to canonical correlation between human and rat to identify conserved epigenomic patterns within the BP GWAS loci. Here we present an example of a human BP locus in the intergenic region between NPR3 and TARS1 on chromosome 5 which has a region of conserved synteny with rat chromosome 2. Comparative analysis and visualization of this region show significant correlation between ATAC-seq peaks from rat and human PT and mTAL at this locus, with predicted conserved regulatory elements. These visualizations can uncover novel biological insights and identify potential regulatory targets for intervention. This work underscores the importance of advanced visualization techniques in understanding hypertension pathogenesis, facilitating cross-species comparisons, and enhancing the utility of genomic databases.

Correlations of Long Noncoding RNA HNF4A-AS1 Alternative Transcripts with Liver Diseases and Drug Metabolism.

Hepatocyte nuclear factor 4 alpha antisense 1 (HNF4A-AS1) is a long noncoding RNA (lncRNA) gene physically located next to the transcription factor HNF4A gene in the human genome. Its transcription products have been reported to inhibit the progression of hepatocellular carcinoma (HCC) and negatively regulate the expression of cytochrome P450s (CYPs), including CYP1A2, 2B6, 2C9, 2C19, 2E1, and 3A4. By altering CYP expression, lncRNA HNF4A-AS1 also contributes to the susceptibility of drug-induced liver injury. Thus, HNF4A-AS1 lncRNA is a promising target for controlling HCC and modulating drug metabolism. However, HNF4A-AS1 has four annotated alternative transcripts in the human genome browsers, and it is unclear which transcripts the small interfering RNAs or small hairpin RNAs used in the previous studies are silenced and which transcripts should be used as the target. In this study, four annotated and two newly identified transcripts were confirmed. These six transcripts showed different expression levels in different liver disease conditions, including metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, and obesity. The expression patterns of all HNF4A-AS1 transcripts were further investigated in liver cell growth from human embryonic stem cells to matured hepatocyte-like cells, HepaRG differentiation, and exposure to rifampicin treatment. Several HNF4A-AS1 transcripts highly displayed correlations with these situations. In addition, some of the HNF4A-AS1 transcripts also showed a strong correlation with CYP3A4 during HepaRG maturation and rifampicin exposure. Our findings provide valuable insights into the specific roles of HNF4A-AS1 transcripts, paving the way for more targeted therapeutic strategies for liver diseases and drug metabolism. SIGNIFICANCE STATEMENT: This study explores the alternative transcripts of HNF4A-AS1, showing how their expression changes in different biological conditions, from various liver diseases to the growth and differentiation of hepatocytes and drug metabolism. The generated knowledge is essential for understanding the independent roles of different transcripts from the same lncRNA in different liver diseases and drug metabolism situations.

A Comprehensive Review of Bioinformatics Tools for Genomic Biomarker Discovery Driving Precision Oncology.

The rapid advancement of high-throughput technologies, particularly next-generation sequencing (NGS), has revolutionized cancer research by enabling the investigation of genetic variations such as SNPs, copy number variations, gene expression, and protein levels. These technologies have elevated the significance of precision oncology, creating a demand for biomarker identification and validation. This review explores the complex interplay of oncology, cancer biology, and bioinformatics tools, highlighting the challenges in statistical learning, experimental validation, data processing, and quality control that underpin this transformative field. This review outlines the methodologies and applications of bioinformatics tools in cancer genomics research, encompassing tools for data structuring, pathway analysis, network analysis, tools for analyzing biomarker signatures, somatic variant interpretation, genomic data analysis, and visualization tools. Open-source tools and repositories like The Cancer Genome Atlas (TCGA), Genomic Data Commons (GDC), cBioPortal, UCSC Genome Browser, Array Express, and Gene Expression Omnibus (GEO) have emerged to streamline cancer omics data analysis. Bioinformatics has significantly impacted cancer research, uncovering novel biomarkers, driver mutations, oncogenic pathways, and therapeutic targets. Integrating multi-omics data, network analysis, and advanced ML will be pivotal in future biomarker discovery and patient prognosis prediction.

Setting Up the JBrowse 2 Genome Browser.

JBrowse 2 is a modular genome browser that can visualize many common genomic file formats. While JBrowse 2 supports a variety of different usages, it is particularly suited for deployment on websites, such as model organism databases or other web-based genomic data resources. This protocol provides detailed instructions for setting up JBrowse 2 on an Ubuntu Linux web server, loading a reference genome from a FASTA format file, and adding a gene annotation track from a GFF3 format file. By the end of the protocol, users will have a working JBrowse 2 instance that is accessible via the web. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Setting up JBrowse 2 on your web server.

Comprehensive identification of genomic and environmental determinants of phenotypic plasticity in maize.

Maize phenotypes are plastic, determined by the complex interplay of genetics and environmental variables. Uncovering the genes responsible and understanding how their effects change across a large geographic region are challenging. In this study, we conducted systematic analysis to identify environmental indices that strongly influence 19 traits (including flowering time, plant architecture, and yield component traits) measured in the maize nested association mapping (NAM) population grown in 11 environments. Identified environmental indices based on day length, temperature, moisture, and combinations of these are biologically meaningful. Next, we leveraged a total of more than 20 million SNP and SV markers derived from recent de novo sequencing of the NAM founders for trait prediction and dissection. When combined with identified environmental indices, genomic prediction enables accurate performance predictions. Genome-wide association studies (GWASs) detected genetic loci associated with the plastic response to the identified environmental indices for all examined traits. By systematically uncovering the major environmental and genomic factors underlying phenotypic plasticity in a wide variety of traits and depositing our results as a track on the MaizeGDB genome browser, we provide a community resource as well as a comprehensive analytical framework to facilitate continuing complex trait dissection and prediction in maize and other crops. Our findings also provide a conceptual framework for the genetic architecture of phenotypic plasticity by accommodating two alternative models, regulatory gene model and allelic sensitivity model, as special cases of a continuum.

In Silico Analysis of the Missense Variants of Uncertain Significance of CTNNB1 Gene Reported in GnomAD Database.

CTNNB1 pathogenic variants are related to the improper functioning of the WNT/β-catenin pathway, promoting the development of different types of cancer of somatic origin. Bioinformatics analyses of genetic variation are a great tool to understand the possible consequences of these variants on protein structure and function and their probable implication in pathologies. The objective of this study is to describe the impact of the missense variants of uncertain significance (VUS) of the CTNNB1 gene on structure and function of the β-catenin protein. The CTNNB1 variants were obtained from the GnomAD v2.1.1 database; subsequently, a bioinformatic analysis was performed using the VarSome, UCSC Genome Browser, UniProt, the Kinase Library database, and DynaMut2 platforms to evaluate clinical significance, gene conservation, consensus sites for post-translational modifications, and the dynamics and stability of proteins. The GnomAD v2.1.1 database included 826 variants of the CTNNB1 gene, of which 385 were in exons and exon/intron boundaries. Among these variants, 214 were identified as missense, of which 146 were classified as VUS. Notably, 12 variants were in proximity to consensus sites for post-translational modifications (PTMs). The in silico analysis showed a slight tendency towards probably pathogenic for c.59C>T (p.Ala20Val) and c.983T>C (p.Met328Thr) missense VUS. These findings provide possible functional implications of these variants in some types of cancer.

The Genome Explorer genome browser.

Genome browsers provide graphical depictions of genome information to speed the uptake of complex genome data by scientists. They provide search operations to help scientists find information and zoom operations to enable scientists to view genome features at different resolutions. We introduce the Genome Explorer browser, which provides extremely fast zooming and panning of genome visualizations and displays with high information density.

An efficient in vivo-inducible CRISPR interference system for group A Streptococcus genetic analysis and pathogenesis studies.

While group A Streptococcus (GAS) remains a predominant cause of bacterial infections worldwide, there are limited genetic tools available to study its basic cell biology. Here, we bridge this gap by creating a highly transformable, fully virulent M1T1 GAS strain. In addition, we established a tight and titratable doxycycline-inducible system and developed CRISPR interference (CRISPRi) for controlled gene expression in GAS. We show that CRISPRi is functional in vivo in a mouse infection model. Additionally, we present SpyBrowse, an intuitive and accessible genome browser (https://veeninglab.com/SpyBrowse). Overall, this work overcomes significant technical challenges of working with GAS and, together with SpyBrowse, represents a valuable resource for researchers in the GAS field.