Pacific Biosciences (United States)

Anthocyanins are specialized flavonoid pigments that play critical roles in plant coloration, photoprotection, and responses to environmental stress. Arabidopsis thaliana serves as a valuable genetic model for dissecting anthocyanin biosynthesis and regulatory networks. Conventional methods for anthocyanin quantification, such as crude spectrophotometric assays, often compromise pigment integrity, yield inconsistent results, and provide limited information on compound composition. Here, we describe a simple, reproducible, and high-fidelity protocol for the induction, extraction, quantification, and chromatographic profiling of anthocyanins in Arabidopsis thaliana seedlings. The workflow employs well-defined anthocyanin-inductive conditions (AIC), methanol/formic acid extraction, lyophilization for dry-weight normalization, and dual quantification via spectrophotometry and High-performance liquid chromatography with diode-array detection (HPLC-DAD) analysis. This protocol enables accurate comparison between wild-type and mutant genotypes, facilitating both mutant screening and metabolic pathway analysis. The approach minimizes pigment degradation, enhances reproducibility across replicates, and offers a robust tool for research in plant metabolism, stress physiology, and flavonoid biochemistry.Key features• This protocol establishes well-defined anthocyanin-inductive conditions (AIC) using sucrose and continuous light, enabling reproducible pigment accumulation in Arabidopsis thaliana seedlings.• This protocol employs methanol/formic acid extraction and lyophilization to maintain anthocyanin stability and minimize degradation during sample processing.• This protocol integrates spectrophotometric OD532 normalization with HPLC-DAD profiling for quantification of total anthocyanins and characterization of individual anthocyanin species.• This protocol is suitable for mutant screening, metabolic pathway analysis, and stress-response studies in Arabidopsis thaliana.

Hi-C characterizes three-dimensional chromatin organization, facilitates haplotype phasing, and enables genome-assembly scaffolding, but encounters difficulties across complex regions. By coupling chromosome conformation capture (3C) with PacBio HiFi long-read sequencing, here we develop a method (CiFi) that enables analysis of genomic interactions across repetitive regions. Starting with as little as 60,000 cells (sub-microgram DNA), the method produces multi-kilobasepair HiFi reads that contain multiple interacting, concatenated segments (~350 bp to 2 kbp). This multiplicity and increase in segment length versus standard short-read-based Hi-C improves read-mapping efficiency and coverage in repetitive regions and enhances haplotype phasing. CiFi pairwise interactions are largely concordant with Hi-C from a human lymphoblastoid cell line, with gains in assigning topologically associating domains across centromeres, segmental duplications, and human disease-associated genomic hotspots. As CiFi requires less input versus established methods, we apply the approach to characterize single small insects: assaying chromatin interactions across the genome from an Anopheles coluzzii mosquito and producing a chromosome-scale scaffolded assembly from a Ceratitis capitata Mediterranean fruit fly. Together, CiFi enables assessment of chromosome-scale interactions of previously recalcitrant low-complexity loci, low-input samples, and small organisms.

BackgroundEpigenetic modifications, such as DNA methylation, regulate transcription and influence key biological traits. While many efforts were made to understand their stability in annual crops, their long-term persistence in clonally propagated plants remains poorly understood. Grapevine (Vitis vinifera) provides a unique model, with cultivars vegetatively propagated for centuries.ResultsHere, we assemble the phased genomes of Cabernet Sauvignon and its parental lineages, Cabernet Franc and Sauvignon Blanc, using HiFi long-reads and a gene map tenfold denser than existing maps. Using three clones per cultivar, we quantify methylation with very consistent short- and long-read sequencing and ensure both varietal representativeness and assessment of clonal variability. We leverage the parent-progeny sequence graph to highlight allele-specific methylation and conserved transcriptomic patterns for genes and small RNA. Such a format is essential to integrate multi-omics data and reveals that, despite less clonal conservation than genetic polymorphisms, methylation marks are remarkably inherited. By further demonstrating the linear-reference limitations, we determine that the correct representation of genetic variants by the sequence graph is crucial for the accurate allelic quantification of the methylome.ConclusionsThese findings reveal the remarkable stability of epigenetic marks in a model propagated by asexual reproduction. Using a phased sequence graph, we introduce a scalable framework that accounts for genomic variation, accurately quantifies allele-specific methylation, and supports multi-omics integration such as our evaluation of the transcriptional impact of epigenetic inheritance. This approach has broad implications for perennial crops, where epigenetic variation could influence traits relevant to breeding, adaptation, and long-term agricultural sustainability.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13059-025-03858-2.

Our main objective for the CACHE Challenge #6 was to identify novel inhibitors of SETDB1 that bind to its distinctive triple Tudor domain (TTD). As CACHE challenges are inherently collaborative, we partnered with HTuO Biosciences Inc., a Vancouver-based company developing advanced physics-based computational drug discovery technology, to share knowledge and expertise. Together, we developed a comprehensive drug discovery workflow focused on a structure-based approach. First, we carried out in-depth structural analysis on the existing SETDB1 crystal structures to identify key structural elements that we could leverage in a prospective screening campaign. Then, we carried out a retrospective benchmarking study (i.e., self-, cross-docking) of our docking program Fitted on a select number of structures, followed by extensive pharmacophore modeling. We implemented the learnings from previous CACHE challenges by considering a relatively large library of small molecules (Enamine REAL Diversity Set, ~67M compounds) for screening. We filtered this library according to CACHE and medicinal chemistry guidelines and screened it against our pharmacophore models, obtaining ~263K hits. We used Fitted to dock and score these compounds against several SETDB1 structures and our in-house protein-ligand analysis platform to identify those compounds that interacted with key amino acids identified in our structural analysis (~26K compounds). We further trimmed down the list using a combination of ranking by dock score and clustering, to arrive at a final list of 629 compounds for visualization. We developed a thorough visual inspection scheme that focused on aspects such as key protein-ligand interactions, ligand conformation, favorable and unfavorable contacts, and overall pocket fit. Compounds were scored by each team member on a scale of 1-10 and statistics were gathered; the compounds were assigned to different confidence tiers (low, medium-low, medium-high, high), depending on the standard deviation of the visual scores. The compounds from the (medium-)high tiers with a mean score ≥ 5.5 were automatically advanced to rescoring with AtomForge, a highly accurate polarizable general-purpose forcefield developed by HTuO Biosciences for use in drug discovery. Compounds in the (medium-)low tiers were debated as a group and included in the selection for rescoring if arguments for their inclusion were persuasive. Overall, 186 compounds were rescored. The selection of the preliminary list of 150 compounds focused primarily on compounds with good docking/visual scores and AtomForge affinity ranking better than positive controls. However, we also sampled compounds with different combinations of docking scores, visual scores, and AtomForge affinity ranking, which will allow us to critique our different evaluation metrics. From this list, we selected 100 compounds for purchase and testing based on practical considerations of cost, availability, and synthetic feasibility.

BackgroundStructural variants are genomic variants that impact at least 50 nucleotides. Structural variants can play major roles in diversity and human health. Many structural variants are difficult to interpret and understand with existing visualization tools, especially when comprised of inverted sequences or multiple breakend pairs.ResultsWe present SVTopo, a tool to visualize germline structural variants with supporting evidence from high-accuracy long reads in easily understood figures. We include examples of 101 visually complex structural variants from seven unrelated human genomes, manually assigned to ten categories. These demonstrate a broad spectrum of rearrangement and showcase the frequency of complex structural variants in human genomes.ConclusionsSVTopo shows breakpoint evidence in ways that aid reasoning about the impact of multi-breakpoint rearrangements. The images created aid human reasoning about the result of structural variation on gene and regulatory regions.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12864-025-12088-6.

Rheumatoid arthritis synovial fibroblasts (RASFs) play a pivotal role in joint destruction in RA. Myostatin (MSTN), a myokine, is highly expressed in the RA synovium; however, its role in the function of RASFs is unclear. We hypothesized that MSTN amplifies inflammatory cytokines/chemokines, promotes RASF invasion, and facilitates CD4+ Th cell transmigration. Immortalized MH7A cells (RASFs) and healthy synovial fibroblasts (HSFs) were treated with MSTN (0, 10, 20 ng/mL) for 0, 24, and 48 h. Cytokines (IL-8, IL-17, TNF-α, IL-6, IL-23, IFN-γ, IFN-β) and chemokines (CCL2, CCL20, CXCL13, CXCL1) were quantified by ELISA, RT-qPCR, and Western blotting. To evaluate MSTN regulation, cells were treated with pro-inflammatory mediators (TNF-α, IL-17, IFN-γ, IFN-β, CCL2, CXCL1). MSTN’s effects on Thy-1(CD90)+ RASF/HSF proliferation, RASF invasion, and CD4+ T-cell transmigration were assessed. Compared with HSFs, RASFs exhibited greater proliferative activity. MSTN significantly upregulated cytokines/chemokines, with CXCL1 showing the strongest induction in RASFs. IFN-γ and IL-17 robustly increased MSTN expression, indicating a feed-forward loop. MSTN did not alter Thy-1(CD90)+ fibroblast proliferation but significantly enhanced RASF invasion and CD4+ T-cell transmigration. Neutralizing CXCL1 or IL-17 reduced transmigration, with stronger inhibition via CXCL1. These findings offer new insights into the role of MSTN in RA pathogenesis and highlight its potential as a therapeutic target.

Multimodal transcriptional analysis reveal how Ewing sarcoma tumors use distinct gene programs, including one linked to TGF-β, to drive cancer behavior and progression.

ABSTRACTCRISPR technologies are rapidly transforming agriculture by enabling precise and programmable modifications across a wide range of organisms. This review provides an overview of CRISPR applications in crops, livestock, aquaculture, and microbial systems, highlighting key advances in sustainable agriculture. In crops, CRISPR has accelerated the improvement of traits such as drought tolerance, nutrient efficiency, and pathogen resistance. In livestock and aquaculture, CRISPR has enabled disease‐resistant pigs and poultry, hornless cattle, and fast‐growing, stress‐tolerant fish. Engineered microbes are also being leveraged to enhance nitrogen fixation and reduce input reliance. We examine the evolution of CRISPR tools, such as base and prime editing, multiplex editing, and epigenome modulation, that expand precision and control beyond traditional gene knockouts. These innovations offer significant advantages over conventional breeding, yet challenges remain, including off‐target effects, delivery efficiency, and regulatory variability across countries. The review also explores emerging directions such as novel Cas variants and AI‐integrated breeding platforms for high‐throughput trait discovery. Together, these developments demonstrate the transformative potential of CRISPR technology to reshape agriculture, not only by enhancing productivity and resilience but also by reducing environmental impacts. With responsible implementation, CRISPR‐enabled innovations are well‐positioned to support global food security and sustainability targets by 2050.