Base Pairs Research Articles

Abstract 5034: Comparative whole genome sequencing between matched cryopreserved and FFPE tumor samples

Background & Aims: Next generation sequencing, specifically whole genome sequencing (WGS), plays a key role in precision medicine. Currently, the main source of cancer biospecimens for WGS is formalin-fixed, paraffin-embedded (FFPE) tissues. This is partly because cryopreserved (CP) tissues have not been routinely stored in real-world clinical settings. This study aimed to compare the outcomes of WGS by using matched CP and FFPE samples. We hypothesized that CP samples would demonstrate superior quality metrics before and after sequencing the DNA. Methods: A total of 50 matched pairs of CP and FFPE tumor samples were obtained from patients with various types of cancers, primarily representing gynecological cancers. DNA was extracted and quality and quantity were determined. WGS was performed using 200 ng of DNA extracted from each sample. We conducted a comparison between CP and FFPE samples in terms of the sequencing quality control metrics and the number of identified variants. Results: Our samples consisted of 18 ovary, 5 liver, 6 kidney, 7 uterus, 4 colon, and 10 other cancers. Metrics were obtained before sequencing, and it was found that gDNA concentration in ng/ul was significantly higher in CP (85.2) than FFPE (12.5) tissue. Additionally, DIN number (FFPE: 4.7; CP: 8.4) and fragment size in base pairs (FFPE: 444.1; CP: 644.6) were also significantly higher in CP tissue. WGS was then performed, and it was found that both mean read depth (FFPE: 34.6; CP: 54.2) and insert size (FFPE: 243.6 CP: 365.7) were significantly higher in CP than FFPE tissues. The percentage mapped over 15x was similar and not statistically different with FFPE being 99.3% and CP being 99.7%. To determine concordance between the matched samples, 94,147 variants were found in FFPE, and 80,036 variants were found in CP. The median point mutation overlap (VAP>=5.0%) was used to find a concordance percentage, with that being 43.5% between FFPE and CP tissues (shared: 51,619; FFPE: 38,690; CP:28,434). Tumer mutation burden was determined on 8 samples because germ line sequencing was performed on available blood samples. FFPE had a TMB of 13.7 and CP exhibited a TMB of 6.4, demonstrating a statistical difference with a p-value = 0.02. Lastly, structural variance was evaluated and FFPE averaged 21 and CP averaged 38. Conclusion: WGS utilizing CP samples provides superior quality indices compared to FFPE samples. Despite matched samples, there was significant discordance in variants identified in the cancers. Therefore, CP sample collection should be prioritized when performing WGS. Citation Format: Paytin Curran, DeLaney Anderson, Jeffrey Okojie, Ryan Miller, Sangmoon Lee, Ken Dixon, Jared James Barrott. Comparative whole genome sequencing between matched cryopreserved and FFPE tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5034.

Abstract 3754: ecDNAInspector nominates high-confidence structural predictions of extrachromosomal DNA for downstream analysis

Abstract Extrachromosomal DNA (ecDNA) are circular, megabase-scale regions of the genome found outside canonical chromosomes and characterized by high copy-number and frequent oncogene amplification. They are implicated in tumorigenesis, therapeutic resistance, and shortened survival for patients across multiple cancer types. Existing tools to identify and predict ecDNA structures are limited to low throughput, high sensitivity enrichment-based assays or high throughput, low sensitivity computational methods using whole-genome sequencing data. Recent advances in long-read sequencing offer potential improvements in ecDNA detection but such data are currently limited. Evaluating the impact of ecDNA in relation to clinical characteristics requires large cohorts such as The Cancer Genome Atlas (TCGA) or the International Cancer Genome Consortium (ICGC). Hence, there is value in leveraging short-read sequencing data from these existing cohorts while improving confidence in computational predictions of ecDNA presence and structure. Here we present ecDNAInspector, a computational tool that enables systematic selection of high-confidence ecDNA predictions from sequencing data. Each ecDNA prediction is characterized using structure-based metrics: an extreme cycle size Boolean, a breakpoint mapping error Boolean, and adapted classification metrics that assess the frequency of paired ends between neighboring cycle segments with orthogonal structural variant call support. ecDNA predictions are clustered by these metrics and the user can select high-confidence groups. A subsequent filtering step enables rescue of additional ecDNA predictions based on user-defined thresholds. After selection of a final high-confidence group of ecDNA predictions, ecDNAInspector offers modules for structural comparison and analysis of ecDNA within a cohort, including inspection of structural conservation (i.e. maintenance of similar sequence) and feature comparisons across tumors. Applying ecDNAInspector to a breast cancer cohort, we nominated a subset of high-confidence ecDNA with strong orthogonal structural variant support and additional indicators of high quality. We identified both base pair and oncogene inclusion conservation within breast cancer subtype groups, and noted significant variations in structural metrics across subtype groups. Since structure often indicates origin and dictates function, these differences suggest potential biological differences in ecDNA genesis and evolution across breast cancer subtypes. Thus, ecDNAInspector provides a systematic method for selecting high-confidence ecDNA predictions for downstream structural analysis, enabling improved utilization of existing sequencing data in valuable clinical cohorts. Citation Format: Sophia J. Pribus, Kathleen E. Houlahan, Lise Mangiante, Christina Curtis. ecDNAInspector nominates high-confidence structural predictions of extrachromosomal DNA for downstream analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3754.

Abstract 4663: Human papillomavirus circulating tumor DNA for risk stratification in cervical cancer

Background: Human papillomavirus (HPV) DNA is detectable in the peripheral blood plasma from patients with locally advanced and metastatic cervical cancer. Levels of HPV circulating tumor DNA (ctDNA) in pretreatment plasma have weak associations with prognosis, but the significance of detecting HPV integration into the host genome or fragmentation features within HPV ctDNA has not been explored. We hypothesized that these molecular features of HPV ctDNA may serve as prognostic biomarkers and reflect HPV biology, independent from total ctDNA abundance. Methods: Plasma cell-free DNA was collected at baseline from 57 patients with locally advanced cervical cancer (stage IB-IVA) and 21 patients with metastatic cervical cancer. Whole viral genome sequencing was performed following hybrid capture. HPV ctDNA levels were expressed in copies/mL plasma. HPV integration sites were detected using SearcHPV. Progression-free survival (PFS) was evaluated using Kaplan-Meier analysis and log-rank tests. The normalized fragment midpoint coverage across the HPV-16 genome was calculated for individual samples and averaged across patient groups. NuPoP, was used to calculate the expected nucleosome occupancy at each base pair of the HPV-16 genome. Peaks corresponding to the observed nucleosome occupancy within our cohorts were called using pracma, and occupancy probabilities were calculated for each peak. Results: Baseline HPV ctDNA levels were detected in 57/57 locally advanced patients (median=283 copies/mL) and 20/21 metastatic patients (median=299 copies/mL). Unique HPV integration sites were detected at varying levels in 21/57 locally advanced patients (median sites:1, range:0-23) and 12/21 metastatic patients (median sites:2, range:0-45) (Wilcoxon p=0.8). No significant differences in PFS were observed in locally advanced or metastatic patients when stratified by median ctDNA levels (p=0.7 and p=0.8 respectively). However, high confidence integration detected at baseline was associated with inferior PFS in locally advanced patients (p=0.01), but not metastatic (p=0.28). HPV ctDNA fragment coverage varied across the HPV-16 genome with the number of observed merged peaks being 32 in the locally advanced cohort (n=36) and 31 in the metastatic cohort (n=14). The median expected nucleosome occupancy probabilities across all peaks were 98.6% and 97.2%, respectively. Conclusion: Detection of viral integration within baseline HPV ctDNA was associated with significantly inferior PFS in locally advanced patients. Peaks in the average HPV-16 ctDNA coverage profiles corresponded to high expected nucleosome occupancy in both the locally advanced and metastatic cohorts, suggesting that ctDNA may reflect chromatin accessibility of the virus. These findings suggest that quantitative and qualitative features of HPV ctDNA from baseline plasma may reflect HPV biology associated with cervical cancer. Citation Format: Emma M. Collier, Lucas Penny, Jinfeng Zou, Zhen Zhao, Yangqiao Zheng, Pamela Soberanis Pina, Michelle McMullen, Eric Y. Stutheit-Zhao, Michael M. Hoffman, Sarah E. Ferguson, Kathy Han, Eric Leung, Stephanie Lheureux, Scott V. Bratman. Human papillomavirus circulating tumor DNA for risk stratification in cervical cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4663.

Abstract 3697: Cell-free DNA fragmentome dynamics as a biomarker for immune-checkpoint inhibition in advanced carcinoma

Background: Immune-checkpoint inhibitors (ICIs) have revolutionized cancer treatment, but a large proportion of patients is resistant to the treatment. Genome-wide cfDNA fragmentation profiles (fragmentome) represent a promising non-invasive approach able to monitor and predict response. Methods: The SChISM (Size cfDNA Immunotherapies Signature Monitoring) enrolled 128 advanced pan-cancer ICI-treated patients. Using Adelis technologies (France), based on the patented BIABooster system, pre- and on-treatment cfDNA size profiles were generated from the plasma, without prior DNA extraction. First, associations of pre-treatment fragmentome-derived metrics (e.g., concentration within multiple size ranges, position of peaks in the distribution) with early progression (EP, defined as progression at the first imaging evaluation) and progression-free survival (PFS) were assessed using logistic/Cox proportional hazard regression models. To assess predictive performances, data were split into training (n=90) and test (n=38) sets. Then, a mechanistic model for the joint dynamics of cfDNA and tumor lesions at the systemic level was developed. It relies on the following biological hypotheses: 1), wild-type cfDNA is primarily released through the apoptosis of hematopoietic cells, 2) cancer cells can be either resistant or sensitive to treatment, 3) cancer cells release a higher amount of DNA fragments due to the chaotic apoptosis-proliferation cycle characteristics of tumor cells, 4) cfDNA fragments are continuously cleared by liver and kidneys, with half-life ranging from 15min to 2h, 5) immunotherapy induces apoptosis in cancer cells, leading to the release of short cfDNA fragments, and 6) in the tumor microenvironment, cells undergo necrosis as the tumor grows, resulting in the release of longer fragments. Results; The ratio of long fragments (≥ 1650 base pairs (bp), LF) - normalized by total concentration - was significantly associated with non-EP (odds ratio = 0.3 (95%: 0.16-0.55), p <0.001) and longer PFS (p<0.001, hazard ratio 0.44 (95%: 0.31 - 0.64)). It also showed the best predictive performances of EP, on the test set: AUC = 0.74 (95% (CI): 0.65-0.82)), accuracy = 0.71 (95% CI: 0.62-0.77), positive predictive value 0.58 (0.46-0.69). The mechanistic model was able to accurately describe cfDNA-cancer dynamics under ICI, including steady decrease/increase of cfDNA concentration in either the long- or short-size ranges, but also non-trivial patterns, such as initial cfDNA concentration bumps. Conclusions: High-molecular-weight fragments are associated with early progression in ICI-treated patients. Mechanistic modeling offers biological insights for the interplay between cfDNA and tumor kinetics. Citation Format: Linh Nguyen Phuong,Frédéric Fina,Romain Zakrajsek,Laurent Greillier,Pascale Tomasini,Jean-Laurent Deville,Audrey Boutonnet,Frédéric Ginot,Jean-Charles Garcia,Sébastien Salas,Sébastien Benzekry. Cell-free DNA fragmentome dynamics as a biomarker for immune-checkpoint inhibition in advanced carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3697.

Abstract 4560: Use of ctDNA fragmentomics as a predictive biomarker in locally advanced non-small cell lung cancer

Abstract Introduction: Locally advanced non-small cell lung cancer (NSCLC) is a serious condition with a poor 5-year survival rate of approximately 30%. Standard treatment involves chemoradiotherapy (CRT) followed by immunotherapy (IO). However, predicting benefit prior to CRT and monitoring response post treatment are areas of unmet need. Cancers, like many tissues, release fragments of DNA into the bloodstream, which can be detected using whole genome sequencing (WGS). Research has shown that cancer cells tend to release shorter DNA fragments, typically between 90-150 base pairs, at higher rates than normal tissues. This study aims to analyze cell-free DNA fragment sizes (fragmentomics) as a predictive tool for assessing treatment response in patients with LA NSCLC. This tumor-uninformed approach is cost-effective and can be implemented using routine blood samples. Methods: Low-pass WGS at 0.1x coverage was performed on 40 pre-treatment plasma samples from patients LA NSCLC obtained from the UCL biobank. The median follow-up for the cohort was 33 months. To investigate the cancer origin of short DNA fragments (90-150 bp), mutation calling was conducted using Mutect2. Mutation density was defined as the number of mutations per million bases (MPM). Tumor volumes were obtained using CT imaging, and the percentage quantity of short DNA fragments was plotted against tumor volume. Enrichment of short fragments (SFE) <20% was assessed and correlated with clinical outcomes, including relapse and overall survival. Results: Short DNA fragments (90-150 bp) had a significantly higher mutation density (973.8 MPM) compared to unselected fragments (381.7 MPM; p<0.0001). This elevated mutational burden supports the hypothesis that shorter fragments are of cancer origin. Linear regression analysis showed no significant relationship between tumor volume and the percentage of short DNA fragments for the entire cohort (R2 = 0.035, p = 0.35). However, in lung squamous cell carcinoma (LUSC), a strong positive correlation was observed (R2 = 0.6787, p = 0.003). Suggesting a potential quantitative link between tumor burden and ctDNA quantity in this subtype. SFE was observed in 31 of 40 patients (78%) prior to treatment. SFE was found in similar proportions in LUSC (78%; 15/19) and lung adenocarcinoma (75%; 15/20). Mortality occurred in 45% (14/31) of patients with SFE, compared to 11.1% (1/9) of those without enrichment. Among patients for whom consolidation IO was indicated, relapse rates were higher in those with SFE (44%; 7/16) than in those without enrichment (25%; 1/4). Findings of the research were limited by sample size; however further centers have been recruited to address this issue. These findings suggest that fragmentomic patterns represent a cost-effective, non-invasive prognostic biomarker for LA NSCLC, with particular potential in LUSC. Ongoing research is exploring patterns following treatment. Citation Format: Kishen R. Patel, Anisha Mistry, Robert Monfries, Florent Mouliere, John R. Conibear, James Wilson, Karim Keshwani, Wing K. Liu, Crispin Hiley. Use of ctDNA fragmentomics as a predictive biomarker in locally advanced non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4560.

Abstract 4089: A novel NGS-based sample tracking system for robust sample chain of custody and quality control in fresh frozen and FFPE tumor samples

Abstract When processing large cohorts of samples, sample identity and functional quality are key to ensure the derived data is accurate and attributed to the appropriate sample. This is especially critical when working with precious and degraded material such as formalin-fixed paraffin-embedded (FFPE) samples. A potential sample swap or poor sample quality may result in incorrect data or delays due to re-processing. While traditional methods such as qPCR can be used for quality control, they may not be an effective predictor of sample success in Next-Generation Sequencing (NGS) based assays due to differential susceptibility to inhibitors and interfering substances. Performing a functional quality control assessment using the same methodology for data generation allows for a more accurate prediction of performance as it would be similarly affected by interfering substances or sample degradation. We have created a scalable, cost-effective sample tracking and functional quality control assay that may be assessed prior to performing more expensive downstream sequencing assays. This assay was designed to confirm consistency in sample identity during processing and confirm identity when multiple samples are submitted from the same subject. This amplicon panel targets autosomal SNPs with varying minor allele frequencies in different ethnic populations, limiting a bias towards variation in European ethnic populations. The average minor allele frequency for the panel developed for the general population is 0.45, more specifically 0.46 for European background, 0.44 for African background and 0.46 for Asian background based on data from the Allele Frequency Aggregator (ALFA) database. Most amplicons were designed to be less than 150 base pairs to increase the likelihood of success for samples with degraded DNA. Targets were included on the X and Y chromosome for sex determination. Tumor-normal paired samples were processed on the sample tracking assay, targeting regions throughout the exome to allow tracking of sample identity. When comparing “normal” samples extracted from blood to their paired FFPE tumor tissue, known matches had an average of 98.0% concordance, while known mismatches had an average of 40.4% concordance, with the highest known mismatch showing 61.9% concordance. Additionally, when comparing well-characterized samples to their corresponding data from the 1000 Genomes Project, samples had 99.4% concordance. This exemplifies a robust sample tracking assay that can ensure sample identity is correct. A strong quality control assay enables NGS laboratories to identify poor sample quality or degradation, allowing for re-extraction or new sample collection before processing on a more expensive assay. This newly developed sample tracking assay ensures both sample integrity and identity, leading to an overall increase in data quality for cancer research studies. Citation Format: Katherine Milligan, Yu Qiu, Andrea O'Hara, Carrie Ziemniak, David Corney, Haythem Latif. A novel NGS-based sample tracking system for robust sample chain of custody and quality control in fresh frozen and FFPE tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4089.

Abstract 5039: Machine learning enhances histology-agnostic detection of PTEN deletions in panel sequencing of advanced cancers

Abstract Targeted panel sequencing of known genetic driver alterations is an established part of the initial clinical diagnostic routine for many tumors. However, exploratory sequencing for advanced and rare cancers remains experimental. MASTERsg is a prospective clinical broad panel sequencing program that utilizes the TSO500 and TST170 DNA/RNA sequencing assays to identify therapeutically relevant alterations in patients with advanced cancers. The TSO500 pipeline detects copy number variations (CNVs) by dividing the CNV caller’s raw data into gene-specific bins, each consisting of 50-250 base pairs. This approach enables the detection of both amplifications and deletions through bin count averaging. However, it may miss focal CNVs that do not meet the standard caller’s threshold fold change. This study aimed to enhance the CNV calling capabilities of the TSO500 pipeline to include focal CNVs. To achieve this, we developed a graphical representation of each gene's bins through plotting, enabling the visual identification of focal CNVs. Additionally, we sought to automate this identification process using machine learning, exemplified by detecting focal deletions of Phosphatase and Tensin homolog (PTEN), a tumor suppressor gene whose functional loss often serves as the basis for recommending mTOR/Akt inhibition in molecular tumor boards. For this purpose, we implemented an Extreme Gradient Boosting (XGBoost) model utilizing normalized PTEN bin counts, enhanced with feature transformations such as polynomial line fitting and derivative to capture read depth variations. Our dataset included 59 patients representing 20 advanced solid tumor entities: 29 PTEN deletions identified by the TSO500 pipeline with a gene-specific fold change cutoff of <0.65 (FC range: 0.05-0.64), five focal PTEN deletions detected only by visual bin plot analysis (FC range: 0.66-1.051), and 25 wildtype cases (FC range: 0.65-1.096). A balanced test set of 16 patients was selected for evaluation. To verify the results, all sequenced tumor samples underwent PTEN immunohistochemical (IHC) staining, with staining results quantified using the H-Score, which ranges from 0 (completely negative) to 300 (strongly positive).Our best-performing model achieved a Receiver Operating Characteristic Area Under the Curve (ROC AUC) of 0.97, accurately identifying all five focal PTEN deletions missed by the TSO500 pipeline. The biological relevance of these deletions was confirmed by IHC, with H-Scores of 0 in 4/5 cases and 35 in 1/5 cases. This study demonstrates that machine learning can enhance PTEN deletion detection in TSO500 panel sequencing, with potential applications for other genes. Prospective validation on additional tumor samples is currently ongoing. Citation Format: Irina A. Kerle, Oleksandr Husak, Thomas Gross, Andreas Hartig, Daniela Richter, Sascha Brückmann, Andreas Mock, Anja Kögler, Rebecca Prause, Alexander A. Wurm, Maximilian Werner, Dorothea Hanf, Lino Möhrmann, Doreen William, Daniela E. Aust, Evelin Schröck, Christoph Heining, Hanno Glimm. Machine learning enhances histology-agnostic detection of PTEN deletions in panel sequencing of advanced cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5039.

Trans-Kingdom RNA Dialogues: miRNA and milRNA Networks as Biotechnological Tools for Sustainable Crop Defense and Pathogen Control

MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 20–24 nucleotides in length, which play a crucial role during gene regulation in plant–pathogen interaction. They negatively regulate the expression of target genes, primarily at the transcriptional or post-transcriptional level, through complementary base pairing with target gene sequences. Recent studies reveal that during pathogen infection, miRNAs produced by plants and miRNA-like RNAs (milRNAs) produced by fungi can regulate the expression of endogenous genes in their respective organisms and undergo trans-kingdom transfer. They can thereby negatively regulate the expression of target genes in recipient cells. These findings provide novel perspectives for deepening our understanding of the regulatory mechanisms underlying plant–pathogen interactions. Here, we summarize and discuss the roles of miRNAs and milRNAs in mediating plant–pathogen interactions via multiple pathways, providing new insights into the functions of these RNAs and their modes of action. Collectively, these insights lay a theoretical foundation for the targeted management of crop diseases.

Decoding the Complex Functional Landscape of the ykkC Riboswitches.

The ykkC class is the most diverse riboswitch class to date, recognizing structurally and chemically diverse ligands using only minor changes in sequence and structure. Structural studies have demonstrated how sequence changes correspond to altered specificity; however, they are insufficient to define the requirements for functional riboswitch specificity. Here, we report an extensive mutational analysis of the ppGpp riboswitch to investigate the functional role in transcriptional control for this variant riboswitch. Disruption of the terminator hairpin at a single base pair is sufficient to abolish nearly all function, highlighting the fine-tuning of the terminator hairpin to its corresponding aptamer domain. This fine-tuning has been observed in other riboswitches, suggesting that high levels of tunability may be a common feature of riboswitches. Additionally, mutational analysis shows that the previously reported binding site position, G93, does not necessarily correspond to PRPP-driven function as expected. Phylogenetic analysis of natural riboswitches that contain G93 revealed an additional ykkC subclass that binds to both XMP and GMP. This variant subclass is associated with genes for de novo GMP synthesis. Identification of this variant class provides further evidence for small sequence changes corresponding to altered ligand specificity.

MCDAG: indexing maximal common subsequences for k strings

Analyzing and comparing sequences of symbols is among the most fundamental problems in computer science, possibly even more so in bioinformatics. Maximal Common Subsequences (MCSs), i.e., inclusion-maximal sequences of non-contiguous symbols common to two or more strings, have only recently received attention in this area, despite being a basic notion and a natural generalization of more common tools like Longest Common Substrings/Subsequences. In this paper we simplify and engineer recent advancements in MCSs into a practical tool called MCDAG, the first publicly available tool that can index MCSs of real genomic data, and show that its definition can be generalized to multiple strings. We demonstrate that our tool can index pairs of sequences exceeding 10,000 base pairs within minutes, utilizing only 4-7% more than the minimum required nodes. For three or more sequences, we observe experimentally that the minimum index may exhibit a significant increase in the number of nodes.

Multimeric transcription factor BCL11A utilizes two zinc-finger tandem arrays to bind clustered short sequence motifs

BCL11A, a transcription factor, is vital for hematopoiesis, including B and T cell maturation and the fetal-to-adult hemoglobin switch. Mutations in BCL11A are linked to neurodevelopmental disorders. BCL11A contains two DNA-binding zinc-finger arrays, low-affinity ZF2-3 and high-affinity ZF4-6, separated by a 300-amino-acid linker. ZF2-3 and ZF4-5 share 73% identity, including five out of six DNA base-interacting residues. These arrays bind similar short sequence motifs in clusters, with the linker enabling a broader binding span. Crystallographic structures of ZF4-6, in complex with oligonucleotides from the β-globin locus region, reveal DNA sequence recognition by residues Asn756 (ZF4), Lys784 and Arg787 (ZF5). A Lys784-to-Thr mutation, linked to a neurodevelopmental disorder with persistent fetal globin expression, reduces DNA binding over 10-fold but gains interaction with a variable base pair. BCL11A isoforms may form oligomers, enhancing chromatin occupancy and repressor functions by allowing multiple copies of both low- and high-affinity ZF arrays to bind DNA. These distinctive properties, apparently conserved among vertebrates, provide essential functional flexibility to this crucial regulator.

Tracking the folding of RNA at its birth.

Tracking the folding of RNA at its birth.

Mechanistic insights into RNA cleavage by human Argonaute2-siRNA complex.

In animals, AGO-clade Argonaute proteins utilize small interfering RNAs (siRNAs) as guides to recognize target with complete complementarity, resulting in target RNA cleavage that is a critical step for target silencing. These proteins feature a constricted nucleic acid-binding channel that limits base pairing between the guide and target beyond the seed region. How the AGO-siRNA complexes overcome this structural limitation and achieve efficient target cleavage remains unclear. We performed cryo-electron microscopy of human AGO-siRNA complexes bound to target RNAs of increasing lengths to examine the conformational changes associated with target recognition and cleavage. Initially, conformational transition propagates from the opening of the PAZ domain and extends through a repositioning of the PIWI-L1-N domain toward the binding channel, facilitating the capture of siRNA-target duplex. Subsequent extension of base pairing drives the downward movement of the PIWI-L1-N domain to enable catalytic activation. Finally, further base pairing toward the 3' end of siRNA destabilizes the PAZ-N domain, resulting in a "uni-lobed" architecture, which might facilitate the multi-turnover action of the AGO-siRNA enzyme complex. In contrast to PIWI-clade Argonautes, the "uni-lobed" structure of the AGO complex makes multiple contacts with the target in the central region of the siRNA-target duplex, positioning it within the catalytic site. Our findings shed light on the stepwise mechanisms by which the AGO-siRNA complex executes target RNA cleavage and offer insights into the distinct operational modalities of AGO and PIWI proteins in achieving such cleavage.

Establishment of a simple prediction method for DNA melting temperature: high-resolution melting curve analysis of PCR products.

High-resolution melting analysis is a technique that leverages the principle that the thermal stability of dsDNA is influenced by its length and base composition. This method generates a melting curve by real-time monitoring of the changes in fluorescence signal as dsDNA melts during the heating process. The melting temperature serves as a fundamental indicator of sample characteristics in HRM analysis. During the initial stages of designing a new HRM experimental system, accurately predicting the Tm position of the established system can significantly enhance research efficiency. Currently, there is a limited number of studies focused on the prediction of Tm values in HRM analysis, with varying levels of predictive accuracy. The nearest-neighbor method model can well reflect the interaction of adjacent base pairs. Therefore, we combined the nearest neighbor method model and applied parameters such as enthalpy change, entropy change, GC content and number of base pairs of the DNA sequence to derive a new empirical formula for predicting Tm values. In this study, five species of seawater diatoms were selected as the research subjects. Four specific primers were employed to amplify the extracted DNA through PCR, and the resulting amplified products underwent HRM analysis and Sanger sequencing. Based on the obtained DNA sequences, we calculated the corresponding GC content, number of base pairs, enthalpy change and entropy change, combined with the Tm value obtained from the experiment. Finally, the following formula for predicting Tm value is obtained: (1) When the GC content is 40%≤GC content≤60%: Tm=ΔH/ΔS-0.27GC%-(150+2n)/n-273.15; (2) When the GC content is <40%: Tm=ΔH/ΔS-GC%/3-(150+2n)/n-273.15. After that, the DNA sequences amplified using two other specific primers were verified, and the predicted Tm values were compared with the measured values. The average error was within 1 °C.The results show that the formula obtained in the study can accurately predict the Tm value, which can be effectively used to identify the species of unknown samples.Therefore, this Tm value prediction method provides new methods and ideas for solving practical problems in multiple related fields.

Isolation of a potentially arsenic-resistant Halomonas elongata strain (ml10562) from hypersaline systems in the Peruvian Andes, Cusco.

Halomonas elongata strain ml10562, was isolated from hypersaline that was collected from Acos Peru. Average Nucleotide Identity (ANI) and dDDH (digital DNA-DNA Hybridization) values between strain ml10562 and type strains of Halomonas elongata species were 71.0-78.4% and 18.8-21.5%, respectively. The draft genome, spanning 4,075,440 base pairs, has a GC content of 64.2% and contains 3,912 genes. Functional characterization revealed the strain's ability to tolerate and resist increasing concentrations of sodium arsenate, with a minimum inhibitory concentration of 25 mM. Bioinformatic analysis revealed the presence of two operons, arsR-arsH-arsB and arsJ-gapdh-arsC, in the genome of strain ml10562, which could play a crucial role in arsenic resistance through transporter-mediated mechanisms. Overall, these results emphasize the potential adaptability of H. elongata ml10562 to arsenic-containing environments and extend our understanding of bacterial arsenic resistance mechanisms, allowing promising applications in bioremediation.

Low overlap of transcription factor DNA binding and regulatory targets.

DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes1,2. How multiple TFs cooperate to regulate individual genes is still unclear. In yeast, most TFs are thought to regulate transcription via binding to upstream activating sequences, which are situated within a few hundred base pairs upstream of the regulated gene3. Although this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way. Here we integrated information on the binding and expression targets for the near-complete set of yeast TFs and show that, contrary to expectations, there are few TFs with dedicated activator or repressor roles, and that most TFs have a dual function. Although nearly all protein-coding genes are regulated by one or more TFs, our analysis revealed limited overlap between TF binding and gene regulation. Rapid depletion of many TFs also revealed many regulatory targets that were distant from detectable TF binding sites, suggesting unexpected regulatory mechanisms. Our study provides a comprehensive survey of TF functions and offers insights into interactions between the set of TFs expressed in a single cell type and how they contribute to the complex programme of gene regulation.

Germline mutation rates and fine-scale recombination parameters in zebra finch.

Most of our understanding of the fundamental processes of mutation and recombination stems from a handful of disparate model organisms and pedigree studies of mammals, with little known about other vertebrates. To gain a broader comparative perspective, we focused on the zebra finch (Taeniopygia castanotis), which, like other birds, differs from mammals in its karyotype (which includes many micro-chromosomes), in the mechanism by which recombination is directed to the genome, and in aspects of ontogenesis. We collected genome sequences from three generation pedigrees that provide information about 80 meioses, inferring 202 single-point de novo mutations, 1,088 crossovers, and 275 non-crossovers. On that basis, we estimated a sex-averaged mutation rate of 5.0 × 10-9 per base pair per generation, on par with mammals that have a similar generation time (~2-3 years). Also as in mammals, we found a paternal germline mutation bias at later stages of gametogenesis (of 1.7:1) but no discernible difference between sexes in early development. Examining recombination patterns, we found that the sex-averaged crossover rate on macro-chromosomes is 0.93 cM/Mb, with a pronounced enrichment of crossovers near telomeres. In contrast, non-crossover rates are more uniformly distributed. On micro-chromosomes, sex-averaged crossover rates are substantially higher (3.96 cM/Mb), in accordance with crossover homeostasis, and both crossover and non-crossover events are more uniformly distributed. At a finer scale, recombination events overlap CpG islands more often than expected by chance, as expected in the absence of PRDM9. Estimates of the degree of GC-biased gene conversion (59%), the mean non-crossover conversion tract length (~32 bp), and the non-crossover-to-crossover ratio (5.4:1) are all comparable to those reported in primates and mice. Therefore, properties of germline mutation and recombination resolutions remain similar over large phylogenetic distances.

Comparative Analysis of the Chloroplast Genomes of Cypripedium: Assessing the Roles of SSRs and TRs in the Non-Coding Regions of LSC in Shaping Chloroplast Genome Size

Cypripedium is renowned for its high morphological diversity and complex genetic and evolutionary characteristics. The chloroplast genome serves as a valuable tool for investigating phylogenetic relationships and evolutionary processes in plants. Currently, research on the evolution of the chloroplast genome within the Cypripedium genus is limited due to insufficient large-scale sampling and a lack of comprehensive understanding. Consequently, the mechanisms underlying the significant differences in chloroplast genome size among Cypripedium species remain poorly understood. In this study, we conducted a comprehensive comparative analysis of the chloroplast genomes of 29 Cypripedium species. The lengths of these genomes ranged from 162,092 to 246,177 base pairs (bp) and contained between 127 and 134 genes. Our results indicate that, while the overall structure of the chloroplast genomes in Cypripedium species is relatively conserved, significant differences were observed among the large single-copy (LSC), small single-copy (SSC), and inverted repeat (IR) regions. Several genes, including psaC, rpl32, ycf1, and psbK, exhibited higher levels of variability and may serve as molecular markers in taxonomic studies. The results of our correlation analysis suggest that the expansion of the LSC region, the increase in simple sequence repeats (SSRs), and tandem repeats (TRs) have significantly enlarged the size of the chloroplast genome in Cypripedium species. Phylogenetic signal testing supports the notion that genetic variation has driven species divergence within the genus. Overall, our findings provide insights into the substantial differences in chloroplast genome length observed among Cypripedium species. However, the relationship between diversification and the evolutionary mechanisms affecting Cypripedium, including ecological adaptive evolution, incomplete lineage sorting (ILS), hybridization, and reticulate events, requires further investigation.

Estimating mutation rate and characterising single nucleotide de novo mutations in pigs

BackgroundDirect estimates of mutation rates in humans have changed our understanding of evolutionary timing and de novo mutations (DNM) have been associated with several developmental disorders in humans. Livestock species, including pigs, can contribute to the study of DNM because of their ideal population structure and routine phenotype collection. In principle, there is the potential for livestock populations to quickly accumulate new genetic variants because of short generation intervals and high selection intensity. However, the impact of DNM on the fitness of individuals is not known and with current genomic selection programs they cannot contribute to estimated breeding values. The aims of our project were to detect and validate single nucleotide DNM in two commercial pig breeding lines, estimate the single nucleotide mutation rate, and characterise DNM.ResultsWe sequenced (150 bp paired end reads, 30X coverage) 46 pig trios from two commercial lines. Single nucleotide DNM were detected using a trio-aware method. We defined candidate DNM as single nucleotide variants (SNVs) found in heterozygous state in trio-offspring with both trio-parents homozygous for the reference allele. In this study, we estimate a lower threshold of the DNM rate in pigs of 6.3 × 10–9 per site per gamete. Our findings are consistent with those from other mammals and those published for a small number of livestock species. Most DNM we detected were in introns (47%) and intergenic regions (49%). The mutational spectrum in pigs differs from that in humans and we found several DNM predicted to have an effect on animal’s fitness based on the base pair change and their location in the genome.ConclusionsWith this study, we have generated fundamental knowledge on mutation rate in a non-primate species and identified DNM that could have an impact on the fitness of individuals.

Adaptive responses of Rhodococcus aetherivorans L13 to oligotrophy: genome and transcriptomic analysis.

The wide ecological distribution of actinobacteria suggests that they have developed efficient mechanisms to adapt to extremely nutritionally deficient (oligotrophic) conditions. The impact of nutrient limitation typically observed in oligotrophic areas on bacteria remains to be assessed for many species. The non-model Rhodococcus aetherivorans L13can grow under oligotrophic conditions, even without an added carbon source. Oligotrophic cells of L13 undergo physiological and morphological changes compared to glucose-grown cells, including forming short-fragmenting cells, producing an extracellular polymeric substance, and a 26-fold decrease in respiratory activity. We conducted genome sequencing of L13 and assembled the entire genome, subsequently comparing the abundance of gene transcripts in oligotrophic cells to those of glucose-grown cells, to explore the oligotrophy-responsive mechanisms at the genetic level. The genome comprises 6,543,485 base pairs, distributed across a single chromosome and six extrachromosomal plasmids (one linear and five circular). RNA-Seq analysis revealed the significant dysregulation of 2,665 genes (44% of the total genes detected). Results suggested a profound reorganization of its carbon and energy metabolism, including the activation of (i) mechanisms for utilizing air components; (ii) various dehydrogenases involved in aldehyde and alcohol metabolism, (iii) several enzymes involved in C2 metabolism, glyoxylate shunt, and TCA bypass routes, and downregulation of several genes that encode CO2 releasing-decarboxylase enzymes. Our results suggested that the adaptation strategy of L13 to oligotrophic conditions is supported by a combination of metabolic events, including low metabolic activity, the activation of C2 and ketoacids metabolism, and the display of a carbon conservative metabolic program.