Annotated Reference Research Articles

Consensus prediction of cell type labels in single-cell data with popV.

Cell-type classification is a crucial step in single-cell sequencing analysis. Various methods have been proposed for transferring a cell-type label from an annotated reference atlas to unannotated query datasets. Existing methods for transferring cell-type labels lack proper uncertainty estimation for the resulting annotations, limiting interpretability and usefulness. To address this, we propose popular Vote (popV), an ensemble of prediction models with an ontology-based voting scheme. PopV achieves accurate cell-type labeling and provides uncertainty scores. In multiple case studies, popV confidently annotates the majority of cells while highlighting cell populations that are challenging to annotate by label transfer. This additional step helps to reduce the load of manual inspection, which is often a necessary component of the annotation process, and enables one to focus on the most problematic parts of the annotation, streamlining the overall annotation process.

LIN28-Targeting Chromenopyrazoles and Tetrahydroquinolines Induced Cellular Morphological Changes and Showed High Biosimilarity with BRD PROTACs.

The probing of small molecules with heterocyclic scaffolds covering unexplored chemical space and the evaluation of their biological relevance are essential parts of forward chemical genetics approaches and for the development of potential small-molecule therapeutics. In this study, we profiled sets of chromenopyrazoles (CMPs) and tetrahydroquinolines (THQs), originally developed to target the protein-RNA interaction of LIN28-let-7, in a cell painting assay (CPA) measuring cellular morphological changes. Selected LIN28-inactive CMPs and THQs induced cellular morphological changes to different extents. The most CPA-active CMPs 2 and 3 exhibited high bio-similarity with the LCH and BET clusters, while the most CPA-active THQs 13 and 20 indicated a mechanism of action beyond the currently established biosimilarity clusters. Overall, this work demonstrated that CPA is useful in revealing "hidden" biological targets and mechanisms of action for biologically inactive small molecules, which are CMPs and THQs targeting the RNA-binding protein LIN28 in this case, evaluated in target-based strategies. When compared with annotated reference compounds, CMP 3 exhibited a high biosimilarity with the dual BRD7/9 degrading PROTAC VZ185, suggesting that CPA could potentially function as a new phenotypic approach to identify degrader molecules.

NCBI RefSeq: reference sequence standards through 25years of curation and annotation.

Reference sequences and annotations serve as the foundation for many lines of research today, from organism and sequence identification to providing a core description of the genes, transcripts and proteins found in an organism's genome. Interpretation of data including transcriptomics, proteomics, sequence variation and comparative analyses based on reference gene annotations informs our understanding of gene function and possible disease mechanisms, leading to new biomedical discoveries. The Reference Sequence (RefSeq) resource created at the National Center for Biotechnology Information (NCBI) leverages both automatic processes and expert curation to create a robust set of reference sequences of genomic, transcript and protein data spanning the tree of life. RefSeq continues to refine its annotation and quality control processes and utilize better quality genomes resulting from advances in sequencing technologies as well as RNA-Seq data to produce high-quality annotated genomes, ortholog predictions across more organisms and other products that are easily accessible through multiple NCBI resources. This report summarizes the current status of the eukaryotic, prokaryotic and viral RefSeq resources, with a focus on eukaryotic annotation, the increase in taxonomic representation and the effect it will have on comparative genomics. The RefSeq resource is publicly accessible at https://www.ncbi.nlm.nih.gov/refseq.

Uncovering functional lncRNAs by scRNA-seq with ELATUS

Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell type-specific, their study at single-cell (sc) level is challenging due to their less accurate annotation and low expression compared to protein-coding genes. Here, we systematically benchmark different preprocessing methods and develop a computational framework, named ELATUS, based on the combination of the pseudoaligner Kallisto with selective functional filtering. ELATUS enhances the detection of functional lncRNAs from scRNA-seq data, detecting their expression with higher concordance than standard methods with the ATAC-seq profiles in single-cell multiome data. Interestingly, the better results of ELATUS are due to its advanced performance with an inaccurate reference annotation such as that of lncRNAs. We independently confirm the expression patterns of cell type-specific lncRNAs exclusively detected with ELATUS and unveil biologically important lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in breast cancer progression is unnoticed by traditional methodologies. Our results emphasize the necessity for an alternative scRNA-seq workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs.

Towards Reliable ECG Analysis: Addressing Validation Gaps in the Electrocardiographic R-Peak Detection

Electrocardiographic (ECG) R-peak detection is essential for every sensor-based cardiovascular health monitoring system. To validate R-peak detectors, comparing the predicted results with reference annotations is crucial. This comparison is typically performed using tools provided by the waveform database (WFDB) or custom methods. However, many studies fail to provide detailed information on the validation process. The literature also highlights inconsistencies in reporting window size, a crucial parameter used to compare predictions with expert annotations to distinguish false peaks from the true R-peak. Additionally, there is also a need for uniformity in reporting the total number of beats for individual or collective records of the widely used MIT-BIH arrhythmia database. Thus, we aim to review validation methods of various R-peak detection methodologies before their implementation in real time. This review discusses the impact of non-beat annotations when using a custom validation method, allowable window tolerance, the effects of window size deviations, and implications of varying numbers of beats and skipping segments on ECG testing, providing a comprehensive guide for researchers. Addressing these validation gaps is critical as they can significantly affect validatory outcomes. Finally, the conclusion section proposes a structured concept as a future approach, a guide to integrate WFDB R-peak validation tools for testing any QRS annotated ECG database. Overall, this review underscores the importance of complete transparency in reporting testing procedures, which prevents misleading assessments of R-peak detection algorithms and enables fair methodological comparison.

Validation of an artificial intelligence system for holter ECG analysis

Abstract Introduction Holter ECG is a commonly used tool to identify heart rhythm disorders. As physician-based analysis of such Holter ECG is time consuming, various approaches using computerized interpretation have been developed. However, accuracy of these tools remains inferior to physician-based analysis. Thus, this study assesses the diagnostic performance of an artificial intelligence (AI)-powered Holter ECG service in comparison to results from reference databases as well as with physician-based evaluation. Methods 231 ECG recordings, covering 2,261 hours of ECG with annotations for 10,024,315 heartbeats from the following reference databases were used: MIT-BIH Arrhythmia (MITDB), American Heart Association ECG (AHDB), MIT-BIH Atrial Fibrillation (AFDB), Long Term Atrial Fibrillation (LTAFDB). Those recordings were originally collected from a mixed population of inpatients and outpatients between 1975 and 2008. Analysis of these recordings regarding the detection of QRS complexes, QRS classification and detection of Atrial Fibrillation (AF) was performed using a novel service for AI-based ECG analysis. Results were compared to the diagnosis stated within the database. QRS complex detection accuracy was performed on recordings from MITDB and AHADB by checking if time positions are within 150 ms to reference annotations. The QRS classification in three classes (normal, supraventricular, ventricular) was then compared for each detected heartbeat. Mismatches were adjudicated manually by three experts. Episodes of Atrial Fibrillation were detected in recordings from MITDB, AFDB and LTAFDB and compared to the reference episodes from the databases. The accuracy was evaluated based on the overlap with the reference annotations in the time-domain. Results Sensitivity and Precision of heartbeat detection compared to the reference databases exceeded 99% Figure 1 displays the results of heartbeat classification. Normal heartbeats were classified with a sensitivity of 99.6%, precision of 99.9% and specificity of 99.6%. For ventricular heartbeats, a sensitivity of 99.58 %, precision of 99.88 and specificity of 99.99% were achieved. Premature supraventricular contractions were recognized with a sensitivity of 99.58 %, precision of 100% and specificity of 100%. When comparing the 248,187 QRS complex classifications of MITDB and AHADB to the AI-powered analysis, 128 discrepancies were revealed. 43 were due to a discrepancy of convention as these beats were in sections that were also marked as AF episodes by the databases and the AI-powered analysis marks all beats in AF episodes as normal. Of the 85 remaining discrepancies, more than 87% were adjudicated in favor of the AI-powered analysis by the experts. Figure 2 shows the comparison of AF detection results showing Sensitivity and Precision above 99%. Conclusion AI-powered Holter ECG analysis compared to reference ECG stripes exceed 99% of sensitivity, specificity and precision.QRS complex detectionAF/ AFib detection

Genomes of Microtus Rodents Highlight the Importance of Olfactory and Immune Systems in Their Fast Radiation.

The characterization of genes and biological functions underlying functional diversification and the formation of species is a major goal of evolutionary biology. In this study, we investigated the fast radiation of Microtus voles, one of the most speciose group of mammals, which shows strong genetic divergence despite few readily observable morphological differences. We produced an annotated reference genome for the common vole, Microtus arvalis, and resequenced the genomes of 10 different species and evolutionary lineages spanning the Microtus speciation continuum. Our full-genome sequences illustrate the recent and fast diversification of this group, and we identified genes in highly divergent genomic windows that have likely particular roles in their radiation. We found three biological functions enriched for highly divergent genes in most Microtus species and lineages: olfaction, immunity and metabolism. In particular, olfaction-related genes (mostly olfactory receptors and vomeronasal receptors) are fast evolving in all Microtus species indicating the exceptional importance of the olfactory system in the evolution of these rodents. Of note is e.g. the shared signature among vole species on Olfr1019 which has been associated with fear responses against predator odors in rodents. Our analyses provide a genome-wide basis for the further characterization of the ecological factors and processes of natural and sexual selection that have contributed to the fast radiation of Microtus voles.

Detailed Profiling of 17-Hydroxygeranyllinalool Diterpene Glycosides from Nicotiana Species Reveals Complex Reaction Networks of Conjugation Isomers.

Specialised anti-herbivory metabolites are abundant in the solanaceous genus Nicotiana. These metabolites include the large family of 17-hydroxygeranyllinalool diterpene glycosides (HGL-DTGs). Many HGL-DTGs occur exclusively within the Nicotiana genus, but information from the molecular model species N. tabacum, N. benthamiana, and the tree tobacco N. glauca is limited. We studied HGL-DTG occurrence and complexity in these species with the aim of providing in-depth reference annotations and comprehensive HGL-DTG inventories. We analysed polar metabolite extracts in comparison to the previously investigated wild reference species N. attenuata using positive ESI(+) and negative ESI(-) mode electrospray ionisation LC-MS and MS/MS. We provide annotations of 66 HGL-DTGs with in-source and MS/MS fragmentation spectra for selected HGL-DTGs with exemplary fragment interpretations of ESI(+) as well as less studied ESI(-) spectra. We assemble a potential biosynthesis pathway comparing the presence of HGL-DTGs in N. tabacum, N. glauca, and N. benthamiana to N. attenuata. Approximately one-third of HGL-DTGs are chromatographically resolved isomers of hexose, deoxyhexose, or malonate conjugates. The number of isomers is especially high for conjugates with low numbers of deoxyhexose moieties. We extend the number of known HGL-DTGs with a focus on Nicotiana model species and demonstrate that the HGL-DTG family of N. tabacum plants can be surprisingly complex. Our study provides an improved basis with detailed references to previous studies of wild Nicotiana species and enables inference of HGL-DTG pathways with required enzymes for the biosynthesis of this important family of specialised defence metabolites.

TE-Seq: A Transposable Element Annotation and RNA-Seq Pipeline.

The recognition that transposable elements (TEs) play important roles in many biological processes has elicited growing interest in analyzing sequencing data derived from this 'dark genome'. This is however complicated by the highly repetitive nature of these sequences in genomes, requiring the deployment of several problem-specific tools as well as the curation of appropriate genome annotations. This pipeline aims to make the analysis of TE sequences and their expression more generally accessible. The TE-Seq pipeline conducts an end-to-end analysis of RNA sequencing data, examining both genes and TEs. It implements the most current computational methods tailor-made for TEs, and produces a comprehensive analysis of TE expression at both the level of the individual element and at the TE clade level. Furthermore, if supplied with long-read DNA sequencing data, it is able to assess TE expression from non-reference (polymorphic) loci. As a demonstration, we analyzed proliferating, early senescent, and late senescent lung fibroblast RNA-Seq data, and created a custom reference genome and annotations for this cell strain using Nanopore sequencing data. We found that several retrotransposable element (RTE) clades were upregulated in senescence, which included non-reference, intact, and potentially active elements. TE-Seq is made available as a Snakemake pipeline which can be obtained at https://github.com/maxfieldk/TE-Seq. All software dependencies besides Snakemake and Docker/Singularity are packaged into a container which is automatically built and deployed by the pipeline at runtime.

Genome sequence resources from three isolates of the apple canker pathogen Neonectria ditissima infecting forest trees

Neonectria ditissima is a generalist ascomycete plant pathogen causing canker diseases on a variety of hardwood tree species and can cross-infect many of them. The fungus enters the plants through wounds throughout the year. N. ditissima is considered a major threat to apple production responsible for the fruit tree canker disease which damages trees and causes rotting of fruits in storage. Nearby forests and shelter belts can serve as source of inoculum for well-managed apple orchards. Thus, knowledge about the N. ditissima isolates infecting different host species is essential for designing integrated pest management strategies. Here, we describe the genomes of three N. ditissima isolates, Nd_iso34, Nd_iso35, and Nd_iso36, infecting European beech, American tulip tree, and American beech, respectively. We obtained genome assemblies of ca. 45 megabases for all isolates, covering 94% of the N. ditissima reference annotation, and 97% of the universal single-copy orthologs (BUSCOs). We conclude that these genome assemblies are a highly relevant resource considering the scarcity of genomic data available for N. ditissima.

Assembly and annotation of a chromosome-level reference genome for the endangered Colorado pikeminnow (Ptychocheilus lucius).

Advancements in genome sequencing technology have brought unprecedented accessibility of high-throughput sequencing to species of conservation interest. The potential knowledge gained from application of these techniques is maximized by availability of high-quality, annotated reference genomes for endangered species. However, these vital resources are often lacking for endangered minnows of North America (Cypriniformes: Leuciscidae). One such endangered species, Colorado pikeminnow (Ptychocheilus lucius), is the largest North American minnow and the top-level native aquatic predator in the Colorado River Basin of the southwestern United States and northwestern Mexico. Over the past century, Colorado pikeminnow has suffered habitat loss and population declines due to anthropogenic habitat modifications and invasive species introductions. The lack of genetic resources for Colorado pikeminnow has hindered conservation genomic study of this unique organism. This study seeks to remedy this issue by presenting a high-quality reference genome for Colorado pikeminnow developed from Pacific Biosciences HiFi sequencing and Hi-C scaffolding. The final assembly was a 1.1 Gb genome comprised of 305 contigs including 25 chromosome-sized scaffolds. Measures of quality, contiguity, and completeness met or exceeded those observed for Danio rerio (Danionidae) and 2 other Colorado River Basin leuciscids (Meda fulgida and Tiaroga cobitis). Comparative genomic analyses identified enrichment of gene families for growth, development, immune activity, and gene transcription; all of which are important for a large-bodied piscivorous fish living in a dynamic environment. This reference genome will provide a basis for important conservation genomic study of Colorado pikeminnow and help efforts to better understand the evolution of desert fishes.

Unveiling the Genomic Symphony: Identification Cultivar-Specific Genes and Enhanced Insights on Sweet Sorghum Genomes Through Comprehensive superTranscriptomic Analysis.

Sorghum (Sorghum bicolor (L.) Moench) is a multipurpose crop grown for food, fodder, and bioenergy production. Its cultivated varieties, along with their wild counterparts, contribute to the core genetic pool. Despite the availability of several re-sequenced sorghum genomes, a variable portion of sorghum genomes is not reported during reference genome assembly and annotation. The present analysis used 223 publicly available RNA-seq datasets from seven sweet sorghum cultivars to construct superTranscriptome. This approach yielded 45,864 Representative Transcript Assemblies (RTAs) that showcased intriguing Presence/Absence Variation (PAV) across 15 published sorghum genomes. We found 301 superTranscripts were exclusive to sweet sorghum, including 58 de novo genes encoded core and linker histones, zinc finger domains, glucosyl transferases, cellulose synthase, etc. The superTranscriptome added 2,802 new protein-coding genes to the Sweet Sorghum Reference Genome (SSRG), of which 559 code for different transcription factors (TFs). Our analysis revealed that MULE-like transposases were abundant in the sweet sorghum genome and could play a hidden role in the evolution of sweet sorghum. We observed large deletions in the D locus and terminal deletions in four other NAC encoding loci in the SSRG compared to its wild progenitor (353) suggesting non-functional NAC genes contributed to trait development in sweet sorghum. Moreover, superTranscript-based methods for Differential Exon Usage (DEU) and Differential Gene Expression (DGE) analyses were more accurate than those based on the SSRG. This study demonstrates that the superTranscriptome can enhance our understanding of fundamental sorghum mechanisms, improve genome annotations, and potentially even replace the reference genome.

Quantitative Analysis of Small Intestinal Motility in 3D Cine-MRI Using Centerline-Aware Motion Estimation.

Currently available tools for noninvasive motility quantification of the small intestine are limited to dynamic 2D MRI scans, which are limited in their ability to differentiate between types of intestinal motility. To develop a method for quantification and characterization of small intestinal motility in 3D, capable of differentiating motile, non-motile and peristaltic motion patterns. Prospective. Fourteen healthy volunteers (127 small intestinal segments) and 10 patients with Crohn's disease (87 small intestinal segments). 3.0 T, 3D balanced fast field echo sequence, 1 volume per second. Using deformable image registration between subsequent volumes, the local velocity within the intestinal lumen was quantified. Average velocity and average absolute velocity along intestinal segments were used with linear classifiers to differentiate motile from non-motile intestines, as well as erratic motility from peristalsis. The mean absolute velocity of small intestinal content was compared between healthy volunteers and Crohn's disease patients, and the discriminative power of the proposed motility metrics for detecting motility and peristalsis was determined. The consensus of two observers was used as referenced standard. Student's t-test to assess differences between groups; area under the receiver operating characteristic curve (AUC) to assess discriminative ability. P < 0.001 was considered significant. A significant difference in the absolute velocity of intestinal content between Crohn's patients and healthy volunteers was observed (median [IQR] 1.06 [0.61, 1.56] mm/s vs. 1.84 [1.37, 2.43] mm/s), which was consistent with manual reference annotations of motile activity. The proposed method had a strong discriminative performance for detecting non-motile intestines (AUC 0.97) and discernible peristalsis (AUC 0.81). Analysis of 3D cine-MRI using centerline-aware motion estimation has the potential to allow noninvasive characterization of small intestinal motility and peristaltic motion in 3D. 3 TECHNICAL EFFICACY: Stage 2.

Chromosome-level genome assembly and annotation of the Spinibarbus caldwelli

Spinibarbus caldwelli is an important freshwater economic fish in China. Owing to uncontrolled fishing, wild resources of S. caldwelli have decreased rapidly and may be on the verge of extinction. In this study, utilizing single-molecule real-time (SMRT) sequencing technology and chromatin interaction mapping (Hi-C) technologies, we assembled the first chromosome-scale genome for S. caldwelli about 1.77 Gb in size, with a contig N50 length of 11.83 Mb and scaffold N50 length of 33.91 Mb. In total 1.72 Gb (97.01%) of the contig sequences were anchored onto fifty chromosomes with the longest scaffold being 56.20 Mb. Furthermore, proximately 49.41% of the genome was composed of repetitive elements. In total, 49,377 protein-coding genes were predicted, of which 47,724 (96.65%) genes have been functionally annotated. The high-quality chromosome-level reference genome and annotation are vital for supporting basic genetic studies and will be contribute to genetic structure, functional elucidation, evolutionary inquiry, and germplasm conservation for S. caldwelli.

A reference genome, mitochondrial genome and associated transcriptomes for the critically endangered swift parrot (Lathamus discolor)

Abstract* The swift parrot (Lathamus discolor) is a Critically Endangered migratory parrot that breeds in Tasmania and winters on the Australian mainland. Here we provide a reference genome assembly for the swift parrot. We sequence PacBio HiFi reads to create a high-quality reference assembly and identify a complete mitochondrial sequence. We also generate a reference transcriptome from five organs to inform genome annotation. The genome was 1.24 Gb in length and consisted of 847 contigs with a contig N50 of 18.97 Gb and L50 of 20 contigs. This study provides an annotated reference assembly and transcriptomic resources for the swift parrot to assist in future conservation genomic research.

Different radiomics annotation methods comparison in rectal cancer characterisation and prognosis prediction: a two-centre study

ObjectivesTo explore the performance differences of multiple annotations in radiomics analysis and provide a reference for tumour annotation in large-scale medical image analysis.MethodsA total of 342 patients from two centres who underwent radical resection for rectal cancer were retrospectively studied and divided into training, internal validation, and external validation cohorts. Three predictive tasks of tumour T-stage (pT), lymph node metastasis (pLNM), and disease-free survival (pDFS) were performed. Twelve radiomics models were constructed using Lasso-Logistic or Lasso-Cox to evaluate and four annotation methods, 2D detailed annotation along tumour boundaries (2D), 3D detailed annotation along tumour boundaries (3D), 2D bounding box (2DBB), and 3D bounding box (3DBB) on T2-weighted images, were compared. Radiomics models were used to establish combined models incorporating clinical risk factors. The DeLong test was performed to compare the performance of models using the receiver operating characteristic curves.ResultsFor radiomics models, the area under the curve values ranged from 0.627 (0.518–0.728) to 0.811 (0.705–0.917) in the internal validation cohort and from 0.619 (0.469–0.754) to 0.824 (0.689–0.918) in the external validation cohort. Most radiomics models based on four annotations did not differ significantly, except between the 3D and 3DBB models for pLNM (p = 0.0188) in the internal validation cohort. For combined models, only the 2D model significantly differed from the 2DBB (p = 0.0372) and 3D models (p = 0.0380) for pDFS.ConclusionRadiomics and combined models constructed with 2D and bounding box annotations showed comparable performances to those with 3D and detailed annotations along tumour boundaries in rectal cancer characterisation and prognosis prediction.Critical relevance statementFor quantitative analysis of radiological images, the selection of 2D maximum tumour area or bounding box annotation is as representative and easy to operate as 3D whole tumour or detailed annotations along tumour boundaries.Key PointsThere is currently a lack of discussion on whether different annotation efforts in radiomics are predictively representative.No significant differences were observed in radiomics and combined models regardless of the annotations (2D, 3D, detailed, or bounding box).Prioritise selecting the more time and effort-saving 2D maximum area bounding box annotation.Graphical

High-throughput single-molecule long-read RNA sequencing analysis of tissue-specific genes and isoforms in lettuce (Lactuca sativa L.)

Lettuce is one of the most widely cultivated and consumed dicotyledonous vegetables globally. Despite the availability of its reference genome sequence, lettuce gene annotation remains incomplete, impeding comprehensive research and the broad application of genomic resources. Long-read RNA isoform sequencing (Iso-Seq) offers substantial advantages for analyzing RNA alternative splicing and aiding gene annotation, yet it faces throughput limitations. We present the HIT-ISOseq method tailored for bulk sample analysis, significantly enhancing RNA sequencing throughput on the PacBio platform by concatenating cDNA. Here we show, HIT-ISOseq generates 3-4 cDNA molecules per CCS read in lettuce, yielding 15.7 million long reads per PacBio Sequel II SMRT Cell 8 M. We validate its effectiveness in analyzing six lettuce tissue samples, including roots, stems, and leaves, revealing tissue-specific gene expression patterns and RNA isoforms. Leveraging diverse tissue long-read RNA sequencing, we refine the transcript annotation of the lettuce reference genome, expanding its GO and KEGG annotation repertoire. Collectively, this study serves as a foundational reference for genome annotation and the analysis of multi-sample isoform expression, utilizing high-throughput long-read transcriptome sequencing.

Chromosome-Level Reference Genome of the Ponza Grayling (Hipparchia sbordonii), an Italian Endemic and Endangered Butterfly.

Islands are crucial evolutionary hotspots, providing unique opportunities for differentiation of novel biodiversity and long-term segregation of endemic species. Islands are also fragile ecosystems, where biodiversity is more exposed to environmental and anthropogenic pressures than on continents. The Ponza grayling, Hipparchia sbordonii, is an endemic butterfly species that is currently found only in two tiny islands of the Pontine archipelago, off the coast of Italy, occupying an area smaller than 10 km2. It has been classified as Endangered (IUCN) because of the extremely limited area of occurrence, population fragmentation, and the recent demographic decline. Thanks to a combination of different assemblers of long and short genomic reads, bulk transcriptome RNAseq, and synteny analysis with phylogenetically close butterflies, we produced a highly contiguous, chromosome-scale annotated reference genome for the Ponza grayling, including 28 autosomes and the Z sexual chromosomes. The final assembly spanned 388.61 Gb with a contig N50 of 14.5 Mb and a BUSCO completeness score of 98.5%. Synteny analysis using four other butterfly species revealed high collinearity with Hipparchia semele and highlighted 10 intrachromosomal inversions longer than 10 kb, of which two appeared on the lineage leading to H. sbordonii. Our results show that a chromosome-scale reference genome is attainable also when chromatin conformation data may be impractical or present specific technical challenges. The high-quality genomic resource for H. sbordonii opens up new opportunities for the accurate assessment of genetic diversity and genetic load and for the investigations of the genomic novelties characterizing the evolutionary path of this endemic island species.

Reshaping free-text radiology notes into structured reports with generative question answering transformers

BackgroundRadiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently, the adoption of structured reporting (SR) has been recommended by various medical societies thanks to the advantages it offers, e.g. standardization, completeness, and information retrieval. We propose a pipeline to extract information from Italian free-text radiology reports that fits with the items of the reference SR registry proposed by a national society of interventional and medical radiology, focusing on CT staging of patients with lymphoma. MethodsOur work aims to leverage the potential of Natural Language Processing and Transformer-based models to deal with automatic SR registry filling. With the availability of 174 Italian radiology reports, we investigate a rule-free generative Question Answering approach based on the Italian-specific version of T5: IT5. To address information content discrepancies, we focus on the six most frequently filled items in the annotations made on the reports: three categorical (multichoice), one free-text (free-text), and two continuous numerical (factual). In the preprocessing phase, we encode also information that is not supposed to be entered. Two strategies (batch-truncation and ex-post combination) are implemented to comply with the IT5 context length limitations. Performance is evaluated in terms of strict accuracy, f1, and format accuracy, and compared with the widely used GPT-3.5 Large Language Model. Unlike multichoice and factual, free-text answers do not have 1-to-1 correspondence with their reference annotations. For this reason, we collect human-expert feedback on the similarity between medical annotations and generated free-text answers, using a 5-point Likert scale questionnaire (evaluating the criteria of correctness and completeness). ResultsThe combination of fine-tuning and batch splitting allows IT5 ex-post combination to achieve notable results in terms of information extraction of different types of structured data, performing on par with GPT-3.5. Human-based assessment scores of free-text answers show a high correlation with the AI performance metrics f1 (Spearman's correlation coefficients>0.5, p-values<0.001) for both IT5 ex-post combination and GPT-3.5. The latter is better at generating plausible human-like statements, even if it systematically provides answers even when they are not supposed to be given. ConclusionsIn our experimental setting, a fine-tuned Transformer-based model with a modest number of parameters (i.e., IT5, 220 M) performs well as a clinical information extraction system for automatic SR registry filling task. It can extract information from more than one place in the report, elaborating it in a manner that complies with the response specifications provided by the SR registry (for multichoice and factual items), or that closely approximates the work of a human-expert (free-text items); with the ability to discern when an answer is supposed to be given or not to a user query.

Genome-wide association study and candidate gene identification for agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum

Pepper agronomic traits serve as pivotal indicators for characterizing germplasm attributes and correlations. It is important to study differential genotypic variation through phenotypic differences of target traits. Whole genome resequencing was used to sequence the whole genome among different individuals of species with known reference genomes and annotations, and based on this, differential analyses of individuals or populations were carried out to identify SNPs for agronomic traits related to pepper. This study conducted a genome-wide association study encompassing 26 key agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum. The population structure (phylogenetics, population structure, population principal component analysis, genetic relationship) and linkage disequilibrium analysis were realized to ensure the accuracy and reliability of GWAS results, and the optimal statistical model was determined. A total of 929 SNPs significantly associated with 26 agronomic traits, were identified, alongside the detection of 519 candidate genes within 100 kb region adjacent to these SNPs. Additionally, through gene annotation and expression pattern scrutiny, genes such as GAUT1, COP10, and DDB1 correlated with fruit traits in Capsicum frutescens and Capsicum annuum were validated via qRT-PCR. In the CH20 (Capsicum annuum) and YB-4 (Capsicum frutescens) cultivars, GAUT1 and COP10 were cloned with cDNA lengths of 1065 bp and 561 bp, respectively, exhibiting only a small number of single nucleotide variations and nucleotide deletions. This validation provides a robust reference for molecular marker-assisted breeding of pepper agronomic traits, offering both genetic resources and theoretical foundations for future endeavors in molecular marker-assisted breeding for pepper.