Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Ensembl 2024.

Ensembl (https://www.ensembl.org) is a freely available genomic resource that has produced high-quality annotations, tools, and services for vertebrates and model organisms for more than two decades. In recent years, there has been a dramatic shift in the genomic landscape, with a large increase in the number and phylogenetic breadth of high-quality reference genomes, alongside major advances in the pan-genome representations of higher species. In order to support these efforts and accelerate downstream research, Ensembl continues to focus on scaling for the rapid annotation of new genome assemblies, developing new methods for comparative analysis, and expanding the depth and quality of our genome annotations. This year we have continued our expansion to support global biodiversity research, doubling the number of annotated genomes we support on our Rapid Release site to over 1700, driven by our close collaboration with biodiversity projects such as Darwin Tree of Life. We have also strengthened support for key agricultural species, including the first regulatory builds for farmed animals, and have updated key tools and resources that support the global scientific community, notably the Ensembl Variant Effect Predictor. Ensembl data, software, and tools are freely available.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Ensembl 2023.

Ensembl (https://www.ensembl.org) has produced high-quality genomic resources for vertebrates and model organisms for more than twenty years. During that time, our resources, services and tools have continually evolved in line with both the publicly available genome data and the downstream research and applications that utilise the Ensembl platform. In recent years we have witnessed a dramatic shift in the genomic landscape. There has been a large increase in the number of high-quality reference genomes through global biodiversity initiatives. In parallel, there have been major advances towards pangenome representations of higher species, where many alternative genome assemblies representing different breeds, cultivars, strains and haplotypes are now available. In order to support these efforts and accelerate downstream research, it is our goal at Ensembl to create high-quality annotations, tools and services for species across the tree of life. Here, we report our resources for popular reference genomes, the dramatic growth of our annotations (including haplotypes from the first human pangenome graphs), updates to the Ensembl Variant Effect Predictor (VEP), interactive protein structure predictions from AlphaFold DB, and the beta release of our new website.

GENCODE: reference annotation for the human and mouse genomes in 2023.

GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function. Here, we present an update on the annotation of human and mouse genes, including developments in the tools, data, analyses and major collaborations which underpin this progress. For example, we report the creation of a set of non-canonical ORFs identified in GENCODE transcripts, the LRGASP collaboration to assess the use of long transcriptomic data to build transcript models, the progress in collaborations with RefSeq and UniProt to increase convergence in the annotation of human and mouse protein-coding genes, the propagation of GENCODE across the human pan-genome and the development of new tools to support annotation of regulatory features by GENCODE. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

A joint NCBI and EMBL-EBI transcript set for clinical genomics and research.

Comprehensive genome annotation is essential to understand the impact of clinically relevant variants. However, the absence of a standard for clinical reporting and browser display complicates the process of consistent interpretation and reporting. To address these challenges, Ensembl/GENCODE1 and RefSeq2 launched a joint initiative, the Matched Annotation from NCBI and EMBL-EBI (MANE) collaboration, to converge on human gene and transcript annotation and to jointly define a high-value set of transcripts and corresponding proteins. Here, we describe the MANE transcript sets for use as universal standards for variant reporting and browser display. The MANE Select set identifies a representative transcript for each human protein-coding gene, whereas the MANE Plus Clinical set provides additional transcripts at loci where the Select transcripts alone are not sufficient to report all currently known clinical variants. Each MANE transcript represents an exact match between the exonic sequences of an Ensembl/GENCODE transcript and its counterpart in RefSeq such that the identifiers can be used synonymously. We have now released MANE Select transcripts for 97% of human protein-coding genes, including all American College of Medical Genetics and Genomics Secondary Findings list v3.0 (ref. 3) genes. MANE transcripts are accessible from major genome browsers and key resources. Widespread adoption of these transcript sets will increase the consistency of reporting, facilitate the exchange of data regardless of the annotation source and help to streamline clinical interpretation.

Ensembl 2022.

Ensembl (https://www.ensembl.org) is unique in its flexible infrastructure for access to genomic data and annotation. It has been designed to efficiently deliver annotation at scale for all eukaryotic life, and it also provides deep comprehensive annotation for key species. Genomes representing a greater diversity of species are increasingly being sequenced. In response, we have focussed our recent efforts on expediting the annotation of new assemblies. Here, we report the release of the greatest annual number of newly annotated genomes in the history of Ensembl via our dedicated Ensembl Rapid Release platform (http://rapid.ensembl.org). We have also developed a new method to generate comparative analyses at scale for these assemblies and, for the first time, we have annotated non-vertebrate eukaryotes. Meanwhile, we continually improve, extend and update the annotation for our high-value reference vertebrate genomes and report the details here. We have a range of specific software tools for specific tasks, such as the Ensembl Variant Effect Predictor (VEP) and the newly developed interface for the Variant Recoder. All Ensembl data, software and tools are freely available for download and are accessible programmatically.

A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain.

Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 ( www.isoformAtlas.com ). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity.

GENCODE 2021.

The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Isolating peripheral effects of endogenous opioids in modulating exertional breathlessness in people with moderate or severe COPD: a randomised controlled trial.

QUESTION ADDRESSED BY THE STUDY: Endogenous opioids (endorphins) have been reported to modulate exercise-induced breathlessness, but the relative contribution of peripheral opioid receptors has not been tested. MATERIALS PARTICIPANTS AND METHODS: This was a double-blind, randomised, three-arm, cross-over trial in outpatients with spirometry-verified moderate to severe chronic obstructive pulmonary disease. Participants undertook an incremental symptom-limited treadmill test followed by five endurance treadmill tests at 75% of their maximal work rate; two tests for familiarisation and three tests 30 min after intravenous injection of either methylnaltrexone 0.3 mg·kg-1 (blocking peripheral opioid receptors only) or naloxone 0.1 mg·kg-1 (blocking both central and peripheral opioid receptors) or normal saline, in randomised order. The primary end-point was the regression slope between breathlessness intensity (0-10 numerical rating scale) and oxygen consumption (V'O2 ) during the walk tests, comparing methylnaltrexone and placebo using a paired t-test. RESULTS: 17 participants completed the trial: median (range) 66 (55-82) years; 15 males; mean±sd forced expiratory volume (FEV1) 53.8±17.6% predicted; FEV1/forced vital capacity ratio 0.55±15.9. There was no statistically or clinically significant difference in the primary end-point (regression slope of breathlessness intensity and V'O2 ) for methylnaltrexone (p=0.498) or naloxone (p=0.804), compared to placebo. Secondary outcomes were similar between the three treatment groups, including peak and mean breathlessness intensity and unpleasantness, exercise capacity, endurance time and leg fatigue. ANSWER TO THE QUESTION: Blocking peripheral opioid receptors (methylnaltrexone) or peripheral and central opioid receptors (naloxone) did not appear to modulate breathlessness intensity nor exercise capacity when compared with placebo (no blockade).

A chromosome-level assembly of the Atlantic herring genome-detection of a supergene and other signals of selection.

The Atlantic herring is a model species for exploring the genetic basis for ecological adaptation, due to its huge population size and extremely low genetic differentiation at selectively neutral loci. However, such studies have so far been hampered because of a highly fragmented genome assembly. Here, we deliver a chromosome-level genome assembly based on a hybrid approach combining a de novo Pacific Biosciences (PacBio) assembly with Hi-C-supported scaffolding. The assembly comprises 26 autosomes with sizes ranging from 12.4 to 33.1 Mb and a total size, in chromosomes, of 726 Mb, which has been corroborated by a high-resolution linkage map. A comparison between the herring genome assembly with other high-quality assemblies from bony fishes revealed few inter-chromosomal but frequent intra-chromosomal rearrangements. The improved assembly facilitates analysis of previously intractable large-scale structural variation, allowing, for example, the detection of a 7.8-Mb inversion on Chromosome 12 underlying ecological adaptation. This supergene shows strong genetic differentiation between populations. The chromosome-based assembly also markedly improves the interpretation of previously detected signals of selection, allowing us to reveal hundreds of independent loci associated with ecological adaptation.

Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci.

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.

GENCODE reference annotation for the human and mouse genomes.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.

Patterns of Time Use across the Chronic Obstructive Pulmonary Disease Severity Spectrum.

Descriptions of time use patterns in people with chronic obstructive pulmonary disease (COPD) are scarce and the relationship between use-of-time and COPD severity remains unclear. This study aimed to describe a typical day for people with COPD and to explore the differences in time-use patterns across the Body Mass-Index, Airflow Obstruction, Dyspnoea and Exercise Capacity (BODE) index using compositional analyses. Using a cross-sectional design, 141 adults with clinically stable COPD had their demographics, objective measures of function (pulmonary, exercise capacity and physical activity), and self-reported COPD-related impairment recorded. Daily time-use compositions were derived from 24-h accelerometry and 24-h use-of-time recall interviews. Compositional multiple linear regression models were used to explore the relationship between the BODE index and 24-h time-use compositions. These models were used to predict daily time (min/d) that is spent in time-use components across the BODE index. The BODE index score was clearly associated with 24-h accelerometry (p < 0.0001) and 24-h use-of-time recall (p < 0.0001) compositions. Relative to the remaining time-use components, higher BODE index scores were associated with greater sedentary behaviour (p < 0.0001), Quiet time (p < 0.0001), Screen time (p = 0.001) and Self-care (p = 0.022), and less daily Chores (p < 0.0001) and Household administration (p = 0.015) time. As the BODE index scores increased, time-use predictions were strongly associated with decreases in Chores (up to 206 min/d), and increases in Screen (up to 156 min/d) and Quiet time (up to 131 min/d). Time-use patterns may provide a basis for planning interventions relative to the severity of COPD.

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation.

The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community.

A Comprehensive Evaluation of Nasal and Bronchial Cytokines and Chemokines Following Experimental Rhinovirus Infection in Allergic Asthma: Increased Interferons (IFN-γ and IFN-λ) and Type 2 Inflammation (IL-5 and IL-13).

BACKGROUND: Rhinovirus infection is a major cause of asthma exacerbations. OBJECTIVES: We studied nasal and bronchial mucosal inflammatory responses during experimental rhinovirus-induced asthma exacerbations. METHODS: We used nasosorption on days 0, 2-5 and 7 and bronchosorption at baseline and day 4 to sample mucosal lining fluid to investigate airway mucosal responses to rhinovirus infection in patients with allergic asthma (n=28) and healthy non-atopic controls (n=11), by using a synthetic absorptive matrix and measuring levels of 34 cytokines and chemokines using a sensitive multiplex assay. RESULTS: Following rhinovirus infection asthmatics developed more upper and lower respiratory symptoms and lower peak expiratory flows compared to controls (all P<0.05). Asthmatics also developed higher nasal lining fluid levels of an anti-viral pathway (including IFN-γ, IFN-λ/IL-29, CXCL11/ITAC, CXCL10/IP10 and IL-15) and a type 2 inflammatory pathway (IL-4, IL-5, IL-13, CCL17/TARC, CCL11/eotaxin, CCL26/eotaxin-3) (area under curve day 0-7, all P<0.05). Nasal IL-5 and IL-13 were higher in asthmatics at day 0 (P<0.01) and levels increased by days 3 and 4 (P<0.01). A hierarchical correlation matrix of 24 nasal lining fluid cytokine and chemokine levels over 7days demonstrated expression of distinct interferon-related and type 2 pathways in asthmatics. In asthmatics IFN-γ, CXCL10/IP10, CXCL11/ITAC, IL-15 and IL-5 increased in bronchial lining fluid following viral infection (all P<0.05). CONCLUSIONS: Precision sampling of mucosal lining fluid identifies robust interferon and type 2 responses in the upper and lower airways of asthmatics during an asthma exacerbation. Nasosorption and bronchosorption have potential to define asthma endotypes in stable disease and at exacerbation.

The pig X and Y Chromosomes: structure, sequence, and evolution.

We have generated an improved assembly and gene annotation of the pig X Chromosome, and a first draft assembly of the pig Y Chromosome, by sequencing BAC and fosmid clones from Duroc animals and incorporating information from optical mapping and fiber-FISH. The X Chromosome carries 1033 annotated genes, 690 of which are protein coding. Gene order closely matches that found in primates (including humans) and carnivores (including cats and dogs), which is inferred to be ancestral. Nevertheless, several protein-coding genes present on the human X Chromosome were absent from the pig, and 38 pig-specific X-chromosomal genes were annotated, 22 of which were olfactory receptors. The pig Y-specific Chromosome sequence generated here comprises 30 megabases (Mb). A 15-Mb subset of this sequence was assembled, revealing two clusters of male-specific low copy number genes, separated by an ampliconic region including the HSFY gene family, which together make up most of the short arm. Both clusters contain palindromes with high sequence identity, presumably maintained by gene conversion. Many of the ancestral X-related genes previously reported in at least one mammalian Y Chromosome are represented either as active genes or partial sequences. This sequencing project has allowed us to identify genes--both single copy and amplified--on the pig Y Chromosome, to compare the pig X and Y Chromosomes for homologous sequences, and thereby to reveal mechanisms underlying pig X and Y Chromosome evolution.

Sedentary Behavior in People with and without a Chronic Health Condition: How Much, What and When?

PURPOSE: To describe sedentary behaviors (duration, bouts and context) in people with and without a chronic health condition. METHODS: Design: Secondary analysis of two cross-sectional studies. Participants: People with stable chronic obstructive pulmonary disease (COPD) (n = 24, male:female 18:6) and their spousal carers (n = 24, 6:18); stroke survivors (n = 24, 16:8) and age- and sex-matched healthy adults (n = 19, 11:8). Level of physiological impairment was measured with post-bronchodilator spirometry (FEV1 %predicted) for people with COPD, and walking speed for people with stroke. Outcomes: Participants were monitored over seven days (triaxial accelerometer, Sensewear armband) to obtain objective data on daily sedentary time, and prolonged sedentary bouts (≥ 30 min). During the monitoring period, a 24-hour use of time recall instrument was administered by telephone interview to explore the context of sedentary activities (e.g. television, computer or reading). Sedentary time was quantified using accelerometry and recall data, and group differences were explored. Linear regression examined associations between physiological impairment and sedentary time. RESULTS: Participant groups were similar in terms of age (COPD 75 ± 8, carers 70 ± 11, stroke 69 ± 10, healthy 73 ± 7 years) and body mass index (COPD 28 ± 4, carers 27 ± 4, stroke 31 ± 4, healthy 26 ± 4 kg.m-2). The healthy group had the lowest sedentary time (45% of waking hours), followed by the carer (54%), stroke (60%) and COPD (62%) groups (p < 0.0001). Level of physiological impairment was an independent predictor of waking sedentary time (p = 0.001). CONCLUSIONS: People with a chronic health condition spent more time sedentary than those without a chronic condition, and there were small but clear differences between groups in the types of activities undertaken during sedentary periods. The study findings may aid in the design of targeted interventions to decrease sedentary time in people with chronic health conditions.