Gene Size Matters: An Analysis of Gene Length in the Human Genome

DNA repair deficiencies and neurodegeneration

Neurodegenerative diseases are the second most prevalent cause of death in industrialized countries. Alzheimer's Disease is the most widespread and also most acknowledged form of dementia today. Together with Parkinson's Disease they account for over 90 % cases of neurodegenerative disorders caused by proteopathies. Far less known are the neurodegenerative pathologies in DNA repair deficiency syndromes. Such diseases like Cockayne - or Werner Syndrome are described as progeroid syndromes - diseases that cause the premature ageing of the affected persons, and there are clear implications of such diseases in neurologic dysfunction and degeneration. In this review, we aim to draw the attention on commonalities between proteopathy-associated neurodegeneration and neurodegeneration caused by DNA repair defects and discuss how mitochondria are implicated in the development of both disorder classes. Furthermore, we highlight how nematodes are a valuable and indispensable model organism to study conserved neurodegenerative processes in a fast-forward manner.

The molecular evolution of cancer associated genes in mammals

Cancer is a disease that many multicellular organisms have faced for millions of years, and species have evolved various tumour suppression mechanisms to control oncogenesis. Although cancer occurs across the tree of life, cancer related mortality risks vary across mammalian orders, with Carnivorans particularly affected. Evolutionary theory predicts different selection pressures on genes associated with cancer progression and suppression, including oncogenes, tumour suppressor genes and immune genes. Therefore, we investigated the evolutionary history of cancer associated gene sequences across 384 mammalian taxa, to detect signatures of selection across categories of oncogenes (GRB2, FGL2 and CDC42), tumour suppressors (LITAF, Casp8 and BRCA2) and immune genes (IL2, CD274 and B2M). This approach allowed us to conduct a fine scale analysis of gene wide and site-specific signatures of selection across mammalian lineages under the lens of cancer susceptibility. Phylogenetic analyses revealed that for most species the evolution of cancer associated genes follows the species' evolution. The gene wide selection analyses revealed oncogenes being the most conserved, tumour suppressor and immune genes having similar amounts of episodic diversifying selection. Despite BRCA2's status as a key caretaker gene, episodic diversifying selection was detected across mammals. The site-specific selection analyses revealed that the two apoptosis associated domains of the Casp8 gene of bats (Chiroptera) are under opposing forces of selection (positive and negative respectively), highlighting the importance of site-specific selection analyses to understand the evolution of highly complex gene families. Our results highlighted the need to critically assess different types of selection pressure on cancer associated genes when investigating evolutionary adaptations to cancer across the tree of life. This study provides an extensive assessment of cancer associated genes in mammals with highly representative, and substantially large sample size for a comparative genomic analysis in the field and identifies various avenues for future research into the mechanisms of cancer resistance and susceptibility in mammals.

RNA isoform expression landscape of the human dorsal root ganglion generated from long-read sequencing

ABSTRACT

Splicing is a posttranscriptional RNA processing mechanism that enhances genomic complexity by creating multiple isoforms from the same gene. We aimed to characterize the isoforms expressed in the human peripheral nervous system, with the goal of creating a resource to identify novel isoforms of functionally relevant genes associated with somatosensation and nociception. We used long-read sequencing to document isoform expression in the human dorsal root ganglia from 3 organ donors and validated in silico by confirming expression in short-read sequencing from 3 independent organ donors. Nineteen thousand five hundred forty-seven isoforms of protein-coding genes were detected and validated. We identified 763 isoforms with at least one previously undescribed splice junction. Previously unannotated isoforms of multiple pain-associated genes, including ASIC3, MRGPRX1, and HNRNPK, were identified. In the novel isoforms of ASIC3, a region comprising approximately 35% of the 5'UTR was excised. By contrast, a novel splice junction was used in isoforms of MRGPRX1 to include an additional exon upstream of the start codon, consequently adding a region to the 5'UTR. Novel isoforms of HNRNPK were identified, which used previously unannotated splice sites to both excise exon 14 and include a sequence in the 3' end of exon 13. This novel insertion is predicted to introduce a tyrosine phosphorylation site potentially phosphorylated by SRC. We also independently confirm a recently reported DRG-specific splicing event in WNK1 that gives insight into how painless peripheral neuropathy occurs when this gene is mutated. Our findings give a clear overview of mRNA isoform diversity in the human dorsal root ganglia obtained using long-read sequencing.

Development of a compact bidirectional promoter-driven dual chimeric antigen receptor (CAR) construct targeting CD19 and CD20 in the Sleeping Beauty (SB) transposon system

BACKGROUND

A bidirectional promoter-driven chimeric antigen receptor (CAR) cassette provides the simultaneous expression of two CARs, which significantly enhances dual antigen-targeted CAR T-cell therapy.

METHODS

We developed a second-generation CAR directing CD19 and CD20 antigens, incorporating them in a head-to-head orientation from a bidirectional promoter using a single Sleeping Beauty transposon system. The efficacy of bidirectional promoter-driven dual CD19 and CD20 CAR T cells was determined in vitro against cell lines expressing either, or both, CD19 and CD20 antigens. In vivo antitumor activity was tested in Raji lymphoma-bearing immunodeficient NOD-scid IL2Rgammanull (NSG) mice.

RESULTS

Of all tested promoters, the bidirectional EF-1α promoter optimally expressed transcripts from both sense (CD19-CAR) and antisense (GFP.CD20-CAR) directions. Superior cytotoxicity, cytokine production and antigen-specific activation were observed in vitro in the bidirectional EF-1α promoter-driven CD19/CD20 CAR T cells. In contrast, a unidirectional construct driven by the EF-1α promoter, but using self-cleaving peptide-linked CD19 and CD20 CARs, showed inferior expression and in vitro function. Treatment of mice bearing advanced Raji lymphomas with bidirectional EF-1α promoter-driven CD19/CD20 CAR T cells effectively controlled tumor growth and extended the survival of mice compared with group treated with single antigen targeted CAR T cells.

CONCLUSION

The use of bidirectional promoters in a single vector offers advantages of size and robust CAR expression with the potential to expand use in other forms of gene therapies like CAR T cells.

Parallel gene size and isoform expansion of ancient neuronal genes

How nervous systems evolved is a central question in biology. A diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning hundreds of thousands of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. Although many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and, in many cases, the emergence of neurons as dedicated cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes potentially driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection, as demonstrated by low dN/dS ratios, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

Essentiality, protein-protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning

The distinctive nature of cancer as a disease prompts an exploration of the special characteristics the genes implicated in cancer exhibit. The identification of cancer-associated genes and their characteristics is crucial to further our understanding of this disease and enhanced likelihood of therapeutic drug targets success. However, the rate at which cancer genes are being identified experimentally is slow. Applying predictive analysis techniques, through the building of accurate machine learning models, is potentially a useful approach in enhancing the identification rate of these genes and their characteristics. Here, we investigated gene essentiality scores and found that they tend to be higher for cancer-associated genes compared to other protein-coding human genes. We built a dataset of extended gene properties linked to essentiality and used it to train a machine-learning model; this model reached 89% accuracy and > 0.85 for the Area Under Curve (AUC). The model showed that essentiality, evolutionary-related properties, and properties arising from protein-protein interaction networks are particularly effective in predicting cancer-associated genes. We were able to use the model to identify potential candidate genes that have not been previously linked to cancer. Prioritising genes that score highly by our methods could aid scientists in their cancer genes research.

Evolutionary neurogenomics: Lengthy resolutions for complex brains

Genomic blueprints underlying unique neuronal organization are enigmatic. A new study reveals the recruitment of ancient, larger genes for synaptic machinery, providing evolutionary constraints and flexibility, with increasing gene sizes being found in animal lineages that led to cephalopods and vertebrates.

Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis

Transcriptional regulation is a critical adaptive mechanism that allows bacteria to respond to changing environments, yet the concept of transcriptional plasticity (TP) - the variability of gene expression in response to environmental changes - remains largely unexplored. In this study, we investigate the genome-wide TP profiles of Mycobacterium tuberculosis (Mtb) genes by analyzing 894 RNA sequencing samples derived from 73 different environmental conditions. Our data reveal that Mtb genes exhibit significant TP variation that correlates with gene function and gene essentiality. We also find that critical genetic features, such as gene length, GC content, and operon size independently impose constraints on TP, beyond trans-regulation. By extending our analysis to include two other Mycobacterium species -- M. smegmatis and M. abscessus -- we demonstrate a striking conservation of the TP landscape. This study provides a comprehensive understanding of the TP exhibited by mycobacteria genes, shedding light on this significant, yet understudied, genetic feature encoded in bacterial genomes.

Time is ticking faster for long genes in aging

Recent studies of aging organisms have identified a systematic phenomenon, characterized by a negative correlation between gene length and their expression in various cell types, species, and diseases. We term this phenomenon gene-length-dependent transcription decline (GLTD) and suggest that it may represent a bottleneck in the transcription machinery and thereby significantly contribute to aging as an etiological factor. We review potential links between GLTD and key aging processes such as DNA damage and explore their potential in identifying disease modification targets. Notably, in Alzheimer's disease, GLTD spotlights extremely long synaptic genes at chromosomal fragile sites (CFSs) and their vulnerability to postmitotic DNA damage. We suggest that GLTD is an integral element of biological aging.

Meta-Research: Understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results

Present-day publications on human genes primarily feature genes that already appeared in many publications prior to completion of the Human Genome Project in 2003. These patterns persist despite the subsequent adoption of high-throughput technologies, which routinely identify novel genes associated with biological processes and disease. Although several hypotheses for bias in the selection of genes as research targets have been proposed, their explanatory powers have not yet been compared. Our analysis suggests that understudied genes are systematically abandoned in favor of better-studied genes between the completion of -omics experiments and the reporting of results. Understudied genes remain abandoned by studies that cite these -omics experiments. Conversely, we find that publications on understudied genes may even accrue a greater number of citations. Among 45 biological and experimental factors previously proposed to affect which genes are being studied, we find that 33 are significantly associated with the choice of hit genes presented in titles and abstracts of -omics studies. To promote the investigation of understudied genes, we condense our insights into a tool, find my understudied genes (FMUG), that allows scientists to engage with potential bias during the selection of hits. We demonstrate the utility of FMUG through the identification of genes that remain understudied in vertebrate aging. FMUG is developed in Flutter and is available for download at fmug.amaral.northwestern.edu as a MacOS/Windows app.

Meta-analysis of 46,000 germline de novo mutations linked to human inherited disease

BACKGROUND

De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories.

RESULTS

Most disease-associated DNMs reported to date are found to be associated with developmental and psychiatric disorders, a reflection of the focus of sequencing efforts over the last decade. Of the 13,277 human genes in which DNMs have so far been found, the top-10 genes with the highest proportions of DNM relative to gene size were H3-3 A, DDX3X, CSNK2B, PURA, ZC4H2, STXBP1, SCN1A, SATB2, H3-3B and TUBA1A. The distribution of CADD and REVEL scores for both disease-associated DNMs and those mutations not reported to be de novo revealed a trend towards higher deleteriousness for DNMs, consistent with the likely lower selection pressure impacting them. This contrasts with the non-DNMs, which are presumed to have been subject to continuous negative selection over multiple generations.

CONCLUSION

This meta-analysis provides important information on the occurrence and distribution of disease-associated DNMs in association with heritable disease and should make a significant contribution to our understanding of this major type of mutation.

Molecular characterization of genes involved in tolerance of cadmium in Triticum aestivum (L.) under Cd stress

The NRAMPs (natural resistance-associated macrophage proteins) are major transporters for the absorption and transport of metals like Pb, Zn, Mn, Fe, and Cd in plants. While NRAMP gene family members have been extensively studied as metal transporters in model and other plants, little information has been reported on their role in Triticum aestivum, particularly in response to Cd stress. Current study reported 13 NRAMP candidates in the genome of T. aestivum. Phylogenetic analysis divided these into three clades. Motif and gene structure study showed that members in the same clades shared the same location and pattern, which further supported the phylogenetic analysis. The analysis of cis-acting elements in promoter sequences of NRAMP genes in wheat identified stress-responsive transcription factor binding sites. Multiple sequence alignment identified the conservation of important residues. Based on RNA-seq and qRT-PCR analysis, Cd stress-responsive variations of TaNRAMP gene expression were reported. This study provides comprehensive data to understand the TaNRAMP gene family, its features, and its expression, which will be a helpful framework for functional research.

Profiling of RNA-binding protein binding sites by in situ reverse transcription-based sequencing

RNA-binding proteins (RBPs) regulate diverse cellular processes by dynamically interacting with RNA targets. However, effective methods to capture both stable and transient interactions between RBPs and their RNA targets are still lacking, especially when the interaction is dynamic or samples are limited. Here we present an assay of reverse transcription-based RBP binding site sequencing (ARTR-seq), which relies on in situ reverse transcription of RBP-bound RNAs guided by antibodies to identify RBP binding sites. ARTR-seq avoids ultraviolet crosslinking and immunoprecipitation, allowing for efficient and specific identification of RBP binding sites from as few as 20 cells or a tissue section. Taking advantage of rapid formaldehyde fixation, ARTR-seq enables capturing the dynamic RNA binding by RBPs over a short period of time, as demonstrated by the profiling of dynamic RNA binding of G3BP1 during stress granule assembly on a timescale as short as 10 minutes.

Unique Patterns in Amino Acid Sequences of Aging-Related Proteins

Aging has strong genetic components and the list of genes that may regulate the aging process is collected in the GenAge database. There may be characteristic patterns in the amino acid sequences of aging-related proteins that distinguish them from other proteins and this information will lead to a better understanding of the aging process. To test this hypothesis, human protein sequences are extracted from the UniProt database and the relative frequency of every amino acid residue in aging-related proteins and the remaining proteins is calculated. The main observation is that the mean relative frequency of aspartic acid (D) is consistently higher, while the mean relative frequencies of tryptophan (W) and leucine (L) are consistently lower in aging-related proteins compared to the non-aging-related proteins for the human and four examined model organisms. It is also observed that the mean relative frequency of aspartic acid is higher, while the mean relative frequency of tryptophan is lower in pro-longevity proteins compared to anti-longevity proteins in model organisms. Finally, it is found that aging-related proteins tend to be longer than non-aging-related proteins. It is hoped that this analysis initiates further computational and experimental research to explore the underlying mechanisms of these findings.

sRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.

Contrasting and Combining Transcriptome Complexity Captured by Short and Long RNA Sequencing Reads

Mapping transcriptomic variations using either short or long reads RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, while short reads still provides improved coverage and error rates. Yet how to quantitatively compare the technologies, can we combine those, and what may be the benefit of such a combined view remain open questions. We tackle these questions by first creating a pipeline to assess matched long and short reads data using a variety of transcriptome statistics. We find that across datasets, algorithms and technologies, matched short reads data detects roughly 50% more splice junctions, with 10-30% of the splice junctions included at 20% or more are missed by long reads. In contrast, long reads detect many more intron retention events, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long reads technology or algorithm, and combine it with short reads data for improved transcriptome analysis.

RNA isoform expression landscape of the human dorsal root ganglion (DRG) generated from long read sequencing

Splicing is a post-transcriptional RNA processing mechanism that enhances genomic complexity by creating multiple isoforms from the same gene. Diversity in splicing in the mammalian nervous system is associated with neuronal development, synaptic function and plasticity, and is also associated with diseases of the nervous system ranging from neurodegeneration to chronic pain. We aimed to characterize the isoforms expressed in the human peripheral nervous system, with the goal of creating a resource to identify novel isoforms of functionally relevant genes associated with somatosensation and nociception. We used long read sequencing (LRS) to document isoform expression in the human dorsal root ganglia (hDRG) from 3 organ donors. Isoforms were validated in silico by confirming expression in hDRG short read sequencing (SRS) data from 3 independent organ donors. 19,547 isoforms of protein-coding genes were detected using LRS and validated with SRS and strict expression cutoffs. We identified 763 isoforms with at least one previously undescribed splice-junction. Previously unannotated isoforms of multiple pain-associated genes, including ASIC3, MRGPRX1 and HNRNPK were identified. In the novel isoforms of ASIC3, a region comprising ~35% of the 5'UTR was excised. In contrast, a novel splice-junction was utilized in isoforms of MRGPRX1 to include an additional exon upstream of the start-codon, consequently adding a region to the 5'UTR. Novel isoforms of HNRNPK were identified which utilized previously unannotated splice-sites to both excise exon 14 and include a sequence in the 5' end of exon 13. The insertion and deletion in the coding region was predicted to excise a serine-phosphorylation site favored by cdc2, and replace it with a tyrosine-phosphorylation site potentially phosphorylated by SRC. We also independently confirm a recently reported DRG-specific splicing event in WNK1 that gives insight into how painless peripheral neuropathy occurs when this gene is mutated. Our findings give a clear overview of mRNA isoform diversity in the hDRG obtained using LRS. Using this work as a foundation, an important next step will be to use LRS on hDRG tissues recovered from people with a history of chronic pain. This should enable identification of new drug targets and a better understanding of chronic pain that may involve aberrant splicing events.

FTLD targets brain regions expressing recently evolved genes

In frontotemporal lobar degeneration (FTLD), pathological protein aggregation is associated with a decline in human-specialized social-emotional and language functions. Most disease protein aggregates contain either TDP-43 (FTLD-TDP) or tau (FTLD-tau). Here, we explored whether FTLD targets brain regions that express genes containing human accelerated regions (HARs), conserved sequences that have undergone positive selection during recent human evolution. To this end, we used structural neuroimaging from patients with FTLD and normative human regional transcriptomic data to identify genes expressed in FTLD-targeted brain regions. We then integrated primate comparative genomic data to test our hypothesis that FTLD targets brain regions expressing recently evolved genes. In addition, we asked whether genes expressed in FTLD-targeted brain regions are enriched for genes that undergo cryptic splicing when TDP-43 function is impaired. We found that FTLD-TDP and FTLD-tau subtypes target brain regions that express overlapping and distinct genes, including many linked to neuromodulatory functions. Genes whose normative brain regional expression pattern correlated with FTLD cortical atrophy were strongly associated with HARs. Atrophy-correlated genes in FTLD-TDP showed greater overlap with TDP-43 cryptic splicing genes compared with atrophy-correlated genes in FTLD-tau. Cryptic splicing genes were enriched for HAR genes, and vice versa, but this effect was due to the confounding influence of gene length. Analyses performed at the individual-patient level revealed that the expression of HAR genes and cryptically spliced genes within putative regions of disease onset differed across FTLD-TDP subtypes. Overall, our findings suggest that FTLD targets brain regions that have undergone recent evolutionary specialization and provide intriguing potential leads regarding the transcriptomic basis for selective vulnerability in distinct FTLD molecular-anatomical subtypes.

A sub-set of guanine- and cytosine-rich genes are actively transcribed at the nuclear Lamin B1 region

Chromatin organization in the mammalian cell nucleus plays a vital role in the regulation of gene expression. The lamina-associated domain at the inner nuclear membrane has been proposed to harbor heterochromatin, while the nuclear interior has been shown to contain most of the euchromatin. Here, we show that a sub-set of actively transcribing genes, marked by RNA Pol II pSer2, are associated with Lamin B1 at the inner nuclear envelop in mESCs and the number of genes proportionally increases upon in vitro differentiation of mESC to olfactory precursor cells. These nuclear periphery-associated actively transcribing genes primarily represent housekeeping genes, and their gene bodies are significantly enriched with guanine and cytosine compared to genes actively transcribed at the nuclear interior. We found the promoters of these genes to also be significantly enriched with guanine and to be predominantly regulated by zinc finger protein transcription factors. We provide evidence supporting the emerging notion that the Lamin B1 region is not solely transcriptionally silent.

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

Copy number losses (deletions) are a major contributor to the etiology of severe genetic disorders. Although haploinsufficient genes play a critical role in deletion pathogenicity, current methods for deletion pathogenicity prediction fail to integrate multiple lines of evidence for haploinsufficiency at the gene level, limiting their power to pinpoint deleterious deletions associated with genetic disorders. Here we introduce DosaCNV, a deep multiple-instance learning framework that, for the first time, models deletion pathogenicity jointly with gene haploinsufficiency. By integrating over 30 gene-level features potentially predictive of haploinsufficiency, DosaCNV shows unmatched performance in prioritizing pathogenic deletions associated with a broad spectrum of genetic disorders. Furthermore, DosaCNV outperforms existing methods in predicting gene haploinsufficiency even though it is not trained on known haploinsufficient genes. Finally, DosaCNV leverages a state-of-the-art technique to quantify the contributions of individual gene-level features to haploinsufficiency, allowing for human-understandable explanations of model predictions. Altogether, DosaCNV is a powerful computational tool for both fundamental and translational research.

To Break or Not to Break: The Role of TOP2B in Transcription

Transcription and its regulation pose challenges related to DNA torsion and supercoiling of the DNA template. RNA polymerase tracking the helical groove of the DNA introduces positive helical torsion and supercoiling upstream and negative torsion and supercoiling behind its direction of travel. This can inhibit transcriptional elongation and other processes essential to transcription. In addition, chromatin remodeling associated with gene activation can generate or be hindered by excess DNA torsional stress in gene regulatory regions. These topological challenges are solved by DNA topoisomerases via a strand-passage reaction which involves transiently breaking and re-joining of one (type I topoisomerases) or both (type II topoisomerases) strands of the phosphodiester backbone. This review will focus on one of the two mammalian type II DNA topoisomerase enzymes, DNA topoisomerase II beta (TOP2B), that have been implicated in correct execution of developmental transcriptional programs and in signal-induced transcription, including transcriptional activation by nuclear hormone ligands. Surprisingly, several lines of evidence indicate that TOP2B-mediated protein-free DNA double-strand breaks are involved in signal-induced transcription. We discuss the possible significance and origins of these DSBs along with a network of protein interaction data supporting a variety of roles for TOP2B in transcriptional regulation.

Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis

Transcriptional regulation is a critical adaptive mechanism that allows bacteria to respond to changing environments, yet the concept of transcriptional plasticity (TP) remains largely unexplored. In this study, we investigate the genome-wide TP profiles of Mycobacterium tuberculosis (Mtb) genes by analyzing 894 RNA sequencing samples derived from 73 different environmental conditions. Our data reveal that Mtb genes exhibit significant TP variation that correlates with gene function and gene essentiality. We also found that critical genetic features, such as gene length, GC content, and operon size independently impose constraints on TP, beyond trans-regulation. By extending our analysis to include two other Mycobacterium species -- M. smegmatis and M. abscessus -- we demonstrate a striking conservation of the TP landscape. This study provides a comprehensive understanding of the TP exhibited by mycobacteria genes, shedding light on this significant, yet understudied, genetic feature encoded in bacterial genomes.

Analysis and Prediction of Pathogen Nucleic Acid Specificity for Toll-like Receptors in Vertebrates

Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like receptors (TLRs), a representative class of membrane-bound sensor proteins, from 17 vertebrate species covering mammals, birds, reptiles, amphibians, and fishes in this comparative study. We identified the molecular signatures of host TLRs that are responsible for sensing pathogen nucleic acids or other pathogen-associated molecular patterns (PAMPs), and potentially play important roles in host defence mechanism. Interestingly, our findings reveal that such host-specific features are directly related to the strand (single or double) specificity of nucleic acid from pathogens. However, during host-pathogen interactions, such features were unable to explain the pathogenic PAMP (i.e., DNA, RNA or other) selectivity, suggesting a more complex mechanism. Using these features, we developed a number of machine learning models, of which Random Forest achieved a high performance (94.57% accuracy) to predict strand specificity of TLRs from protein-derived features. We applied the trained model to propose strand specificity of some previously uncharacterized distinct fish-specific novel TLRs (TLR18, TLR23, TLR24, TLR25, TLR27).

sRNAfrag: A pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs hold biological relevance. However, they remain poorly understood, calling for more comprehensive methods for analysis. We developed sRNAfrag, a standardized workflow and set of scripts to quantify and analyze sRNA fragmentation of any biotype. In a benchmark, it is able to detect loci of mature microRNAs fragmented from precursors and, utilizing multi-mapping events, the conserved 5' seed sequence of miRNAs which we believe may extraoplate to other small RNA fragments. The tool detected 1411 snoRNA fragment conservation events between 2/4 eukaryotic species, providing the opportunity to explore motifs and fragmentation patterns not only within species, but between. Availability: https://github.com/kenminsoo/sRNAfrag.

Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis

Transcriptional regulation is a critical adaptive mechanism that allows bacteria to respond to changing environments, yet the concept of transcriptional plasticity (TP) remains largely unexplored. In this study, we investigate the genome-wide TP profiles of Mycobacterium tuberculosis (Mtb) genes by analyzing 894 RNA sequencing samples derived from 73 different environmental conditions. Our data reveal that Mtb genes exhibit significant TP variation that correlates with gene function and gene essentiality. We also found that critical genetic features, such as gene length, GC content, and operon size independently impose constraints on TP, beyond trans-regulation. By extending our analysis to include two other Mycobacterium species -- M. smegmatis and M. abscessus -- we demonstrate a striking conservation of the TP landscape. This study provides a comprehensive understanding of the TP exhibited by mycobacteria genes, shedding light on this significant, yet understudied, genetic feature encoded in bacterial genomes.

Whole Genome Duplication and Gene Evolution in the Hyperdiverse Venomous Gastropods

The diversity of venomous organisms and the toxins they produce have been increasingly investigated, but taxonomic bias remains important. Neogastropods, a group of marine predators representing almost 22% of the known gastropod diversity, evolved a wide range of feeding strategies, including the production of toxins to subdue their preys. However, whether the diversity of these compounds is at the origin of the hyperdiversification of the group and how genome evolution may correlate with both the compounds and species diversities remain understudied. Among the available gastropods genomes, only eight, with uneven quality assemblies, belong to neogastropods. Here, we generated chromosome-level assemblies of two species belonging to the Tonnoidea and Muricoidea superfamilies (Monoplex corrugatus and Stramonita haemastoma). The two obtained high-quality genomes had 3 and 2.2 Gb, respectively, and 92-89% of the total assembly conformed 35 pseudochromosomes in each species. Through the analysis of syntenic blocks, Hox gene cluster duplication, and synonymous substitutions distribution pattern, we inferred the occurrence of a whole genome duplication event in both genomes. As these species are known to release venom, toxins were annotated in both genomes, but few of them were found in homologous chromosomes. A comparison of the expression of ohnolog genes (using transcriptomes from osphradium and salivary glands in S. haemastoma), where both copies were differentially expressed, showed that most of them had similar expression profiles. The high quality of these genomes makes them valuable reference in their respective taxa, facilitating the identification of genome-level processes at the origin of their evolutionary success.

Adjusting for gene-specific covariates to improve RNA-seq analysis

SUMMARY

This article suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by using two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning parameter through cross-validation that maximizes the expected number of hypotheses declared significant. A simulation study demonstrates that our method is comparable to or better than existing methods across realistic scenarios. In data analysis, we find support for our method's premise that the null probability varies with a gene-specific covariate variable.

AVAILABILITY AND IMPLEMENTATION

The source code repository is publicly available at https://github.com/hsjeon1217/conditional_method.

CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we developed CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5'capped, full-length transcripts, together with the data processing pipeline LyRic. We benchmarked CapTrap-seq and other popular RNA-seq library preparation protocols in a number of human tissues using both ONT and PacBio sequencing. To assess the accuracy of the transcript models produced, we introduced a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5'cap formation in RNA spike-in molecules. We found that the vast majority (up to 90%) of transcript models that LyRic derives from CapTrap-seq reads are full-length. This makes it possible to produce highly accurate annotations with minimal human intervention.

Strong ubiquitous micro-promoters for recombinant adeno-associated viral vectors

Significant progress has been made in developing recombinant adeno-associated virus (rAAV) for clinical gene therapy. While rAAV is a versatile gene delivery platform, its packaging limit of 4.7 kb limits the diseases it can target. Here, we report two unusually small promoters that enable the expression of larger transgenes than standard promoters. These micro-promoters are only 84 (MP-84) and 135 bp (MP-135) in size but have activity in most cells and tissues comparable to the CAG promoter, the strongest ubiquitous promoter to date. MP-84- and MP-135-based rAAV constructs displayed robust activity in cultured cells from the three different germ-layer lineages. In addition, reporter gene expression was documented in human primary hepatocytes and pancreatic islets and in multiple mouse tissues in vivo, including brain and skeletal muscle. MP-84 and MP-135 will enable the therapeutic expression of transgenes currently too large for rAAV vectors.

Protein length distribution is remarkably uniform across the tree of life

BACKGROUND

In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species but has so far been scarcely studied.

RESULTS

Here we evaluate this diversity by comparing protein length distribution across 2326 species (1688 bacteria, 153 archaea, and 485 eukaryotes). We find that proteins tend to be on average slightly longer in eukaryotes than in bacteria or archaea, but that the variation of length distribution across species is low, especially compared to the variation of other genomic features (genome size, number of proteins, gene length, GC content, isoelectric points of proteins). Moreover, most cases of atypical protein length distribution appear to be due to artifactual gene annotation, suggesting the actual variation of protein length distribution across species is even smaller.

CONCLUSIONS

These results open the way for developing a genome annotation quality metric based on protein length distribution to complement conventional quality measures. Overall, our findings show that protein length distribution between living species is more uniform than previously thought. Furthermore, we also provide evidence for a universal selection on protein length, yet its mechanism and fitness effect remain intriguing open questions.

Dissociation protocols used for sarcoma tissues bias the transcriptome observed in single-cell and single-nucleus RNA sequencing

BACKGROUND

Single-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the methods used for tissue processing, cell disaggregation, and preservation can significantly bias gene expression and alter the observed cell types. To determine whether sarcomas - tumors of mesenchymal origin - are subject to the same technical artifacts, we profiled patient-derived tumor explants (PDXs) propagated from three aggressive subtypes: osteosarcoma (OS), Ewing sarcoma (ES), desmoplastic small round cell tumor (DSRCT). Given the rarity of these sarcoma subtypes, we explored whether single-nuclei RNA-seq from more widely available archival frozen specimens could accurately be identified by gene expression signatures linked to tissue phenotype or pathognomonic fusion proteins.

RESULTS

We systematically assessed dissociation methods across different sarcoma subtypes. We compared gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from ES, DSRCT, and OS PDXs. We detected warm dissociation artifacts in single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of the dissociation method. In addition, we showed that dissociation method biases could be computationally corrected.

CONCLUSIONS

We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.

DNA damage-induced stalling of transcription drives aging through gene expression imbalance

Age-related changes in gene expression have long been examined to understand the biology of aging. The hallmarks of aging are biological processes known to be associated with aging, but whether there is a unifying driver of these attributes, is not well understood. With the advent of technology over the last few years, it is quite clear that aging leads to global decline in transcription. In this Perspective, we highlight a new study in Nature Genetics that aimed to determine why global transcription rate reduces with age and how this phenomenon is the driver that interconnects multiple hallmarks of aging. This study recognizes that age-related accumulation of DNA damage, particularly transcription-blocking lesions, stalls RNA polymerase. This phenomenon affects longer genes leading to a gradual loss of transcription and skewing the transcriptome. In order to design a successful aging intervention, future work will be needed to test how some promising therapies in pre-clinical trials target affect transcriptional rate.

U1 snRNP increases RNA Pol II elongation rate to enable synthesis of long genes

The expansion of introns within mammalian genomes poses a challenge for the production of full-length messenger RNAs (mRNAs), with increasing evidence that these long AT-rich sequences present obstacles to transcription. Here, we investigate RNA polymerase II (RNAPII) elongation at high resolution in mammalian cells and demonstrate that RNAPII transcribes faster across introns. Moreover, we find that this acceleration requires the association of U1 snRNP (U1) with the elongation complex at 5' splice sites. The role of U1 to stimulate elongation rate through introns reduces the frequency of both premature termination and transcriptional arrest, thereby dramatically increasing RNA production. We further show that changes in RNAPII elongation rate due to AT content and U1 binding explain previous reports of pausing or termination at splice junctions and the edge of CpG islands. We propose that U1-mediated acceleration of elongation has evolved to mitigate the risks that long AT-rich introns pose to transcript completion.

HIV persistence: silence or resistance?

Despite decades of suppressive antiretroviral therapy, human immunodeficiency virus (HIV) reservoirs in infected individuals persist and fuel viral rebound once therapy is interrupted. The persistence of viral reservoirs is the main obstacle to achieving HIV eradication or a long-term remission. The last decade has seen a profound change in our understanding of the mechanisms behind HIV persistence, which appears to be much more complex than originally assumed. In addition to the persistence of transcriptionally silent proviruses in a stable latent reservoir that is invisible to the immune system, HIV is increasingly recognized to persist by resistance to the immune clearance, which appears to play a surprisingly prominent role in shaping the reservoir. In this review, we discuss some emerging insights into the mechanisms of HIV persistence, as well as their implications for the development of strategies towards an HIV cure.

The Road Less Traveled: Uncovering the Convergence Toward Specific Pleiotropic Phenotypes in Aging

Aging is a complex process influenced by a wide range of environmental and molecular factors. Despite this complexity, individuals tend to age in highly similar ways, leading to the question of what drives this convergence. Recent research, including my own discoveries, suggests that the length of transcript molecules plays a crucial role in age-dependent changes to the transcriptome. Drawing inspiration from the road trip analogy of cellular transcription, I propose that a non-linear scaling law drives convergence towards specific pleiotropic phenotypes in biological aging. This scaling law is based on the notion that molecular changes observed during aging may reflect unspecific damage to cellular physiology. By validating this hypothesis, I can improve our understanding of biological aging and identify new candidate compounds for anti-aging interventions, as well as re-identify one known intervention. This work has actionable implications for improving human health and extending lifespans.

Integrator is a global promoter-proximal termination complex

Integrator is a metazoan-specific protein complex capable of inducing termination at all RNAPII-transcribed loci. Integrator recognizes paused, promoter-proximal RNAPII and drives premature termination using dual enzymatic activities: an endonuclease that cleaves nascent RNA and a protein phosphatase that removes stimulatory phosphorylation associated with RNAPII pause release and productive elongation. Recent breakthroughs in structural biology have revealed the overall architecture of Integrator and provided insights into how multiple Integrator modules are coordinated to elicit termination effectively. Furthermore, functional genomics and biochemical studies have unraveled how Integrator-mediated termination impacts protein-coding and noncoding loci. Here, we review the current knowledge about the assembly and activity of Integrator and describe the role of Integrator in gene regulation, highlighting the importance of this complex for human health.

Genome-wide RNA polymerase stalling shapes the transcriptome during aging

Gene expression profiling has identified numerous processes altered in aging, but how these changes arise is largely unknown. Here we combined nascent RNA sequencing and RNA polymerase II chromatin immunoprecipitation followed by sequencing to elucidate the underlying mechanisms triggering gene expression changes in wild-type aged mice. We found that in 2-year-old liver, 40% of elongating RNA polymerases are stalled, lowering productive transcription and skewing transcriptional output in a gene-length-dependent fashion. We demonstrate that this transcriptional stress is caused by endogenous DNA damage and explains the majority of gene expression changes in aging in most mainly postmitotic organs, specifically affecting aging hallmark pathways such as nutrient sensing, autophagy, proteostasis, energy metabolism, immune function and cellular stress resilience. Age-related transcriptional stress is evolutionary conserved from nematodes to humans. Thus, accumulation of stochastic endogenous DNA damage during aging deteriorates basal transcription, which establishes the age-related transcriptome and causes dysfunction of key aging hallmark pathways, disclosing how DNA damage functionally underlies major aspects of normal aging.

The position of the longest intron is related to biological functions in some human genes

The evidence that introns can influence different levels of transfer of genetic information between DNA and the final product is increasing. Longer first introns were found to be a general property of eukaryotic gene structure and shown to contain a higher fraction of conserved sequence and different functional elements. Our work brings more precise information about the position of the longest introns in human protein-coding genes and possible connection with biological function and gene expression. According to our results, the position of the longest intron can be localized to the first third of introns in 64%, the second third in 19%, and the third in 17%, with notable peaks at the middle and last introns of approximately 5% and 6%, respectively. The median lengths of the longest introns decrease with increasing distance from the start of the gene from approximately 15,000 to 5,000 bp. We have shown that the position of the longest intron is in some cases linked to the biological function of the given gene. For example, DNA repair genes have the longest intron more often in the second or third. In the distribution of gene expression according to the position of the longest intron, tissue-specific profiles can be traced with the highest expression usually at the absolute positions of intron 1 and 2. In this work, we present arguments supporting the hypothesis that the position of the longest intron in a gene is another biological factor modulating the transmission of genetic information. The position of the longest intron is related to biological functions in some human genes.

Conserved noncoding sequences and de novo Mutator insertion alleles are imprinted in maize

Genomic imprinting is an epigenetic phenomenon in which differential allele expression occurs in a parent-of-origin-dependent manner. Imprinting in plants is tightly linked to transposable elements (TEs), and it has been hypothesized that genomic imprinting may be a consequence of demethylation of TEs. Here, we performed high-throughput sequencing of ribonucleic acids from four maize (Zea mays) endosperms that segregated newly silenced Mutator (Mu) transposons and identified 110 paternally expressed imprinted genes (PEGs) and 139 maternally expressed imprinted genes (MEGs). Additionally, two potentially novel paternally suppressed MEGs are associated with de novo Mu insertions. In addition, we find evidence for parent-of-origin effects on expression of 407 conserved noncoding sequences (CNSs) in maize endosperm. The imprinted CNSs are largely localized within genic regions and near genes, but the imprinting status of the CNSs are largely independent of their associated genes. Both imprinted CNSs and PEGs have been subject to relaxed selection. However, our data suggest that although MEGs were already subject to a higher mutation rate prior to their being imprinted, imprinting may be the cause of the relaxed selection of PEGs. In addition, although DNA methylation is lower in the maternal alleles of both the maternally and paternally expressed CNSs (mat and pat CNSs), the difference between the two alleles in H3K27me3 levels was only observed in pat CNSs. Together, our findings point to the importance of both transposons and CNSs in genomic imprinting in maize.

Gene length is a pivotal feature to explain disparities in transcript capture between single transcriptome techniques

The scale and capability of single-cell and single-nucleus RNA-sequencing technologies are rapidly growing, enabling key discoveries and large-scale cell mapping operations. However, studies directly comparing technical differences between single-cell and single-nucleus RNA sequencing are still lacking. Here, we compared three paired single-cell and single-nucleus transcriptomes from three different organs (Heart, Lung and Kidney). Differently from previous studies that focused on cell classification, we explored disparities in the transcriptome output of whole cells relative to the nucleus. We found that the major cell clusters could be recovered by either technique from matched samples, but at different proportions. In 2/3 datasets (kidney and lung) we detected clusters exclusively present with single-nucleus RNA sequencing. In all three organ groups, we found that genomic and gene structural characteristics such as gene length and exon content significantly differed between the two techniques. Genes recovered with the single-nucleus RNA sequencing technique had longer sequence lengths and larger exon counts, whereas single-cell RNA sequencing captured short genes at higher rates. Furthermore, we found that when compared to the whole host genome (mouse for kidney and lung datasets and human for the heart dataset), single transcriptomes obtained with either technique skewed from the expected proportions in several points: a) coding sequence length, b) transcript length and c) genomic span; and d) distribution of genes based on exons counts. Interestingly, the top-100 DEG between the two techniques returned distinctive GO terms. Hence, the type of single transcriptome technique used affected the outcome of downstream analysis. In summary, our data revealed both techniques present disparities in RNA capture. Moreover, the biased RNA capture affected the calculations of basic cellular parameters, raising pivotal points about the limitations and advantages of either single transcriptome techniques.

An effect of large-scale deletions and duplications on transcript expression

Since copy number variants (CNVs) have been recognized as an important source of genetic and transcriptomic variation, we aimed to characterize the impact of CNVs located within coding, intergenic, upstream, and downstream gene regions on the expression of transcripts. Regions in which deletions occurred most often were introns, while duplications in coding regions. The transcript expression was lower for deleted coding (P = 0.008) and intronic regions (P = 1.355 × 10^-10), but it was not changed in the case of upstream and downstream gene regions (P = 0.085). Moreover, the expression was decreased if duplication occurred in the coding region (P = 8.318 × 10^-5). Furthermore, a negative correlation (r =  - 0.27) between transcript length and its expression was observed. The correlation between the percent of deleted/duplicated transcript and transcript expression level was not significant for all concerned genomic regions in five out of six animals. The exceptions were deletions in coding regions (P = 0.004) and duplications in introns (P = 0.01) in one individual. CNVs in coding (deletions, duplications) and intronic (deletions) regions are important modulators of transcripts by reducing their expression level. We hypothesize that deletions imply severe consequences by interrupting genes. The negative correlation between the size of the transcript and its expression level found in this study is consistent with the hypothesis that selection favours shorter introns and a moderate number of exons in highly expressed genes. This may explain the transcript expression reduction by duplications. We did not find the correlation between the size of deletions/duplications and transcript expression level suggesting that expression is modulated by CNVs regardless of their size.

New Assay Reveals Vast Excess of Defective over Intact HIV-1 Transcripts in Antiretroviral Therapy-Suppressed Individuals

Most of the HIV DNA in infected individuals is noninfectious because of deleterious mutations. However, it is unclear how much of the transcribed HIV RNA is potentially infectious or defective. To address this question, we developed and validated a novel intact viral RNA assay (IVRA) that uses droplet digital reverse transcriptase PCR (dd-RT-PCR) for the commonly mutated packaging signal (Psi) and Rev response element (RRE) regions (from the intact proviral DNA assay [IPDA]) to quantify likely intact (Psi⁺ RRE⁺), 3' defective (Psi⁺ RRE^-), and 5' defective (Psi^- RRE⁺) HIV RNA. We then applied the IPDA and IVRA to quantify intact and defective HIV DNA and RNA from peripheral CD4⁺ T cells from 9 antiretroviral therapy (ART)-suppressed individuals. Levels of 3' defective HIV DNA were not significantly different from those of 5' defective HIV DNA, and both were higher than intact HIV DNA. In contrast, 3' defective HIV RNA (median 86 copies/10⁶ cells; 94% of HIV RNA) was much more abundant than 5' defective (2.1 copies/10⁶ cells; 5.6%) or intact (0.6 copies/10⁶ cells; <1%) HIV RNA. Likewise, the frequency of CD4⁺ T cells with 3' defective HIV RNA was greater than the frequency with 5' defective or intact HIV RNA. Intact HIV RNA was transcribed by a median of 0.018% of all proviruses and 2.2% of intact proviruses. The vast excess of 3' defective RNA over 5' defective or intact HIV RNA, which was not observed for HIV DNA, suggests that HIV transcription is completely blocked prior to the RRE in most cells with intact proviruses and/or that cells transcribing intact HIV RNA are cleared at very high rates. IMPORTANCE We developed a new assay that can distinguish and quantify intact (potentially infectious) as well as defective HIV RNA. In ART-treated individuals, we found that the vast majority of all HIV RNA is defective at the 3' end, possibly due to incomplete transcriptional processivity. Only a very small percentage of all HIV RNA is intact, and very few total or intact proviruses transcribe intact HIV RNA. Though rare, this intact HIV RNA is tremendously important because it is necessary to serve as the genome of infectious virions that allow transmission and spread, including rebound after stopping ART. Moreover, intact viral RNA may contribute disproportionately to the immune activation, inflammation, and organ damage observed with untreated and treated HIV infection. The intact viral RNA assay can be applied to many future studies aimed at better understanding HIV pathogenesis and barriers to HIV cure.

Aging is associated with a systemic length-associated transcriptome imbalance

Aging is among the most important risk factors for morbidity and mortality. To contribute toward a molecular understanding of aging, we analyzed age-resolved transcriptomic data from multiple studies. Here, we show that transcript length alone explains most transcriptional changes observed with aging in mice and humans. We present three lines of evidence supporting the biological importance of the uncovered transcriptome imbalance. First, in vertebrates the length association primarily displays a lower relative abundance of long transcripts in aging. Second, eight antiaging interventions of the Interventions Testing Program of the National Institute on Aging can counter this length association. Third, we find that in humans and mice the genes with the longest transcripts enrich for genes reported to extend lifespan, whereas those with the shortest transcripts enrich for genes reported to shorten lifespan. Our study opens fundamental questions on aging and the organization of transcriptomes.

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression

MOTIVATION

Clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic perturbation screen is a powerful tool to probe gene function. However, experimental noises, especially for the lowly expressed genes, need to be accounted for to maintain proper control of false positive rate.

METHODS

We develop a statistical method, named CRISPR screen with Expression Data Analysis (CEDA), to integrate gene expression profiles and CRISPR screen data for identifying essential genes. CEDA stratifies genes based on expression level and adopts a three-component mixture model for the log-fold change of single-guide RNAs (sgRNAs). Empirical Bayesian prior and expectation-maximization algorithm are used for parameter estimation and false discovery rate inference.

RESULTS

Taking advantage of gene expression data, CEDA identifies essential genes with higher expression. Compared to existing methods, CEDA shows comparable reliability but higher sensitivity in detecting essential genes with moderate sgRNA fold change. Therefore, using the same CRISPR data, CEDA generates an additional hit gene list.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantum computing algorithms: getting closer to critical problems in computational biology

The recent biotechnological progress has allowed life scientists and physicians to access an unprecedented, massive amount of data at all levels (molecular, supramolecular, cellular and so on) of biological complexity. So far, mostly classical computational efforts have been dedicated to the simulation, prediction or de novo design of biomolecules, in order to improve the understanding of their function or to develop novel therapeutics. At a higher level of complexity, the progress of omics disciplines (genomics, transcriptomics, proteomics and metabolomics) has prompted researchers to develop informatics means to describe and annotate new biomolecules identified with a resolution down to the single cell, but also with a high-throughput speed. Machine learning approaches have been implemented to both the modelling studies and the handling of biomedical data. Quantum computing (QC) approaches hold the promise to resolve, speed up or refine the analysis of a wide range of these computational problems. Here, we review and comment on recently developed QC algorithms for biocomputing, with a particular focus on multi-scale modelling and genomic analyses. Indeed, differently from other computational approaches such as protein structure prediction, these problems have been shown to be adequately mapped onto quantum architectures, the main limit for their immediate use being the number of qubits and decoherence effects in the available quantum machines. Possible advantages over the classical counterparts are highlighted, along with a description of some hybrid classical/quantum approaches, which could be the closest to be realistically applied in biocomputation.

Integrator endonuclease drives promoter-proximal termination at all RNA polymerase II-transcribed loci

RNA polymerase II (RNAPII) pausing in early elongation is critical for gene regulation. Paused RNAPII can be released into productive elongation by the kinase P-TEFb or targeted for premature termination by the Integrator complex. Integrator comprises endonuclease and phosphatase activities, driving termination by cleavage of nascent RNA and removal of stimulatory phosphorylation. We generated a degron system for rapid Integrator endonuclease (INTS11) depletion to probe the direct consequences of Integrator-mediated RNA cleavage. Degradation of INTS11 elicits nearly universal increases in active early elongation complexes. However, these RNAPII complexes fail to achieve optimal elongation rates and exhibit persistent Integrator phosphatase activity. Thus, only short transcripts are significantly upregulated following INTS11 loss, including transcription factors, signaling regulators, and non-coding RNAs. We propose a uniform molecular function for INTS11 across all RNAPII-transcribed loci, with differential effects on particular genes, pathways, or RNA biotypes reflective of transcript lengths rather than specificity of Integrator activity.

Distinct chromosomal “niches” in the genome of Saccharomyces cerevisiae provide the background for genomic innovation and shape the fate of gene duplicates

Nearly one third of Saccharomyces cerevisiae protein coding sequences correspond to duplicate genes, equally split between small-scale duplicates (SSD) and whole-genome duplicates (WGD). While duplicate genes have distinct properties compared to singletons, to date, there has been no systematic analysis of their positional preferences. In this work, we show that SSD and WGD genes are organized in distinct gene clusters that occupy different genomic regions, with SSD being more peripheral and WGD more centrally positioned close to centromeric chromatin. Duplicate gene clusters differ from the rest of the genome in terms of gene size and spacing, gene expression variability and regulatory complexity, properties that are also shared by singleton genes residing within them. Singletons within duplicate gene clusters have longer promoters, more complex structure and a higher number of protein–protein interactions. Particular chromatin architectures appear to be important for gene evolution, as we find SSD gene-pair co-expression to be strongly associated with the similarity of nucleosome positioning patterns. We propose that specific regions of the yeast genome provide a favourable environment for the generation and maintenance of small-scale gene duplicates, segregating them from WGD-enriched genomic domains. Our findings provide a valuable framework linking genomic innovation with positional genomic preferences.

Modeling tissue-specific breakpoint proximity of structural variations from whole-genomes to identify cancer drivers

Structural variations (SVs) in cancer cells often impact large genomic regions with functional consequences. However, identification of SVs under positive selection is a challenging task because little is known about the genomic features related to the background breakpoint distribution in different cancers. We report a method that uses a generalized additive model to investigate the breakpoint proximity curves from 2,382 whole-genomes of 32 cancer types. We find that a multivariate model, which includes linear and nonlinear partial contributions of various tissue-specific features and their interaction terms, can explain up to 57% of the observed deviance of breakpoint proximity. In particular, three-dimensional genomic features such as topologically associating domains (TADs), TAD-boundaries and their interaction with other features show significant contributions. The model is validated by identification of known cancer genes and revealed putative drivers in cancers different than those with previous evidence of positive selection.

Identifying structural variants (SVs) under positive selection in cancer is challenging. Here, the authors develop CSVDriver, a method that computes SV breakpoint proximity and the contribution of elements such as topologically associating domains, and identifies loci that show signs of positive selection and contain known and putative drivers.

Stressful steps: Progress and challenges in understanding stress-induced mRNA condensation and accumulation in stress granules

Stress-induced condensation of mRNA and protein into massive cytosolic clusters is conserved across eukaryotes. Known as stress granules when visible by imaging, these structures remarkably have no broadly accepted biological function, mechanism of formation or dispersal, or even molecular composition. As part of a larger surge of interest in biomolecular condensation, studies of stress granules and related RNA/protein condensates have increasingly probed the biochemical underpinnings of condensation. Here, we review open questions and recent advances, including the stages from initial condensate formation to accumulation in mature stress granules, mechanisms by which stress-induced condensates form and dissolve, and surprising twists in understanding the RNA components of stress granules and their role in condensation. We outline grand challenges in understanding stress-induced RNA condensation, centering on the unique and substantial barriers in the molecular study of cellular structures, such as stress granules, for which no biological function has been firmly established.