Biology subjects

Weile, J.

Publications and source records attributed to Weile, J..

15 recordsLinked to original sources

bioRxiv2025

Using GPT-4 to Automate the Generation of Lay Summaries for Cancer Publications

BackgroundCancer research literature is often riddled with technical jargon that is not digestible to the average person. Individuals interested in research studies may want to contribute through patient partner engagement or sample donation but find the relevant literature overwhelming. Through the generation of lay summaries, previously inaccessible research papers become easier to comprehend, especially for patient partners or data donors. With large language models (LLMs) continuing to advance, so does their capability to summarize large texts. ObjectivesIn this study, we examined whether LLMs can produce lay summaries of scientific literature at-scale, while maintaining readability and accuracy to their source texts. MethodsWe developed a tool to generate lay summaries of open-access article abstracts and their full texts with GPT-4-Turbo. Prompt development aimed for a target 8th grade reading level assessed with Flesch-Kincaid Grade Level. Human-review metrics were used to evaluate readability and accuracy when generated using abstracts versus full text articles. ResultsThe average Flesch-Kincaid Grade Level Score was 7.13 for abstract-based summaries and 7.39 for full text-based summaries, indicating summaries at around 7th grade reading level. Human-review metrics showed these summaries were of similar readability and accuracy when generated using abstracts versus full text articles, with mean accuracy scores from human review of 7.09 vs 7.42 out of 10 respectively. Additionally, qualitative patient-based assessment indicated these summaries would encourage participation in research studies. ConclusionBy generating lay summaries for complex and lengthy research papers, their scientific information becomes accessible to a larger audience, including patient partners interested in contributing to cancer research. Summaries that are easy to understand will allow participants to make informed decisions about their involvement and appreciate the impact of their contributions if and when their results are published. Lay SummaryThis study explores if artificial intelligence (AI) can help make hard to read cancer research papers easier to understand for members of the public. ProblemWhen people donate cancer tissue samples or participate in research studies, they often want to know how their contributions are being used. However, scientific papers are full of technical language thats hard for most people to grasp. People in past studies have said this can make them less willing to take part in research. MethodsThe study created a computer program using AI (GPT-4-Turbo) to turn complex kidney cancer research papers into simple summaries. They tested whether the AI could summarize both short abstracts and full-length papers effectively. They aimed for summaries at a 6th to 8th-grade reading level. This was to follow Canadian and U.S. health communication guidelines. ResultsThe AI created 106 summaries. Computer measures showed the summaries were close to a 7th-grade reading level. Though, researchers had to tell the AI to write for a 2nd-grade audience to achieve this. Of note, summaries from short abstracts were just as accurate and readable as those from full papers. Eighteen volunteers, including five patient partners, reviewed the summaries and rated them for clarity and accuracy. They were rated at around 7 out of 10 points. All patient partners said these summaries would help them decide whether to join research studies and feel more informed about how their contributions matter. Why It MattersThis tool could help patients and donors better understand research without needing a science degree. When people can see how studies work, they are more likely to participate in future research. While patient partners emphasized the need for summaries to be accurate and reliable, this approach shows promise as a unique strategy to better connect the public with research.

scientific communication and education↗

bioRxiv2025

Systematic and proactive evaluation of AIRE missense variant effects

Pathogenic variants in the Autoimmune Regulator (AIRE) gene cause Autoimmune Polyendocrine Syndrome Type 1 (APS-1), a rare primary immunodeficiency disease with symptoms including hypoparathyroidism, adrenal insufficiency, and chronic mucocutaneous candidiasis. AIRE increases the expression and presentation of tissue-specific genes expressing self antigens in the developing T cell niche, thus triggering the elimination of self-reactive T cells and preventing autoimmunity. Earlier diagnoses can benefit patients, and APS-1 diagnosis by AIRE sequencing is increasingly common. However, two thirds of reported clinical variants are missense, and more than half of these are "variants of uncertain significance" (VUS). Cell-based variant functional assays can provide strong evidence towards more informative variant classification, but these are carried out reactively, often years after clinical presentation. By contrast, proactively assessing all possible missense variants could provide immediate evidence to guide genetic diagnosis, even for never-before-seen variants. Here we used an insulin promoter-driven reporter to proactively assess the function of 9790 AIRE missense variants. The resulting AIRE variant effect map both validates and extends current biochemical knowledge, concords with pathogenicity annotations, and provides proactive evidence for 70% of previously-reported VUS. Placing our map in the context of both an international APS-1 cohort and the UK BioBank revealed quantitative genotype-phenotype correlations. Using current guidelines, we provide classifications for 32% of current VUS. Together, our proactive resource of AIRE variant impacts offers the potential to improve patient outcomes via more rapid and definitive APS-1 diagnosis.

genetics↗

bioRxiv2025

Comprehensively Testing the Function of Missense Variation in the STK11 Tumour Suppressor

The tumor suppressor gene STK11 encoding Serine/Threonine Kinase 11 (STK11) is associated with Peutz-Jeghers Syndrome (PJS), a heritable gastrointestinal disease that increases lifetime cancer risk, and with somatic variation that contributes to [~]30% of lung and 20% of cervical cancers. Although identifying pathogenic variants is clinically actionable, over 94% of STK11 missense variants that have been observed clinically lack a definitive classification. We therefore measured the impact of STK11 variants at scale in a mammalian cell-based assay, scoring 6,026 (73% of all possible) amino acid substitutions across the full-length gene. Functional scores--which were consistent with biochemical properties, smaller-scale assays, and pathogenicity annotations--identified a subset of PJS patients with germline STK11 variants diagnosed later in life, as well as somatic STK11 variants found in cancer patients that had comparable overall survival estimates to wild-type STK11. Our scores provided new evidence for 350 annotated VUS STK11 missense variants and [~]80% of missense variants that have not yet been reported clinically, but we might expect to observe in the future. Thus, our effect map provides a proactive resource for gaining sequence-structure-function insights and evidence for actionable interpretation of clinical missense variants.

cancer biology↗

bioRxiv2025

Landscapes of missense variant impact for human superoxide dismutase 1

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease for which important subtypes are caused by variation in the Superoxide Dismutase 1 gene SOD1. Diagnosis based on SOD1 sequencing can not only be definitive but also indicate specific therapies available for SOD1-associated ALS (SOD1-ALS). Unfortunately, SOD1-ALS diagnosis is limited by the fact that a substantial fraction (currently 26%) of ClinVar SOD1 missense variants are classified as "variants of uncertain significance" (VUS). Although functional assays can provide strong evidence for clinical variant interpretation, SOD1 assay validation is challenging, given the current incomplete and controversial understanding of SOD1-ALS disease mechanism. Using saturation mutagenesis and multiplexed cell-based assays, we measured the functional impact of over two thousand SOD1 amino acid substitutions on both enzymatic function and protein abundance. The resulting missense variant effect maps not only reflect prior biochemical knowledge of SOD1 but also provide sequence-structure-function insights. Importantly, our variant abundance assay can discriminate pathogenic missense variation and provides new evidence for 41% of missense variants that had been previously reported as VUS, offering the potential to identify additional patients who would benefit from therapy approved for SOD1-ALS.

genetics↗

bioRxiv2024

A missense variant effect map for the human tumour suppressor protein CHK2

The tumour suppressor CHEK2 encodes the serine/threonine protein kinase CHK2 which, upon DNA damage, is important for pausing the cell cycle, initiating DNA repair and inducing apoptosis. CHK2 phosphorylation of the tumour suppressor BRCA1 is also important for mitotic spindle assembly and chromosomal stability. Consistent with its cell cycle checkpoint role, both germline and somatic variants in CHEK2 have been linked to breast and multiple other cancer types. Over 90% of clinical germline CHEK2 missense variants are classified as variants of uncertain significance, complicating diagnosis of CHK2-dependent cancer. We therefore sought to test the functional impact of all possible missense variants in CHK2. Using a scalable multiplexed assay based on the ability of human CHK2 to complement DNA sensitivity of a S. cerevisiae lacking its ortholog RAD53, we generated a systematic missense variant effect map for CHEK2 missense variation. Map scores reflect known biochemical features of CHK2 and exhibit good performance in separating pathogenic from benign clinical missense variants. Thus, the missense variant effect map for CHK2 offers value in understanding both known and yet-to-be-observed CHK2 variants.

genetics↗

bioRxiv2023

Pacybara: Accurate long-read sequencing for barcoded mutagenized allelic libraries

SummaryLong read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library. Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or non-unique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues. Availability and ImplementationPacybara, freely available at https://github.com/rothlab/pacybara, is implemented using R, Python and bash for Linux. It has both a single-threaded implementation and, for GNU/Linux clusters that use Slurm, PBS, or GridEngine schedulers, a multi-node version. Supplementary MaterialSupplementary materials are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation

Defects in hydroxymethylbilane synthase (HMBS) can cause Acute Intermittent Porphyria (AIP), an acute neurological disease. Although sequencing-based diagnosis can be definitive, ~[1/3] of clinical HMBS variants are missense variants, and most clinically-reported HMBS missense variants are designated as "variants of uncertain significance" (VUS). Using saturation mutagenesis, en masse selection, and sequencing, we applied a multiplexed validated assay to both the erythroid-specific and ubiquitous isoforms of HMBS, obtaining confident functional impact scores for >84% of all possible amino-acid substitutions. The resulting variant effect maps generally agreed with biochemical expectation. However, the maps showed variants at the dimerization interface to be unexpectedly well tolerated, and suggested residue roles in active site dynamics that were supported by molecular dynamics simulations. Most importantly, these HMBS variant effect maps can help discriminate pathogenic from benign variants, proactively providing evidence even for yet-to-be-observed clinical missense variants.

molecular biology↗

bioRxiv2022

Genome-scale mapping of DNA damage suppressors identifies GNB1L as essential for ATM and ATR biogenesis

To maintain genome integrity, cells must avoid DNA damage by ensuring the accurate duplication of the genome and by having efficient repair and signaling systems that counteract the genome-destabilizing potential of DNA lesions. To uncover genes and pathways that suppress DNA damage in human cells, we undertook genome-scale CRISPR/Cas9 screens that monitored the levels of DNA damage in the absence or presence of DNA replication stress. We identified 160 genes in RKO cells whose mutation caused high levels of DNA damage in the absence of exogenous genotoxic treatment. This list was highly enriched in essential genes, highlighting the importance of genomic integrity for cellular fitness. Furthermore, the majority of these 160 genes are involved in a limited set of biological processes related to DNA replication and repair, nucleotide biosynthesis, RNA metabolism and iron sulfur cluster biogenesis, suggesting that genome integrity may be insulated from a wide range of cellular processes. Among the many genes identified and validated in this study, we discovered that GNB1L, a schizophrenia/autism-susceptibility gene implicated in 22q11.2 syndrome, protects cells from replication catastrophe promoted by mild DNA replication stress. We show that GNB1L is involved in the biogenesis of ATR and related phosphatidylinositol 3-kinase-related kinases (PIKKs) through its interaction with the TTT co-chaperone complex. These results implicate PIKK biogenesis as a potential root cause for the neuropsychiatric phenotypes associated with 22q11.2 syndrome. The phenotypic mapping of genes that suppress DNA damage in human cells therefore provides a powerful approach to probe genome maintenance mechanisms.

molecular biology↗

bioRxiv2021

A systematic genotype-phenotype map for missense variants in the human intellectual disability-associated gene GDI1

Next generation sequencing has become a common tool in the diagnosis of genetic diseases. However, for the vast majority of genetic variants that are discovered, a clinical interpretation is not available. Variant effect mapping allows the functional effects of many single amino acid variants to be characterized in parallel. Here, we combine multiplexed functional assays with machine learning to assess the effects of amino acid substitutions in the human intellectual disability-associated gene, GDI1. We show that the resulting variant effect map can be used to discriminate pathogenic from benign variants. Our variant effect map recovers known biochemical and structural features of GDI1 and reveals additional aspects of GDI1 function. We explore how our functional assays can aid in the interpretation of novel GDI1 variants as they are discovered, and to re-classify previously observed variants of unknown significance.

genetics↗

bioRxiv2021

Assessing computational variant effect predictors with a large prospective cohort

BackgroundCausal gene/trait relationships can be identified via observation of an excess (or reduced) burden of rare variation in a given gene within humans who have that trait. Although computational predictors can improve the power of such burden tests, it is unclear which are optimal for this task. MethodUsing 140 gene-trait combinations with a reported rare-variant burden association, we evaluated the ability of 20 computational predictors to predict human traits. We used the best-performing predictors to increase the power of genome-wide rare variant burden scans based on [~]450K UK Biobank participants. ResultsTwo predictors--VARITY and REVEL--outperformed all others in predicting human traits in the UK Biobank from missense variation. Genome-scale burden scans using the two best-performing predictors identified 1,038 gene-trait associations (FDR < 5%), including 567 (55%) that had not been previously reported. We explore 54 cardiovascular gene-trait associations (including 15 not reported in other burden scans) in greater depth. ConclusionsRigorous selection of computational missense variant effect predictors can improve the power of rare-variant burden scans for human gene-trait associations, yielding many new associations with potential value in informing mechanistic understanding and therapeutic development. The strategy we describe here is generalizable to future computational variant effect predictors, traits and organisms.

systems biology↗

bioRxiv2020

MaveRegistry: a collaboration platform for multiplexed assays of variant effect

SummaryMultiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating variant effect maps, which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets, and enable tracking and sharing of progress on ongoing MAVE projects. Availability and implementationhttps://registry.varianteffect.org Contactfritz.roth@utoronto.ca

bioinformatics↗

bioRxiv2019

An open-source platform to distribute and interpret data from multiplexed assays of variant effect

Multiplex Assays of Variant Effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here we present MaveDB, a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first of these applications, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

genomics↗

bioRxiv2018

A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase

Success in precision medicine depends on our ability to determine which rare human genetic variants have functional effects. Classical homocystinuria--characterized by elevated homocyst(e)ine in plasma and urine--is caused by primarily-rare variants in the cystathionine beta-synthase (CBS) gene. About half of patients respond to vitamin B6 therapy. With early detection in newborns, existing therapies are highly effective. Functional CBS variants, especially those that respond to vitamin B6, can be detected based on their ability to restore growth in yeast cells lacking CYS4 (the yeast ortholog of CBS). This assay has previously been carried out only reactively after first observation of a variant in patients. Here we describe a proactive comprehensive missense variant effect map for human CBS. Together, saturation codon-replacement mutagenesis, en masse growth selection at different vitamin B6 levels, and sequencing yielded a look-up table for CBS missense variant function and vitamin B6-remediability in yeast. The CBS variant effect map identified disease variants and predicted both disease severity (r = 0.82) and human clinical response to vitamin B6 (r = 0.89). Thus, highly-multiplexed cell-based assays can yield proactive maps of variant function and patient response to therapy, even for rare variants not previously seen in the clinic.

genetics↗

bioRxiv2017

Mapping DNA damage-dependent genetic interactions in yeast via orgy mating and barcode fusion genetics

Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double mutant strains, does not scale readily to multi-condition studies. Here we describe Barcode Fusion Genetics to map Genetic Interactions (BFG-GI), by which double mutant strains generated via en masse party mating can also be monitored en masse for growth and genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to a decrease in the activation or activity of the checkpoint protein kinase Rad53.

systems biology↗

bioRxiv2017

Expanding the Atlas of Functional Missense Variation for Human Genes

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon-mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features, and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.

molecular biology↗