Base by Base

Lilljebjörn H et al., Nat Commun - Single-cell and bulk sequencing of 120 AML cases reveal two NPM1-mutated subtypes with distinct immune evasion mechanisms and divergent responses to hematopoietic stem cell transplantation. Key terms: acute myeloid leukemia, single-cell RNA-seq, NPM1, immune evasion, hematopoietic stem cell transplantation.

Study Highlights:
Bulk RNA-seq profiles are strongly confounded by variable mature cell-type signatures that can conceal subtype-specific blast programs. Single-cell multimodal sequencing of AML identified four main clusters of immature leukemic cells and separated NPM1-mutated cases into NPM1class I and NPM1class II. NPM1class I is marked by MHC class II downregulation and shows a significant survival benefit from HSCT, while NPM1class II resists allogeneic T cell killing ex vivo and does not benefit from HSCT. A 180-gene signature, and a shorter 30-gene panel, distinguished the classes across external bulk cohorts and associated each subtype with different co-mutation patterns.

Conclusion:
Single-cell transcriptional profiling defines two clinically relevant NPM1 subtypes with distinct immune evasion strategies that may inform HSCT decisions and immunotherapy approaches.

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Lilljebjörn H

Journal:
Nature Communications

DOI:
10.1038/s41467-025-66546-6

Reference:
Lilljebjörn H, Henningsson R, Rissler M, Landberg N, Puente-Moncada N, von Palffy S, Rissler V, Stanek P, Desponds J, Lazarevic V, Lehmann S, Fontes M, Ågerstam H, Sandén C, Orsmark-Pietras C, Zhong X, Juliusson G, Thorsson H, Fioretos T. The AML cellular state space unveils NPM1 immune evasion subtypes with distinct clinical outcomes. Nat Commun. 2025;16:10592. https://doi.org/10.1038/s41467-025-66546-6

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/npm1-immune-evasion-subtypes

️ Episode:
220: The AML cellular state space reveals NPM1 immune evasion subtypes

️ Season:
1

Article title:
The AML cellular state space unveils NPM1 immune evasion subtypes with distinct clinical outcomes

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-06.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript sections describing AML heterogeneity, single-cell sequencing approaches, isolation of AML immature cells, the NPM1 class I/II dichotomy, MHC-II downregulation and CIITA, intrinsic T cell resistance, ex vivo T cell assays, HSCT outcomes, and the minimal 30-gene panel for clinical implementation.
- transcript topics: AML heterogeneity and leukemia stem cells; Single-cell multimodal sequencing (scRNA-seq + scADT-seq); Isolation and characterization of AML immature cells; NPM1-mutated AML: NPM1 class I and NPM1 class II; MHC class II downregulation and CIITA regulation; Intrinsic T cell resistance and alternative checkpoint pathways

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- AML heterogeneity and leukemia stem cells drive relapse
- Single-cell multimodal sequencing identifies AML immature cells and two NPM1 subtypes
- NPM1 class I downregulates MHC II and HSCT improves survival
- NPM1 class II shows intrinsic resistance to donor T cells and lacks HSCT benefit
- Ex vivo T cell co-culture shows differential sensitivity between NPM1 classes I and II
- A minimal 30-gene expression panel can distinguish the two NPM1 subtypes for clinical use

QC result: Pass.

Hällqvist J et al., Nature Communications - Targeted multi-region lipidomics with proteomic and mitochondrial data reveals region- and stage-specific lipid alterations in Parkinson’s disease that converge on mitochondrial dysfunction. Key terms: lipids, parkinsons disease, putamen, ceramide, plasmalogens.

Study Highlights:
The study quantified 146 lipid species across eight anatomically distinct post-mortem brain regions in controls and mid- and late-stage Parkinson’s disease using targeted LC-MS/MS and integrated proteomics and mitochondrial assays. Control brains showed distinct regional lipid signatures and age-associated increases in hexosylceramides, while PD brains exhibited cortical elevations of gangliosides, HexCer and Hex2Cer and subcortical reductions of glycosphingolipids alongside increased sphingolipids and decreased phospholipids. The putamen displayed the most pronounced mid-stage changes with depletion of very long-chain ceramides and plasmalogen PE that normalized in late-stage disease, and lyso-phosphatidylcholine rose progressively with disease stage. Correlative multi-omic analysis linked sphingomyelin species to PD-related proteins and associated putaminal lipids including plasmalogens, long-chain ceramides, lyso-PC and HexCer with altered mitochondrial complex I activity.

Conclusion:
Region- and stage-specific lipid remodeling in Parkinson’s disease converges with mitochondrial dysfunction and identifies lipid pathways that may contribute to disease progression and therapeutic targeting

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Hällqvist J

Journal:
Nature Communications

DOI:
10.1038/s41467-025-65489-2

Reference:
Hällqvist J, Toomey CE, Pinto R, Baldwin T, Doykov I, Wernick A, Al Shahrani M, Evans JR, Lachica J, Pope S, Heales S, Eaton S, Mills K, Gandhi S & Heywood WE. Multi-omic analysis reveals lipid dysregulation associated with mitochondrial dysfunction in Parkinson’s disease brain. Nature Communications. 2025;16:10490. https://doi.org/10.1038/s41467-025-65489-2

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/lipid-dysregulation-parkinsons-brain

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-06.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantive auditing of the transcript's scientific claims about regional lipid remodeling in PD, ceramide chain-length shifts, putamen-specific changes, mitochondrial correlations, and multi-omic integration, with attention to disease progression and potential protective responses.
- transcript topics: Regional lipid remodeling across eight brain regions; Ceramide chain-length alterations (short vs very long); Putamen mid-stage changes and plasmalogen PE; Glycosphingolipid patterns cortical vs subcortical; Lyso-phospholipids and plasmalogens across PD stages; Lipid-proteomics and mitochondrial complex I correlations

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 8
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- 8 anatomically distinct brain regions analyzed
- 146 lipid species quantified
- Braak staging used: mid-stage Braak 3-4 and late-stage Braak 5-6
- Putamen mid-stage shows depletion of very long-chain ceramides and plasmalogen PE
- Short-chain ceramides (C16, C18) elevated broadly in PD
- Cortical regions show increased glycosphingolipids (GM1, GM2, GM3) while subcortical regions show decreases

QC result: Pass.

Bright U et al., Nat Commun - A large multi-ancestry GWAS meta-analysis identifies a dominant SIM1-linked locus and multiple genetic connections between electronic health record-defined erectile dysfunction and cardiometabolic, psychiatric, and substance-use traits. Key terms: erectile dysfunction, GWAS, SIM1, obesity, polygenic risk.

Study Highlights:
Meta-analysis of 913,194 European and 125,315 African ancestry individuals (136,867 and 51,599 cases respectively) identified 40 independent variants in Europeans, two in Africans, and 51 lead SNPs in cross-ancestry analyses. The strongest associations mapped to a non-coding region regulating SIM1, led by rs78677597 in Europeans and rs17185536 in Africans and in the cross-ancestry meta-analysis. Genetic correlations and local analyses linked EHR-defined ED with psychiatric disorders, cardiometabolic traits, and substance use traits, and Mendelian randomization inferred bidirectional and directional causal relationships involving obesity, type 2 diabetes, cannabis use disorder and opioid use disorder. Polygenic risk scores explained up to 9.2% of variance but showed limited predictive power (AUC = 0.52), while gene-based and TWAS analyses highlighted ESR1, CTNNB1 and SLC39A8 and drug-repurposing nominated ER-α antagonists and sulindac as candidates.

Conclusion:
The study confirms a dominant SIM1-associated genetic signal for erectile dysfunction and reveals a complex, multi-factorial genetic architecture linking ED to cardiometabolic, psychiatric, and substance-use biology

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Bright U

Journal:
Nat Commun

DOI:
10.1038/s41467-025-66723-7

Reference:
Bright U, Chen Y, Deak JD, Zhou H, Levey DF, Gelernter J. Multi-ancestry investigation of the genomics of erectile dysfunction. Nat Commun. 2025. https://doi.org/10.1038/s41467-025-66723-7

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/genomics-erectile-dysfunction

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-04.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantively audited the transcript's scientific claims describing the multi-ancestry ED GWAS, SIM1 locus, ancestry-specific signals, EHR-defined ED, MR, gSEM, correlations with psychiatric/metabolic traits, and drug repurposing implications.
- transcript topics: SIM1 regulatory locus as main ED signal; EUR/AFR/cross-ancestry GWAS results; EHR-defined erectile dysfunction phenotype; Mendelian randomization analyses linking ED to obesity and other traits; Genomic structural equation modeling: two major genetic factors; Gene-level signals (ESR1, CTNNB1, PHF21B, SLC39A8) and TWAS/MAGMA

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- strongest ED genetic signal maps to SIM1 regulatory region on chromosome 6; lead variants rs78677597 (EUR) and rs17185536 (AFR/cross-ancestry)
- 40 lead SNPs in European ancestry; 2 lead SNPs in African ancestry; 51 lead SNPs in cross-ancestry analyses
- EHR-defined ED (EHR-ED) phenotype defined by ICD-10 code N52 or ED drug prescriptions
- Mendelian randomization (MR) shows ED risk variants are a stronger causal factor for morbid obesity than obesity-related ED; bidirectional relations with some traits
- Genomic SEM identifies two major genetic factors: Factor 1 (behavioral/psychiatric) and Factor 3 (metabolic); ED loads on both via co-loading
- Drug repurposing highlights ESR1 antagonists and CTNNB1-related targets; sulindac discussed as PDE5 inhibitor and β-catenin modulator

QC result: Pass.

White MA et al., Nature Communications - FFT and inverse-FFT analysis of Zip3/Zip2, Hop1 and Zip1 on yeast pachytene chromosomes reveals two interdigitated tiers of evenly spaced protein triads that correspond to canonical and minority crossovers and are differentially regulated by Pch2/TRIP13. Key terms: crossover interference, meiotic chromosomes, Zip3/Zip2, Hop1, Pch2.

Study Highlights:
Quantitative fluorescence profiles and Fourier analysis identify two dominant spatial periodicities centered near 0.5 µm and 1.0 µm for Zip3/Zip2, Hop1 and Zip1 along pachytene chromosomes. Inverse FFT reconstructs narrow and broad peaks that colocalize into triads of the three proteins with intra-triad separations of ~70 nm. Shorter-periodicity triads map to canonical Zip3-defined crossovers and show classical interference, while longer-periodicity triads are interdigitated with shorter triads and also exhibit interference. The ratio, spacing relationships, and modulation by Pch2/TRIP13 support the interpretation that longer-periodicity triads correspond to minority crossovers and that Pch2 selectively alters abundance and relative loading in the longer-tier triads

Conclusion:
Crossover interference establishes two interdigitated, multiscale patterns of tightly clustered Zip2/Zip3–Hop1–Zip1 triads along meiotic chromosomes, linking canonical and minority crossovers into a single interference-governed process

Music:
Enjoy the music based on this article at the end of the episode.

First author:
White MA

Journal:
Nature Communications

DOI:
10.1038/s41467-025-65423-6

Reference:
White MA, Weiner B, Chu L, Lim G, Prentiss M & Kleckner N. Crossover interference mediates multiscale patterning along meiotic chromosomes. Nature Communications. 2025;16:10453. https://doi.org/10.1038/s41467-025-65423-6

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/multiscale-crossover-triad-patterning

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-03.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript's discussion of the paper's key scientific claims and methods: FFT/IFFT decomposition revealing two periodicities, triad clustering of Zip3-Hop1-Zip1, canonical vs minority crossovers, interdigitation and spacing, CoC/LCoC analyses, and the role of Pch2, including a two-tier sequential model and
- transcript topics: Crossover interference and canonical vs minority crossovers; FFT and inverse-FFT analysis revealing two periodicities; Triad structure of Zip3-Hop1-Zip1 along chromosomes; Interference metrics: CoC and LCoC; Interdigitation of two triad types and precursor spacing (~0.23 μm); Minority crossovers and their ratio to canonical crossovers (~0.46:1)

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 8
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- Two interdigitated patterns with shorter (~0.5 μm) and longer (~1 μm) periodicities for crossover-related components
- Triplet (triad) clustering of Zip3, Hop1, Zip1 at periodicities (≈0.5 μm and ≈1 μm)
- Shorter periodicity triads correspond to canonical crossovers with strong interference (CoC/LCoC values similar to canonical crossovers)
- Longer periodicity triads correspond to minority crossovers with strong interference and interdigitation with shorter triads
- Inter-triad distance between long and short triads ≈0.27 μm; nearest precursor site spacing ≈0.23 μm
- Ratio of longer to shorter periodicity triads and their relation to minority vs canonical crossovers ≈0.5:1; minority/canonical crossover ratio ≈0.46:1

QC result: Pass.

Makins K et al., Nature Communications - This episode reviews a study showing that 53BP1-RIF1 and DNA-PKcs have different genetic relationships across blunt end joining, deletion patterns, HDR, and radiosensitivity. Key terms: 53BP1, DNA-PKcs, RIF1, non-homologous end joining, microhomology.

Study Highlights:
Using EJ7-GFP and MA-del reporters in HEK293 cells, loss of 53BP1 alone did not reduce blunt No Indel EJ but amplified the decrease caused by DNA-PKcs kinase inhibition (M3814) or PRKDC knockout. Disruption of 53BP1 or RIF1, and DNA-PKcs inhibition or loss, each caused a similar shift toward deletions with increased microhomology and reduced non-microhomology deletions, with combined disruption not additive. 53BP1 loss reduced blunt EJ efficiency in XLF-deficient cells and the deletion pattern of the 53BP1/XLF double mutant resembled that of 53BP1 loss alone. DNA-PKcs kinase inhibition produced marked increases in HDR and radiosensitivity that differed from genetic DNA-PKcs loss and were not fully additive with 53BP1 or RIF1 loss.

Conclusion:
53BP1-RIF1 act as a backup to DNA-PKcs for blunt DSB end joining but function in the same pathway as DNA-PKcs to limit microhomology-mediated deletions, while DNA-PKcs kinase inhibition broadly perturbs repair outcomes and increases radiosensitivity

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Makins K

Journal:
Nature Communications

DOI:
10.1038/s41467-025-65329-3

Reference:
Makins K, Cisneros-Aguirre M, Lopezcolorado FW & Stark JM. 53BP1-RIF1 and DNA-PKcs show distinct genetic interactions with diverse chromosomal break repair outcomes. Nature Communications. 2025;16:10361. https://doi.org/10.1038/s41467-025-65329-3

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/53bp1-rif1-dna-pkcs

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-02.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript sections describing (a) the interplay between 53BP1-RIF1 and DNA-PKcs in blunt end joining, (b) deletion/microhomology patterns (MA-del and related assays), (c) HDR and radiosensitivity outcomes (LMNA-HDR and clonogenic assays), (d) role of XLF and RIF1 as context modifiers, and (e) comparisons b
- transcript topics: EJ7-GFP No Indel EJ assay and 53BP1/DNA-PKcs interaction; MA-del assay: deletion patterns and microhomology usage; HDR frequency via LMNA-HDR assay; Radiosensitivity and clonogenic survival after IR; Roles of 53BP1, RIF1, XLF in end-joining and synapsis; DNA-PKcs kinase inhibition vs genetic loss

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 7
- claims flagged for review: 0
- metadata checks passed: 3
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- 53BP1-RIF1 acts as a backup to DNA-PKcs for blunt DSB end joining (NHEJ).
- Disruption of 53BP1 or RIF1 increases microhomology-mediated deletions; combined disruption with DNA-PKcs disruption is not additive for this outcome.
- DNA-PKcs kinase inhibition (M3814) produces larger shifts in repair outcomes (HDR increases and radiosensitivity) than genetic loss of DNA-PKcs.
- HDR frequency increases with 53BP1 loss in DNA-PKcs-proficient cells; M3814 treatment also increases HDR; combined perturbations show context-dependent effects.
- XLF interacts with 53BP1 in promoting end-joining; 53BP1 loss can reduce blunt EJ in XLF-deficient cells.
- RIF1 loss mirrors 53BP1 loss in several microhomology deletion patterns and its effects become pronounced under DNA-PKcs inhibition.

QC result: Pass.

Martin et al., Nat Commun (2025) - Protein Set Transformer (PST) is a protein-based genome language model that represents genomes as sets of proteins to improve genome and protein representations across diverse viral datasets. Key terms: viromics, protein-language-model, genome-embeddings, triplet-loss, host-prediction.

Study Highlights:
PST embeds proteins with ESM2, concatenates positional and strand vectors, contextualizes proteins with a multi-head attention encoder, and produces genome embeddings via a learnable weighted decoder pooling. The foundation PST-TL models were pretrained on >100k dereplicated viral genomes encoding >6M proteins using a triplet-loss objective with PointSwap augmentation and evaluated on IMG/VR v4 and MGnify soil virus test sets. PST-TL outperformed other protein- and nucleotide-based methods at recovering genome–genome relationships, including remote relationships, and its protein embeddings clustered structural capsid folds and late-gene functional modules. PST improved annotation transfer for hypothetical proteins via embedding and structure-aware clustering and boosted viral host-species prediction when used in a graph link-prediction framework.

Conclusion:
PST provides transferable genome- and protein-level embeddings that strengthen representation, annotation, and host-prediction tasks for diverse viral and microbial genomics applications

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Martin

Journal:
Nat Commun (2025)

DOI:
10.1038/s41467-025-66049-4

Reference:
Martin, C., Gitter, A., Anantharaman, K. Protein Set Transformer: a protein-based genome language model to power high-diversity viromics. Nat Commun (2025). https://doi.org/10.1038/s41467-025-66049-4

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/protein-set-transformer

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-12-01.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantive audit of the core scientific claims and results described in PST工作 (architecture, training, data, evaluation, functional insights, host prediction, generalizability, and biosafety/licensing) as presented in the transcript.
- transcript topics: PST architecture: genome modeled as set of proteins with context; Protein embeddings and genome-position/strand augmentation; Triplet loss training: Chamfer distance and PointSwap; Pretraining data scale: >100k viral genomes, >6M proteins; Performance: PST-TL outperforms PST-CTX and PST-MLM; Remote relation detection: ASI correlations with PST embeddings

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 8
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- Genomes are modeled as sets of proteins with context (not as linear sequences)
- ESM2 protein embeddings are augmented with two learnable vectors representing protein position and coding strand
- Training uses triplet loss with Chamfer distance and PointSwap augmentation
- Pretraining dataset scales: >100k viral genomes encoding >6M proteins
- PST-TL outperforms alternative methods (PST-CTX, PST-MLM, etc.)
- PST embeddings correlate with ASI for remote relationships (positive ASI correlation when AI is near zero)

QC result: Pass.

Kaur M et al., Nature Communications - Reconstitution of asymmetric membranes and matched cell experiments show that transbilayer asymmetry of PI(4,5)P2 lowers the energetic barrier for FGF2-driven lipidic pore formation and enables rapid unconventional secretion. Disrupting PI(4,5)P2 asymmetry in cells blocks FGF2 export. Key terms: FGF2, PI(4,5)P2, membrane asymmetry, unconventional secretion, lipidic pore.

Study Highlights:
The authors created asymmetric LUVs and GUVs by enzymatic conversion of outer-leaflet PI(4)P to PI(4,5)P2 using PIP5K1C. Time-lapse GUV assays showed that PI(4,5)P2 asymmetry accelerated FGF2-dependent lipidic pore formation (mean ≈45 min asymmetric vs ≈95 min symmetric). In CHO-K1 cells, delivering PI(4,5)P2 to the outer leaflet to disturb asymmetry prevented reappearance of surface FGF2-GFP after heparin wash. Addition of other FGF2-binding phosphoinositides (PI(3,4)P2, PI(3,4,5)P3) similarly inhibited secretion, while PI(4)P and PS did not.

Conclusion:
Transbilayer asymmetry of PI(4,5)P2 is a key biophysical determinant that facilitates FGF2 oligomer–dependent lipidic pore formation and efficient unconventional secretion.

Music:
Enjoy the music based on this article at the end of the episode.

Article title:
Plasma membrane transbilayer asymmetry of PI(4,5)P2 drives unconventional secretion of Fibroblast Growth Factor 2

First author:
Kaur M

Journal:
Nature Communications

DOI:
10.1038/s41467-025-66860-z

Reference:
Kaur M, Lolicato F, Nickel W. Plasma membrane transbilayer asymmetry of PI(4,5)P2 drives unconventional secretion of Fibroblast Growth Factor 2. Nat Commun (2025). https://doi.org/10.1038/s41467-025-66860-z

License:
Creative Commons Attribution 4.0 International (CC BY 4.0)

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/pi45p2-asymmetry-drives-fgf2-secretion

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-11-30.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript's coverage of PI(4,5)P2 transbilayer asymmetry driving FGF2 secretion, including in vitro asymmetric membranes (LUVs/GUVs), kinase-driven outer-leaflet PI(4,5)P2 generation, cell-based disruption of asymmetry and secretion, lipid controls, kinetics, and recovery dynamics.
- transcript topics: FGF2 unconventional secretion overview; PI(4,5)P2 transbilayer asymmetry concept; In vitro reconstitution with asymmetric LUVs/GUVs; PIP5K1C-mediated outer-leaflet PI(4,5)P2 generation and asymmetry verification; Kinetics of FGF2 pore formation in asymmetric vs symmetric membranes; Cell-based disruption of PI(4,5)P2 asymmetry and impact on FGF2 secretion

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- Core mechanism: PI(4,5)P2 transbilayer asymmetry lowers energy barrier for FGF2 membrane pore formation.
- In vitro, asymmetric PI(4,5)P2 on outer leaflet accelerates pore formation (GUVs) compared with symmetric membranes.
- Cell-based disruption of PI(4,5)P2 asymmetry inhibits FGF2 secretion.
- Controls show PS and PI(4)P do not inhibit secretion; PI(3,4)P2 and PI(3,4,5)P3 do inhibit secretion.
- GPC1 captures FGF2 after pore formation, enabling extracellular release.
- Kinetics: asymmetric GUVs show ~45 min pore-formation time vs ~95 min for symmetric; cells show ~30 min acute secretion window after heparin wash; recovery occurs as outer-leaflet

QC result: Pass.

Deng R et al. - BRAIN-MAGNET couples a ChIP-STARR-seq atlas of 148,198 neural regulatory elements with a validated convolutional neural network to predict enhancer activity and prioritize disease-relevant non-coding variants. Key terms: enhancers, neural stem cells, convolutional neural network, non-coding variants, functional genomics.

Study Highlights:
The authors generated an activity-ranked functional genomics atlas of 148,198 non-coding regulatory elements in human neural stem cells. Comparative ChIP-STARR-seq revealed many elements are epigenetically primed in embryonic stem cells for later neural activity. BRAIN-MAGNET, a convolutional neural network trained on the atlas, predicts enhancer activity from DNA sequence and computes nucleotide-level contribution scores to identify functional motifs. The model outperformed other prioritization scores at tested loci and enabled prioritization and functional validation of both common GWAS SNPs and rare variants, including a putative RAB7A enhanceropathy.

Conclusion:
The NCRE atlas and BRAIN-MAGNET provide a functionally validated resource to interpret non-coding genetic variation relevant to neurodevelopment and neurological disease

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Deng R

DOI:
10.1016/j.cell.2025.10.029

Reference:
Deng R, Perenthaler E, Nikoncuk A, Yousefi S, Lanko K, Schot R, Maresca M, Medico-Salsench E, Sanderson LE, Parker MJ, van Ijcken WFJ, Park J, Sturm M, Haack TB, Roshchupkin GV, Mulugeta E, Barakat TS. BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants. Cell. 2026 Jan 22;189:1–20. https://doi.org/10.1016/j.cell.2025.10.029

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/brain-magnet-ncre-atlas

️ Episode:
213: Episode 213: BRAIN-MAGNET: a functional atlas for non-coding variants

️ Season:
1

Article title:
BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants

Journal:
Cell

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-11-29.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited core scientific content: NSC-ChIP-STARR-seq atlas, Brain-Magnet model with nucleotide-level contribution scores, ESC–NSC enhancer priming, motif and TE enrichments, motif deletions/validation, RAB7A enhanceropathy, GWAS/rare-disease variant prioritization, and limitations of episomal MPRA.
- transcript topics: NSC-ChIP-STARR-seq atlas of non-coding regulatory elements; Brain-Magnet CNN and nucleotide-level contribution scores; Primed enhancers and ESC-to-NSC differentiation; Motif and transposable element enrichment (YY1, TP53/p53, MER61, LTR10); Functional validation of high cb-score motifs (30 bp deletions, point mutations); RAB7A enhanceropathy and in vivo validation

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 8
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- ChIP-STARR-seq NSCs produced an atlas of ~148,000 NCREs with top-10% activity category.
- BRAIN-MAGNET predicts NCRE activity from DNA sequence and outputs per-nucleotide cb scores.
- Highly active NCREs link to higher target gene expression and LoF-intolerant (pLI) genes.
- NCREs show ESCs-primed enhancer status, with priming markers (H3K4me2/3) preceding NSC activation.
- High cb-score motifs (e.g., TP53/TP73/YY1) and TE enrichments (MER61, LTR10) observed in NSCs.
- Functional validation: deleting high-cb motifs in 16/17 NCREs reduces activity; low-cb regions show little/no effect.

QC result: Pass.

Raven A et al. - This study shows that hepatic zonation determines whether mutant β-catenin drives proliferation and liver cancer by forcing differentiation to a non-permissive zone 3 fate or, when reversed, enabling MAPK- and mTOR-dependent growth. Key terms: hepatic zonation, beta-catenin, MYC, mTOR, IGFBP2.

Study Highlights:
β-catenin exon 3 mutations cooperate with exogenous MYC to produce a proliferative translatome that supports tumour outgrowth. Differentiation to an extreme zone 3 GLUL+Lgr5+ hepatocyte fate suppresses the pro-growth translatome and is refractory to WNT/MYC-driven tumorigenesis. Early proliferative lesions that progress show reduced WNT activation, elevated MAPK signalling and engagement of an IGFBP2–mTOR–cyclin D1 axis, and inhibition of IGFBP2, mTOR or Yap/Taz impairs lesion formation and tumorigenesis. High-level WNT activation from Apc loss is less compatible with tumour formation, whereas MAPK activation (BrafV600E) antagonizes zone 3 differentiation to permit Lgr5+ hepatocyte transformation that can be suppressed by PORCN or BRAF inhibitors

Conclusion:
Hepatocyte zonal identity dictates susceptibility to WNT-driven HCC, and escape from WNT-induced zone 3 differentiation plus activation of MAPK/mTOR pro-growth pathways is required for tumour initiation

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Raven A

DOI:
10.1038/s41586-025-09733-1

Reference:
Raven A. et al. Hepatic zonation determines tumorigenic potential of mutant β-catenin. Nature. 2025. https://doi.org/10.1038/s41586-025-09733-1

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/hepatic-zonation-wnt-tumorigenesis

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-11-28.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the main scientific narrative in the transcript: hepatic zonation, CTNNB1 mutations and MYC cooperation, zone 3 differentiation as tumor suppressor, the IGFBP2–mTOR–CCND1 axis, MAPK signaling and BRAF involvement, and pharmacological proof-of-concept (rapamycin, dabrafenib, LGK974).
- transcript topics: Hepatic zonation and WNT signaling; CTNNB1 exon 3 mutations and MYC cooperation; Zone 3 differentiation as tumor suppressor and zone 2 growth axis; IGFBP2–mTOR–CCND1 pro-growth axis; MAPK signaling and BRAF involvement in tumorigenesis; Ribosome profiling and translational control

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 5
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- CTNNB1 exon 3 mutations cooperate with MYC to drive a proliferative translatome
- 81% of CTNNB1-mutated tumors exhibit MYC copy-number gain
- Zone 3 GLUL+ Lgr5+ hepatocytes are refractory to WNT- and MYC-driven tumorigenesis
- Early proliferative lesions show reduced WNT activation and elevated MAPK signaling
- IGFBP2–mTOR–CCND1 axis supports lesion growth; IGFBP2/mTOR inhibition reduces tumorigenesis
- Rapamycin reduces lesion number and extends survival in mouse models; dabrafenib inhibits BRafV600E-driven tumor growth

QC result: Pass.

Sankar et al. - This episode explores the discovery of genetic elements that promote the retention of extrachromosomal DNA (ecDNA) in cancer cells, enhancing their survival and evolution. Key terms: ecDNA, retention elements, cancer cells, genomic elements, oncogenes.

Study Highlights:
Researchers identified a family of genomic elements known as retention elements that tether ecDNA to mitotic chromosomes, facilitating its transmission to daughter cells during division. The study utilized a novel genome-scale assay called Retain-seq, revealing thousands of retention elements that enhance the persistence of ecDNA. These elements are primarily located at gene promoters and are characterized by high CpG density, which is crucial for their function. The findings suggest that retention elements play a significant role in the maintenance of oncogenic ecDNA across generations of cancer cells.

Conclusion:
Understanding the mechanisms of ecDNA retention may provide insights into cancer evolution and potential therapeutic targets.

Music:
Enjoy the music based on this article at the end of the episode.

First author:
Sankar

DOI:
10.1038/s41586-025-09764-8

Reference:
Sankar, V., Hung, K. L., Gnanasekar, A., Wong, I. T.-L., Shi, Q., Kraft, K., Jones, M. G., He, B. J., Yan, X., Belk, J. A., Liu, K. J., Agarwal, S., Wang, S. K., Henssen, A. G., Mischel, P. S., & Chang, H. Y. (2025). Genetic elements promote retention of extrachromosomal DNA in cancer cells. Nature. https://doi.org/10.1038/s41586-025-09764-8

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/retention-elements-cancer

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-11-27.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript sections describing Retain-seq, identification and features of retention elements, tethering mechanism to mitotic chromosomes via bookmarking, promoter/enhancer-like interactions, epigenetic regulation (CpG methylation and CRISPRoff), and tumor-data implications; cross-checked these against the a
- transcript topics: ecDNA and mitotic inheritance; Retain-seq methodology and discovery of retention elements; Sequence features of retention elements (CpG-rich promoters, active chromatin); Retention element tethering to mitotic chromosomes via mitotic bookmarking; Promoter–enhancer-like interactions recapitulated in trans; Additive effect of multiple retention elements on retention

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 7
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- Retention elements are a family of human genomic elements that tether episomes to mitotic chromosomes to promote ecDNA transmission
- Retain-seq identifies thousands of retention elements across the genome
- Retention elements are CpG-rich promoters and active regulatory regions associated with active chromatin
- Retention elements tether to chromosomes at mitotically bookmarked regions, recapitulating promoter–enhancer interactions across ecDNA and chromosomes
- Retention elements show additive effects: more elements increase episomal retention
- Retention elements are hypomethylated; targeted methylation abrogates retention and reduces ecDNA maintenance

QC result: Pass.