Publications

@article{Liu2025,

title = {Profiling the epigenome using long-read sequencing},

author = {Tianyuan Liu and Ana Conesa},

doi = {10.1038/s41588-024-02038-5},

issn = {1546-1718},

year  = {2025},

date = {2025-01-08},

journal = {Nat Genet},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Paniagua2024,

title = {Evaluation of strategies for evidence-driven genome annotation using long-read RNA-seq},

author = {Alejandro Paniagua and Cristina Agustin-García and Francisco J Pardo-Palacios and Thomas Brown and Maite De Maria and Nancy D Denslow and Camila Mazzoni and Ana Conesa},

doi = {10.1101/gr.279864.124},

issn = {1088-9051},

year  = {2024},

date = {2024-12-23},

journal = {Genome Res.},

publisher = {Cold Spring Harbor Laboratory},

abstract = {While the production of a draft genome has become more accessible due to long-read sequencing, the annotation of these new genomes has not been developed at the same pace. Long-read RNA sequencing (lrRNA-seq) offers a promising solution for enhancing gene annotation. In this study, we explore how sequencing platforms, Oxford Nanopore R9.4.1 chemistry or PacBio Sequel II CCS, and data processing methods influence evidence-driven genome annotation using long reads. Incorporating PacBio transcripts into our annotation pipeline significantly outperformed traditional methods, such as ab initio predictions and short-read-based annotations. We applied this strategy to a nonmodel species, the Florida manatee, and compared our results to existing short-read-based annotation. At the loci level, both annotations were highly concordant, with 90% agreement. However, at the transcript level, the agreement was only 35%. We identified 4,906 novel loci, represented by 5,707 isoforms, with 64% of these isoforms matching known sequences in other mammalian species. Overall, our findings underscore the importance of using high-quality curated transcript models in combination with ab initio methods for effective genome annotation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Anczukow2024,

title = {Steering research on mRNA splicing in cancer towards clinical translation},

author = {Olga Anczukow and Frédéric H.-T. Allain and Brittany L. Angarola and Douglas L. Black and Angela N. Brooks and Chonghui Cheng and Ana Conesa and Edie I. Crosse and Eduardo Eyras and Ernesto Guccione and Sydney X. Lu and Karla M. Neugebauer and Priyanka Sehgal and Xiao Song and Zuzana Tothova and Juan Valcárcel and Kevin M. Weeks and Gene W. Yeo and Andrei Thomas-Tikhonenko},

doi = {10.1038/s41568-024-00750-2},

issn = {1474-1768},

year  = {2024},

date = {2024-12-00},

journal = {Nat Rev Cancer},

volume = {24},

number = {12},

pages = {887--905},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {scMaSigPro: differential expression analysis along single-cell trajectories },

author = {Priyansh Srivastava, Marta Benegas Coll, Stefan Götz, María José Nueda, Ana Conesa},

doi = {https://doi.org/10.1093/bioinformatics/btae443},

year  = {2024},

date = {2024-07-08},

journal = {Bioinformatics},

volume = {40},

issue = {7},

abstract = {Motivation

Understanding the dynamics of gene expression across different cellular states is crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit variation in mean expression as a function of Pseudotime and between branching trajectories are expected to govern cell fate decisions. We introduce scMaSigPro, a method for the identification of differential gene expression patterns along Pseudotime and branching paths simultaneously.



Results

We assessed the performance of scMaSigPro using synthetic and public datasets. Our evaluation shows that scMaSigPro outperforms existing methods in controlling the False Positive Rate and is computationally efficient.

Availability and implementation

scMaSigPro is available as a free R package (version 4.0 or higher) under the GPL(⁠>2⁠) license on GitHub at ‘github.com/BioBam/scMaSigPro’ and archived with version 0.03 on Zenodo at ‘zenodo.org/records/12568922’.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pardo-Palacios2024,

title = {Systematic assessment of long-read RNA-seq methods for transcript identification and quantification},

author = {Francisco J. Pardo-Palacios and Dingjie Wang and Fairlie Reese and Mark Diekhans and Sílvia Carbonell-Sala and Brian Williams and Jane E. Loveland and Maite De María and Matthew S. Adams and Gabriela Balderrama-Gutierrez and Amit K. Behera and Jose M. Gonzalez Martinez and Toby Hunt and Julien Lagarde and Cindy E. Liang and Haoran Li and Marcus Jerryd Meade and David A. Moraga Amador and Andrey D. Prjibelski and Inanc Birol and Hamed Bostan and Ashley M. Brooks and Muhammed Hasan Çelik and Ying Chen and Mei R. M. Du and Colette Felton and Jonathan Göke and Saber Hafezqorani and Ralf Herwig and Hideya Kawaji and Joseph Lee and Jian-Liang Li and Matthias Lienhard and Alla Mikheenko and Dennis Mulligan and Ka Ming Nip and Mihaela Pertea and Matthew E. Ritchie and Andre D. Sim and Alison D. Tang and Yuk Kei Wan and Changqing Wang and Brandon Y. Wong and Chen Yang and If Barnes and Andrew E. Berry and Salvador Capella-Gutierrez and Alyssa Cousineau and Namrita Dhillon and Jose M. Fernandez-Gonzalez and Luis Ferrández-Peral and Natàlia Garcia-Reyero and Stefan Götz and Carles Hernández-Ferrer and Liudmyla Kondratova and Tianyuan Liu and Alessandra Martinez-Martin and Carlos Menor and Jorge Mestre-Tomás and Jonathan M. Mudge and Nedka G. Panayotova and Alejandro Paniagua and Dmitry Repchevsky and Xingjie Ren and Eric Rouchka and Brandon Saint-John and Enrique Sapena and Leon Sheynkman and Melissa Laird Smith and Marie-Marthe Suner and Hazuki Takahashi and Ingrid A. Youngworth and Piero Carninci and Nancy D. Denslow and Roderic Guigó and Margaret E. Hunter and Rene Maehr and Yin Shen and Hagen U. Tilgner and Barbara J. Wold and Christopher Vollmers and Adam Frankish and Kin Fai Au and Gloria M. Sheynkman and Ali Mortazavi and Ana Conesa and Angela N. Brooks},

doi = {10.1038/s41592-024-02298-3},

issn = {1548-7105},

year  = {2024},

date = {2024-06-07},

urldate = {2024-06-07},

journal = {Nat Methods},

publisher = {Springer Science and Business Media LLC},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pardo-Palacios2024b,

title = {SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms},

author = {Francisco J. Pardo-Palacios and Angeles Arzalluz-Luque and Liudmyla Kondratova and Pedro Salguero and Jorge Mestre-Tomás and Rocío Amorín and Eva Estevan-Morió and Tianyuan Liu and Adalena Nanni and Lauren McIntyre and Elizabeth Tseng and Ana Conesa},

doi = {10.1038/s41592-024-02229-2},

issn = {1548-7105},

year  = {2024},

date = {2024-05-00},

urldate = {2024-05-00},

journal = {Nat Methods},

volume = {21},

number = {5},

pages = {793--797},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title><jats:p>SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Nanni2024,

title = {Nucleotide-level distance metrics to quantify alternative splicing implemented in \textit{TranD}},

author = {Adalena Nanni and James Titus-McQuillan and Kinfeosioluwa S Bankole and Francisco Pardo-Palacios and Sarah Signor and Srna Vlaho and Oleksandr Moskalenko and Alison M Morse and Rebekah L Rogers and Ana Conesa and Lauren M McIntyre},

doi = {10.1093/nar/gkae056},

issn = {1362-4962},

year  = {2024},

date = {2024-03-21},

volume = {52},

number = {5},

pages = {e28--e28},

publisher = {Oxford University Press (OUP)},

abstract = {Abstract

               Advances in affordable transcriptome sequencing combined with better exon and gene prediction has motivated many to compare transcription across the tree of life. We develop a mathematical framework to calculate complexity and compare transcript models. Structural features, i.e. intron retention (IR), donor/acceptor site variation, alternative exon cassettes, alternative 5′/3′ UTRs, are compared and the distance between transcript models is calculated with nucleotide level precision. All metrics are implemented in a PyPi package, TranD and output can be used to summarize splicing patterns for a transcriptome (1GTF) and between transcriptomes (2GTF). TranD output enables quantitative comparisons between: annotations augmented by empirical RNA-seq data and the original transcript models; transcript model prediction tools for longread RNA-seq (e.g. FLAIR versus Isoseq3); alternate annotations for a species (e.g. RefSeq vs Ensembl); and between closely related species. In C. elegans, Z. mays, D. melanogaster, D. simulans and H. sapiens, alternative exons were observed more frequently in combination with an alternative donor/acceptor than alone. Transcript models in RefSeq and Ensembl are linked and both have unique transcript models with empirical support. D. melanogaster and D. simulans, share many transcript models and long-read RNAseq data suggests that both species are under-annotated. We recommend combined references.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Baghdadi2024,

title = {Intermittent rapamycin feeding recapitulates some effects of continuous treatment while maintaining lifespan extension},

author = {Maarouf Baghdadi, Tobias Nespital, Carolina Monzó, Joris Deelen, Sebastian Grönke, Linda Partridge },

doi = {https://doi.org/10.1016/j.molmet.2024.101902},

year  = {2024},

date = {2024-03-01},

urldate = {2024-03-01},

journal = {Molecular Metabolism},

volume = {81},

number = {101902},

issue = {March 2024},

abstract = {Objective

Rapamycin, a powerful geroprotective drug, can have detrimental effects when administered chronically. We determined whether intermittent treatment of mice can reduce negative effects while maintaining benefits of chronic treatment.

Methods

From 6 months of age, male and female C3B6F1 hybrid mice were either continuously fed with 42 mg/kg rapamycin, or intermittently fed by alternating weekly feeding of 42 mg/kg rapamycin food with weekly control feeding. Survival of these mice compared to control animals was measured. Furthermore, longitudinal phenotyping including metabolic (body composition, GTT, ITT, indirect calorimetry) and fitness phenotypes (treadmil, rotarod, electrocardiography and open field) was performed. Organ specific pathology was assessed at 24 months of age.

Results

Chronic rapamycin treatment induced glucose intolerance, which was partially ameliorated by intermittent treatment. Chronic and intermittent rapamycin treatments increased lifespan equally in males, while in females chronic treatment resulted in slightly higher survival. The two treatments had equivalent effects on testicular degeneration, heart fibrosis and liver lipidosis. In males, the two treatment regimes led to a similar increase in motor coordination, heart rate and Q-T interval, and reduction in spleen weight, while in females, they equally reduced BAT inflammation and spleen weight and maintained heart rate and Q-T interval. However, other health parameters, including age related pathologies, were better prevented by continuous treatment.

Conclusions

Intermittent rapamycin treatment is effective in prolonging lifespan and reduces some side-effects of chronic treatment, but chronic treatment is more beneficial to healthspan.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Conesa2024RevolutionizingGA,

title = {Revolutionizing genomics and medicine—one long molecule at a time},

author = {Ana Conesa and Alexander Hoischen and Fritz J. Sedlazeck},

url = {https://api.semanticscholar.org/CorpusID:274261201},

year  = {2024},

date = {2024-01-01},

journal = {Genome Research},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mestre-Tomás2023,

title = {SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark},

author = {Jorge Mestre-Tomás and Tianyuan Liu and Francisco Pardo-Palacios and Ana Conesa},

doi = {10.1186/s13059-023-03127-0},

issn = {1474-760X},

year  = {2023},

date = {2023-12-00},

journal = {Genome Biol},

volume = {24},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractLong-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel transcripts remains a challenge. Here, we present SQANTI-SIM, a versatile tool that wraps around popular long-read simulators to allow precise management of transcript novelty based on the structural categories defined by SQANTI3. By selectively excluding specific transcripts from the reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, the tool provides customizable features and supports the simulation of additional types of data, representing the first multi-omics simulation tool for the lrRNA-seq field.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{AmoríndeHegedüs2023,

title = {Integration of multi-omics data to elucidate keystone unknown taxa within microbialite-forming ecosystems},

author = {Rocío Amorín de Hegedüs and Ana Conesa and Jamie S. Foster},

doi = {10.3389/fmicb.2023.1174685},

issn = {1664-302X},

year  = {2023},

date = {2023-07-28},

urldate = {2023-07-28},

journal = {Front. Microbiol.},

volume = {14},

publisher = {Frontiers Media SA},

abstract = {<jats:p>Microbes continually shape Earth’s biochemical and physical landscapes by inhabiting diverse metabolic niches. Despite the important role microbes play in ecosystem functioning, most microbial species remain unknown highlighting a gap in our understanding of structured complex ecosystems. To elucidate the relevance of these unknown taxa, often referred to as “microbial dark matter,” the integration of multiple high throughput sequencing technologies was used to evaluate the co-occurrence and connectivity of all microbes within the community. Since there are no standard methodologies for multi-omics integration of microbiome data, we evaluated the abundance of “microbial dark matter” in microbialite-forming communities using different types meta-omic datasets: amplicon, metagenomic, and metatranscriptomic sequencing previously generated for this ecosystem. Our goal was to compare the community structure and abundances of unknown taxa within the different data types rather than to perform a functional characterization of the data. Metagenomic and metatranscriptomic data were input into SortMeRNA to extract 16S rRNA gene reads. The output, as well as amplicon sequences, were processed through QIIME2 for taxonomy analysis. The R package mdmnets was utilized to build co-occurrence networks. Most hubs presented unknown classifications, even at the phyla level. Comparisons of the highest scoring hubs of each data type using sequence similarity networks allowed the identification of the most relevant hubs within the microbialite-forming communities. This work highlights the importance of unknown taxa in community structure and proposes that ecosystem network construction can be used on several types of data to identify keystone taxa and their potential function within microbial ecosystems.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36894419,

title = {Differences in uterine and serum metabolome associated with metritis in dairy cows},

author = {C C Figueiredo and L Balzano-Nogueira and D Z Bisinotto and A Revilla Ruiz and G A Duarte and A Conesa and K N Galvão and R S Bisinotto},

doi = {10.3168/jds.2022-22552},

issn = {1525-3198},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {J Dairy Sci},

volume = {106},

number = {5},

pages = {3525--3536},

abstract = {Objectives were to evaluate differences in the uterine and serum metabolomes associated with metritis in dairy cows. Vaginal discharge was evaluated using a Metricheck device (Simcro) at 5, 7, and 11 d in milk (DIM; herd 1) or 4, 6, 8, 10, and 12 DIM (herd 2). Cows with reddish or brownish, watery, and fetid discharge were diagnosed with metritis (n = 24). Cows with metritis were paired with herdmates without metritis (i.e., clear mucous vaginal discharge or clear lochia with ≤50% of pus) based on DIM and parity (n = 24). Day of metritis diagnosis was considered study d 0. All cows diagnosed with metritis received antimicrobial therapy. The metabolome of uterine lavage collected on d 0 and 5, and serum samples collected on d 0 were evaluated using untargeted gas chromatography time-of-flight mass spectrometry. Normalized data were subjected to multivariate canonical analysis of population using the MultBiplotR and MixOmics packages in R Studio. Univariate analyses including t-test, principal component analyses, partial least squares discriminant analyses, and pathway analyses were conducted using Metaboanalyst. The uterine metabolome differed between cows with and without metritis on d 0. Differences in the uterine metabolome associated with metritis on d 0 were related to the metabolism of butanoate, amino acids (i.e., glycine, serine, threonine, alanine, aspartate, and glutamate), glycolysis and gluconeogenesis, and the tricarboxylic acid cycle. No differences in the serum metabolome were observed between cows diagnosed with metritis and counterparts without metritis on d 0. Similarly, no differences in uterine metabolome were observed between cows with metritis and counterparts not diagnosed with metritis on d 5. These results indicate that the establishment of metritis in dairy cows is associated with local disturbances in amino acid, lipid, and carbohydrate metabolism in the uterus. The lack of differences in the uterine metabolome on d 5 indicates that processes implicated with the disease are reestablished by d 5 after diagnosis and treatment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Thompson2023,

title = {Identification of food and nutrient components as predictors of Lactobacillus colonization},

author = {Sharon C. Thompson and Amanda L. Ford and Elijah J. Moothedan and Lauren S. Stafford and Timothy J. Garrett and Wendy J. Dahl and Ana Conesa and Claudio F. Gonzalez and Graciela L. Lorca},

doi = {10.3389/fnut.2023.1118679},

issn = {2296-861X},

year  = {2023},

date = {2023-04-21},

journal = {Front. Nutr.},

volume = {10},

publisher = {Frontiers Media SA},

abstract = {A previous double-blind, randomized clinical trial of 42 healthy individuals conducted with Lactobacillus johnsonii N6.2 found that the probiotic’s mechanistic tryptophan pathway was significantly modified when the data was stratified based on the individuals’ lactic acid bacteria (LAB) stool content. These results suggest that confounding factors such as dietary intake which impact stool LAB content may affect the response to the probiotic treatment. Using dietary intake, serum metabolite, and stool LAB colony forming unit (CFU) data from a previous clinical trial, the relationships between diet, metabolic response, and fecal LAB were assessed. The diets of subject groups with high vs. low CFUs of LAB/g of wet stool differed in their intakes of monounsaturated fatty acids, vegetables, proteins, and dairy. Individuals with high LAB consumed greater amounts of cheese, fermented meats, soy, nuts and seeds, alcoholic beverages, and oils whereas individuals with low LAB consumed higher amounts of tomatoes, starchy vegetables, and poultry. Several dietary variables correlated with LAB counts; positive correlations were determined for nuts and seeds, fish high in N-3 fatty acids, soy, and processed meats, and negative correlations to consumption of vegetables including tomatoes. Using machine learning, predictors of LAB count included cheese, nuts and seeds, fish high in N-3 fatty acids, and erucic acid. Erucic acid alone accurately predicted LAB categorization, and was shown to be utilized as a sole fatty acid source by several Lactobacillus species regardless of their mode of fermentation. Several metabolites were significantly upregulated in each group based on LAB titers, notably polypropylene glycol, caproic acid, pyrazine, and chondroitin sulfate; however, none were correlated with the dietary intake variables. These findings suggest that dietary variables may drive the presence of LAB in the human gastrointestinal tract and potentially impact response to probiotic interventions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36302651,

title = {Palmitate impairs circadian transcriptomics in muscle cells through histone modification of enhancers},

author = {Nicolas J Pillon and Laura Sardón Puig and Ali Altıntaş and Prasad G Kamble and Salvador Casaní-Galdón and Brendan M Gabriel and Romain Barrès and Ana Conesa and Alexander V Chibalin and Erik Näslund and Anna Krook and Juleen R Zierath},

doi = {10.26508/lsa.202201598},

issn = {2575-1077},

year  = {2023},

date = {2023-01-01},

journal = {Life Sci Alliance},

volume = {6},

number = {1},

abstract = {Obesity and elevated circulating lipids may impair metabolism by disrupting the molecular circadian clock. We tested the hypothesis that lipid overload may interact with the circadian clock and alter the rhythmicity of gene expression through epigenomic mechanisms in skeletal muscle. Palmitate reprogrammed the circadian transcriptome in myotubes without altering the rhythmic mRNA expression of core clock genes. Genes with enhanced cycling in response to palmitate were associated with post-translational modification of histones. The cycling of histone 3 lysine 27 acetylation (H3K27ac), a marker of active gene enhancers, was modified by palmitate treatment. Chromatin immunoprecipitation and sequencing confirmed that palmitate exposure altered the cycling of DNA regions associated with H3K27ac. The overlap between mRNA and DNA regions associated with H3K27ac and the pharmacological inhibition of histone acetyltransferases revealed novel cycling genes associated with lipid exposure of primary human myotubes. Palmitate exposure disrupts transcriptomic rhythmicity and modifies enhancers through changes in histone H3K27 acetylation in a circadian manner. Thus, histone acetylation is responsive to lipid overload and may redirect the circadian chromatin landscape, leading to the reprogramming of circadian genes and pathways involved in lipid biosynthesis in skeletal muscle.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37577445,

title = {Integration of multi-omics data to elucidate keystone unknown taxa within microbialite-forming ecosystems},

author = {Rocío Amorín de Hegedüs and Ana Conesa and Jamie S Foster},

doi = {10.3389/fmicb.2023.1174685},

issn = {1664-302X},

year  = {2023},

date = {2023-01-01},

journal = {Front Microbiol},

volume = {14},

pages = {1174685},

abstract = {Microbes continually shape Earth's biochemical and physical landscapes by inhabiting diverse metabolic niches. Despite the important role microbes play in ecosystem functioning, most microbial species remain unknown highlighting a gap in our understanding of structured complex ecosystems. To elucidate the relevance of these unknown taxa, often referred to as "microbial dark matter," the integration of multiple high throughput sequencing technologies was used to evaluate the co-occurrence and connectivity of all microbes within the community. Since there are no standard methodologies for multi-omics integration of microbiome data, we evaluated the abundance of "microbial dark matter" in microbialite-forming communities using different types meta-omic datasets: amplicon, metagenomic, and metatranscriptomic sequencing previously generated for this ecosystem. Our goal was to compare the community structure and abundances of unknown taxa within the different data types rather than to perform a functional characterization of the data. Metagenomic and metatranscriptomic data were input into SortMeRNA to extract 16S rRNA gene reads. The output, as well as amplicon sequences, were processed through QIIME2 for taxonomy analysis. The R package mdmnets was utilized to build co-occurrence networks. Most hubs presented unknown classifications, even at the phyla level. Comparisons of the highest scoring hubs of each data type using sequence similarity networks allowed the identification of the most relevant hubs within the microbialite-forming communities. This work highlights the importance of unknown taxa in community structure and proposes that ecosystem network construction can be used on several types of data to identify keystone taxa and their potential function within microbial ecosystems.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36494864,

title = {New roles for AP-1/JUNB in cell cycle control and tumorigenic cell invasion via regulation of cyclin E1 and TGF-β2},

author = {Beatriz Pérez-Benavente and Alihamze Fathinajafabadi and Lorena de la Fuente and Carolina Gandía and Arantxa Martínez-Férriz and José Miguel Pardo-Sánchez and Lara Milián and Ana Conesa and Octavio A Romero and Julián Carretero and Rune Matthiesen and Isabelle Jariel-Encontre and Marc Piechaczyk and Rosa Farràs},

doi = {10.1186/s13059-022-02800-0},

issn = {1474-760X},

year  = {2022},

date = {2022-12-01},

journal = {Genome Biol},

volume = {23},

number = {1},

pages = {252},

abstract = {BACKGROUND: JUNB transcription factor contributes to the formation of the ubiquitous transcriptional complex AP-1 involved in the control of many physiological and disease-associated functions. The roles of JUNB in the control of cell division and tumorigenic processes are acknowledged but still unclear.



RESULTS: Here, we report the results of combined transcriptomic, genomic, and functional studies showing that JUNB promotes cell cycle progression via induction of cyclin E1 and repression of transforming growth factor (TGF)-β2 genes. We also show that high levels of JUNB switch the response of TGF-β2 stimulation from an antiproliferative to a pro-invasive one, induce endogenous TGF-β2 production by promoting TGF-β2 mRNA translation, and enhance tumor growth and metastasis in mice. Moreover, tumor genomic data indicate that JUNB amplification associates with poor prognosis in breast and ovarian cancer patients.



CONCLUSIONS: Our results reveal novel functions for JUNB in cell proliferation and tumor aggressiveness through regulation of cyclin E1 and TGF-β2 expression, which might be exploited for cancer prognosis and therapy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36097183,

title = {Independent phenotypic plasticity axes define distinct obesity sub-types},

author = {Chih-Hsiang Yang and Luca Fagnocchi and Stefanos Apostle and Vanessa Wegert and Salvador Casaní-Galdón and Kathrin Landgraf and Ilaria Panzeri and Erez Dror and Steffen Heyne and Till Wörpel and Darrell P Chandler and Di Lu and Tao Yang and Elizabeth Gibbons and Rita Guerreiro and Jose Bras and Martin Thomasen and Louise G Grunnet and Allan A Vaag and Linn Gillberg and Elin Grundberg and Ana Conesa and Antje Körner and  and J Andrew Pospisilik},

doi = {10.1038/s42255-022-00629-2},

issn = {2522-5812},

year  = {2022},

date = {2022-09-01},

journal = {Nat Metab},

volume = {4},

number = {9},

pages = {1150--1165},

abstract = {Studies in genetically 'identical' individuals indicate that as much as 50% of complex trait variation cannot be traced to genetics or to the environment. The mechanisms that generate this 'unexplained' phenotypic variation (UPV) remain largely unknown. Here, we identify neuronatin (NNAT) as a conserved factor that buffers against UPV. We find that Nnat deficiency in isogenic mice triggers the emergence of a bi-stable polyphenism, where littermates emerge into adulthood either 'normal' or 'overgrown'. Mechanistically, this is mediated by an insulin-dependent overgrowth that arises from histone deacetylase (HDAC)-dependent β-cell hyperproliferation. A multi-dimensional analysis of monozygotic twin discordance reveals the existence of two patterns of human UPV, one of which (Type B) phenocopies the NNAT-buffered polyphenism identified in mice. Specifically, Type-B monozygotic co-twins exhibit coordinated increases in fat and lean mass across the body; decreased NNAT expression; increased HDAC-responsive gene signatures; and clinical outcomes linked to insulinemia. Critically, the Type-B UPV signature stratifies both childhood and adult cohorts into four metabolic states, including two phenotypically and molecularly distinct types of obesity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36066904,

title = {The absence of the queuosine tRNA modification leads to pleiotropic phenotypes revealing perturbations of metal and oxidative stress homeostasis in Escherichia coli K12},

author = {Leticia Pollo-Oliveira and Nick K Davis and Intekhab Hossain and Peiying Ho and Yifeng Yuan and Pedro Salguero García and Cécile Pereira and Shane R Byrne and Jiapeng Leng and Melody Sze and Crysten E Blaby-Haas and Agnieszka Sekowska and Alvaro Montoya and Thomas Begley and Antoine Danchin and Daniel P Aalberts and Alexander Angerhofer and John Hunt and Ana Conesa and Peter C Dedon and Valérie de Crécy-Lagard},

doi = {10.1093/mtomcs/mfac065},

issn = {1756-591X},

year  = {2022},

date = {2022-09-01},

journal = {Metallomics},

volume = {14},

number = {9},

abstract = {Queuosine (Q) is a conserved hypermodification of the wobble base of tRNA containing GUN anticodons but the physiological consequences of Q deficiency are poorly understood in bacteria. This work combines transcriptomic, proteomic and physiological studies to characterize a Q-deficient Escherichia coli K12 MG1655 mutant. The absence of Q led to an increased resistance to nickel and cobalt, and to an increased sensitivity to cadmium, compared to the wild-type (WT) strain. Transcriptomic analysis of the WT and Q-deficient strains, grown in the presence and absence of nickel, revealed that the nickel transporter genes (nikABCDE) are downregulated in the Q- mutant, even when nickel is not added. This mutant is therefore primed to resist to high nickel levels. Downstream analysis of the transcriptomic data suggested that the absence of Q triggers an atypical oxidative stress response, confirmed by the detection of slightly elevated reactive oxygen species (ROS) levels in the mutant, increased sensitivity to hydrogen peroxide and paraquat, and a subtle growth phenotype in a strain prone to accumulation of ROS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36046619,

title = {Reference-based comparison of adaptive immune receptor repertoires},

author = {Cédric R Weber and Teresa Rubio and Longlong Wang and Wei Zhang and Philippe A Robert and Rahmad Akbar and Igor Snapkov and Jinghua Wu and Marieke L Kuijjer and Sonia Tarazona and Ana Conesa and Geir K Sandve and Xiao Liu and Sai T Reddy and Victor Greiff},

doi = {10.1016/j.crmeth.2022.100269},

issn = {2667-2375},

year  = {2022},

date = {2022-08-01},

journal = {Cell Rep Methods},

volume = {2},

number = {8},

pages = {100269},

abstract = {B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}