Publications by authors named "Alessandra Breschi"

14 Publications

  • Page 1 of 1

Response to Hulman and colleagues regarding "Glucotypes reveal new patterns of glucose dysregulation".

PLoS Biol 2021 Mar 11;19(3):e3001092. Epub 2021 Mar 11.

Stanford University, Department of Genetics, Stanford, California, United States of America.

In a response to a Formal Comment critiquing their model for classifying individualized glucose patterns into glucotypes, these authors stand by their results and conclusions, which can be reproduced using their publicly available data, and maintain that improved algorithms for analyzing CGM data will continue to emerge and enrich the field.
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http://dx.doi.org/10.1371/journal.pbio.3001092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7951842PMC
March 2021

bsAS, an antisense long non-coding RNA, essential for correct wing development through regulation of blistered/DSRF isoform usage.

PLoS Genet 2020 12 28;16(12):e1009245. Epub 2020 Dec 28.

Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona (BIST), Catalonia, Spain.

Natural Antisense Transcripts (NATs) are long non-coding RNAs (lncRNAs) that overlap coding genes in the opposite strand. NATs roles have been related to gene regulation through different mechanisms, including post-transcriptional RNA processing. With the aim to identify NATs with potential regulatory function during fly development, we generated RNA-Seq data in Drosophila developing tissues and found bsAS, one of the most highly expressed lncRNAs in the fly wing. bsAS is antisense to bs/DSRF, a gene involved in wing development and neural processes. bsAS plays a crucial role in the tissue specific regulation of the expression of the bs/DSRF isoforms. This regulation is essential for the correct determination of cell fate during Drosophila development, as bsAS knockouts show highly aberrant phenotypes. Regulation of bs isoform usage by bsAS is mediated by specific physical interactions between the promoters of these two genes, which suggests a regulatory mechanism involving the collision of RNA polymerases transcribing in opposite directions. Evolutionary analysis suggests that bsAS NAT emerged simultaneously to the long-short isoform structure of bs, preceding the emergence of wings in insects.
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http://dx.doi.org/10.1371/journal.pgen.1009245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793246PMC
December 2020

A limited set of transcriptional programs define major cell types.

Genome Res 2020 07 29;30(7):1047-1059. Epub 2020 Jul 29.

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, E-08003 Barcelona, Catalonia, Spain.

We have produced RNA sequencing data for 53 primary cells from different locations in the human body. The clustering of these primary cells reveals that most cells in the human body share a few broad transcriptional programs, which define five major cell types: epithelial, endothelial, mesenchymal, neural, and blood cells. These act as basic components of many tissues and organs. Based on gene expression, these cell types redefine the basic histological types by which tissues have been traditionally classified. We identified genes whose expression is specific to these cell types, and from these genes, we estimated the contribution of the major cell types to the composition of human tissues. We found this cellular composition to be a characteristic signature of tissues and to reflect tissue morphological heterogeneity and histology. We identified changes in cellular composition in different tissues associated with age and sex, and found that departures from the normal cellular composition correlate with histological phenotypes associated with disease.
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http://dx.doi.org/10.1101/gr.263186.120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397875PMC
July 2020

Dynamics of microRNA expression during mouse prenatal development.

Genome Res 2019 11 23;29(11):1900-1909. Epub 2019 Oct 23.

Department of Developmental and Cell Biology, University of California Irvine, Irvine, California 92697, USA.

MicroRNAs (miRNAs) play a critical role as posttranscriptional regulators of gene expression. The ENCODE Project profiled the expression of miRNAs in an extensive set of organs during a time-course of mouse embryonic development and captured the expression dynamics of 785 miRNAs. We found distinct organ-specific and developmental stage-specific miRNA expression clusters, with an overall pattern of increasing organ-specific expression as embryonic development proceeds. Comparative analysis of conserved miRNAs in mouse and human revealed stronger clustering of expression patterns by organ type rather than by species. An analysis of messenger RNA expression clusters compared with miRNA expression clusters identifies the potential role of specific miRNA expression clusters in suppressing the expression of mRNAs specific to other developmental programs in the organ in which these miRNAs are expressed during embryonic development. Our results provide the most comprehensive time-course of miRNA expression as part of an integrated ENCODE reference data set for mouse embryonic development.
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http://dx.doi.org/10.1101/gr.248997.119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6836743PMC
November 2019

The histone code reader PHD finger protein 7 controls sex-linked disparities in gene expression and malignancy in .

Sci Adv 2019 08 14;5(8):eaaw7965. Epub 2019 Aug 14.

IRB Barcelona, BIST, Carrer de Baldiri Reixac, 10, 08028 Barcelona, Spain.

The notable male predominance across many human cancer types remains unexplained. Here, we show that l(3)mbt brain tumors are more invasive and develop as malignant neoplasms more often in males than in females. By quantitative proteomics, we have identified a signature of proteins that are differentially expressed between male and female tumor samples. Prominent among them is the conserved chromatin reader PHD finger protein 7 (Phf7). We show that depletion reduces sex-dependent differences in gene expression and suppresses the enhanced malignant traits of male tumors. Our results identify potential regulators of sex-linked tumor dimorphism and show that these genes may serve as targets to suppress sex-linked malignant traits.
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http://dx.doi.org/10.1126/sciadv.aaw7965DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693905PMC
August 2019

ggsashimi: Sashimi plot revised for browser- and annotation-independent splicing visualization.

PLoS Comput Biol 2018 08 17;14(8):e1006360. Epub 2018 Aug 17.

Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.

We present ggsashimi, a command-line tool for the visualization of splicing events across multiple samples. Given a specified genomic region, ggsashimi creates sashimi plots for individual RNA-seq experiments as well as aggregated plots for groups of experiments, a feature unique to this software. Compared to the existing versions of programs generating sashimi plots, it uses popular bioinformatics file formats, it is annotation-independent, and allows the visualization of splicing events even for large genomic regions by scaling down the genomic segments between splice sites. ggsashimi is freely available at https://github.com/guigolab/ggsashimi. It is implemented in python, and internally generates R code for plotting.
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http://dx.doi.org/10.1371/journal.pcbi.1006360DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114895PMC
August 2018

Glucotypes reveal new patterns of glucose dysregulation.

PLoS Biol 2018 07 24;16(7):e2005143. Epub 2018 Jul 24.

Stanford University, Department of Genetics, Stanford, California, United States of America.

Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10% of the population, in the United States are diagnosed with diabetes. Another 84 million are prediabetic, and without intervention, up to 70% of these individuals may progress to type 2 diabetes. Current methods for quantifying blood glucose dysregulation in diabetes and prediabetes are limited by reliance on single-time-point measurements or on average measures of overall glycemia and neglect glucose dynamics. We have used continuous glucose monitoring (CGM) to evaluate the frequency with which individuals demonstrate elevations in postprandial glucose, the types of patterns, and how patterns vary between individuals given an identical nutrient challenge. Measurement of insulin resistance and secretion highlights the fact that the physiology underlying dysglycemia is highly variable between individuals. We developed an analytical framework that can group individuals according to specific patterns of glycemic responses called "glucotypes" that reveal heterogeneity, or subphenotypes, within traditional diagnostic categories of glucose regulation. Importantly, we found that even individuals considered normoglycemic by standard measures exhibit high glucose variability using CGM, with glucose levels reaching prediabetic and diabetic ranges 15% and 2% of the time, respectively. We thus show that glucose dysregulation, as characterized by CGM, is more prevalent and heterogeneous than previously thought and can affect individuals considered normoglycemic by standard measures, and specific patterns of glycemic responses reflect variable underlying physiology. The interindividual variability in glycemic responses to standardized meals also highlights the personal nature of glucose regulation. Through extensive phenotyping, we developed a model for identifying potential mechanisms of personal glucose dysregulation and built a webtool for visualizing a user-uploaded CGM profile and classifying individualized glucose patterns into glucotypes.
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http://dx.doi.org/10.1371/journal.pbio.2005143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057684PMC
July 2018

The effects of death and post-mortem cold ischemia on human tissue transcriptomes.

Nat Commun 2018 02 13;9(1):490. Epub 2018 Feb 13.

Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, E-08003, Catalonia, Spain.

Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.
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http://dx.doi.org/10.1038/s41467-017-02772-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811508PMC
February 2018

Comparative transcriptomics in human and mouse.

Nat Rev Genet 2017 07 8;18(7):425-440. Epub 2017 May 8.

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.

Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level. Insights have been gained into the degree of conservation between human and mouse at the level of not only gene expression but also epigenetics and inter-individual variation. However, a number of limitations exist, including incomplete transcriptome characterization and difficulties in identifying orthologous phenotypes and cell types, which are beginning to be addressed by emerging technologies. Ultimately, these comparisons will help to identify the conditions under which the mouse is a suitable model of human physiology and disease, and optimize the use of animal models.
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http://dx.doi.org/10.1038/nrg.2017.19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413734PMC
July 2017

Gene-specific patterns of expression variation across organs and species.

Genome Biol 2016 07 8;17(1):151. Epub 2016 Jul 8.

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.

Background: A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species.

Results: We use linear models to quantify this pattern. We find a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species.

Conclusions: Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans.
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http://dx.doi.org/10.1186/s13059-016-1008-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937605PMC
July 2016

Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression.

Nat Commun 2015 Jan 13;6:5903. Epub 2015 Jan 13.

Functional Genomics Group, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, USA.

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles.
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http://dx.doi.org/10.1038/ncomms6903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308717PMC
January 2015

Comparison of the transcriptional landscapes between human and mouse tissues.

Proc Natl Acad Sci U S A 2014 Dec 20;111(48):17224-9. Epub 2014 Nov 20.

Department of Genetics, Stanford University, Stanford, CA 94305;

Although the similarities between humans and mice are typically highlighted, morphologically and genetically, there are many differences. To better understand these two species on a molecular level, we performed a comparison of the expression profiles of 15 tissues by deep RNA sequencing and examined the similarities and differences in the transcriptome for both protein-coding and -noncoding transcripts. Although commonalities are evident in the expression of tissue-specific genes between the two species, the expression for many sets of genes was found to be more similar in different tissues within the same species than between species. These findings were further corroborated by associated epigenetic histone mark analyses. We also find that many noncoding transcripts are expressed at a low level and are not detectable at appreciable levels across individuals. Moreover, the majority lack obvious sequence homologs between species, even when we restrict our attention to those which are most highly reproducible across biological replicates. Overall, our results indicate that there is considerable RNA expression diversity between humans and mice, well beyond what was described previously, likely reflecting the fundamental physiological differences between these two organisms.
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http://dx.doi.org/10.1073/pnas.1413624111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4260565PMC
December 2014

A comparative encyclopedia of DNA elements in the mouse genome.

Nature 2014 Nov;515(7527):355-64

Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain.

The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
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http://dx.doi.org/10.1038/nature13992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266106PMC
November 2014

Transcriptional diversity during lineage commitment of human blood progenitors.

Science 2014 Sep;345(6204):1251033

Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.
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http://dx.doi.org/10.1126/science.1251033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254742PMC
September 2014