The Human Transcriptome across Tissues and Individuals
Event details
| Date | 06.07.2016 |
| Hour | 11:30 |
| Speaker | Prof. Roderic Guigó, Universitat Pompeu Fabra, Barcelona (E) |
| Location | |
| Category | Conferences - Seminars |
BIOENGINEERING SEMINAR
Abstract:
The pilot phase of the Genotype-Tissue Expression (GTEx) project has produced RNASeq from 1,641 samples originated from up to 43 tissues from 175 post-mortem donors, and constitutes a unique resource to investigate the human transcriptome across tissues and individuals. Clustering of samples based on gene expression recapitulates tissue types, separating solid from not solid tissues, while clustering based on splicing separates neural from non-neural tissues, suggesting that post-transcriptional regulation plays a comparatively important role in the definition of neural tissues .About 47 % of the variation in gene expression can be explained by variation of across tissues, while only 4% by variation across individuals. We find that the relative contribution of individual variation is similar for lncRNAs and for protein coding genes. However, we find that genes that vary with ethnicity are enriched in lncRNAs, whereas genes that vary with age are mostly protein coding. Among genes that vary with gender, we find novel candidates both to participate and to escape X-inactivation. In addition, by merging information on GWAS we are able to identify specific candidate genes that may explain differences in susceptibility to cardiovascular diseases between males and females and different ethnic groups. We find that genes that decrease with age are involved in neurodegenerative diseases such as Parkinson and Alzheimer and identify novel candidates that could be involved in these diseases. In contrast to gene expression, splicing varies similarly among tissues and individuals, and exhibits a larger proportion of residual unexplained variance. This may reflect that that stochastic, non-functional fluctuations of the relative abundances of splice isoforms may be more common than random fluctuations of gene expression. By comparing the variation of the abundance of individual isoforms across all GTEx samples, we find that a large fraction of this variation between tissues (84%) can be simply explained by variation in bulk gene expression, with splicing variation contributing comparatively little. This strongly suggests that regulation at the primary transcription level is the main driver of tissue specificity. Although blood is the most transcriptionally distinct of the surveyed tissues, RNA levels monitored in blood may retain clinically relevant information that can be used to help assess medical or biological conditions.
Bio:
1988 Ph.D. in Statistics. Universitat de Barcelona. (Spain).
1988-1993 Postdoctoral researcher at the Molecular Biology Computer Research Resource. Dana Farber Cancer Institute, Harvard University (Division of Biostatistics) BioMolecular Engineering Research Center. Boston University and Theoretical Biology And Biophysics Group (Los Alamos national Laboratory).
Since 1994 Investigator at Institut Municipal d’Investigació Mèdica (IMIM). Barcelona, (Spain).
Since 2001 Associate Professor at the Universitat Pompeu Fabra and coordinator of the Bioinformatics Programme at the Centre de Regulació Genòmica, Barcelona, (Spain).
Research areas:
Investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, ...). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences
Abstract:
The pilot phase of the Genotype-Tissue Expression (GTEx) project has produced RNASeq from 1,641 samples originated from up to 43 tissues from 175 post-mortem donors, and constitutes a unique resource to investigate the human transcriptome across tissues and individuals. Clustering of samples based on gene expression recapitulates tissue types, separating solid from not solid tissues, while clustering based on splicing separates neural from non-neural tissues, suggesting that post-transcriptional regulation plays a comparatively important role in the definition of neural tissues .About 47 % of the variation in gene expression can be explained by variation of across tissues, while only 4% by variation across individuals. We find that the relative contribution of individual variation is similar for lncRNAs and for protein coding genes. However, we find that genes that vary with ethnicity are enriched in lncRNAs, whereas genes that vary with age are mostly protein coding. Among genes that vary with gender, we find novel candidates both to participate and to escape X-inactivation. In addition, by merging information on GWAS we are able to identify specific candidate genes that may explain differences in susceptibility to cardiovascular diseases between males and females and different ethnic groups. We find that genes that decrease with age are involved in neurodegenerative diseases such as Parkinson and Alzheimer and identify novel candidates that could be involved in these diseases. In contrast to gene expression, splicing varies similarly among tissues and individuals, and exhibits a larger proportion of residual unexplained variance. This may reflect that that stochastic, non-functional fluctuations of the relative abundances of splice isoforms may be more common than random fluctuations of gene expression. By comparing the variation of the abundance of individual isoforms across all GTEx samples, we find that a large fraction of this variation between tissues (84%) can be simply explained by variation in bulk gene expression, with splicing variation contributing comparatively little. This strongly suggests that regulation at the primary transcription level is the main driver of tissue specificity. Although blood is the most transcriptionally distinct of the surveyed tissues, RNA levels monitored in blood may retain clinically relevant information that can be used to help assess medical or biological conditions.
Bio:
1988 Ph.D. in Statistics. Universitat de Barcelona. (Spain).
1988-1993 Postdoctoral researcher at the Molecular Biology Computer Research Resource. Dana Farber Cancer Institute, Harvard University (Division of Biostatistics) BioMolecular Engineering Research Center. Boston University and Theoretical Biology And Biophysics Group (Los Alamos national Laboratory).
Since 1994 Investigator at Institut Municipal d’Investigació Mèdica (IMIM). Barcelona, (Spain).
Since 2001 Associate Professor at the Universitat Pompeu Fabra and coordinator of the Bioinformatics Programme at the Centre de Regulació Genòmica, Barcelona, (Spain).
Research areas:
Investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, ...). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences
Practical information
- Informed public
- Free