Genetic regulation of blood cells: Proximity of a gene to a genetic change plays an important role
- Date:
- September 22, 2021
- Source:
- Universität Leipzig
- Summary:
- Researchers have gained significant new insight into the genetic regulation of blood cells. They achieved this by analyzing a dataset that included more than 31,000 study participants, to date the largest dataset of its kind.
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Genetic causes of traits and diseases are being intensively researched today. And more than 250,000 such connections are now known. In many of these cases, however, it is unclear how the genetic variant found affects the corresponding trait. One possible explanation is that the genetic variant affects gene expression, that is, how the gene is read, and thus alters trait expression.
The international eQTLGen Consortium has therefore conducted large-scale research on how genetic variants influence the expression of genes in the blood. A major finding of the study was that genetic regulations were found in close proximity to the gene in 88 per cent of all the genes analysed. These are called cis effects. It was also shown that 37 per cent of the trait-related genetic variants studied were regulated by distant genes, a phenomenon called trans effects.
Mechanisms identified that determine the first occurrence of menstruation
The many cis and trans effects on gene expression found offer numerous new ways to explain molecular relationships for a wide range of traits and diseases. For example, researchers identified trans mechanisms caused by the gene ZNF131 that determine the first occurrence of menstruation. In some cases, these mechanisms have already been confirmed in the laboratory. Another such example is new mechanistic insight into how the FADS1 and FADS2 genes influence fatty acid metabolism.
"The results significantly expand our knowledge of how gene expression in the blood is regulated and go far beyond the information in databases currently available such as GTEx, the world's largest database to date," said Professor Markus Scholz. "We expect this to provide us a better understanding of genetic associations. Although not typical for the sciences, other study groups were already using the data from our study to interpret the genetic associations they found before it was even published," said the Leipzig bioinformatics researcher.
Data from 7524 subjects and patients at Leipzig University's Faculty of Medicine
The Consortium, established in 2014, included 37 studies with a total number of 31,684 subjects and patients. Leipzig University's Faculty of Medicine contributed significantly to the overall numbers as the data analysed from its three cohorts (Sorben, LIFE Adult and LIFE Heart) came from 7524 individuals.
The Consortium was established by researchers from the Institute of Medical Informatics, Statistics and Epidemiology (IMISE) and led by a team from the University of Groningen. The researchers also developed a comprehensive analysis plan together. "The analyses are very complex because, for one thing, several billion tests are performed and the control of the error rate has to be tailored to the type of correlations being studied," said Dr Holger Kirsten, a researcher at IMISE.
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Journal Reference:
- Urmo Võsa, Annique Claringbould, Harm-Jan Westra, Marc Jan Bonder, Patrick Deelen, Biao Zeng, Holger Kirsten, Ashis Saha, Roman Kreuzhuber, Seyhan Yazar, Harm Brugge, Roy Oelen, Dylan H. de Vries, Monique G. P. van der Wijst, Silva Kasela, Natalia Pervjakova, Isabel Alves, Marie-Julie Favé, Mawussé Agbessi, Mark W. Christiansen, Rick Jansen, Ilkka Seppälä, Lin Tong, Alexander Teumer, Katharina Schramm, Gibran Hemani, Joost Verlouw, Hanieh Yaghootkar, Reyhan Sönmez Flitman, Andrew Brown, Viktorija Kukushkina, Anette Kalnapenkis, Sina Rüeger, Eleonora Porcu, Jaanika Kronberg, Johannes Kettunen, Bernett Lee, Futao Zhang, Ting Qi, Jose Alquicira Hernandez, Wibowo Arindrarto, Frank Beutner, Peter A. C. ’t Hoen, Joyce van Meurs, Jenny van Dongen, Maarten van Iterson, Morris A. Swertz, Marc Jan Bonder, Julia Dmitrieva, Mahmoud Elansary, Benjamin P. Fairfax, Michel Georges, Bastiaan T. Heijmans, Alex W. Hewitt, Mika Kähönen, Yungil Kim, Julian C. Knight, Peter Kovacs, Knut Krohn, Shuang Li, Markus Loeffler, Urko M. Marigorta, Hailang Mei, Yukihide Momozawa, Martina Müller-Nurasyid, Matthias Nauck, Michel G. Nivard, Brenda W. J. H. Penninx, Jonathan K. Pritchard, Olli T. Raitakari, Olaf Rotzschke, Eline P. Slagboom, Coen D. A. Stehouwer, Michael Stumvoll, Patrick Sullivan, Peter A. C. ’t Hoen, Joachim Thiery, Anke Tönjes, Jenny van Dongen, Maarten van Iterson, Jan H. Veldink, Uwe Völker, Robert Warmerdam, Cisca Wijmenga, Morris Swertz, Anand Andiappan, Grant W. Montgomery, Samuli Ripatti, Markus Perola, Zoltan Kutalik, Emmanouil Dermitzakis, Sven Bergmann, Timothy Frayling, Joyce van Meurs, Holger Prokisch, Habibul Ahsan, Brandon L. Pierce, Terho Lehtimäki, Dorret I. Boomsma, Bruce M. Psaty, Sina A. Gharib, Philip Awadalla, Lili Milani, Willem H. Ouwehand, Kate Downes, Oliver Stegle, Alexis Battle, Peter M. Visscher, Jian Yang, Markus Scholz, Joseph Powell, Greg Gibson, Tõnu Esko, Lude Franke. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nature Genetics, 2021; 53 (9): 1300 DOI: 10.1038/s41588-021-00913-z
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