Omnigenetic model for complex traits

In summary, the Stanford researchers propose that most complex traits are due to the interactions of a large number of genes.
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Ygggdrasil
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Related to the recent discussions on this forum about the potential for genetically engineering humans in the future, researchers from Stanford University recently published a fascinating article in the journal Cell, looking into the genetics of complex traits, like height, as well as the genetics of complex diseases, like schizophrenia, rheumatoid arthritis, and Crohn's disease. From their analysis they propose an "omnigenetic" model for complex traits:
More specifically, it means that all the genes that are switched on in a particular type of cell—say, a neuron or a heart muscle cell—are probably involved in almost every complex trait that involves those cells. So, for example, nearly every gene that’s switched on in neurons would play some role in defining a person’s intelligence, or risk of dementia, or propensity to learn. Some of these roles may be staring parts. Others might be mere cameos. But few genes would be left out of the production altogether.

This might explain why the search for genetic variants behind complex traits has been so arduous. For example, a giant study called… er… GIANT looked at the genomes of 250,000 people and identified 700 variants that affect our height. As predicted, each has a tiny effect, raising a person’s stature by just a millimeter. And collectively, they explain just 16 percent of the variation in heights that you see in people of European ancestry. That’s not very much, especially when scientists estimate that some 80 percent of all human height variation can be explained by genetic factors. Where’s that missing fraction?

Pritchard’s team re-analyzed the GIANT data and calculated that there are probably more than 100,000 variants that affect our height, and most of these shift it by just a seventh of a millimeter. They’re so minuscule in their effects that it’s hard to tell them apart from statistical noise, which is why geneticists typically ignore them. And yet, Pritchard’s team noted that many of these weak signals cropped up consistently across different studies, which suggests that they are real results. And since these variants are spread evenly across the entire genome, they implicate a “substantial fraction of all genes,” Pritchard says.
https://www.theatlantic.com/science/archive/2017/06/its-like-all-connected-man/530532/

If true, the results would have important implications for understanding complex diseases like schizophrenia and for efforts to genetically engineer humans. For example, the results suggests that looking for mutations or genetic variants that predispose individuals to higher risks of complex diseases may not shed any light into the underlying biology of the disease because such studies would ultimately find that every gene is implicated in the disease. Similarly, if every gene expressed in a cell contributes to every complex trait, we should be very careful when editing any gene as there is the potential for the edit to have unintended consequences on many different traits.

More detail about the model and the data supporting it are available in the paper cited below:

Boyle, Li and Pritchard. 2017. An expanded view of complex traits: From polygenetic to omnigenetic. Cell 169: 1177. doi:10.1016/j.cell.2017.05.038

Abstract:
A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome—including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways. We refer to this hypothesis as an “omnigenic” model.
 
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“Historically, even understanding the role of one gene in one disease has been considered a major success. Now we have to somehow understand how combinations of seemingly hundreds or thousands of genes work together in very complicated ways. It’s beyond our current ability.”
From your first link... sounds like trying to program a computer when you know nothing of it's programming language except you have sample programs to disassemble. Sounds like it may be a few more decades before we even know where to start redefining genomes.
 
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jerromyjon said:
From your first link... sounds like trying to program a computer when you know nothing of it's programming language except you have sample programs to disassemble. Sounds like it may be a few more decades before we even know where to start redefining genomes.

Obligatory XKCD reference:
dna.png

https://xkcd.com/1605/

We are probably a decade or so from having the capability to synthesize genomes on the scale of the human genome (~ 3 billion base pairs). However, there is an effort underway that aims to make human-scale genome synthesis feasible in 10 years (http://engineeringbiologycenter.org/). In the meantime, researchers have already synthesized a bacterial genome as well as the genome of a baker's yeast, so these will be a good system for studying how to begin making large-scale changes to genomes. For example, researchers recently pared down the genome of a bacterium to synthesize a genome with the minimum number of genes to support life. Unfortunately, about 30% of the genes in this organism had an unknown function, so there is still a lot we need to learn.
 
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FAQ: Omnigenetic model for complex traits

1. What is the omnigenetic model for complex traits?

The omnigenetic model for complex traits proposes that multiple genes, as well as environmental factors, contribute to the development of complex traits and diseases. It suggests that there is no single gene responsible for these traits, but rather a combination of genetic and environmental factors.

2. How does the omnigenetic model differ from other genetic models?

The omnigenetic model differs from other genetic models, such as the polygenic and monogenic models, by acknowledging the role of environmental factors in the development of complex traits. It also suggests that the interactions between genes and the environment are crucial in determining the expression of these traits.

3. What evidence supports the omnigenetic model?

Studies have shown that complex traits, such as intelligence and personality, are influenced by multiple genes and environmental factors. Additionally, research on gene-environment interactions has provided evidence for the importance of both genetic and environmental factors in the development of complex traits.

4. How does the omnigenetic model impact our understanding of complex traits?

The omnigenetic model expands our understanding of complex traits by highlighting the complexity of their development. It emphasizes the importance of considering both genetic and environmental factors and their interactions, rather than focusing solely on genetics or the environment.

5. Can the omnigenetic model be applied to all complex traits?

While the omnigenetic model is a useful framework for understanding complex traits, it may not apply to all traits and diseases. Some may be better explained by other genetic models, such as the polygenic model, which suggests that multiple genes with small effects contribute to the development of a trait. Further research is needed to determine the applicability of the omnigenetic model to different complex traits.

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