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      Decoding ‘Unnecessary Complexity’: A Law of Complexity and a Concept of Hidden Variation Behind “Missing Heritability” in Precision Medicine

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          Abstract

          The high hopes for the Human Genome Project and personalized medicine were not met because the relationship between genotypes and phenotypes turned out to be more complex than expected. In a previous study we laid the foundation of a theory of complexity and showed that because of the blind nature of evolution, and molecular and historical contingency, cells have accumulated unnecessary complexity, complexity beyond what is necessary and sufficient to describe an organism. Here we provide empirical evidence and show that unnecessary complexity has become integrated into the genome in the form of redundancy and is relevant to molecular evolution of phenotypic complexity. Unnecessary complexity creates uncertainty between molecular and phenotypic complexity, such that phenotypic complexity ( C P) is higher than molecular complexity ( C M), which is higher than DNA complexity ( C D). The qualitative inequality in complexity is based on the following hierarchy: C P >  C M >  C D. This law-like relationship holds true for all complex traits, including complex diseases. We present a hypothesis of two types of variation, namely open and closed (hidden) systems, show that hidden variation provides a hitherto undiscovered “ third source” of phenotypic variation, beside genotype and environment, and argue that “missing heritability” for some complex diseases is likely to be a case of “diluted heritability”. There is a need for radically new ways of thinking about the principles of genotype–phenotype relationship. Understanding how cells use hidden, pathway variation to respond to stress can shed light on why two individuals who share the same risk factors may not develop the same disease, or how cancer cells escape death.

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          Finding the missing heritability of complex diseases.

          Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
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            The mystery of missing heritability: Genetic interactions create phantom heritability.

            Human genetics has been haunted by the mystery of "missing heritability" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator--that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating "phantom heritability." Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.
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              A global genetic interaction network maps a wiring diagram of cellular function.

              We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.
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                Author and article information

                Contributors
                singh@mcmaster.ca
                Journal
                J Mol Evol
                J Mol Evol
                Journal of Molecular Evolution
                Springer US (New York )
                0022-2844
                1432-1432
                2 August 2021
                2 August 2021
                : 1-14
                Affiliations
                GRID grid.25073.33, ISNI 0000 0004 1936 8227, Department of Biology, and Origins Institute, , McMaster University, ; 1280 Main Street West, Hamilton, ON L8S4K1 Canada
                Author notes

                Handling editor: Konstantinos Voskarides.

                Author information
                http://orcid.org/0000-0002-5407-537X
                Article
                10023
                10.1007/s00239-021-10023-3
                8327892
                34341835
                6a3e627a-8f0f-4824-9dee-79cf45b027ce
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 April 2021
                : 20 July 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002790, canadian network for research and innovation in machining technology, natural sciences and engineering research council of canada;
                Funded by: FundRef http://dx.doi.org/10.13039/100009776, mcmaster university;
                Categories
                Review

                Evolutionary Biology
                unnecessary complexity,hidden variation,missing heritability,molecular evolution,redundancy,phenotypic complexity,diluted heritability

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