Envirome

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"Envirome" is a concept that relates the core of environmental conditions with the successful biological performance of living beings. This concept was created in genetic epidemiology, in which an envirome is defined as the total set of environmental factors, both present, and past, that affect the state, and in particular the disease state, of an organism. [1] The study of the envirome and its effects is termed enviromics. The term was first coined in the field of psychiatric epidemiology by J.C. Anthony in 1995. [2] [3] More recently, use of the term has been extended to the cellular domain, where cell functional enviromics studies both the genome and envirome from a systems biology perspective. [4] In plants, enviromics is directly related to complex ecophysiology, in which the wide environment of the plants, into an omics scale, can be dissected and understood as a mosaic of possible growing factors and the balance of diverse resources available. [5] [6] In ecology, this concept can be related to the Shelford's law of tolerance. [7] The enviromics (study of the enviromes) is conceived as a pillar of the Modern Plant Breeding, [8] capable to connect the design and development of breeding goals concealing it with the agronomic targets for a climate-smart agriculture. [9] It also has the ability to bridge the knowledge gaps between the different levels of systems biology and phenomics in the context of Gene–environment interaction. [10]

Contents

Envirome classification in humans

While there can be both positive and negative effects of the envirome on the organism, negative effects are often emphasized in discussing disease. A typology of envirome health hazards suggested by McDowall is natural physico-chemical, man-made physico-chemical, biological/organic, natural or man-made, macrosocial, micro- or psychosocial. [3] One approach to classifying the envirome is to organize the factors based on their likely disease-specific causality such as cardiovascular disease [11]

The time-scale of the envirome hazard is another possible dimension of classification; an envirome hazard are said to be a sudden change (such as a disaster), a rapid environmental change, or a slow change or a static situation. [3] In twin studies, envirome influences are often decomposed into shared environmental factors, common to both twins and non-shared environmental factors that differ between the twins. [12]

Envirome classification in plants

In plants, the enviromics term was probably first scientifically mentioned by Xu, [13] in his iconic article on Envirotyping, and also comprehensively described by Resende et al., [14] which is the field of applied data science that integrates databases of environmental factors into quantitative genetics. [7] Then, it can leverage an important plant ecophysiology knowledge capable to bridge the gaps about how the environment acts across different levels of the systems biology (genes, transcripts, proteins, and metabolites). Consequently, it can boost the ability to better understand/model the phenotypic plasticity of the main agronomic traits under diverse growing conditions. The plant breeding community has experienced reduced costs for acquiring environmental sensors (e.g., weather stations) to be installed in the field trials while increasing the reliability and resolution of the remote sensing techniques. [6] The combination of those two factors has started the spring of enviromics-aided breeding in recent years. Recently, Costa-Neto et al. [7] introduced the concept of enviromic-aided genomic prediction involving the use of adaptation typologies to process the raw environmental data into a reliable descriptor of the environmental diversity. This data is then used for training accurate GxE prediction models, mostly involving molecular breeding protocols in agriculture and forestry improvement.

Genetic methods can be applied to elucidate the phenotypic variations caused by enviromics. SFig2A.jpg
Genetic methods can be applied to elucidate the phenotypic variations caused by enviromics.

Phenotypic plasticity, the ability of an organism to express different traits in response to internal and external environmental factors, is influenced by both genetic and environmental factors. Similar to how genetics approaches have been used to identify and predict performance based on genetic markers, the contribution of environmental factors to phenotypic plasticity can be systematically analyzed and predicted. [15] The Critical Environmental Regressor through Informed Search (CERIS [16] [17] [18] [19] ) uses whole-season environmental variants to identify major explicit environmental conditions that contribute to performance, similar to how QTL/ GWAS analysis identifies major genes from genome-wide markers. Enviromic prediction can be used to predict how an organism will perform under new growth conditions based on analysis of the whole-season environmental variants, akin to how genomic prediction is used to predict the performance of new genotypes.

Genotype-environment correlation and interaction

The effect of an envirome on an organism can be potentially modulated by its genetic makeup, i.e., its genome. The two main ways genes and environment may interact is through genotype-environment correlation and interaction. [12] Genotype-environment correlation occurs because, for example, children both inherit genes from their parents and live under the influence of their parents. [12] In the context of genetic epidemiology, interaction refers to the genes and the environment both participating in a causal way that departs from a simple additive model of the effects. [3] An example of a genotype-environment interaction is the increased risk of getting Alzheimer's disease following a head injury in persons carrying the APOE allele. [20]

Criticism in human health

Some researchers see envirome as a renaming of the already well-established nurture component of the nature-nurture dichotomy in explaining psychological behavior. [3] Steven Rose has argued that in psychiatry, it is time to abandon the genome-envirome dichotomy altogether in favor of an integrative view of a person's life course. [21]

See also

Related Research Articles

The genotype of an organism is its complete set of genetic material. Genotype can also be used to refer to the alleles or variants an individual carries in a particular gene or genetic location. The number of alleles an individual can have in a specific gene depends on the number of copies of each chromosome found in that species, also referred to as ploidy. In diploid species like humans, two full sets of chromosomes are present, meaning each individual has two alleles for any given gene. If both alleles are the same, the genotype is referred to as homozygous. If the alleles are different, the genotype is referred to as heterozygous.

<span class="mw-page-title-main">Phenotype</span> Composite of the organisms observable characteristics or traits

In genetics, the phenotype is the set of observable characteristics or traits of an organism. The term covers the organism's morphology, its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior. An organism's phenotype results from two basic factors: the expression of an organism's genetic code and the influence of environmental factors. Both factors may interact, further affecting the phenotype. When two or more clearly different phenotypes exist in the same population of a species, the species is called polymorphic. A well-documented example of polymorphism is Labrador Retriever coloring; while the coat color depends on many genes, it is clearly seen in the environment as yellow, black, and brown. Richard Dawkins in 1978 and then again in his 1982 book The Extended Phenotype suggested that one can regard bird nests and other built structures such as caddisfly larva cases and beaver dams as "extended phenotypes".

<span class="mw-page-title-main">Genotype–phenotype distinction</span> Distinction made in genetics

The genotype–phenotype distinction is drawn in genetics. The "Genotype" is an organism's full hereditary information. The "Phenotype" is an organism's actual observed properties, such as morphology, development, or behavior. This distinction is fundamental in the study of inheritance of traits and their evolution.

<span class="mw-page-title-main">Heritability</span> Estimation of effect of genetic variation on phenotypic variation of a trait

Heritability is a statistic used in the fields of breeding and genetics that estimates the degree of variation in a phenotypic trait in a population that is due to genetic variation between individuals in that population. The concept of heritability can be expressed in the form of the following question: "What is the proportion of the variation in a given trait within a population that is not explained by the environment or random chance?"

<span class="mw-page-title-main">Penetrance</span> Proportion of individuals that express the trait associated with a gene variant

Penetrance in genetics is the proportion of individuals carrying a particular variant of a gene (genotype) that also expresses an associated trait (phenotype). In medical genetics, the penetrance of a disease-causing mutation is the proportion of individuals with the mutation that exhibit clinical symptoms among all individuals with such mutation. For example: If a mutation in the gene responsible for a particular autosomal dominant disorder has 75% penetrance, then 75% of those with the mutation will go on to develop the disease, showing its phenotype, whereas 25% will not. 

A quantitative trait locus (QTL) is a locus that correlates with variation of a quantitative trait in the phenotype of a population of organisms. QTLs are mapped by identifying which molecular markers correlate with an observed trait. This is often an early step in identifying the actual genes that cause the trait variation.

An environmental factor, ecological factor or eco factor is any factor, abiotic or biotic, that influences living organisms. Abiotic factors include ambient temperature, amount of sunlight, air, soil, water and pH of the water soil in which an organism lives. Biotic factors would include the availability of food organisms and the presence of biological specificity, competitors, predators, and parasites.

Genetic architecture is the underlying genetic basis of a phenotypic trait and its variational properties. Phenotypic variation for quantitative traits is, at the most basic level, the result of the segregation of alleles at quantitative trait loci (QTL). Environmental factors and other external influences can also play a role in phenotypic variation. Genetic architecture is a broad term that can be described for any given individual based on information regarding gene and allele number, the distribution of allelic and mutational effects, and patterns of pleiotropy, dominance, and epistasis.

In genetics, expressivity is the degree to which a phenotype is expressed by individuals having a particular genotype. Alternatively, it may refer to the expression of a particular gene by individuals having a certain phenotype. Expressivity is related to the intensity of a given phenotype; it differs from penetrance, which refers to the proportion of individuals with a particular genotype that share the same phenotype.

<span class="mw-page-title-main">Gene–environment interaction</span> Response to the same environmental variation differently by different genotypes

Gene–environment interaction is when two different genotypes respond to environmental variation in different ways. A norm of reaction is a graph that shows the relationship between genes and environmental factors when phenotypic differences are continuous. They can help illustrate GxE interactions. When the norm of reaction is not parallel, as shown in the figure below, there is a gene by environment interaction. This indicates that each genotype responds to environmental variation in a different way. Environmental variation can be physical, chemical, biological, behavior patterns or life events.

In ecology and genetics, a reaction norm, also called a norm of reaction, describes the pattern of phenotypic expression of a single genotype across a range of environments. One use of reaction norms is in describing how different species—especially related species—respond to varying environments. But differing genotypes within a single species may also show differing reaction norms relative to a particular phenotypic trait and environment variable. For every genotype, phenotypic trait, and environmental variable, a different reaction norm can exist; in other words, an enormous complexity can exist in the interrelationships between genetic and environmental factors in determining traits. The concept was introduced by Richard Woltereck in 1909.

<span class="mw-page-title-main">Phenotypic plasticity</span> Trait change of an organism in response to environmental variation

Phenotypic plasticity refers to some of the changes in an organism's behavior, morphology and physiology in response to a unique environment. Fundamental to the way in which organisms cope with environmental variation, phenotypic plasticity encompasses all types of environmentally induced changes that may or may not be permanent throughout an individual's lifespan.

Phenomics is the systematic study of traits that make up a phenotype. It was coined by UC Berkeley and LBNL scientist Steven A. Garan. As such, it is a transdisciplinary area of research that involves biology, data sciences, engineering and other fields. Phenomics is concerned with the measurement of the phenotype where a phenome is a set of traits that can be produced by a given organism over the course of development and in response to genetic mutation and environmental influences. It is also important to remember that an organisms phenotype changes with time. The relationship between phenotype and genotype enables researchers to understand and study pleiotropy. Phenomics concepts are used in functional genomics, pharmaceutical research, metabolic engineering, agricultural research, and increasingly in phylogenetics.

<span class="mw-page-title-main">Genome-wide association study</span> Study of genetic variants in different individuals

In genomics, a genome-wide association study, is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms.

Genetic epidemiology is the study of the role of genetic factors in determining health and disease in families and in populations, and the interplay of such genetic factors with environmental factors. Genetic epidemiology seeks to derive a statistical and quantitative analysis of how genetics work in large groups.

Behavioural genetics, also referred to as behaviour genetics, is a field of scientific research that uses genetic methods to investigate the nature and origins of individual differences in behaviour. While the name "behavioural genetics" connotes a focus on genetic influences, the field broadly investigates the extent to which genetic and environmental factors influence individual differences, and the development of research designs that can remove the confounding of genes and environment. Behavioural genetics was founded as a scientific discipline by Francis Galton in the late 19th century, only to be discredited through association with eugenics movements before and during World War II. In the latter half of the 20th century, the field saw renewed prominence with research on inheritance of behaviour and mental illness in humans, as well as research on genetically informative model organisms through selective breeding and crosses. In the late 20th and early 21st centuries, technological advances in molecular genetics made it possible to measure and modify the genome directly. This led to major advances in model organism research and in human studies, leading to new scientific discoveries.

A recombinant inbred strain or recombinant inbred line (RIL) is an organism with chromosomes that incorporate an essentially permanent set of recombination events between chromosomes inherited from two or more inbred strains. F1 and F2 generations are produced by intercrossing the inbred strains; pairs of the F2 progeny are then mated to establish inbred strains through long-term inbreeding.

Molecular breeding is the application of molecular biology tools, often in plant breeding and animal breeding. In the broad sense, molecular breeding can be defined as the use of genetic manipulation performed at the level of DNA to improve traits of interest in plants and animals, and it may also include genetic engineering or gene manipulation, molecular marker-assisted selection, and genomic selection. More often, however, molecular breeding implies molecular marker-assisted breeding (MAB) and is defined as the application of molecular biotechnologies, specifically molecular markers, in combination with linkage maps and genomics, to alter and improve plant or animal traits on the basis of genotypic assays.

Photothermal time (PTT) is a product between growing degree-days (GDD) and day length (hours) for each day. PTT = GDD × DL It can be used to quantify environment, as well as the timing of developmental stages of plants.

Invasion genetics is the area of study within biology that examines evolutionary processes in the context of biological invasions. Invasion genetics considers how genetic and demographic factors affect the success of a species introduced outside of its native range, and how the mechanisms of evolution, such as natural selection, mutation, and genetic drift, operate in these populations. Researchers exploring these questions draw upon theory and approaches from a range of biological disciplines, including population genetics, evolutionary ecology, population biology, and phylogeography.

References

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  2. ↑ Shayne Cox Gad (2008). Preclinical Development Handbook: Toxicology. John Wiley & Sons. p. 778. ISBN   9780470249048.
  3. 1 2 3 4 5 Cooper, Brian (2001). "Nature, nurture and mental disorder: old concepts in the new millennium". The British Journal of Psychiatry. 178 (suppl. 40): 91–102. doi: 10.1192/bjp.178.40.s91 . PMID   11315233.
  4. ↑ Teixeira, Ana P; ML Dias, João; Carinhas, Nuno; Sousa, Marcos; J Clemente, João; E Cunha, António; von Stosch, Moritz; M Alves, Paula; JT Carrondo, Manuel; Oliveira, Rui (2011). "Cell functional enviromics: Unravelling the function of environmental factors". BMC Systems Biology. 5: 92–108. doi: 10.1186/1752-0509-5-92 . PMC   3118353 . PMID   21645360.
  5. ↑ Resende, Rafael T.; Piepho, Hans-Peter; Rosa, Guilherme; Silva-Junior, Orzenil B.; Resende, Marcos Deon V.; Grattapaglia, Dario (2021). "Enviromics in breeding: applications and perspectives on envirotypic-assisted selection". Theoretical and Applied Genetics. 134 (4): 95–112. doi: 10.1007/s00122-016-2691-5 . PMC   4799247 . PMID   26932121.
  6. 1 2 Costa-Neto, G., Galli, G., Carvalho, H. F., Crossa, J., and Fritsche-Neto, R. (2021b). EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture. G3 Genes|Genomes|Genetics. doi:10.1093/g3journal/jkab040.
  7. 1 2 3 Costa-Neto, G., Crossa, J., and Fritsche-Neto, R. (2021a). Enviromic Assembly Increases Accuracy and Reduces Costs of the Genomic Prediction for Yield Plasticity in Maize. Frontiers in Plant Science 12. doi:10.3389/fpls.2021.717552.
  8. ↑ Crossa, J., Fritsche-Neto, R., Montesinos-lopez, O. A., Costa-Neto, G., Dreisigacker, S., Montesinos-lopez, A., et al. (2021). The Modern Plant Breeding Triangle : Optimizing the Use of Genomics , Phenomics , and Enviromics Data. Frontiers in plant science 12, 1–6. doi:10.3389/fpls.2021.651480.
  9. ↑ Cooper, M., and Messina, C. D. (2021). Can We Harness “Enviromics” to Accelerate Crop Improvement by Integrating Breeding and Agronomy? Frontiers in Plant Science 12. doi:10.3389/fpls.2021.735143.
  10. ↑ Costa-Neto, G., and Fritsche-Neto, R. (2021). Enviromics: bridging different sources of data, building one framework. Crop Breeding and Applied Biotechnology 21, https://cbab.sbmp.org.br/2021/07/06/article-enviromics-bridging-different-sources-of-data-building-one-framework/
  11. ↑ Riggs, Daniel W.; Yeager, Ray A.; Bhatnagar, Aruni (2018-04-27). "Defining the Human Envirome: An Omics Approach for Assessing the Environmental Risk of Cardiovascular Disease". Circulation Research. 122 (9): 1259–1275. doi:10.1161/CIRCRESAHA.117.311230. ISSN   0009-7330. PMC   6398443 . PMID   29700071.
  12. 1 2 3 Neiderhiser, Jenae M. (2018). "Understanding the roles of genome and envirome: methods in genetic epidemiology". British Journal of Psychiatry. 178 (S40): s12–s17. doi: 10.1192/bjp.178.40.s12 . ISSN   0007-1250. PMID   11315218.
  13. ↑ Xu, Yunbi (2016). "Envirotyping for deciphering environmental impacts on crop plants". Theoretical and Applied Genetics. 129 (4): 653–673. doi: 10.1007/s00122-016-2691-5 . PMC   4799247 . PMID   26932121.
  14. ↑ Resende, Rafael T.; Piepho, Hans-Peter; Silva-Junior, Orzenil B.; Resende, Marcos Deon V.; Grattapaglia, Dario (2019). "Enviromics in breeding: applications and perspectives on envirotypic-assisted selection". bioRxiv: 1–23. doi:10.1101/726513. S2CID   201196743.
  15. 1 2 Li, Xianran; Guo, Tingting; Bai, Guihua; Zhang, Zhiwu; See, Deven; Marshall, Juliet; Garland-Campbell, Kimberly A.; Yu, Jianming (2022-02-07). "Genetics-inspired data-driven approaches explain and predict crop performance fluctuations attributed to changing climatic conditions". Molecular Plant. 15 (2): 203–206. doi: 10.1016/j.molp.2022.01.001 . ISSN   1752-9867. PMID   34999020.
  16. ↑ Li, Xianran; Guo, Tingting; Wang, Jinyu; Bekele, Wubishet A.; Sukumaran, Sivakumar; Vanous, Adam E.; McNellie, James P.; Tibbs-Cortes, Laura E.; Lopes, Marta S.; Lamkey, Kendall R.; Westgate, Mark E.; McKay, John K.; Archontoulis, Sotirios V.; Reynolds, Matthew P.; Tinker, Nicholas A. (2021-06-07). "An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops". Molecular Plant. 14 (6): 874–887. doi: 10.1016/j.molp.2021.03.010 . ISSN   1674-2052. PMID   33713844.
  17. ↑ Guo, Tingting; Mu, Qi; Wang, Jinyu; Vanous, Adam E.; Onogi, Akio; Iwata, Hiroyoshi; Li, Xianran; Yu, Jianming (2020-05-01). "Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation". Genome Research. 30 (5): 673–683. doi:10.1101/gr.255703.119. ISSN   1088-9051. PMC   7263186 . PMID   32299830.
  18. ↑ Li, Xin; Guo, Tingting; Mu, Qi; Li, Xianran; Yu, Jianming (2018-06-26). "Genomic and environmental determinants and their interplay underlying phenotypic plasticity". Proceedings of the National Academy of Sciences. 115 (26): 6679–6684. Bibcode:2018PNAS..115.6679L. doi: 10.1073/pnas.1718326115 . ISSN   0027-8424. PMC   6042117 . PMID   29891664.
  19. ↑ Mu, Qi; Guo, Tingting; Li, Xianran; Yu, Jianming (2022). "Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range". New Phytologist. 233 (4): 1768–1779. doi: 10.1111/nph.17904 . ISSN   0028-646X. PMID   34870847.
  20. ↑ Nicoll, J.A.; Roberts, G. W.; Graham, D. I. (1996). "Amyloid beta-protein, APOE genotype and head injury (review)". Annals of the New York Academy of Sciences. 777: 271–275. doi:10.1111/j.1749-6632.1996.tb34431.x. PMID   8624097. S2CID   84564798.
  21. ↑ Rose, S. (2001). "Moving on from old dichotomies: beyond nature ^ nurture towards a lifeline perspective" (PDF). British Journal of Psychiatry. 178 (suppl. 40): s3–s7. doi: 10.1192/bjp.178.40.s3 . PMID   11315221.
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