The transcriptional legacy of developmental stochasticity

Ballouz, Sara; Peña, María; Knight, Frank M.; Adams, Linda B.; Gillis, Jesse

doi:10.1101/2019.12.11.873265

Cited by 16 publications

(16 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In reality, phenotypic heterogeneity is widespread even among genetically identical individuals reared in carefully controlled environments. This phenomenon is well documented among microbes, but it is also true for diverse plants, fungi and animals (Vogt 2015) and for traits as diverse as gene expression (Ballouz et al 2019; Elowitz et al 2002), antibiotic (Balaban et al 2004) and formaldehyde (Lee et al 2019) resistance, motility (Salek et al 2019), phototaxis (Kain et al 2012), cell number (Herron et al 2014), predator evasion behavior (Schuett et al 2011), and number of sense organs (Vogt et al 2008).…”

Section: Discussionmentioning

confidence: 97%

Spontaneous emergence of multicellular heritability

Dahaj

Burnetti

Day

et al. 2021

Preprint

View full text Add to dashboard Cite

The Major Transitions in evolution include events and processes that result in the emergence of new levels of biological individuality. For collectives to undergo Darwinian evolution, their traits must be heritable, but the emergence of higher-level heritability is poorly understood and has long been considered a stumbling block for nascent evolutionary transitions. A change in the means by which genetic information is utilized and transmitted has been presumed necessary. Using analytical models, synthetic biology, and biologically-informed simulations, we explored the emergence of trait heritability during the evolution of multicellularity. Contrary to existing theory, we show that no additional layer of genetic regulation is necessary for traits of nascent multicellular organisms to become heritable; rather, heritability and the capacity to respond to natural selection on multicellular-level traits can arise ''for free.'' In fact, we find that a key emergent multicellular trait, organism size at reproduction, is usually more heritable than the underlying cell-level trait upon which it is based, given reasonable assumptions.

show abstract

Section: Discussionmentioning

confidence: 97%

Spontaneous emergence of multicellular heritability

Dahaj

Burnetti

Day

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…This estimate still biases stochastic contributions low, because selective and neutral genetic variation cannot be fully decomposed. Other studies support the idea that stochastic events play a major role at all levels, from stochastic gene expression, to the protein level, to the cell and organismal organization level, and these studies range from relatively simple organisms such as bacteria to complex ones such as mammals [52][53][54][55][56][57][58] . As population genetics has long recognized, such variability in individual fates means that stochastic effects are larger in small populations.…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies have been devoted to determining the impact of stochastic events on variation at the molecular, cellular and organismal level. At each of these levels substantial evidence suggests that stochasticity plays an important role 18,44,49,[51][52][53][54][55][56][57]67 . In some circumstances the cause of the "stochastic" outcome can be tracked down to a mechanistic cause at a lower level, but this mechanistic cause may be triggered by other stochastic events.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata

Steiner

Tuljapurkar

Roach

2021

Sci Rep

View full text Add to dashboard Cite

Simple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.

show abstract

“…Lastly, about 18% of height-growth variation remained unexplained in our study. Recent studies have highlighted the important role that developmental stochasticity can play in differences between individuals with the same genotype (Vogt 2015, Ballouz et al 2019). Height growth may also be influenced by the correlative effects of other traits.…”

Section: Discussionmentioning

confidence: 99%

Combining climatic and genomic data improves range-wide tree height growth prediction in a forest tree

Archambeau

Benito-Garzón

Barraquand

et al. 2020

Preprint

View full text Add to dashboard Cite

Predicting adaptive-trait variation across species ranges is essential to assess the potential of populations to survive under future environmental conditions. In forest trees, multi-site common gardens have long been the gold standard for separating the genetic and plastic components of trait variation and predicting population responses to new environments. However, relying on common gardens alone limits our ability to extrapolate predictions to populations or sites not included in these logistically expensive and time-consuming experiments. In this study, we aimed to determine whether models that integrate large-scale climatic and genomic data could capture the underlying drivers of tree adaptive-trait variation, and thus improve predictions at large geographical scales. Using a clonal common garden consisting of 34 provenances of maritime pine (523 genotypes and 12,841 trees) planted in five sites under contrasted environments, we compared twelve statistical models to: (i) separate the genetic and plastic components of height growth, a key adaptive trait in forest trees, (ii) identify the relative importance of factors underlying height-growth variation across individuals and populations, and (iii) improve height-growth prediction of unknown observations and provenances. We found that the height-growth plastic component exceeded more than twice the genetic component. The plastic component was likely due to multiple environmental factors, including annual climatic variables, while the genetic component was driven by the confounded effects of past demographic history and provenance adaptation to the climate-of-origin. Distinct gene pools were characterized by different total genetic variance, with broad-sense heritability ranging from 0.104 (95% CIs: 0.065-0.146) to 0.223 (95% CIs: 0.093-0.363), suggesting different potential response to selection along the geographical distribution of maritime pine. When predicting height-growth of new observations, models combining population demographic history, provenance climate-of-origin, and positive-effect height-associated alleles (PEAs; previously identified by GWAs) explained as much variance as models relying directly on the common garden design. Noteworthy, these models explained substantially more variance when predicting height-growth in new provenances, particularly in harsh environments. Predicting quantitative traits of ecological and/or economic importance across species ranges would therefore benefit from integrating ecological and genomic information.

show abstract

The transcriptional legacy of developmental stochasticity

Cited by 16 publications

References 29 publications

Spontaneous emergence of multicellular heritability

Spontaneous emergence of multicellular heritability

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata

Combining climatic and genomic data improves range-wide tree height growth prediction in a forest tree

Contact Info

Product

Resources

About