Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

AbstractThe need for tools to cost-effectively identify adaptive variation within ecologically and economically important plant species is mounting as the detrimental effects of climate change become increasingly apparent. For crop and wild populations alike, mismatches between adaptive variation and climatic optima will reduce health, growth, survival, reproduction, and continued establishment. The ease with which land managers can quantify the relative importance of different climate factors or the spatial scale of local adaptation to climate will have direct implications for the potential of mitigating or resolving such risks. Using seed collected from 281 provenances of lodgepole pine (Pinus contorta) from across western Canada, we compare genomic data to phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and spatial scale of local adaptation in this species. We find that genomic and climate data are nearly equivalent for describing local adaptation in seedling traits. We also find strong agreement between the climate variables associated with genomic variation and with 20-year heights from a long-term provenance trial, suggesting that genomic data may be a viable option for identifying climatic drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with cold injury occur at broad spatial scales, suggesting that standing variation of adaptive alleles for this and similar species does not require management at scales finer than are indicated by phenotypic data. This study demonstrates that genomic data are most useful when paired with phenotypic data, but can also fill some of the traditional roles of phenotypic data in management of species for which phenotypic trials are not feasible.

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Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

Evolutionary Applications ◽

10.1111/eva.12871 ◽

2019 ◽

Vol 13 (1) ◽

pp. 116-131 ◽

Cited By ~ 10

Author(s):

Colin R. Mahony ◽

Ian R. MacLachlan ◽

Brandon M. Lind ◽

Jeremy B. Yoder ◽

Tongli Wang ◽

...

Keyword(s):

Local Adaptation ◽

Lodgepole Pine ◽

Genomic Data ◽

Changing Climate

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Population genomic data in spider mites point to a role for local adaptation in shaping range shifts

Evolutionary Applications ◽

10.1111/eva.13086 ◽

2020 ◽

Vol 13 (10) ◽

pp. 2821-2835

Author(s):

Lei Chen ◽

Jing‐Tao Sun ◽

Peng‐Yu Jin ◽

Ary A. Hoffmann ◽

Xiao‐Li Bing ◽

...

Keyword(s):

Local Adaptation ◽

Genomic Data ◽

Spider Mites ◽

Range Shifts ◽

Population Genomic

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The theory on and software simulating large-scale genomic data for genotype-by-environment interactions

BMC Genomics ◽

10.1186/s12864-021-08191-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Xiujin Li ◽

Hailiang Song ◽

Zhe Zhang ◽

Yunmao Huang ◽

Qin Zhang ◽

...

Keyword(s):

Large Scale ◽

Simulated Data ◽

Genomic Data ◽

Efficient Tool ◽

Phenotypic Data ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Threshold Trait ◽

Genome Wide ◽

Increasing Demand

Abstract Background With the emphasis on analysing genotype-by-environment interactions within the framework of genomic selection and genome-wide association analysis, there is an increasing demand for reliable tools that can be used to simulate large-scale genomic data in order to assess related approaches. Results We proposed a theory to simulate large-scale genomic data on genotype-by-environment interactions and added this new function to our developed tool GPOPSIM. Additionally, a simulated threshold trait with large-scale genomic data was also added. The validation of the simulated data indicated that GPOSPIM2.0 is an efficient tool for mimicking the phenotypic data of quantitative traits, threshold traits, and genetically correlated traits with large-scale genomic data while taking genotype-by-environment interactions into account. Conclusions This tool is useful for assessing genotype-by-environment interactions and threshold traits methods.

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Intraspecific genomic variation and local adaptation in a young hybrid species

10.1101/732313 ◽

2019 ◽

Author(s):

Angélica Cuevas ◽

Mark Ravinet ◽

Glenn-Peter Sætre ◽

Fabrice Eroukhmanoff

Keyword(s):

Genetic Variation ◽

Local Adaptation ◽

Climatic Variation ◽

Genomic Variation ◽

Population Divergence ◽

Parent Species ◽

Evolutionary Potential ◽

Variable Environment ◽

Hybrid Species ◽

Species Population

ABSTRACTHybridization increases genetic variation, hence hybrid species may have a strong evolutionary potential once their admixed genomes have stabilized and incompatibilities have been purged. Yet, little is known about how such hybrid lineages evolve at the genomic level following their formation, in particular the characteristics of their adaptive potential, i.e. constraints and facilitations of diversification. Here we investigate how the Italian sparrow (Passer italiae), a homoploid hybrid species, has evolved and locally adapted to its variable environment. Using restriction site-associated DNA sequencing (RAD-seq) on several populations across the Italian peninsula, we evaluate how genomic constraints and novel genetic variation have influenced population divergence and adaptation. We show that population divergence within this hybrid species has evolved in response to climatic variation. As in non-hybrid species, climatic differences may even reduce gene flow between populations, suggesting ongoing local adaptation. We report outlier genes associated with adaptation to climatic variation, known to be involved in beak morphology in other species. Most of the strongly divergent loci among Italian sparrow populations seem not to be differentiated between its parent species, the house and Spanish sparrow. Within the parental species, population divergence has occurred mostly in loci where different alleles segregate in the parent species, unlike in the hybrid, suggesting that novel combinations of parental alleles in the hybrid have not necessarily enhanced its evolutionary potential. Rather, our study suggests that constraints linked to incompatibilities may have restricted the evolution of this admixed genome, both during and after hybrid species formation.

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Genomic variation associated with local adaptation of weedy rice during de-domestication

Nature Communications ◽

10.1038/ncomms15323 ◽

2017 ◽

Vol 8 (1) ◽

Cited By ~ 46

Author(s):

Jie Qiu ◽

Yongjun Zhou ◽

Lingfeng Mao ◽

Chuyu Ye ◽

Weidi Wang ◽

...

Keyword(s):

Local Adaptation ◽

Genomic Variation ◽

Weedy Rice

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Evolution of genomic variation in the burrowing owl in response to recent colonization of urban areas

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2018.0206 ◽

2018 ◽

Vol 285 (1878) ◽

pp. 20180206 ◽

Cited By ~ 20

Author(s):

Jakob C. Mueller ◽

Heiner Kuhl ◽

Stefan Boerno ◽

Jose L. Tella ◽

Martina Carrete ◽

...

Keyword(s):

Urban Areas ◽

Demographic History ◽

Genomic Variation ◽

Rural Populations ◽

Urban Habitat ◽

Restricted Gene Flow ◽

Athene Cunicularia ◽

Urban Populations ◽

Burrowing Owl ◽

Standing Variation

When a species successfully colonizes an urban habitat it can be expected that its population rapidly adapts to the new environment but also experiences demographic perturbations. It is, therefore, essential to gain an understanding of the population structure and the demographic history of the urban and neighbouring rural populations before studying adaptation at the genome level. Here, we investigate populations of the burrowing owl ( Athene cunicularia ), a species that colonized South American cities just a few decades ago. We assembled a high-quality genome of the burrowing owl and re-sequenced 137 owls from three urban–rural population pairs at 17-fold median sequencing coverage per individual. Our data indicate that each city was independently colonized by a limited number of founders and that restricted gene flow occurred between neighbouring urban and rural populations, but not between urban populations of different cities. Using long-range linkage disequilibrium statistics in an approximate Bayesian computation approach, we estimated consistently lower population sizes in the recent past for the urban populations in comparison to the rural ones. The current urban populations all show reduced standing variation in rare single nucleotide polymorphisms (SNPs), but with different subsets of rare SNPs in different cities. This lowers the potential for local adaptation based on rare variants and makes it harder to detect consistent signals of selection in the genome.

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Intraspecific genomic variation and local adaptation in a young hybrid species

Molecular Ecology ◽

10.1111/mec.15760 ◽

2020 ◽

Author(s):

Angélica Cuevas ◽

Mark Ravinet ◽

Glenn‐Peter Sætre ◽

Fabrice Eroukhmanoff

Keyword(s):

Local Adaptation ◽

Genomic Variation ◽

Hybrid Species

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The role of spatial scale and soil for local adaptation in Inula hirta

Basic and Applied Ecology ◽

10.1016/j.baae.2011.01.001 ◽

2011 ◽

Vol 12 (2) ◽

pp. 152-160 ◽

Cited By ~ 28

Author(s):

Jana Raabová ◽

Zuzana Münzbergová ◽

Markus Fischer

Keyword(s):

Spatial Scale ◽

Local Adaptation

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Limited potential for adaptation to climate change in a broadly distributed marine crustacean

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2011.0542 ◽

2011 ◽

Vol 279 (1727) ◽

pp. 349-356 ◽

Cited By ~ 175

Author(s):

Morgan W. Kelly ◽

Eric Sanford ◽

Richard K. Grosberg

Keyword(s):

Climate Change ◽

Local Adaptation ◽

Thermal Tolerance ◽

Extinction Risk ◽

Empirical Studies ◽

Natural Populations ◽

Adaptation To Climate Change ◽

Isolated Populations ◽

Tigriopus Californicus ◽

Standing Variation

The extent to which acclimation and genetic adaptation might buffer natural populations against climate change is largely unknown. Most models predicting biological responses to environmental change assume that species' climatic envelopes are homogeneous both in space and time. Although recent discussions have questioned this assumption, few empirical studies have characterized intraspecific patterns of genetic variation in traits directly related to environmental tolerance limits. We test the extent of such variation in the broadly distributed tidepool copepod Tigriopus californicus using laboratory rearing and selection experiments to quantify thermal tolerance and scope for adaptation in eight populations spanning more than 17° of latitude. Tigriopus californicus exhibit striking local adaptation to temperature, with less than 1 per cent of the total quantitative variance for thermal tolerance partitioned within populations. Moreover, heat-tolerant phenotypes observed in low-latitude populations cannot be achieved in high-latitude populations, either through acclimation or 10 generations of strong selection. Finally, in four populations there was no increase in thermal tolerance between generations 5 and 10 of selection, suggesting that standing variation had already been depleted. Thus, plasticity and adaptation appear to have limited capacity to buffer these isolated populations against further increases in temperature. Our results suggest that models assuming a uniform climatic envelope may greatly underestimate extinction risk in species with strong local adaptation.

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Large-Scale Analysis of Genetic and Clinical Patient Data

Annual Review of Biomedical Data Science ◽

10.1146/annurev-biodatasci-080917-013508 ◽

2018 ◽

Vol 1 (1) ◽

pp. 263-274 ◽

Cited By ~ 6

Author(s):

Marylyn D. Ritchie

Keyword(s):

Clinical Data ◽

Large Scale ◽

Data Science ◽

Genomic Analysis ◽

Genomic Data ◽

Data Sets ◽

Biomedical Data ◽

Data Types ◽

Phenotypic Data ◽

Clinical Patient

Biomedical data science has experienced an explosion of new data over the past decade. Abundant genetic and genomic data are increasingly available in large, diverse data sets due to the maturation of modern molecular technologies. Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries, and epidemiologic studies. The methods and approaches for interrogating these large genetic/genomic and clinical data sets continue to evolve rapidly, as our understanding of the questions and challenges continue to emerge. In this review, the state-of-the-art methodologies for genetic/genomic analysis along with complex phenomics will be discussed. This field is changing and adapting to the novel data types made available, as well as technological advances in computation and machine learning. Thus, I will also discuss the future challenges in this exciting and innovative space. The promises of precision medicine rely heavily on the ability to marry complex genetic/genomic data with clinical phenotypes in meaningful ways.

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