---
_id: '12248'
abstract:
- lang: eng
text: Eurasian brine shrimp (genus Artemia) have closely related sexual and asexual
lineages of parthenogenetic females, which produce rare males at low frequencies.
Although they are known to have ZW chromosomes, these are not well characterized,
and it is unclear whether they are shared across the clade. Furthermore, the underlying
genetic architecture of the transmission of asexuality, which can occur when rare
males mate with closely related sexual females, is not well understood. We produced
a chromosome-level assembly for the sexual Eurasian species Artemia sinica and
characterized in detail the pair of sex chromosomes of this species. We combined
this new assembly with short-read genomic data for the sexual species Artemia
sp. Kazakhstan and several asexual lineages of Artemia parthenogenetica, allowing
us to perform an in-depth characterization of sex-chromosome evolution across
the genus. We identified a small differentiated region of the ZW pair that is
shared by all sexual and asexual lineages, supporting the shared ancestry of the
sex chromosomes. We also inferred that recombination suppression has spread to
larger sections of the chromosome independently in the American and Eurasian lineages.
Finally, we took advantage of a rare male, which we backcrossed to sexual females,
to explore the genetic basis of asexuality. Our results suggest that parthenogenesis
is likely partly controlled by a locus on the Z chromosome, highlighting the interplay
between sex determination and asexuality.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "This work was supported by the European Research Council under the
European Union’s Horizon 2020 research and innovation program (grant agreement no.
715257) and by the Austrian Science Foundation (FWF SFB F88-10).\r\nWe thank the
Vicoso group for comments on the manuscript and the ISTA Scientific computing team
and the Vienna Biocenter Sequencing facility for technical support."
article_number: iyac123
article_processing_charge: No
article_type: original
author:
- first_name: Marwan N
full_name: Elkrewi, Marwan N
id: 0B46FACA-A8E1-11E9-9BD3-79D1E5697425
last_name: Elkrewi
orcid: 0000-0002-5328-7231
- first_name: Uladzislava
full_name: Khauratovich, Uladzislava
id: 5eba06f4-97d8-11ed-9f8f-d826ebdd9434
last_name: Khauratovich
- first_name: Melissa A
full_name: Toups, Melissa A
id: 4E099E4E-F248-11E8-B48F-1D18A9856A87
last_name: Toups
orcid: 0000-0002-9752-7380
- first_name: Vincent K
full_name: Bett, Vincent K
id: 57854184-AAE0-11E9-8D04-98D6E5697425
last_name: Bett
- first_name: Andrea
full_name: Mrnjavac, Andrea
id: 353FAC84-AE61-11E9-8BFC-00D3E5697425
last_name: Mrnjavac
- first_name: Ariana
full_name: Macon, Ariana
id: 2A0848E2-F248-11E8-B48F-1D18A9856A87
last_name: Macon
- first_name: Christelle
full_name: Fraisse, Christelle
id: 32DF5794-F248-11E8-B48F-1D18A9856A87
last_name: Fraisse
orcid: 0000-0001-8441-5075
- first_name: Luca
full_name: Sax, Luca
id: 701c5602-97d8-11ed-96b5-b52773c70189
last_name: Sax
- first_name: Ann K
full_name: Huylmans, Ann K
id: 4C0A3874-F248-11E8-B48F-1D18A9856A87
last_name: Huylmans
orcid: 0000-0001-8871-4961
- first_name: Francisco
full_name: Hontoria, Francisco
last_name: Hontoria
- first_name: Beatriz
full_name: Vicoso, Beatriz
id: 49E1C5C6-F248-11E8-B48F-1D18A9856A87
last_name: Vicoso
orcid: 0000-0002-4579-8306
citation:
ama: Elkrewi MN, Khauratovich U, Toups MA, et al. ZW sex-chromosome evolution and
contagious parthenogenesis in Artemia brine shrimp. Genetics. 2022;222(2).
doi:10.1093/genetics/iyac123
apa: Elkrewi, M. N., Khauratovich, U., Toups, M. A., Bett, V. K., Mrnjavac, A.,
Macon, A., … Vicoso, B. (2022). ZW sex-chromosome evolution and contagious parthenogenesis
in Artemia brine shrimp. Genetics. Oxford University Press. https://doi.org/10.1093/genetics/iyac123
chicago: Elkrewi, Marwan N, Uladzislava Khauratovich, Melissa A Toups, Vincent K
Bett, Andrea Mrnjavac, Ariana Macon, Christelle Fraisse, et al. “ZW Sex-Chromosome
Evolution and Contagious Parthenogenesis in Artemia Brine Shrimp.” Genetics.
Oxford University Press, 2022. https://doi.org/10.1093/genetics/iyac123.
ieee: M. N. Elkrewi et al., “ZW sex-chromosome evolution and contagious parthenogenesis
in Artemia brine shrimp,” Genetics, vol. 222, no. 2. Oxford University
Press, 2022.
ista: Elkrewi MN, Khauratovich U, Toups MA, Bett VK, Mrnjavac A, Macon A, Fraisse
C, Sax L, Huylmans AK, Hontoria F, Vicoso B. 2022. ZW sex-chromosome evolution
and contagious parthenogenesis in Artemia brine shrimp. Genetics. 222(2), iyac123.
mla: Elkrewi, Marwan N., et al. “ZW Sex-Chromosome Evolution and Contagious Parthenogenesis
in Artemia Brine Shrimp.” Genetics, vol. 222, no. 2, iyac123, Oxford University
Press, 2022, doi:10.1093/genetics/iyac123.
short: M.N. Elkrewi, U. Khauratovich, M.A. Toups, V.K. Bett, A. Mrnjavac, A. Macon,
C. Fraisse, L. Sax, A.K. Huylmans, F. Hontoria, B. Vicoso, Genetics 222 (2022).
date_created: 2023-01-16T09:56:10Z
date_published: 2022-10-01T00:00:00Z
date_updated: 2024-03-25T23:30:26Z
day: '01'
ddc:
- '570'
department:
- _id: BeVi
doi: 10.1093/genetics/iyac123
ec_funded: 1
external_id:
isi:
- '000850270300001'
pmid:
- '35977389'
file:
- access_level: open_access
checksum: f79ff5383e882ea3f95f3da47a78029d
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T08:59:58Z
date_updated: 2023-01-30T08:59:58Z
file_id: '12440'
file_name: 2022_Genetics_Elkrewi.pdf
file_size: 1347136
relation: main_file
success: 1
file_date_updated: 2023-01-30T08:59:58Z
has_accepted_license: '1'
intvolume: ' 222'
isi: 1
issue: '2'
keyword:
- Genetics
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 250BDE62-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715257'
name: Prevalence and Influence of Sexual Antagonism on Genome Evolution
- _id: 34ae1506-11ca-11ed-8bc3-c14f4c474396
grant_number: F8810
name: The highjacking of meiosis for asexual reproduction
publication: Genetics
publication_identifier:
issn:
- 1943-2631
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
related_material:
record:
- id: '11653'
relation: research_data
status: public
scopus_import: '1'
status: public
title: ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine
shrimp
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 222
year: '2022'
...
---
_id: '9168'
abstract:
- lang: eng
text: Interspecific crossing experiments have shown that sex chromosomes play a
major role in reproductive isolation between many pairs of species. However, their
ability to act as reproductive barriers, which hamper interspecific genetic exchange,
has rarely been evaluated quantitatively compared to Autosomes. This genome-wide
limitation of gene flow is essential for understanding the complete separation
of species, and thus speciation. Here, we develop a mainland-island model of secondary
contact between hybridizing species of an XY (or ZW) sexual system. We obtain
theoretical predictions for the frequency of introgressed alleles, and the strength
of the barrier to neutral gene flow for the two types of chromosomes carrying
multiple interspecific barrier loci. Theoretical predictions are obtained for
scenarios where introgressed alleles are rare. We show that the same analytical
expressions apply for sex chromosomes and autosomes, but with different sex-averaged
effective parameters. The specific features of sex chromosomes (hemizygosity and
absence of recombination in the heterogametic sex) lead to reduced levels of introgression
on the X (or Z) compared to autosomes. This effect can be enhanced by certain
types of sex-biased forces, but it remains overall small (except when alleles
causing incompatibilities are recessive). We discuss these predictions in the
light of empirical data comprising model-based tests of introgression and cline
surveys in various biological systems.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "The computations were performed with the IST Austria High-Performance
Computing (HPC) Cluster and the Institut Français de Bioinformatique (IFB) Core
Cluster. We are grateful to Nick Barton and Beatriz Vicoso for critical comments
on the model and the manuscript. We also thank Brian Charlesworth, Stuart Baird,
and an anonymous reviewer for insightful comments.\r\nC.F. was supported by an Austrian
Science Foundation FWF grant (Project M 2463-B29)."
article_number: iyaa025
article_processing_charge: No
article_type: original
author:
- first_name: Christelle
full_name: Fraisse, Christelle
id: 32DF5794-F248-11E8-B48F-1D18A9856A87
last_name: Fraisse
orcid: 0000-0001-8441-5075
- first_name: Himani
full_name: Sachdeva, Himani
id: 42377A0A-F248-11E8-B48F-1D18A9856A87
last_name: Sachdeva
citation:
ama: 'Fraisse C, Sachdeva H. The rates of introgression and barriers to genetic
exchange between hybridizing species: Sex chromosomes vs autosomes. Genetics.
2021;217(2). doi:10.1093/genetics/iyaa025'
apa: 'Fraisse, C., & Sachdeva, H. (2021). The rates of introgression and barriers
to genetic exchange between hybridizing species: Sex chromosomes vs autosomes.
Genetics. Genetics Society of America. https://doi.org/10.1093/genetics/iyaa025'
chicago: 'Fraisse, Christelle, and Himani Sachdeva. “The Rates of Introgression
and Barriers to Genetic Exchange between Hybridizing Species: Sex Chromosomes
vs Autosomes.” Genetics. Genetics Society of America, 2021. https://doi.org/10.1093/genetics/iyaa025.'
ieee: 'C. Fraisse and H. Sachdeva, “The rates of introgression and barriers to genetic
exchange between hybridizing species: Sex chromosomes vs autosomes,” Genetics,
vol. 217, no. 2. Genetics Society of America, 2021.'
ista: 'Fraisse C, Sachdeva H. 2021. The rates of introgression and barriers to genetic
exchange between hybridizing species: Sex chromosomes vs autosomes. Genetics.
217(2), iyaa025.'
mla: 'Fraisse, Christelle, and Himani Sachdeva. “The Rates of Introgression and
Barriers to Genetic Exchange between Hybridizing Species: Sex Chromosomes vs Autosomes.”
Genetics, vol. 217, no. 2, iyaa025, Genetics Society of America, 2021,
doi:10.1093/genetics/iyaa025.'
short: C. Fraisse, H. Sachdeva, Genetics 217 (2021).
date_created: 2021-02-18T14:41:30Z
date_published: 2021-02-01T00:00:00Z
date_updated: 2023-08-07T13:47:01Z
day: '01'
department:
- _id: NiBa
doi: 10.1093/genetics/iyaa025
external_id:
isi:
- '000637218100005'
intvolume: ' 217'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1093/genetics/iyaa025
month: '02'
oa: 1
oa_version: Published Version
project:
- _id: 2662AADE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02463
name: Sex chromosomes and species barriers
publication: Genetics
publication_identifier:
issn:
- 1943-2631
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
status: public
title: 'The rates of introgression and barriers to genetic exchange between hybridizing
species: Sex chromosomes vs autosomes'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 217
year: '2021'
...
---
_id: '7723'
abstract:
- lang: eng
text: Genome-wide association studies (GWAS) have identified thousands of loci that
are robustly associated with complex diseases. The use of linear mixed model (LMM)
methodology for GWAS is becoming more prevalent due to its ability to control
for population structure and cryptic relatedness and to increase power. The odds
ratio (OR) is a common measure of the association of a disease with an exposure
(e.g., a genetic variant) and is readably available from logistic regression.
However, when the LMM is applied to all-or-none traits it provides estimates of
genetic effects on the observed 0–1 scale, a different scale to that in logistic
regression. This limits the comparability of results across studies, for example
in a meta-analysis, and makes the interpretation of the magnitude of an effect
from an LMM GWAS difficult. In this study, we derived transformations from the
genetic effects estimated under the LMM to the OR that only rely on summary statistics.
To test the proposed transformations, we used real genotypes from two large, publicly
available data sets to simulate all-or-none phenotypes for a set of scenarios
that differ in underlying model, disease prevalence, and heritability. Furthermore,
we applied these transformations to GWAS summary statistics for type 2 diabetes
generated from 108,042 individuals in the UK Biobank. In both simulation and real-data
application, we observed very high concordance between the transformed OR from
the LMM and either the simulated truth or estimates from logistic regression.
The transformations derived and validated in this study improve the comparability
of results from prospective and already performed LMM GWAS on complex diseases
by providing a reliable transformation to a common comparative scale for the genetic
effects.
article_processing_charge: No
article_type: original
author:
- first_name: Luke R.
full_name: Lloyd-Jones, Luke R.
last_name: Lloyd-Jones
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
- first_name: Jian
full_name: Yang, Jian
last_name: Yang
- first_name: Peter M.
full_name: Visscher, Peter M.
last_name: Visscher
citation:
ama: Lloyd-Jones LR, Robinson MR, Yang J, Visscher PM. Transformation of summary
statistics from linear mixed model association on all-or-none traits to odds ratio.
Genetics. 2018;208(4):1397-1408. doi:10.1534/genetics.117.300360
apa: Lloyd-Jones, L. R., Robinson, M. R., Yang, J., & Visscher, P. M. (2018).
Transformation of summary statistics from linear mixed model association on all-or-none
traits to odds ratio. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.117.300360
chicago: Lloyd-Jones, Luke R., Matthew Richard Robinson, Jian Yang, and Peter M.
Visscher. “Transformation of Summary Statistics from Linear Mixed Model Association
on All-or-None Traits to Odds Ratio.” Genetics. Genetics Society of America,
2018. https://doi.org/10.1534/genetics.117.300360.
ieee: L. R. Lloyd-Jones, M. R. Robinson, J. Yang, and P. M. Visscher, “Transformation
of summary statistics from linear mixed model association on all-or-none traits
to odds ratio,” Genetics, vol. 208, no. 4. Genetics Society of America,
pp. 1397–1408, 2018.
ista: Lloyd-Jones LR, Robinson MR, Yang J, Visscher PM. 2018. Transformation of
summary statistics from linear mixed model association on all-or-none traits to
odds ratio. Genetics. 208(4), 1397–1408.
mla: Lloyd-Jones, Luke R., et al. “Transformation of Summary Statistics from Linear
Mixed Model Association on All-or-None Traits to Odds Ratio.” Genetics,
vol. 208, no. 4, Genetics Society of America, 2018, pp. 1397–408, doi:10.1534/genetics.117.300360.
short: L.R. Lloyd-Jones, M.R. Robinson, J. Yang, P.M. Visscher, Genetics 208 (2018)
1397–1408.
date_created: 2020-04-30T10:45:19Z
date_published: 2018-04-01T00:00:00Z
date_updated: 2021-01-12T08:15:06Z
day: '01'
doi: 10.1534/genetics.117.300360
extern: '1'
intvolume: ' 208'
issue: '4'
language:
- iso: eng
month: '04'
oa_version: None
page: 1397-1408
publication: Genetics
publication_identifier:
issn:
- 0016-6731
- 1943-2631
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
status: public
title: Transformation of summary statistics from linear mixed model association on
all-or-none traits to odds ratio
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 208
year: '2018'
...
---
_id: '7731'
abstract:
- lang: eng
text: 'Genetic association studies in admixed populations are underrepresented in
the genomics literature, with a key concern for researchers being the adequate
control of spurious associations due to population structure. Linear mixed models
(LMMs) are well suited for genome-wide association studies (GWAS) because they
account for both population stratification and cryptic relatedness and achieve
increased statistical power by jointly modeling all genotyped markers. Additionally,
Bayesian LMMs allow for more flexible assumptions about the underlying distribution
of genetic effects, and can concurrently estimate the proportion of phenotypic
variance explained by genetic markers. Using three recently published Bayesian
LMMs, Bayes R, BSLMM, and BOLT-LMM, we investigate an existing data set on eye
(n = 625) and skin (n = 684) color from Cape Verde, an island nation off West
Africa that is home to individuals with a broad range of phenotypic values for
eye and skin color due to the mix of West African and European ancestry. We use
simulations to demonstrate the utility of Bayesian LMMs for mapping loci and studying
the genetic architecture of quantitative traits in admixed populations. The Bayesian
LMMs provide evidence for two new pigmentation loci: one for eye color (AHRR)
and one for skin color (DDB1).'
article_processing_charge: No
article_type: original
author:
- first_name: Luke R.
full_name: Lloyd-Jones, Luke R.
last_name: Lloyd-Jones
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
- first_name: Gerhard
full_name: Moser, Gerhard
last_name: Moser
- first_name: Jian
full_name: Zeng, Jian
last_name: Zeng
- first_name: Sandra
full_name: Beleza, Sandra
last_name: Beleza
- first_name: Gregory S.
full_name: Barsh, Gregory S.
last_name: Barsh
- first_name: Hua
full_name: Tang, Hua
last_name: Tang
- first_name: Peter M.
full_name: Visscher, Peter M.
last_name: Visscher
citation:
ama: Lloyd-Jones LR, Robinson MR, Moser G, et al. Inference on the genetic basis
of eye and skin color in an admixed population via Bayesian linear mixed models.
Genetics. 2017;206(2):1113-1126. doi:10.1534/genetics.116.193383
apa: Lloyd-Jones, L. R., Robinson, M. R., Moser, G., Zeng, J., Beleza, S., Barsh,
G. S., … Visscher, P. M. (2017). Inference on the genetic basis of eye and skin
color in an admixed population via Bayesian linear mixed models. Genetics.
Genetics Society of America. https://doi.org/10.1534/genetics.116.193383
chicago: Lloyd-Jones, Luke R., Matthew Richard Robinson, Gerhard Moser, Jian Zeng,
Sandra Beleza, Gregory S. Barsh, Hua Tang, and Peter M. Visscher. “Inference on
the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian
Linear Mixed Models.” Genetics. Genetics Society of America, 2017. https://doi.org/10.1534/genetics.116.193383.
ieee: L. R. Lloyd-Jones et al., “Inference on the genetic basis of eye and
skin color in an admixed population via Bayesian linear mixed models,” Genetics,
vol. 206, no. 2. Genetics Society of America, pp. 1113–1126, 2017.
ista: Lloyd-Jones LR, Robinson MR, Moser G, Zeng J, Beleza S, Barsh GS, Tang H,
Visscher PM. 2017. Inference on the genetic basis of eye and skin color in an
admixed population via Bayesian linear mixed models. Genetics. 206(2), 1113–1126.
mla: Lloyd-Jones, Luke R., et al. “Inference on the Genetic Basis of Eye and Skin
Color in an Admixed Population via Bayesian Linear Mixed Models.” Genetics,
vol. 206, no. 2, Genetics Society of America, 2017, pp. 1113–26, doi:10.1534/genetics.116.193383.
short: L.R. Lloyd-Jones, M.R. Robinson, G. Moser, J. Zeng, S. Beleza, G.S. Barsh,
H. Tang, P.M. Visscher, Genetics 206 (2017) 1113–1126.
date_created: 2020-04-30T10:47:50Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2021-01-12T08:15:10Z
day: '01'
doi: 10.1534/genetics.116.193383
extern: '1'
intvolume: ' 206'
issue: '2'
language:
- iso: eng
month: '06'
oa_version: None
page: 1113-1126
publication: Genetics
publication_identifier:
issn:
- 0016-6731
- 1943-2631
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
status: public
title: Inference on the genetic basis of eye and skin color in an admixed population
via Bayesian linear mixed models
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 206
year: '2017'
...
---
_id: '7751'
abstract:
- lang: eng
text: "This work demonstrates that environmental conditions experienced by individuals
can shape their development and affect the stability of genetic associations.
The implication of this observation is that the environmental response may influence
the evolution of traits in the wild. Here, we examined how the genetic architecture
of a suite of sexually dimorphic traits changed as a function of environmental
conditions in an unmanaged population of Soay sheep (Ovis aries) on the island
of Hirta, St. Kilda, northwest Scotland. We examined the stability of phenotypic,
genetic, and environmental (residual) covariance in males during the first year
of life between horn length, body weight, and parasite load in environments of
different quality. We then examined the same covariance structures across environments
within and between the adult sexes. We found significant genotype-by-environment
interactions for lamb male body weight and parasite load, leading to a change
in the genetic correlation among environments. Horn length was genetically correlated
with body weight in males but not females and the genetic correlation among traits
within and between the sexes was dependent upon the environmental conditions experienced
during adulthood. Genetic correlations were smaller in more favorable environmental
conditions, suggesting that in good environments, loci are expressed that have
sex-specific effects. The reduction in genetic correlation between the sexes may
allow independent evolutionary trajectories for each sex. This study demonstrates
that the genetic architecture of traits is not stable under temporally varying
environments and highlights the fact that evolutionary processes may depend largely
upon ecological conditions.\r\nENVIRONMENTAL heterogeneity has long been recognized
as an important factor influencing the evolution of fitness-related traits in
the wild (Roff 2002). The evolution of a trait depends upon the selection upon
it, underlying genetic variation, and to a large degree the genetic relationships
with other traits (Lynch and Walsh 1998). There is evidence that selection can
vary considerably from year to year (Price et al. 1984; Robinson et al. 2008)
and genetic variability in quantitative traits can change in response to environmental
conditions (Hoffmann and Merilä 1999; Charmantier and Garant 2005). However, we
know surprisingly little about the influence of environmental conditions on genetic
correlations between traits in wild populations. Laboratory evidence suggests
that the environment may influence genetic relationships between traits (Sgrò
and Hoffmann 2004), but estimates obtained in a controlled or in an arbitrary
range of conditions show a lack of concordance with those obtained in wild habitats
(Conner et al. 2003). As a result, laboratory and environment-specific estimates
of genetic correlations can make predictions for a trait's evolution, but these
are valid only for the environment in which they were measured. Therefore, at
present, it is difficult to generalize about the evolution of a trait that is
expressed in populations that experience variable environmental conditions (Steppan
et al. 2002).\r\nThe influence of changing environmental conditions on the G matrix
(the matrix of additive genetic variance and covariances corresponding to a set
of traits) has been the focus of theoretical quantitative genetic studies (e.g.,
Jones et al. 2003). There is evidence of genotype-by-environment interaction for
many traits expressed in wild populations (Charmantier and Garant 2005) and thus
we may also expect that associations between traits may depend upon the environmental
conditions encountered by an individual. Genetic correlations among traits may
arise from pleiotropy, where a given locus affects more than one trait (Cheverud
1988; Lynch and Walsh 1998), which may limit the potential for those traits to
evolve independently. There has recently been much interest in assessing genetic
correlations between the sexes (Rice and Chippindale 2001; Foerster et al. 2007;
Poissant et al. 2008), but all of these predictions have also been made in average
environmental conditions. For sexually dimorphic traits, expectations of between-sex
genetic correlations are unclear (Lande 1980; Badyaev 2002). We might expect that
the genetic determination of a trait and the patterns of genetic covariance between
traits may differ both within and between the sexes, producing the differences
in trait growth that are commonly observed (Lande 1980; Badyaev 2002; Roff 2002),
but so far evidence suggests that genetic expression in both sexes is influenced
by the same developmental pathway (Roff 2002; Jensen et al. 2003; Parker and Garant
2005). However, to our knowledge, no study has yet determined whether genetic
correlations, both within and between the sexes, vary across gradients of the
environmental conditions encountered by individuals in the wild (Garant et al.
2008).\r\nThis study aims to assess the stability of phenotypic, genetic, and
environmental (residual) associations between traits, within and between the sexes,
across a range of environmental conditions experienced by a wild population. We
focus on the traits of horn length, body weight, and parasite load in a feral
population of Soay sheep (Ovis aries) from the island of Hirta, St. Kilda, United
Kingdom. Weather conditions, population density, and consequently resource availability
fluctuate from year to year, providing substantial differences between individuals
in the environments they experience and thus their survival rates (Clutton-Brock
and Pemberton 2004). These varying conditions, combined with a large pedigree
and extensive repeated morphological measures, provide an excellent opportunity
to assess the potential effects of environmental heterogeneity on genetic architecture
of traits. Previous studies on this population have shown additive genetic variance
for many morphological traits (Milner et al. 2000; Coltman et al. 2001; Wilson
et al. 2005), genetic correlations between traits (Coltman et al. 2001), and genotype-by-environment
interactions for birth weight (Wilson et al. 2006). Here we apply a random regression
animal model approach to assess the extent to which quantitative genetic parameters
of a range of morphological traits measured during life vary as a function of
environmental conditions. We then extend this methodology to the multivariate
case, testing whether the phenotypic covariance structure, and the underlying
G matrix, depends on the environmental conditions experienced. Since the traits
considered here are known to be sexually dimorphic and there are differences in
trait growth and survival across ages, we look at sex-specific traits in lambs
and then across all ages."
article_processing_charge: No
article_type: original
author:
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
- first_name: Alastair J.
full_name: Wilson, Alastair J.
last_name: Wilson
- first_name: Jill G.
full_name: Pilkington, Jill G.
last_name: Pilkington
- first_name: Tim H.
full_name: Clutton-Brock, Tim H.
last_name: Clutton-Brock
- first_name: Josephine M.
full_name: Pemberton, Josephine M.
last_name: Pemberton
- first_name: Loeske E. B.
full_name: Kruuk, Loeske E. B.
last_name: Kruuk
citation:
ama: Robinson MR, Wilson AJ, Pilkington JG, Clutton-Brock TH, Pemberton JM, Kruuk
LEB. The impact of environmental heterogeneity on genetic architecture in a wild
population of soay sheep. Genetics. 2009;181(4):1639-1648. doi:10.1534/genetics.108.086801
apa: Robinson, M. R., Wilson, A. J., Pilkington, J. G., Clutton-Brock, T. H., Pemberton,
J. M., & Kruuk, L. E. B. (2009). The impact of environmental heterogeneity
on genetic architecture in a wild population of soay sheep. Genetics. Genetics
Society of America. https://doi.org/10.1534/genetics.108.086801
chicago: Robinson, Matthew Richard, Alastair J. Wilson, Jill G. Pilkington, Tim
H. Clutton-Brock, Josephine M. Pemberton, and Loeske E. B. Kruuk. “The Impact
of Environmental Heterogeneity on Genetic Architecture in a Wild Population of
Soay Sheep.” Genetics. Genetics Society of America, 2009. https://doi.org/10.1534/genetics.108.086801.
ieee: M. R. Robinson, A. J. Wilson, J. G. Pilkington, T. H. Clutton-Brock, J. M.
Pemberton, and L. E. B. Kruuk, “The impact of environmental heterogeneity on genetic
architecture in a wild population of soay sheep,” Genetics, vol. 181, no.
4. Genetics Society of America, pp. 1639–1648, 2009.
ista: Robinson MR, Wilson AJ, Pilkington JG, Clutton-Brock TH, Pemberton JM, Kruuk
LEB. 2009. The impact of environmental heterogeneity on genetic architecture in
a wild population of soay sheep. Genetics. 181(4), 1639–1648.
mla: Robinson, Matthew Richard, et al. “The Impact of Environmental Heterogeneity
on Genetic Architecture in a Wild Population of Soay Sheep.” Genetics,
vol. 181, no. 4, Genetics Society of America, 2009, pp. 1639–48, doi:10.1534/genetics.108.086801.
short: M.R. Robinson, A.J. Wilson, J.G. Pilkington, T.H. Clutton-Brock, J.M. Pemberton,
L.E.B. Kruuk, Genetics 181 (2009) 1639–1648.
date_created: 2020-04-30T11:01:57Z
date_published: 2009-04-01T00:00:00Z
date_updated: 2021-01-12T08:15:17Z
day: '01'
doi: 10.1534/genetics.108.086801
extern: '1'
intvolume: ' 181'
issue: '4'
language:
- iso: eng
month: '04'
oa_version: None
page: 1639-1648
publication: Genetics
publication_identifier:
issn:
- 0016-6731
- 1943-2631
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
status: public
title: The impact of environmental heterogeneity on genetic architecture in a wild
population of soay sheep
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 181
year: '2009'
...