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![40th
New Phytologist Symposium, Vienna, Austria, 12-15 September 2017 Alexander-Jueterbock@web.de
Poster PDF
Epigenetic variation in seagrass clones
Jueterbock A1
, Bostr¨om C2
, Reusch TBH3
, Olsen JL4
, Kopp M1
, Dhanasiri A1
, Smolina I1
, Arnaud-Haond S5
, Hoarau G1
1 Marine Molecular Ecology Group, Faculty of Biosciences and Aquaculture, Nord University, Universitetsalleen 11, 8026 Bodø, Norway
2 Department of Biosciences, Environmental and Marine Biology, ˚Abo Akademi University, Artillerigatan 6 FI-20520 ˚Abo, Finland
3 GEOMAR Helmholtz-Centre for Ocean Research Kiel, Evolutionary Ecology of Marine Fishes, D¨usternbrooker Weg 20, D-24105 Kiel, Germany
4 Ecological Genetics-Genomics Group, Groningen Institute of Evolutionary Life Sciences, University of Groningen, 9747 AG Groningen, The Netherlands
5 Ifremer, Station de S`ete, Avenue Jean Monnet, CS 30171, 34203 S`ete Cedex, France
BACKGROUND
Evolutionary theory predicts that low genetic variation reduces a population’s ability to
cope with environmental variability and to adapt to changing environments. However,
the evolutionary success of big old clones of the seagrass Zostera marina challenges
the direct relationship between genetic diversity and adaptation potential. We aim to
test the hypothesis that epigenetic variation, a hitherto overlooked layer of evolution-
ary relevant variation, is the key to this paradox. Our main objective is to describe the
spatial pattern of epigenetic variation in a 1000-year old seagrass clone [5].
METHODS
In 2015, we sampled 100 shoots from a single meadow from the ˚Aland Islands, north-
ern Baltic Sea. This meadow has been previously shown to be mostly clonal [5].
Shoots were sampled every 3 meters along a transect of 250 meters (Figure 1).
Figure 1: Sampling site.
We screened 34 shoots along the entire transect for seven microsatellite loci (Zos-
marGA2, -GA3, -GA6, -CT3, -CT12, -CT19, -CT20) following [6]) and used the
R package ’RClone’ [1] in order to determine which shoots belong to the same
clone. We screened for variation of cytosine methylation between the shoots us-
ing MethylRAD sequencing [7]. MethylRAD is a genome-reduction method based on
a methylation-dependant restriction enzyme that targets CCGG and CCWGG motifs
(Figure 2).
Figure 2: Schematic overview of MethylRAD library preparation.
MethylRAD tags (digested fragments) were sequenced with Illumina NextSeq
(1x75bp), and mapped with SOAP [3] to 628,255 in silico predicted MethylRAD tags.
For each individual, raw counts were normalized to reads-per-million by dividing reads
per tag through the total number of reads per sample library, times one million. The
shoots were hierarchically clustered based on results from principle component anal-
ysis with the R package ’FactoMineR’ [2]. The first two principle components, which
together eplained 79% of the variation in the data, were used to calculate euclidean
epigenetic distances between shoots. Single Nucleotide Polymorphisms (SNPs) in
the MethylRAD tags were called with GATK [4].
REFERENCES
[1] Bailleul D, Stoeckel S, Arnaud-Haond S (2016) RClone: a package to identify MultiLocus Clonal Lineages and handle clonal data sets in R.
Methods in Ecology and Evolution 7(8):966-70.
[2] Le S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. Journal of statistical software. 25(1):1-8.
[3] Li R, Li Y, Kristiansen K, Wang J (2008) SOAP: short oligonucleotide alignment program. Bioinformatics. 24(5):713-4.
[4] McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The
Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research 20(9):1297-303.
[5] Reusch TBH, Bostr¨om C, Stam WT, Olsen JL (1999). An ancient eelgrass clone in the Baltic. Marine Ecology Progress Series. 183:301-304.
[6] Reusch TBH, Bostr¨om C. Widespread genetic mosaicism in the marine angiosperm Zostera marina is correlated with clonal reproduction.
Evolutionary Ecology. 25(4):899-913.
[7] Wang S, Lv J, Zhang L, Dou J, Sun Y, Li X, Fu X, Dou H, Mao J, Hu X, Bao Z (2015) MethylRAD: a simple and scalable method for
genome-wide DNA methylation profiling using methylation-dependent restriction enzymes. Open biology. 5(11):150130
RESULTS
All 34 shoots were assigned to the same seven-locus genotype, meaning that they
all belong to the same clone. On average, 30% of the mapped reads (1-6 Million
per individual) mapped uniquely to ca. one third of the 628,255 in-silico predicted
MethylRAD tags. Sufficient sequencing depth was suggested by maximum coverage
values between 155 and 59,359. About 77-78% of the uniquely mapped MethylRAD-
tags fell in intergenic regions, 21-23% in gene regions, and 41% were located in
transposable elements, without much variation between shoots. Epigenetic variation
was independent from shore-distance (Figure 3).
Figure 3: Hierarchical cluster with three main clusters of 34 transect-samples based on the first two
principle components of normalized MethylRAD-tag counts. Tag-wise normalized counts
(z-scores) are shown for 42,941 tags that contributed significantly to between-shoot variation
along the first two principle components. Distance from the shore is color-coded (blue: 9 meters to
red: 236 meters) in the upper color-bar.
Epigenetic and geographic distances between shoots were uncorrelated (p-value =
0.73, Figure 4).
Figure 4: Relation between epigenetic and geographic distance between shoots.
DISCUSSION
Assignment of all samples to the same seven-locus microsatellite genotype confirms
that most of the shoots in this meadow belong to the same clone [5]. Total absence
of SNPs suggests low levels of somatic mutations.
This study shows for the first time that seagrass shoots differ epigenetically, while
being genetically identical. While we could not yet determine factors explaining
this epigenetic variation, we expect that it partly compensates the lack of genetic
variation by creating evolutionary relevant trait variation. We are currently analyzing
data from a heat-stress experiment that will allow to relate differences in heat-stress
performance with epigenetic differences as a first step to demonstrate the relevance
of epigenetic variation under ocean warming.
This work is a first step to uncover whether epigenetic variation may compensate
for the absence of genetic variation by increasing plastic and adaptive potential in
seagrass clones.](https://image.slidesharecdn.com/2017plantepigenetics-170906105123/85/Epigenetic-variation-in-seagrass-clones-1-320.jpg)
![40th
New Phytologist Symposium, Vienna, Austria, 12-15 September 2017 Alexander-Jueterbock@web.de
Poster PDF
Epigenetic variation in seagrass clones
Jueterbock A1
, Bostr¨om C2
, Reusch TBH3
, Olsen JL4
, Kopp M1
, Dhanasiri A1
, Smolina I1
, Arnaud-Haond S5
, Hoarau G1
1 Marine Molecular Ecology Group, Faculty of Biosciences and Aquaculture, Nord University, Universitetsalleen 11, 8026 Bodø, Norway
2 Department of Biosciences, Environmental and Marine Biology, ˚Abo Akademi University, Artillerigatan 6 FI-20520 ˚Abo, Finland
3 GEOMAR Helmholtz-Centre for Ocean Research Kiel, Evolutionary Ecology of Marine Fishes, D¨usternbrooker Weg 20, D-24105 Kiel, Germany
4 Ecological Genetics-Genomics Group, Groningen Institute of Evolutionary Life Sciences, University of Groningen, 9747 AG Groningen, The Netherlands
5 Ifremer, Station de S`ete, Avenue Jean Monnet, CS 30171, 34203 S`ete Cedex, France
BACKGROUND
Evolutionary theory predicts that low genetic variation reduces a population’s ability to
cope with environmental variability and to adapt to changing environments. However,
the evolutionary success of big old clones of the seagrass Zostera marina challenges
the direct relationship between genetic diversity and adaptation potential. We aim to
test the hypothesis that epigenetic variation, a hitherto overlooked layer of evolution-
ary relevant variation, is the key to this paradox. Our main objective is to describe the
spatial pattern of epigenetic variation in a 1000-year old seagrass clone [5].
METHODS
In 2015, we sampled 100 shoots from a single meadow from the ˚Aland Islands, north-
ern Baltic Sea. This meadow has been previously shown to be mostly clonal [5].
Shoots were sampled every 3 meters along a transect of 250 meters (Figure 1).
Figure 1: Sampling site.
We screened 34 shoots along the entire transect for seven microsatellite loci (Zos-
marGA2, -GA3, -GA6, -CT3, -CT12, -CT19, -CT20) following [6]) and used the
R package ’RClone’ [1] in order to determine which shoots belong to the same
clone. We screened for variation of cytosine methylation between the shoots us-
ing MethylRAD sequencing [7]. MethylRAD is a genome-reduction method based on
a methylation-dependant restriction enzyme that targets CCGG and CCWGG motifs
(Figure 2).
Figure 2: Schematic overview of MethylRAD library preparation.
MethylRAD tags (digested fragments) were sequenced with Illumina NextSeq
(1x75bp), and mapped with SOAP [3] to 628,255 in silico predicted MethylRAD tags.
For each individual, raw counts were normalized to reads-per-million by dividing reads
per tag through the total number of reads per sample library, times one million. The
shoots were hierarchically clustered based on results from principle component anal-
ysis with the R package ’FactoMineR’ [2]. The first two principle components, which
together eplained 79% of the variation in the data, were used to calculate euclidean
epigenetic distances between shoots. Single Nucleotide Polymorphisms (SNPs) in
the MethylRAD tags were called with GATK [4].
REFERENCES
[1] Bailleul D, Stoeckel S, Arnaud-Haond S (2016) RClone: a package to identify MultiLocus Clonal Lineages and handle clonal data sets in R.
Methods in Ecology and Evolution 7(8):966-70.
[2] Le S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. Journal of statistical software. 25(1):1-8.
[3] Li R, Li Y, Kristiansen K, Wang J (2008) SOAP: short oligonucleotide alignment program. Bioinformatics. 24(5):713-4.
[4] McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The
Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research 20(9):1297-303.
[5] Reusch TBH, Bostr¨om C, Stam WT, Olsen JL (1999). An ancient eelgrass clone in the Baltic. Marine Ecology Progress Series. 183:301-304.
[6] Reusch TBH, Bostr¨om C. Widespread genetic mosaicism in the marine angiosperm Zostera marina is correlated with clonal reproduction.
Evolutionary Ecology. 25(4):899-913.
[7] Wang S, Lv J, Zhang L, Dou J, Sun Y, Li X, Fu X, Dou H, Mao J, Hu X, Bao Z (2015) MethylRAD: a simple and scalable method for
genome-wide DNA methylation profiling using methylation-dependent restriction enzymes. Open biology. 5(11):150130
RESULTS
All 34 shoots were assigned to the same seven-locus genotype, meaning that they
all belong to the same clone. On average, 30% of the mapped reads (1-6 Million
per individual) mapped uniquely to ca. one third of the 628,255 in-silico predicted
MethylRAD tags. Sufficient sequencing depth was suggested by maximum coverage
values between 155 and 59,359. About 77-78% of the uniquely mapped MethylRAD-
tags fell in intergenic regions, 21-23% in gene regions, and 41% were located in
transposable elements, without much variation between shoots. Epigenetic variation
was independent from shore-distance (Figure 3).
Figure 3: Hierarchical cluster with three main clusters of 34 transect-samples based on the first two
principle components of normalized MethylRAD-tag counts. Tag-wise normalized counts
(z-scores) are shown for 42,941 tags that contributed significantly to between-shoot variation
along the first two principle components. Distance from the shore is color-coded (blue: 9 meters to
red: 236 meters) in the upper color-bar.
Epigenetic and geographic distances between shoots were uncorrelated (p-value =
0.73, Figure 4).
Figure 4: Relation between epigenetic and geographic distance between shoots.
DISCUSSION
Assignment of all samples to the same seven-locus microsatellite genotype confirms
that most of the shoots in this meadow belong to the same clone [5]. Total absence
of SNPs suggests low levels of somatic mutations.
This study shows for the first time that seagrass shoots differ epigenetically, while
being genetically identical. While we could not yet determine factors explaining
this epigenetic variation, we expect that it partly compensates the lack of genetic
variation by creating evolutionary relevant trait variation. We are currently analyzing
data from a heat-stress experiment that will allow to relate differences in heat-stress
performance with epigenetic differences as a first step to demonstrate the relevance
of epigenetic variation under ocean warming.
This work is a first step to uncover whether epigenetic variation may compensate
for the absence of genetic variation by increasing plastic and adaptive potential in
seagrass clones.](https://image.slidesharecdn.com/2017plantepigenetics-170906105123/75/Epigenetic-variation-in-seagrass-clones-1-2048.jpg)
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Epigenetic variation in seagrass clones
- 1. 40th New Phytologist Symposium,Vienna, Austria, 12-15 September 2017 Alexander-Jueterbock@web.de Poster PDF Epigenetic variation in seagrass clones Jueterbock A1 , Bostr¨om C2 , Reusch TBH3 , Olsen JL4 , Kopp M1 , Dhanasiri A1 , Smolina I1 , Arnaud-Haond S5 , Hoarau G1 1 Marine Molecular Ecology Group, Faculty of Biosciences and Aquaculture, Nord University, Universitetsalleen 11, 8026 Bodø, Norway 2 Department of Biosciences, Environmental and Marine Biology, ˚Abo Akademi University, Artillerigatan 6 FI-20520 ˚Abo, Finland 3 GEOMAR Helmholtz-Centre for Ocean Research Kiel, Evolutionary Ecology of Marine Fishes, D¨usternbrooker Weg 20, D-24105 Kiel, Germany 4 Ecological Genetics-Genomics Group, Groningen Institute of Evolutionary Life Sciences, University of Groningen, 9747 AG Groningen, The Netherlands 5 Ifremer, Station de S`ete, Avenue Jean Monnet, CS 30171, 34203 S`ete Cedex, France BACKGROUND Evolutionary theory predicts that low genetic variation reduces a population’s ability to cope with environmental variability and to adapt to changing environments. However, the evolutionary success of big old clones of the seagrass Zostera marina challenges the direct relationship between genetic diversity and adaptation potential. We aim to test the hypothesis that epigenetic variation, a hitherto overlooked layer of evolution- ary relevant variation, is the key to this paradox. Our main objective is to describe the spatial pattern of epigenetic variation in a 1000-year old seagrass clone [5]. METHODS In 2015, we sampled 100 shoots from a single meadow from the ˚Aland Islands, north- ern Baltic Sea. This meadow has been previously shown to be mostly clonal [5]. Shoots were sampled every 3 meters along a transect of 250 meters (Figure 1). Figure 1: Sampling site. We screened 34 shoots along the entire transect for seven microsatellite loci (Zos- marGA2, -GA3, -GA6, -CT3, -CT12, -CT19, -CT20) following [6]) and used the R package ’RClone’ [1] in order to determine which shoots belong to the same clone. We screened for variation of cytosine methylation between the shoots us- ing MethylRAD sequencing [7]. MethylRAD is a genome-reduction method based on a methylation-dependant restriction enzyme that targets CCGG and CCWGG motifs (Figure 2). Figure 2: Schematic overview of MethylRAD library preparation. MethylRAD tags (digested fragments) were sequenced with Illumina NextSeq (1x75bp), and mapped with SOAP [3] to 628,255 in silico predicted MethylRAD tags. For each individual, raw counts were normalized to reads-per-million by dividing reads per tag through the total number of reads per sample library, times one million. The shoots were hierarchically clustered based on results from principle component anal- ysis with the R package ’FactoMineR’ [2]. The first two principle components, which together eplained 79% of the variation in the data, were used to calculate euclidean epigenetic distances between shoots. Single Nucleotide Polymorphisms (SNPs) in the MethylRAD tags were called with GATK [4]. REFERENCES [1] Bailleul D, Stoeckel S, Arnaud-Haond S (2016) RClone: a package to identify MultiLocus Clonal Lineages and handle clonal data sets in R. Methods in Ecology and Evolution 7(8):966-70. [2] Le S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. Journal of statistical software. 25(1):1-8. [3] Li R, Li Y, Kristiansen K, Wang J (2008) SOAP: short oligonucleotide alignment program. Bioinformatics. 24(5):713-4. [4] McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research 20(9):1297-303. [5] Reusch TBH, Bostr¨om C, Stam WT, Olsen JL (1999). An ancient eelgrass clone in the Baltic. Marine Ecology Progress Series. 183:301-304. [6] Reusch TBH, Bostr¨om C. Widespread genetic mosaicism in the marine angiosperm Zostera marina is correlated with clonal reproduction. Evolutionary Ecology. 25(4):899-913. [7] Wang S, Lv J, Zhang L, Dou J, Sun Y, Li X, Fu X, Dou H, Mao J, Hu X, Bao Z (2015) MethylRAD: a simple and scalable method for genome-wide DNA methylation profiling using methylation-dependent restriction enzymes. Open biology. 5(11):150130 RESULTS All 34 shoots were assigned to the same seven-locus genotype, meaning that they all belong to the same clone. On average, 30% of the mapped reads (1-6 Million per individual) mapped uniquely to ca. one third of the 628,255 in-silico predicted MethylRAD tags. Sufficient sequencing depth was suggested by maximum coverage values between 155 and 59,359. About 77-78% of the uniquely mapped MethylRAD- tags fell in intergenic regions, 21-23% in gene regions, and 41% were located in transposable elements, without much variation between shoots. Epigenetic variation was independent from shore-distance (Figure 3). Figure 3: Hierarchical cluster with three main clusters of 34 transect-samples based on the first two principle components of normalized MethylRAD-tag counts. Tag-wise normalized counts (z-scores) are shown for 42,941 tags that contributed significantly to between-shoot variation along the first two principle components. Distance from the shore is color-coded (blue: 9 meters to red: 236 meters) in the upper color-bar. Epigenetic and geographic distances between shoots were uncorrelated (p-value = 0.73, Figure 4). Figure 4: Relation between epigenetic and geographic distance between shoots. DISCUSSION Assignment of all samples to the same seven-locus microsatellite genotype confirms that most of the shoots in this meadow belong to the same clone [5]. Total absence of SNPs suggests low levels of somatic mutations. This study shows for the first time that seagrass shoots differ epigenetically, while being genetically identical. While we could not yet determine factors explaining this epigenetic variation, we expect that it partly compensates the lack of genetic variation by creating evolutionary relevant trait variation. We are currently analyzing data from a heat-stress experiment that will allow to relate differences in heat-stress performance with epigenetic differences as a first step to demonstrate the relevance of epigenetic variation under ocean warming. This work is a first step to uncover whether epigenetic variation may compensate for the absence of genetic variation by increasing plastic and adaptive potential in seagrass clones.