10.5061/DRYAD.P5HQBZKMC
Pais, Andrew
0000-0001-6535-0990
North Carolina State University
Whetten, Ross
North Carolina State University
Xiang, Qiu-Yun (Jenny)
North Carolina State University
Population structure, landscape genomics, and genetic signatures of
adaptation to exotic disease pressure in Cornus florida L. – insights from
GWAS and GBS data
Dryad
dataset
2020
Cornus florida
flowering dogwood
genotype-by-sequencing
landscape ecological-evolutionary genomics
2020-04-28T00:00:00Z
2020-04-28T00:00:00Z
en
31205995 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Understanding the consequences of exotic diseases on native forests is
important to evolutionary ecology and conservation biology because exotic
pathogens have drastically altered US eastern deciduous forests. Cornus
florida L. (flowering dogwood tree) is one such species facing heavy
mortality. Characterizing the genetic structure of C. florida populations
and identifying the genetic signature of adaptation to dogwood anthracnose
(an exotic pathogen responsible for high mortality) remains vital for
conservation efforts. By integrating genetic data from
genotype-by-sequencing (GBS) of 289 trees across the host species range
and distribution of disease, we evaluated the spatial patterns of genetic
variation and population genetic structure of C. florida and compared the
pattern to the distribution of dogwood anthracnose. Using GWAS and
gradient forest analysis, we identified genetic loci under selection and
associated with ecological and diseased regions. The results revealed
signals of weak genetic differentiation of three or more subgroups nested
within two clusters—explaining up to 2-6% of genetic variation. The groups
largely corresponded to the regions within and outside the eastern
Hot-Continental ecoregion, which also overlapped with areas within and
outside the main distribution of dogwood anthracnose. The fungal sequences
contained in the GBS data of sampled trees bolstered visual records of
disease at sampled locations and were congruent with the reported range of
D. destructiva, suggesting fungal sequences within host genomic data were
informative for detecting or predicting disease. The genetic diversity
between populations at diseased vs. disease-free sites across the range of
C. florida showed no significant difference. We identified 72 SNPs from 68
loci putatively under selection, some of which exhibited abrupt turnover
in allele frequencies along the borders of the Hot-Continental ecoregion
and the range of dogwood anthracnose. One such candidate SNP was
independently identified in two prior studies as a possible L-type
lectin-domain containing receptor kinase. While diseased and disease-free
areas do not significantly differ in genetic diversity, overall there are
slight trends to indicate marginally smaller amounts of genetic diversity
in disease-affected areas. Our results were congruent with previous
studies that were based on a limited number of genetic markers in
revealing high genetic variation and weak population structure in C.
florida.
Population genetic datasets and sequences of GBS-tags per sample were
exported as Fasta, Genepop, and PLINK files after processing GBS data via
STACKS (version 1.35).
Various population genetic programs can process, analyze, or convert
Genepop (.gen) or PLINK (.ped and .map) file formats, and sequences in
Fasta (.fa) file may be searched against existing databases to
find similar sequences and functional annotations. For aligning GBS-tags
back to draft genomes of Cornus florida, Erysiphe pulchra, and Discula
destructiva please contact original owners for latest version of draft
genomes (see acknowledgement section of Pais et al. 2020).