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"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana.

Sasaki E, Zhang P, Atwell S, Meng D, Nordborg M - PLoS Genet. (2015)

Bottom Line: The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both.Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%).Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

View Article: PubMed Central - PubMed

Affiliation: Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria.

ABSTRACT
Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

No MeSH data available.


Genome-wide G and G x E effects for SNPs and well as local variance components.Dotted lines correspond to significance cut-offs of p-value = 10−5 for SNP associations (in blue) and log-likelihood ratios = 5 for variance components (in black).
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pgen.1005597.g005: Genome-wide G and G x E effects for SNPs and well as local variance components.Dotted lines correspond to significance cut-offs of p-value = 10−5 for SNP associations (in blue) and log-likelihood ratios = 5 for variance components (in black).

Mentions: Fig 5 shows the distribution of common (i.e., G) and G x E signals across the genome, for SNPs as well as for local variance components. The three highest peaks of Glocal (S5 Table) overlap peaks of common GSNP effect centered around FIO1 on chromosome 2, and FLC on chromosome 5, and position 23,544,472 on chromosome 5. This overlap suggests that a small number of SNPs identified by MTMM might be responsible for the local variance components. Although there are no obvious flowering time candidates in the final region on chromosome 5, a recent study reported that gene in the region, MULTICOPY SUPRESSOR OF IRA 1 (MSI; AT5G58230) delays the transition to flowering [31]. The most significant peak of Glocal x E only was found at the top of chromosome 1 (963,400-1,053,719) and includes eight genes, none of which are known to be involved in flowering.


"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana.

Sasaki E, Zhang P, Atwell S, Meng D, Nordborg M - PLoS Genet. (2015)

Genome-wide G and G x E effects for SNPs and well as local variance components.Dotted lines correspond to significance cut-offs of p-value = 10−5 for SNP associations (in blue) and log-likelihood ratios = 5 for variance components (in black).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4608753&req=5

pgen.1005597.g005: Genome-wide G and G x E effects for SNPs and well as local variance components.Dotted lines correspond to significance cut-offs of p-value = 10−5 for SNP associations (in blue) and log-likelihood ratios = 5 for variance components (in black).
Mentions: Fig 5 shows the distribution of common (i.e., G) and G x E signals across the genome, for SNPs as well as for local variance components. The three highest peaks of Glocal (S5 Table) overlap peaks of common GSNP effect centered around FIO1 on chromosome 2, and FLC on chromosome 5, and position 23,544,472 on chromosome 5. This overlap suggests that a small number of SNPs identified by MTMM might be responsible for the local variance components. Although there are no obvious flowering time candidates in the final region on chromosome 5, a recent study reported that gene in the region, MULTICOPY SUPRESSOR OF IRA 1 (MSI; AT5G58230) delays the transition to flowering [31]. The most significant peak of Glocal x E only was found at the top of chromosome 1 (963,400-1,053,719) and includes eight genes, none of which are known to be involved in flowering.

Bottom Line: The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both.Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%).Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

View Article: PubMed Central - PubMed

Affiliation: Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria.

ABSTRACT
Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

No MeSH data available.