Eriko Sasaki

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

DNA cytosine methylation is an epigenetic mark associated with silencing of transposable elements (TEs) and heterochromatin formation. In plants, it occurs in three sequence contexts: CG, CHG, and CHH (where H is A, T, or C). The latter does not allow direct inheritance of methylation during DNA replication due to lack of symmetry, and methylation must therefore be re-established every cell generation. Genome-wide association studies (GWAS) have previously shown that CMT2 and NRPE1 are major det

Genome-wide association studies (GWAS) have revealed that the striking natural variation for DNA CHH-methylation (mCHH; H is A, T, or C) of transposons has oligogenic architecture involving major alleles at a handful of known methylation regulators. Here we use a conditional GWAS approach to show that CHG-methylation (mCHG) has a similar genetic architecture-once mCHH is statistically controlled for. We identify five key trans-regulators that appear to modulate mCHG levels, and show that they in

Intermediate phenotypes such as gene expression values can be used to elucidate the mechanisms by which genetic variation causes phenotypic variation, but jointly analyzing such heterogeneous data are far from trivial. Here we extend a so-called mediation model to handle the confounding effects of genetic background, and use it to analyze flowering time variation in <i>Arabidopsis thaliana</i>, focusing in particular on the central role played by the key regulator <i>FLOWERING TIME LOCUS C</i> (

Classic genome-wide association studies (GWAS) look for associations between individual single-nucleotide polymorphisms (SNPs) and phenotypes of interest. With the rapid progress of high-throughput genotyping and phenotyping technologies, GWAS have become increasingly powerful for detecting genetic determinants and their molecular mechanisms underpinning natural phenotypic variation. However, GWAS frequently yield results with neither expected nor promising loci, nor any significant associations

The comparison of gene expression profiles among DNA microarray experiments enables the identification of unknown relationships among experiments to uncover the underlying biological relationships. Despite the ongoing accumulation of data in public databases, detecting biological correlations among gene expression profiles from multiple laboratories on a large scale remains difficult. Here, we applied a module (sets of genes working in the same biological action)-based correlation analysis in co

Abstract Genome-wide association studies (GWAS) have revealed that the striking natural variation for DNA CHH-methylation (mCHH; H is A, T, or C) of transposons has oligogenic architecture involving major alleles at a handful of known methylation regulators. Here we use a conditional GWAS approach to show that CHG-methylation (mCHG) has a similar genetic architecture — once mCHH is statistically controlled for. We identify five key trans -regulators that appear to modulate mCHG levels, and show

ABSTRACT Flowering time is a key adaptive trait in plants and is tightly controlled by a complex regulatory network that responds to seasonal signals. In a rapidly changing climate, understanding the genetic basis of flowering time variation is important for both agriculture and ecology. Genetic mapping has revealed many genetic variants affecting flowering time, but the effects on the gene regulatory networks in population-scale are still largely unknown. We dissected flowering time networks us

The segmented nature of the rotavirus genome provides an opportunity for the virus to reassort upon co-infection of more than one rotavirus strain. Previously, two G1P[4] strains isolated from children with diarrhoea, AU64, and AU67, were shown by RNA-RNA hybridization to be a VP7 mono-reassortant possessing a DS-1 genogroup background. However, the origin of the parental G2 strain was not sought for at that time. The aim of this study, therefore, was to identify the G2 strain that provided AU64

When we sequence a diploid individual, the output actually comprises two genomes: one from the paternal parent and the other from the maternal parent. In this study, we introduce a novel heuristic algorithm for distinguishing single-nucleotide polymorphisms (SNPs) from the two parents and phasing them into haplotypes. The algorithm is unique because it simultaneously performs SNP calling and haplotype phasing. This approach can exploit the linkage information of nearby SNPs, which facilitates th

Under fluctuating conditions, plants have evolved complex systems for sensing environmental changes to maximize reproductive success. By utilizing seasonal cues, such as day length and temperatures, plants optimize the timing of flowering to adapt to local environments (Andrés & Coupland, 2012; He et al., 2020). This regulatory network involves many pathways with numerous genes (Srikanth & Schmid, 2011; Bouché et al., 2016). In the network, FIONA1 (FIO1), an RNA methyltransferase, has been ident

Abstract Genome-wide association studies (GWAS) have become a standard approach for exploring the genetic basis of phenotypic variation. However, correlation is not causation, and only a tiny fraction of all associations have been experimentally confirmed. One practical problem is that a peak of association does not always pinpoint a causal gene, but may instead be tagging multiple causal variants. In this study, we reanalyze a previously reported peak associated with flowering time traits in Sw