Additive QTLs on three chromosomes control flowering time in woodland strawberry (Fragaria vesca L.)

Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.

Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.

Plants use day-length information to coordinate flowering time with the appropriate season to maximize reproduction. In Arabidopsis, the long day-specific expression of CONSTANS (CO) protein is crucial for flowering induction. Although light signaling regulates CO protein stability, the mechanism by which CO is stabilized in the long-day afternoon has remained elusive. Here, we demonstrate that FLAVIN-BINDING, KELCH REPEAT, F-BOX 1 (FKF1) protein stabilizes CO protein in the afternoon in long days. FKF1 interacts with CO through its LOV domain, and blue light enhances this interaction. In addition, FKF1 simultaneously removes CYCLING DOF FACTOR 1 (CDF1), which represses CO and FLOWERING LOCUS T (FT) transcription. Together with CO transcriptional regulation, FKF1 protein controls robust FT mRNA induction through multiple feedforward mechanisms that accurately control flowering timing.