To examine the correlation between FLM-ß expression and flowering time, we determined flowering time of accessions at 15°C. To avoid strong interference from the vernalization pathway, we selected 27 genetically diverse summer-annual accessions, which initiate flowering without the need of vernalization (Figure 8—figure supplement 2A, Supplementary file 6B). We measured FLM-ß transcript levels and flowering time at 15°C. As residual FLC transcript in these summer-annual accessions may still affect flowering time, we also determined FLC transcript levels (Coustham et al., 2012; Li et al., 2014; Duncan et al., 2015). Using a multiple linear regression approach, we found that FLM-ß and FLC explained 32.9% (R2 = 0.329, p=0.0083) of flowering time variation, with FLM-ß significantly explaining a subfraction of 21.0% (R2 = 0.210, p=0.011) and FLC only 11.9%, however not significantly (R2 = 0.119, p>0.05) (Figure 8B and Figure 8—figure supplement 2B). Further, by integration of expression data and flowering time data into a multiple linear model and comparison of the slopes, we found that flowering time responded stronger to FLM-ß levels in the accessions than in the transgenic variants (p=0.0321) (Figure 5B and Figure 8). Taken together, we concluded that variations in FLM-ß levels account for flowering time in cool ambient spring temperatures in a diverse population of summer-annual Arabidopsis accessions (Figure 9).10.7554/eLife.22114.021Figure 8.FLM-ß expression shows high correlation with flowering time in Arabidopsis accessions.(A) Correlation (simple linear regression) of FLM-ß transcript levels detected in transgenic plants and natural accessions with identical PRO2+ and INT6+ haplotypes. When the contribution of individual haplotypes was assessed, PRO2+AAAAC INT6+CAA showed an exceptional response in accessions and was excluded. Figure 8—figure supplement 1E shows the complete analysis. Horizontal and vertical error bars depict SD of four replicate transgenic line pools or SD of the accessions. Data of the transgenic lines was taken from Figure 4E. The grey area indicates the 95% confidence interval. (B) Correlation of FLM-ß transcript levels with flowering time (n = 8–10) as measured in rosette leaf number of summer-annual accessions. p=0.011.DOI: http://dx.doi.org/10.7554/eLife.22114.02110.7554/eLife.22114.022Figure 8—figure supplement 1.Geographic and genetic distribution of the PRO2+/INT6+ haplotypes among 840 accessions.(A) Pie chart with the relative distribution of the PRO2+/INT6+ haplotypes among 840 accessions. The Col-0 haplotype is marked in yellow, haplotypes analyzed as part of this study are marked in green. Haplotypes only represented by a single accession are not included. (B) Number of accessions selected from each of the nine PRO2+/INT6+ groups (average 10, in total 94 accessions). The color code indicates the genetic group membership (k = 9) of every accession as retrieved from the 1001 Genomes ADMIXTURE tool (http://tools.1001genomes.org/) (The 1001 Genomes Consortium, 2016). (C) Geographic distribution of the accessions shown in (B). (D) FLM-β transcript levels of accessions shown in (B) and (C) grouped by the PRO2+/INT6+ haplotype. Similar letters indicate no significant difference of total leaf number (Tukey HSD, p<0.05). (E) Correlation (simple linear regression) between FLM-ß transcript levels as detected in the transgenic analysis and in accessions with identical PRO2+/INT6+ haplotypes from plants grown at 15°C. The PRO2+AAAAC INT6+CAA haplotype, which was removed in Figure 8A, is shown and highlighted with a red arrow. Circle sizes represent the number of accessions analysed of each group as specified in the legend. Horizontal and vertical error bars depict SD of four replicate transgenic line pools or SD of the accessions of each group. Data for the transgenic line analysis were taken from Figure 4E. The grey area indicates the 95% confidence interval.DOI: http://dx.doi.org/10.7554/eLife.22114.02210.7554/eLife.22114.023Figure 8—figure supplement 2.Geographic distribution of summer-annual accessions.(A) Geographic distribution of the 27 summer-annual accessions as described in Figure 8B. (B) Correlation of FLC transcript levels with flowering time data (n = 8–10) as measured in rosette leaf number of summer-annual accessions. p>0.05.DOI: http://dx.doi.org/10.7554/eLife.22114.02310.7554/eLife.22114.024Figure 9.Model of the proposed role of PRO2+ and INT6+ haplotypes and temperature on FLM-ß abundance and flowering.The abundance of the flowering repressor FLM-ß decreases in response to higher temperature and flowering is consequently accelerated (Figures 1B and 4E) (Lee et al., 2013; Posé et al., 2013; Lutz et al., 2015). Note, that previous studies showed an especially prominent effect of FLM in a range from 9°C to 21°C (long-day photoperiod) (Lee et al., 2013; Posé et al., 2013; Lutz et al., 2015). At the genetic level, FLM-ß abundance is triggered by the PRO2+ (purple) and/or the INT6+ (pink) haplotype and flowering time correlated to FLM-ß abundance (Figure 4E). Among the PRO2+/INT6+ combinations tested, the Col-0 (grey) reference allele (PRO2+AAAAC/INT6+AAT) showed intermediate FLM-ß levels (Figure 4E). We suggest, that changes in flowering time due to changing ambient temperature can be precisely buffered by modifying the PRO2+ and INT6+ regions, as illustrated by similar plant symbols.DOI: http://dx.doi.org/10.7554/eLife.22114.024