Journal: Nature Communications

Article Title: Natural variation of an E3 ubiquitin ligase encoding gene Chalk9 regulates grain chalkiness in rice

doi: 10.1038/s41467-025-61683-4

Figure Lengend Snippet: a The genome-wide association signals for chalky grain rate (CGR) and degree of chalkiness (DC) in the region at 18–21 Mb on chromosome 9 ( x -axis) across two years. Negative log 10 -transformed P values from the linear mixed model are plotted on the y -axis. The horizontal dashed line indicates the genome-wide significance threshold ( P = 1×10 –6 ). P values were determined using a two-sided Wald test and assessed after Bonferroni correction for multiple comparisons. b Linkage disequilibrium (LD) heatmap of the Chalk9 locus region. Pairwise linkage disequilibrium was determined by calculating r 2 (the square of the correlation coefficient between SNPs). c Relative expression level of the 12 candidate genes in the endosperm of eight high-chalky and eight low-chalky varieties at 20 days after flowering (DAF). The 12 predicted genes in the Chalk9 locus region are labeled by I to XII. Data show means ± SD ( n = 8 varieties). P values were calculated for comparisons between high-chalky and low-chalky groups, with each group comprising 8 varieties. d Relative expression level of the candidate gene III ( Chalk9 ) in the endosperm from the selected varieties at 20 DAF. The P value was calculated for the comparison between high-chalky and low-chalky groups, with each group comprising 8 varieties. Data show means ± SD ( n = 3 biological replicates). e Relative expression level of the 12 candidate genes in the leaves of eight high-chalky and eight low-chalky varieties. Data show means ± SD ( n = 8 varieties). In c – e , statistical analysis between high-chalky and low-chalky groups was performed by two-tailed Student’s t -test. Source data are provided as a Source Data file.

Article Snippet: Correlation analysis, heatmap plotting, and volcano plot analysis were performed using BMKCloud ( www.biocloud.net ).

Techniques: GWAS, Transformation Assay, Genome Wide, Expressing, Labeling, Comparison, Two Tailed Test

Journal: Frontiers in Microbiology

Article Title: Differential Distributions of Synechococcus Subgroups Across the California Current System

doi: 10.3389/fmicb.2011.00059

Figure Lengend Snippet: Multi-dimensional scaling plots of environmental variables and narB subgroup abundances from CN207 samples . Spearman similarity matrices were used to construct the MDS plots. All data used is from the DCM and above, and were log ( x + 1) transformed before any analysis. narB subgroup abundance variables are italicized while environmental variables are not. (A) 3D plot of environmental and abundance variables, with the third dimension being represented by color (Kruskal's stress = 0.08). (B) 2D MDS bubble plot of narB subgroup abundances (dots) and their respective correlation coefficients in relation to nitrate (bubbles; Kruskal's stress = 0.04). A Spearman similarity matrix that contained only subgroup abundance data [same as in 9 (A) ] was used to construct the plot. Bubbles are scaled so that their width equates to the Spearman correlation coefficient value between the abundance of the respective subgroup and nitrate. All correlation coefficient values were significant ( p < 0.05) except for subgroups A_C1 and F_C1 (small bubbles). Colored bubbles represent positive coefficients and grayscale bubbles are for negative values. The width of the largest bubble (C_C1) equates to 0.68, while the smallest bubbles equate to ∼0.18.

Article Snippet: Spearman correlation matrices and MDS plots were generated in XLSTAT (Addinsoft; New York, NY, USA).

Techniques: Construct, Transformation Assay