Table 2.

Multiple regression analysis showing that drought responses of four amino acids fully explain the genotypic variances in YDT

Models	R 2	P(R2)	Metabolites	r	P(r)
YDT~lnFCSerine+lnFCAsparagine+lnFCMethionine+lnFCGalactose	0.99	3.5E-03	l-Serine	–0.27	1.2E-02
			l-Asparagine	–0.05	7.4E-03
			l-Methionine	0.09	4.2E-02
			d-Galactose	0.02	4.2E-02
YDT~lnFCSerine+lnFCAsparagine+lnFCMethionine	0.94	6.9E-03	l-Serine	–0.34	1.5E-02
			l-Asparagine	–0.06	7.5E-03
			l-Methionine	0.12	5.8E-02
YDT~lnFCSerine+lnFCAsparagine+lnFCGlutamine+lnFCLysine	0.98	9.0E-03	l-Serine	–0.28	6.6E-03
			l-Asparagine	–0.09	1.1E-02
			l-Glutamine	0.05	9.5E-02
			l-Lysine	0.11	2.4E-02
YDT~lnFCSerine+lnFCAsparagine+lnFCLysine+lnFCMethionine	0.98	9.0E-03	l-Serine	–0.34	1.1E-02
			l-Asparagine	–0.07	5.7E-03
			l-Lysine	0.05	1.2E-01
			l-Methionine	0.08	9.5E-02

Multiple regression analysis was performed using the lm function in R with the models indicated. The linear and multiple correlation coefficients are indicated as r and R², whereas their significance values at are indicated as P(r) and P(R²), respectively. lnFC represents the natural log-transformed fold changes of the respective amino acids (as subscripts) in drought-treated over control plants. r=the fitted linear effect coefficient in multiple regression; P(r)=the P-value associated with the fitted coefficient; n=8 for all the analysis.