This study discusses the genetic mutations that have a significant association with economically important traits that would benefit tea breeders. The purpose of this study was to analyze the leaf quality and SNPs in quality-related genes in the tea plant collection of 20 mutant genotypes growing without nitrogen fertilizers. Leaf N-content, catechins, L-theanine, and caffeine contents were analyzed in dry leaves via HPLC. Additionally, the photochemical yield, electron transport efficiency, and non-photochemical quenching were analyzed using PAM-fluorimetry. The next generation pooled amplicon–sequencing approach was used for SNPs-calling in 30 key genes related to N metabolism and leaf quality. The leaf N content varied significantly among genotypes (p ≤ 0.05) from 2.3 to 3.7% of dry mass. The caffeine content varied from 0.7 to 11.7 mg g⁻¹, and the L-theanine content varied from 0.2 to 5.8 mg g⁻¹ dry leaf mass. Significant positive correlations were detected between the nitrogen content and biochemical parameters such as theanine, caffeine, and most of the catechins. However, significant negative correlations were observed between the photosynthetic parameters (Y, ETR, Fv/Fm) and several biochemical compounds, including rutin, Quercetin-3-O-glucoside, Kaempferol-3-O-rutinoside, Kaempferol-3-O-glucoside, Theaflavin-3′-gallate, gallic acid. From our SNP-analysis, three SNPs in WRKY57 were detected in all genotypes with a low N content. Moreover, 29 SNPs with a high or moderate effect were specific for #316 (high N-content, high quality) or #507 (low N-content, low quality). The use of a linear regression model revealed 16 significant associations; theaflavin, L-theanine, and ECG were associated with several SNPs of the following genes: ANSa, DFRa, GDH2, 4CL, AlaAT1, MYB4, LHT1, F3′5′Hb, UFGTa. Among them, seven SNPs of moderate effect led to changes in the amino acid contents in the final proteins of the following genes: ANSa, GDH2, 4Cl, F3′5′Hb, UFGTa. These results will be useful for further evaluations of the important SNPs and will help to provide a better understanding of the mechanisms of nitrogen uptake efficiency in tree crops.