As the most important cultured shrimp in China, Litopenaeus vannamei constitutes about 70% of the world's cultured shrimp production, and has high commercial value. With the development of culturing technology, high-density farming has become a trend. In order to obtain a commercial size in a short time, it is necessary to cultivate some varieties that grow fast. Single nucleotide polymorphisms (SNPs) brought genetic diversity research into a new stage. SNPs widely existed in genome, and they serve as suitable markers for linkage map, genome wide association studies (GWAS), and marker assisted selection (MAS) of target traits. There were few researches to discover SNPs of important phenotype in L. vannamei, and therefore there was still insufficient information of SNPs available for genetic diversity studies of L. vannamei. Especially, the discovery of growth-related SNPs by transcriptome sequencing was rarely reported in L. vannamei. With the development of next generation sequencing (NGS), the cost of sequencing has greatly fallen, which makes SNPs identification feasible in non-model species. RNA-seq based on NGS has been used widely, and it can identify SNP markers efficiently, because it focuses on the functional information in the genome with expression level of functional gene. In this study, SNPs of a P450 gene and its potential transcriptional factors were detected in different growth rate individuals by RNA-seq. We hope to give an example for the effective use of transcriptome data and a way for the accumulation of genetic and breeding data of shrimp. The inbreeding and crossbreeding offspring of four L. vannamei strains with diverse genetic backgrounds were cultured in net cages of ponds. The top five fastest growing individuals or top five slowest growing individuals in each net cage were put into a pool, respectively. The two kinds of RNA pools (rapid-growing group, RG; slow-growing group, SG), which were sequenced by RNA-seq, were used to find different expression genes and SNPs. The target DNA fragments, which were amplified from two kinds of DNA pools (RG and SG) by PCR, were sequenced by NGS to find SNPs. A different expression P450 gene, which was selected by comparing transcriptomes of two RNA pools of L. vannamei, was named LvCYP2J3-like with a 1 488 bp open reading frame encoding a protein of 495 aa and an integral P450 domain, which might be involved in the inactivation of ecdysones. Six transcription factors of LvCYP2J3-like were predicted by bioinformatics. They are TATA-box-binding protein (TBP), TBP1, TATA element modulatory factor (TMF), pancreas transcription factor (PTF), PTF1A and PTF1A1. The variance analysis of the 7 gene by q-PCR showed there was significant difference of expression levels in tissues, development stages and molting cycle. LvCYP2J3-like was detected in all tissues samples. The expression levels from high to low were eyestalk, gill, intestinal tract, muscle, hepatopancreas and haemocytes. Multiple comparisons showed that there were significant differences between the two groups (P < 0.05). The expression pattern of PTF1A was similar to that of LvCYP2J3-like, with the highest expression in eyestalk and the second in gill (P < 0.05), but no expression was detected in other tissues. LvCYP2J3-like had significantly different expressions in five development stages, with the highest in mysis larva stage (P < 0.05). The expression pattern of PTF and PTF1A was similar to LvCYP2J3-like in development stages. LvCYP2J3-like had a similar pattern with TBP in molting cycle, and there was the highest expression level in premolt stage D1 (P < 0.05). The expression level of LvCYP2J3-like, PTF and TBP in SG were higher than that in RG (P < 0.05), but PTF1A1, TBP1 and TMF had higher expression levels in RG (P < 0.05). There were 4 and 11 SNPs with significant difference of allele frequency (P < 0.05), in sequences of LvCYP2J3-like and its predictive transcription factors, respectively. The expression pattern of LvCYP2J3-like implied that it played a role in development and molting cycle. Its expression level was closely related to environmental stress. The results suggested that genetic diversity of these genes was related to their activities and expressions, which affects the growth rate of shrimp. This study will provide useful data for the genetic and breeding research of L. vannamei.