Growth and survival tests were conducted on 74 families, comprising both selection and introduced populations with fast growth rates to identify single nucleotide polymorphisms (SNPs) and functional genes associated with growth traits in Litopenaeus vannamei. High-throughput genotyping of individuals from 39 families was carried out using the "Yellow Sea Chip No.1" liquid chip, which included 55K SNPs. Genomic genetic parameters for harvest body weight were estimated using the ssGBLUP method. Additionally, the ssGWAS and FarmCPU methods were employed for the first time to discover potentially associated SNPs and candidate genes. The estimation of genetic parameters revealed a heritability of 0.47 for harvest body weight, indicating a moderate to high potential for genetic improvement within the population. The ssGWAS and FarmCPU analyses identified two and six genome-wide significant SNPs (P<1.26×10^-6), respectively, explaining phenotypic variation ranging from 2.71% to 6.76%. A common SNP was also identified among them. Furthermore, both methods separately screened nine and 14 suggestive genome-wide SNPs (P<2.523×10^-5), explaining phenotypic variation ranging from 1.33% to 6.76%. QQ plots demonstrated that FarmCPU exhibited superior control over false positives compared to ssGWAS. Gene annotation of the seven significantly associated SNPs revealed 15 candidate genes related to functions such as the nervous system, muscle development, and energy metabolism. Notably, the common significantly associated SNP was annotated to two genes: LOC113809777, which encoded a hydrolase promoting glycogen hydrolysis, and LOC113809778, a transcriptional regulatory factor associated with gene expression regulation. In conclusion, utilizing the "Yellow Sea Chip No.1" liquid chip, the ssGWAS and FarmCPU methods facilitated the identification of significantly associated SNPs with harvest weight in L. vannamei, offering valuable insights into the genetic basis of growth traits.