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Pineapple is the most important economic plant in the family Bromeliaceae and the third-most economically important tropical fruit in the world. It has become an important tropical fruit in Guangdong, Hainan, and Guangxi, which are suitable areas for its cultivation. However, modern and well-organized breeding systems have not yet been established for pineapple. In this review, we describe the current status of the geographical distribution, industrial development, and breeding of pineapple in China. The current status of pineapple breeding is introduced, including traditional breeding methods, such as crossbreeding, mutagenesis breeding, and biotechnology breeding, combining cell engineering and gene engineering. In addition, the research progress on assisted breeding technology based on genetic map construction and molecular marker development is presented. New challenges and perspectives for obtaining high fruit quality are discussed in the context of breeding programs for pineapple. [ABSTRACT FROM AUTHOR]

To verify whether PsA-associated HLA alleles proposed in other populations are also related to PsA in Chinese Han population, a study of PsA susceptible alleles in the HLA-A, HLA-B, HLA-C and HLA-DRB1 alleles was presented for Chinese Han population. Genotyping was performed by Illumina Miseq platform (Illumina, USA). 50 subtypes and 77 subtypes of HLA-A, HLA-B, HLA-C and HLA-DRB1 with minor allele frequency (MAF) > 1% were genotyped from two-digit and four-digit resolution analysis in 111 PsA and 207 HCs (healthy controls) collected from Chinese Han population, respectively. Data handling, quality control and association analysis were performed using SPSS 25.0 software. In risk estimate, by mean of Bonferroni correction, a newfound four-digit allele HLA-A*01:01 [P = 5.5 × 10−4, OR 3.35 (1.69–6.66)], four-digit allele HLA-C*06:02 [P = 8.5 × 10−7, OR 3.80 (2.23–6.47)] and six two-digit alleles HLA-A*01 [P = 5.2 × 10−5, OR 3.43 (1.89–6.23)], HLA-B*13 [P = 4.0 × 10−6, OR 2.65 (1.76–4.01)], HLA-B*27 [P = 7.5 × 10−4, OR 5.84 (2.09–16.29)], HLA-B*57 [P = 5.8 × 10−5, OR 20.10 (4.65–86.83)], HLA-C*03 [P = 2.1 × 10−4, OR 0.40 (0.25–0.65)], HLA-C*06 [P = 1.9 × 10−12, OR 4.48 (2.95–6.81)] showed statistical significance by the univariate binary logistic regression analysis. Besides, in the binary logistic regression analysis with multiple variables, when the two alleles HLA-A*01:01 and HLA-C*06:02 were considered as covariates, HLA-A*01:01 [P = 2.7 × 10−3,OR 2.95 (1.46–5.98)] also showed significant association for PsA as risk factor, but may be not the main risk factor [HLA-C*06:02, P = 3.0 × 10−6, OR 3.68 (2.13–6.37)]. When all the above two-digit alleles were included as covariates, HLA-A*01 [P = 4.8 × 10−2, OR 2.00 (1.01–3.94)], HLA-B*13 [P = 4.2 × 10−5, OR 2.62 (1.65–4.16)], HLA-B*27 [P = 1.7 × 10−4, OR 7.62 (2.64–21.96)], HLA-B*57 [P = 2.97 × 10−4, OR 15.90 (3.55–71.18)], HLA-C*06 [P = 6.1 × 10−5, OR 2.70 (1.66–4.40)] showed significant for PsA as risk factors, HLA-C*03 [OR 0.65 (0.39–1.09), P = 0.10] showed no association with PsA. In conclusion, we assessed HLA-A, HLA-B, HLA-C and HLA-DRB1 alleles in PsA cohort of Chinese Han population, found HLA-A*01:01 and HLA-A*01 may be the susceptible genes associated with PsA, and also confirmed the association of four loci with PsA in Chinese Han population. These findings may extend the susceptibility HLA alleles of PsA and help in developing possible genetic markers to predict PsA. [ABSTRACT FROM AUTHOR]