[Genome-wide association analysis of agronomic traits related to eggplant fruits: a review].

Eggplant is an important horticultural crop and one of the most widely grown vegetables in the Solanaceae family. Eggplant fruit-related agronomic traits are complex quantitative traits with low efficiency and long cycle time for traditional breeding selection. With the rapid development of high-throughput sequencing technology and bioinformatics tools, genome-wide association study (GWAS) has shown great application potential in analyzing the genetic rules of complex agronomic traits related to eggplant fruits. This paper first reviews the progress of genome-wide association analysis in eggplant fruit shape, fruit color and other fruit-related agronomic traits. Subsequently, aiming at the problem of missing heritability, which is common in the genetic studies of eggplant quantitative traits, this paper puts forward the development strategies of eggplant GWAS in the future based on the hot spots of application of four GWAS strategies in the research of agronomics traits related to eggplant fruits. Lastly, the application of GWAS strategy in the field of eggplant molecular breeding is expected to provide a theoretical basis and reference for the future use of GWAS to analyze the genetic basis of various eggplant fruit-related traits and to select fruit materials that meet consumer needs.

Gene Association Analysis of Quantitative Trait Based on Functional Linear Regression Model with Local Sparse Estimator.

Functional linear regression models have been widely used in the gene association analysis of complex traits. These models retain all the genetic information in the data and take full advantage of spatial information in genetic variation data, which leads to brilliant detection power. However, the significant association signals identified by the high-power methods are not all the real causal SNPs, because it is easy to regard noise information as significant association signals, leading to a false association. In this paper, a method based on the sparse functional data association test (SFDAT) of gene region association analysis is developed based on a functional linear regression model with local sparse estimation. The evaluation indicators CSR and DL are defined to evaluate the feasibility and performance of the proposed method with other indicators. Simulation studies show that: (1) SFDAT performs well under both linkage equilibrium and linkage disequilibrium simulation; (2) SFDAT performs successfully for gene regions (including common variants, low-frequency variants, rare variants and mix variants); (3) With power and type I error rates comparable to OLS and Smooth, SFDAT has a better ability to handle the zero regions. The Oryza sativa data set is analyzed by SFDAT. It is shown that SFDAT can better perform gene association analysis and eliminate the false positive of gene localization. This study showed that SFDAT can lower the interference caused by noise while maintaining high power. SFDAT provides a new method for the association analysis between gene regions and phenotypic quantitative traits.

[Genome-wide identification and analysis of the TCP gene family in eggplant (Solanum melongena L.)].

TCP (teosinte branched1/cincinnata/proliferating cell factor) is a group of plant-specific transcription factors that play important roles in plant growth and development. To date, there are no report about TCP transcription factors in eggplant (Solanum melongena L). In this study, twenty-nine eggplant TCP (SmTCP) family genes distributed on 11 chromosomes were identified from the genome database of eggplant using bioinformatics methods. The results showed that all members of the family contained sequences encoding TCP conserved domains with length of amino acids ranging from 201 to 538 and exon numbers of 1 or 2. Subcellular localization revealed that three SmTCP proteins (SmTCP02/03/21) were located in the cytoplasm and the other SmTCP proteins were located in the nucleus. The 29 TCP transcription factors were divided into ClassⅠ (PCF) and ClassⅡ (CIN and CYC/TB1) by phylogenetic tree and sequence analysis. Collinearity analysis showed that 17 pairs (21) of SmTCP genes had collinearity, and these collinearity genes belonged to segmental duplication. Analysis of gene expression patterns showed that all 29 members of SmTCP gene family were expressed in 15 tissues or organs, but the expression patterns were different. Among them, four gene (SmTCP18/19/20/25) of CIN subfamily were highly expressed in leaves at different growth stages. Analysis of cis-acting elements in the promoter region of SmTCP showed that there were four types of cis-acting elements, which were light response related cis-acting elements, growth and development related cis-acting elements, hormone response related cis-acting elements and stress related cis-acting elements. In summary, the molecular basis of SmTCP genes in eggplant and the influence of TCP gene on the growth and development of eggplant provided a theoretical basis for molecular breeding of eggplant.