Multi-Omics Analyses Unravel Genetic Relationship of Chinese Coffee Germplasm Resources: Fid-Bau Portal

Multi-Omics Analyses Unravel Genetic Relationship of Chinese Coffee Germplasm Resources

Yu Ge / Butian Wang / Xuedong Shi / Zhenwei Zhang / Meijun Qi / Huabo Du / Peng Qu / Kuaile Jiang / Zhihua Chen / Xuejun Li

Abstract

The genetic relationships between Coffea arabica resources were analyzed via specific length amplified fragment sequencing (SLAF-seq) and transcriptome sequencing to provide the theoretical basis for breeding new varieties. Twenty C. arabica accessions were used to analyze genetic diversity on the basis of SNPs identified in SLAFs and the transcriptome data. For the SLAF-seq analysis of 20 C. arabica accessions, two Coffea canephora accessions, one Coffea liberica accession, and one Coffea racemosa accession, the number of reads ranged from 2,665,424 to 7,210,310, with a GC content of 38.49%–40.91% and a Q30 value of 94.99%–96.36%. A total of 3,347,069 SLAF tags were obtained, with an average sequencing depth of 13.90×. Moreover, the 1,048,575 SNPs identified in the polymorphic SLAFs were filtered, then the remaining 198,955 SNPs were used to construct a phylogenetic tree, perform a principal component analysis, and characterize the population structure. For the transcriptome analysis, 128.50 Gb clean reads were generated for the 20 C. arabica accessions, with a GC content of 44.36%–51.09% and a Q30 value of 94.55%–95.40%. Furthermore, 25,872 genes’ expression levels were used for the correlation analysis. The phylogenetic relationships as well as the results of the principal component analysis, population structure analysis, and correlation analysis clearly distinguished C. arabica Typica-type accessions from the C. arabica Bourbon-type accessions. Notably, several C. arabica local selections with unknown genetic backgrounds were classified according to all four clustering results.