Coffee cherries contain a crucial flavor-precursor and chemical substances influencing roasted bean quality, yet limited knowledge exists on metabolite changes during cherry ripening. Our study identified 1078 metabolites, revealing 46 core differential metabolites using a KEGG pathway analysis. At the GF vs. ROF stage, amino acid synthesis dominated; ROF vs. BRF featured nucleotide catabolism; BRF vs. PRF exhibited glycoside and flavonoid synthesis; and PRF vs. PBF involved secondary metabolite synthesis and catabolism. The PRF stage emerged as the optimal cherry-harvesting period. A correlation analysis identified core differential metabolites strongly linked to taste indicators, suggesting their potential as taste markers. Notably, nucleotides and derivatives exhibited significant negative correlations with glycosides and flavonoids during ripening. This research systematically analyzed flavor and active substances in green coffee beans during cherry ripening, offering valuable insights into substance formation in Coffea arabica L.

This study combined HS-SPME-GC–MS and high-throughput sequencing to explore how honey-processing methods with varying mucilage retentions impact volatile compounds and microbial communities in green coffee beans. HS-SPME-GC–MS revealed that the RH group (75 % to 80 % mucilage retention) had the highest relative content of volatile compounds. According to rOAV >1, 13 key aroma compounds were identified, contributing to flavors like “mellow” and “fruity”. High-throughput sequencing identified seven dominant bacterial genera and four dominant fungal genera, with higher diversity of fungi than bacteria across treatments. Correlation analysis indicated that bacteria and fungi contribute to aroma formation, with bacteria more active in low-mucilage and fungi in high-mucilage treatments. Overall, the RH group was optimal for the aroma quality and bioactivity of green coffee beans. The findings of this research offers insights into aroma compound-microbe interactions in coffee mucilage fermentation, helping coffee producers optimize process parameters for better-quality coffee products.

To date, genomic and transcriptomic data on Coffea arabica L. in public databases are very limited, and there has been no comprehensive integrated investigation conducted on alternative splicing (AS). Previously, we have constructed and sequenced eighteen RNA-seq libraries of C. arabica at different ripening stages of fruit development. From this dataset, a total of 3824, 2445, 2564, 2990, and 3162 DSGs were identified in a comparison of different fruit ripening stages. The largest proportion of DSGs, approximately 65%, were of the skipped exon (SE) type. Biologically, 9 and 29 differentially expressed DSGs in the spliceosome pathway and carbon metabolism pathway, respectively, were identified. These DSGs exhibited significant variations, primarily in S1 vs. S2 and S5 vs. S6, and they involve many aspects of organ development, hormone transduction, and the synthesis of flavor components. Through the examination of research findings regarding the biological functions and biochemical pathways associated with DSGs and DEGs, it was observed that six DSGs significantly enriched in ABC transporters, namely, LOC113712394, LOC113726618, LOC113739972, LOC113725240, LOC113730214, and LOC113707447, were continually down-regulated at the fruit ripening stage. In contrast, a total of four genes, which were LOC113732777, LOC113727880, LOC113690566, and LOC113711936, including those enriched in the cysteine and methionine metabolism, were continually up-regulated. Collectively, our findings may contribute to the exploration of alternative splicing mechanisms for focused investigations of potential genes associated with the ripening of fruits in C. arabica.

Background: Codon usage bias has been analyzed in the Coffea arabica L. nuclear genome, yet comprehensive genomic resources for this species remain limited. The chloroplast genome, characterized by its maternal inheritance and high conservation, represents a valuable resource for investigating plant phylogeny, crop domestication, and maternal lineage evolution. Results: We assembled complete chloroplast genomes for 52 C. arabica accessions, encompassing four cultivars (Geisha, Catimor, Bourbon, and Caturra), four improved breeding lines within the Geisha group (Yunka No. 3, Yunka No. 4, G02, and G13), two Catimor breeding lines (CCCA25 and T5175), and four accessions of unknown cultivar origin. Comparative genomics, unrooted phylogenetic reconstruction (neighbor-joining and maximum likelihood), haplotype inference, and exploratory principal component analysis (PCA) were integrated to characterize the genetic architecture of these chloroplast genomes. These genomes ranged from 155,133 bp to 155,192 bp in length, displayed the typical quadripartite architecture, and exhibited GC contents of 37.43–37.44%. Gene annotation identified 131 genes, comprising 86 protein-coding genes, 37 tRNAs, and 8 rRNAs. Codon usage analysis revealed a pronounced bias toward A or U at the third codon position. We detected 194 SSR loci per plastome, among which mononucleotide A/T repeats predominated. Neighbor-joining and maximum-likelihood phylogenies, PCA, and haplotype network reconstruction consistently resolved the 52 accessions into three genetic clusters (C1–C3; C1 represented by a single divergent accession) and five distinct haplotypes. SNP and InDel profiling further showed that intergenic spacer (IGS) regions harbored the highest density of genetic variation. Conclusions: These genomes provide resources for germplasm characterization, phylogenetic studies, and marker-assisted breeding in coffee. They also establish a chloroplast-genome framework that, when integrated with nuclear genomics and expanded sampling, will help fully resolve the maternal history, domestication, and allopolyploid origin of Coffea arabica.