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Brown coloration and a rough appearance as russet and semi-russet (partial russet) are features unique to the popular Asian sand pear (Pyrus pyrifolia Nakai). The degree of russeting is different between different genotypes. Russeting is sensitive to water fluctuations, where excessive rainwater can trigger/stimulate its development. However, the molecular mechanism of russeting is currently unclear. Here, we employed multi-omics, i.e., metabolomics, transcriptomics, and proteomics, and analyzed the effect of different sand pear genotypes and artificial rainfall on russeting of pear fruits. This led to the identification of 79, 64, and 29 differentially produced/expressed metabolites, transcripts, and proteins that are involved in the biosynthesis of suberin, phenylpropane, cutin, and waxes. Further analysis of these differentially expressed genes and their encoded proteins revealed that four of them exhibited high expression at both transcript and protein levels. Transient expression of one such gene, PbHHT1 (accession number 103966555), which encodes x-hydroxypalmitate-O-feruloyl transferase, in young green non-russet fruits triggered premature suberization in the russeting pear genotypes. This coincided with increased production of 16-feruloyloxypalmitic acid, a conjugated compound between phenols and esters during the polymerization for suberin formation. Collectively, our data from the combined three omics demonstrate that russeting in sand pear is a complex process involving the biosynthesis and transport of suberin and many other secondary metabolites.

Background Cotton (Gossypium spp.) fiber yield is one of the key target traits, and improved fiber yield has always been thought of as an important objective in the breeding programs and production. Although some studies had been reported for the understanding of genetic bases for cotton yield-related traits, the detected quantitative trait loci (QTL) for the traits is still very limited. To uncover the whole-genome QTL controlling three yield-related traits in upland cotton (Gossypium hirsutum L.), phenotypic traits were investigated under four planting environments and 9244 single-nucleotide polymorphism linkage disequilibrium block (SNPLDB) markers were developed in an association panel consisting of 315 accessions. Results A total of 53, 70 and 68 significant SNPLDB loci associated with boll number (BN), boll weight (BW) and lint percentage (LP), were respectively detected through a restricted two-stage multi-locus multi-allele genome-wide association study (RTM-GWAS) procedure in multiple environments. The haplotype/allele effects of the significant SNPLDB loci were estimated and the QTL-allele matrices were organized for offering the abbreviated genetic composition of the population. Among the significant SNPLDB loci, six of them were simultaneously identified in two or more single planting environments and were thought of as the stable SNPLDB loci. Additionally, a total of 115 genes were annotated in the nearby regions of the six stable SNPLDB loci, and 16 common potential candidate genes controlling target traits of them were predicted by two RNA-seq data. One of 16 genes (GH_D06G2161) was mainly expressed in the early ovule-development stages, and the stable SNPLDB locus (LDB_19_62926589) was mapped in its promoter region. Conclusion This study identified the QTL alleles and candidate genes that could provide important insights into the genetic basis of yield-related traits in upland cotton and might facilitate breeding cotton varieties with high yield.

In this study, trends in synonymous codons usage of Volvariella volvecea have been first examined by analysis of complete coding sequences and gene chip data. The results showed that GC content at three codon positions are obviously different and there were several factors shaping the codon usage of V. volvacea genes, including base composition. The comparison of codon usage among four edible fungi such as V. volvacea, Agaricus bisporus, Coprinopsis cinerea, and Pleurotus ostreatus indicated that the similar codon usage pattern was used among V. volvacea, A. bisporus and P. ostreatus, but there was significantly different codon usage pattern of C. cinerea. Two arrays of optimal codons were determined by effective number of codons (ENC) values and gene chip database separately, resulting that most of the ENC-predicted optimal codons were included in the array of gene chip resulted optimal codons. This study can provide useful information for codon usage pattern analysis and gene transformation of V. volvacea.