AprGPD: the apricot genomic and phenotypic database

Abstract

Background Apricot is cultivated worldwide because of its high nutritive content and strong adaptability. Its flesh is delicious and has a unique and pleasant aroma. Apricot kernel is also consumed as nuts. The genome of apricot has been sequenced, and the transcriptome, resequencing, and phenotype data have been increasely generated. However, with the emergence of new information, the data are expected to integrate, and disseminate. Results To better manage the continuous addition of new data and increase convenience, we constructed the apricot genomic and phenotypic database (AprGPD, http://apricotgpd.com). At present, AprGPD contains three reference genomes, 1692 germplasms, 306 genome resequencing data, 90 RNA sequencing data. A set of user-friendly query, analysis, and visualization tools have been implemented in AprGPD. We have also performed a detailed analysis of 59 transcription factor families for the three genomes of apricot. Conclusion Six modules are displayed in AprGPD, including species, germplasm, genome, variation, product, tools. The data integrated by AprGPD will be helpful for the molecular breeding of apricot.

A Chromosome-Level Genome of ‘Xiaobaixing’ (Prunus armeniaca L.) Provides Clues to Its Domestication and Identification of Key bHLH Genes in Amygdalin Biosynthesis

“…Zhang et al obtained high-quality sequences of eight apricot chromosomes with a genome size of 251.19 Mb, a heterozygosity of 0.99%, a duplicate sequence of 46.78%, and 29,230 genes were annotated by using triple-sequencing technology combined with second-generation data error correction and HiC sequencing for sequence mounting using the 'Yinxiangbai' apricot as sequencing material [32]. Chen et al determined and assembled three genomes, namely P. sibirica (the F106 genome was 219 Mb in size, with an overlapping cluster N50 length of 6.70 Mb and eight chromosomes, with 32,959 genes predicted), P. armeniaca (the genome was 217 Mb, with an overlap cluster N50 length of 7.13 Mb, eight chromosomes, and 32,669 genes were predicted), and P. armeniaca × P. sibirica (the genome was 225 Mb, with an overlap cluster N50 length of 6.91 Mb, eight chromosomes and 32,987 genes were predicted) and the results of the study were found to be different [33]. The above studies have shown that different germplasm has an effect on the size of the genome assembled, the size of the N50, the size of the pseudomolecules, and the number of predicted genes.…”

Integration of high-throughput omics technologies in medicinal plant research: The new era of natural drug discovery

“…Divergence of pharmacodynamic components in different species/varieties/strains (Qin et al, 2014;Song et al, 2021), tissues (Guo et al, 2022;Pan et al, 2022) and development stages (Huang et al, 2021;Zhang et al, 2022b) of medicinal plants implicates expression level of key proteins involved in biosynthesis and metabolism of medicinal compounds (Figure 3, yellow part). Based on quantitatively targeted subproteomic analysis of the high and low artemisinin content of sweet wormwood (Artemisia annua), the increase expression of DBR2 accounts for the high artemisinin content (Chen et al, 2020).…”