Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

Abstract

Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

Smart breeding driven by advances in sequencing technology

“…This technique allows for customisation of markers and does not restrict the starting sample size or the number of markers, as liquid‐phase chips are used more than solid‐phase chips. Patented liquid‐phase chips are available for soybean ( Glycine max L. Merr) and a few non‐model plants, including the ‘Zhongdouxin No.1’ (ZDX1) functional array composed of 134,737 characteristic sites of soybean, 48 the Fluidigm genotyping chip of the bellflower ( Platycodon grandiflorus ) with 96 SNPs 49 and the 40K liquid‐phase chip of barley ( Hordeum vulgare L.). Additionally, SNP arrays can also be used to analyse haplotypes of polyploid plant species, making it a significant tool in understanding their evolutionary history.…”

Genome-wide association study (GWAS) with high-throughput SNP chip DNA markers identified novel genetic factors for mesocotyl elongation and seedling emergence in rice (Oryza sativa L.) using multiple GAPIT models

“…The Single Nucleotide Polymorphism (SNP) marker system gained momentum in plant bioscience ( Mammadov et al, 2012 ). Likewise, high-throughput SNP genotyping and DNA chip technology have emerged as powerful genomic tools in plant bioscience-related research to accelerate crops improvement ( Thomson and Biotechnology, 2014 ; You et al, 2018 ; Yu et al, 2021 ; Carrier et al, 2022 ). Recently, with the rapid development of molecular marker technology, several quantitative trait loci (QTLs) for mesocotyl elongation were identified using bi-parental linkage mapping in rice ( Lu et al, 2007 ).…”

Genome-Wide Comparative Profiles of Triterpenoid Biosynthesis Genes in Ginseng and Pseudo Ginseng Medicinal Plants

“…Codonopsis [18] and platycodons [19] roots are also considered poor man's ginseng due to their similar root morphologies to ginseng. These roots contain triterpenoids such as Platycodins and Lancemasides, which are similar to ginsenoside Ro, making them beneficial in traditional medicines [20,21].…”