Genomic prediction with NetGP based on gene network and multi‐omics data in plants

Plant Biotechnology Journal, Год журнала: 2025, Номер unknown

Опубликована: Фев. 14, 2025

Summary Genomic selection (GS) is a new breeding strategy. Generally, traditional methods are used for predicting traits based on the whole genome. However, prediction accuracy of these models remains limited because they cannot fully reflect intricate nonlinear interactions between genotypes and traits. Here, novel single nucleotide polymorphism (SNP) feature extraction technique Pearson‐Collinearity Selection (PCS) firstly presented improves across several known models. Furthermore, gene network model (NetGP) deep learning approach designed phenotypic prediction. It utilizes transcriptomic dataset (Trans), genomic multi‐omics (Trans + SNP). The NetGP demonstrated better performance compared to other in predictions, predictions predictions. performed than independent or Prediction evaluations using plants' data showed good generalizability NetGP. Taken together, our study not only offers effective tool plant but also points avenues future research.

Язык: Английский

Can the molecular and transgenic breeding of crops be an alternative and sustainable technology to meet food demand?

Functional & Integrative Genomics, Год журнала: 2025, Номер 25(1)

Опубликована: Апрель 9, 2025

Язык: Английский

Genetic diversity and population structure of sweet corn in China as revealed by mSNP

Molecular Breeding, Год журнала: 2024, Номер 45(1)

Опубликована: Дек. 26, 2024

Язык: Английский