Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology

Dear Colleagues,

Next-generation sequencing (NGS) technologies have accelerated crop improvement methods by enabling the rapid and cost-effective sequencing of entire genomes, transcriptomes, and epigenomes. The combination of NGS tools with omics approaches such as proteomics and metabolomics generates huge amounts genomic data that is frequently used to speed up the development of new crop varieties with desirable traits. Moreover, artificial intelligence (AI) technologies, such as machine learning and deep learning, are likely to transform the field of plant breeding by facilitating the rapid and accurate prediction of crop performance and yield.

The aim of this Special Issue is to bring to light the recent research progress in plant breeding by applying NGS tools, -omics approaches, and AI tech. Original research articles and concepts for review articles to address major issues are welcome.

This Special Issue will focus include articles related to the following topics:

• Whole genome sequencing, assembly, and annotation;
• Pan-genome assembly;
• Transcriptome sequencing, assembly, differentially expressed gene identification;
• Genotyping-by-sequencing, genetic diversity, and population structure;
• Gene mapping and functional characterization;
• Genomic selection for complex traits;
• Map-based cloning of novel gene(s);
• Molecular markers;
• Comparative genomics;
• Transposable elements and epigenomics;
• Precision phenotyping;
• Crop modelling.

Dr. Manosh Biswas
Guest Editor

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