About this Research Topic
The development of Next Generation Sequencing (NGS) has dramatically changed the course of science research. With these new sequencing biotechnologies, the whole genome can now be sequenced in a matter of days and the expression profiles of many different individual animals or plants can be screened in a single experiment. Thousands of genomes of hundreds of species have been sequenced. Scientists are presented with an unprecedented opportunity to identify the genes controlling complex phenotypes and understand how the genes fulfill functions through the interaction between genes and environmental factors. This provides a new de novo approach for breeding programs in both plants and animals that can significantly reduce the cost and time needed by traditional breeding or domestication approaches.
Ever growing food demand in the world requires new food crops that are both more productive and resistant to harsher environmental conditions, as well as improvements in livestock breeding methods. NGS technologies have been widely used in various breeding programs as a fast and cost-effective alternative to traditional phenotyping. This new approach relies heavily on the analysis of huge volumes of NGS data. However, dissecting NGS data requires new informatic methods and analytical frameworks. One goal of this Research Topic is to present the community with new and effective analytical solutions to tackle the complex data produced by the NGS and other related biotechnologies. Another goal is to inspire novel data-driven approaches to phenotyping and variety improvement. Development of new analytical models and methods will enable high-throughput identification of key genes controlling agronomically important traits, and this can lead to new crops or animals with dramatically reduced breeding cycles.
This Research Topic focuses on the applications of Next Generation Sequencing technology in crop phenotyping, animal breeding, variety improvement, and genomic selection. The collection welcomes, but is not limited to, Original Research and Reviews in the following areas:
1. Genomic selection and phenotype predictions with environmental interactions
2. Pan-genome approach of phenotyping and gene identification
3. Development of new methods for integrative analysis of NGS data
4. Genome-wide association-based phenotyping
Keywords: Phenotype prediction, pan-genome, whole genome sequencing, precision agriculture, crop genetics, animal breeding
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