News Release

Genomic synergy: Boosting apple fruit quality through combined genotyping

Peer-Reviewed Publication

Nanjing Agricultural University The Academy of Science

Changes in marker genotype (ROH)-based inbreeding coefficients in apple parental population.

image: 

Changes in marker genotype (ROH)-based inbreeding coefficients in apple parental population.

view more 

Credit: Horticulture Research

Researchers have successfully combined genotypic data from different platforms to enhance the accuracy of genomic prediction and genome-wide association studies (GWAS) for apple fruit quality traits. This innovation allows for more precise selection of superior apple varieties, improving breeding efficiency and understanding of key genetic factors affecting fruit quality. The study's findings mark a significant step forward in the application of genomics to apple breeding.

Apple breeding faces challenges due to the long juvenile period and large plant size, which limit population size for selecting superior genotypes. Advances in next-generation sequencing have facilitated genomic selection (GS) and genome-wide association studies (GWAS), enabling early selection of promising genotypes. However, integrating data from various genotyping platforms has been problematic. To address these challenges, a comprehensive study was conducted to explore the potential of combining genotypic data.

Researchers from Chiba University and The University of Tokyo, in collaboration with NARO, published a study (DOI: 10.1093/hr/uhae131) in Horticulture Research on July 8, 2024. The study investigates the benefits of integrating genotypic data from Illumina Infinium and GRAS-Di platforms to improve GS and GWAS for apple fruit quality traits. The findings suggest that this approach can significantly enhance breeding efficiency.

The study evaluated the impact of combining genotypic data from Illumina Infinium and GRAS-Di platforms on GS and GWAS in apples. By analyzing over 2,000 apple genotypes, researchers demonstrated that integrated data significantly improved the accuracy of genomic prediction models and the detection power of GWAS. This led to the identification of significant loci associated with key traits such as sweetness and acidity, providing valuable markers for breeding programs. The study also highlighted the benefits of accounting for inbreeding effects, as models incorporating these effects showed higher accuracy for several fruit quality traits. The findings underscore the importance of integrating diverse genotypic data to enhance the genetic improvement of apples, offering a more effective approach to selecting and breeding superior apple varieties.

Dr. Mai F. Minamikawa, the lead researcher, stated, "Our findings demonstrate the potential of combining genotypic data from different platforms to enhance genomic prediction and association studies in apple breeding. This approach not only improves accuracy but also provides valuable insights into the genetic basis of important fruit quality traits."

The integration of genotypic data from multiple platforms offers a promising strategy for apple breeders. By improving the accuracy of genomic predictions and identifying key genetic markers, this approach can accelerate the development of superior apple varieties with desirable traits. Moreover, the study's findings on inbreeding effects provide crucial information for optimizing breeding strategies, ensuring the sustainable production of high-quality apples.

###

References

DOI

10.1093/hr/uhae131

Original Source URL

https://doi.org/10.1093/hr/uhae131

Funding information

This research was supported by a grant from the Ministry of Agriculture, Forestry and Fisheries of Japan (Genomics-based Technology for Agricultural Improvement, NGB-2007 and 2010), Cabinet Office, Government of Japan, Cross-ministerial Strategic Innovation Promotion Program (SIP), ‘Technologies for Smart Bio-industry and Agriculture’ (funding agency: Bio-oriented Technology Research Advancement Institution, NARO), MAFF commissioned project study on ‘Smart breeding technologies to Accelerate the development of new varieties toward achieving “Strategy for Sustainable Food Systems, MIDORI”’ Grant Number JPJ012037 and a Grant-in-Aid for JSPS Research Fellow (JP22K20577 and JP23K13928).

About Horticulture Research

Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2022. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.