ArticleScientific reports2017
Genome-wide association study and genomic prediction in citrus: Potential of genomics-assisted breeding for fruit quality traits.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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65 citing papers in PubMed, 153 citations in OpenAlex.
- Chromosome-scale genome assembly and genomic prediction of essential oil compounds in Atractylodes lancea for genomics-assisted breeding.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026Article
- Genetic insights into bacterial wilt resistance using genomic prediction and association mapping in blueberry.The plant genome · 2026Article
- Accelerating genetic gain through integrated genomic selection in crop plants.Journal of applied genetics · 2026Review
- A new super-pangenome pipeline reveals domestication signatures of conserved noncoding sequences in the orange subfamily.Molecular biology and evolution · 2026Article
- Facilitating genomic breeding in citrus via reference panel-based whole-genome imputation of low-coverage sequencing-derived genotype data.Breeding science · 2026Article
- Advances in tea breeding in Japan: from traditional methods to genomic approaches.Breeding science · 2026Article
- Application of Genome-Assisted Prediction (GAP) for Apple Fruit Weight.Plants (Basel, Switzerland) · 2025Article
- Emanating candidate genes responsible for fruit quality traits in citrus through GBS-based genome wide association studies.BMC genomics · 2025Article
- Genomic selection for growth and wood properties in multi-generation hybrid populations ofHorticulture research · 2025Article
- Genomic prediction in Persian walnut: Optimization levers according to genetic architecture of complex traits.The plant genome · 2025Article
- Genomics unlocks the potential of genetic resources for citrus breeding.Breeding science · 2025Article
- Phenotypic simulation for fruit-related traits in FMolecular genetics and genomics : MGG · 2025Article
- Harnessing genomic technologies for one health solutions in the tropics.Globalization and health · 2024Review
- The art of tartness: the genetics of organic acid content in fresh fruits.Horticulture research · 2024Article
- Genomic selection for crop improvement in fruits and vegetables: a systematic scoping review.Molecular breeding : new strategies in plant improvement · 2024Article
- Genomic prediction and genome-wide association study using combined genotypic data from different genotyping systems: application to apple fruit quality traits.Horticulture research · 2024Article
- Development and Assessment of SNP Genotyping Arrays for Citrus and Its Close Relatives.Plants (Basel, Switzerland) · 2024Article
- The Genetic Dissection of Nitrogen Use-Related Traits in Flax (International journal of molecular sciences · 2023Article
- Genomic region and origin for selected traits during differentiation of small-fruit cultivars in Japanese apricot (Prunus mume).Molecular genetics and genomics : MGG · 2023Article
- Comprehensive genome-wide identification and transferability of chromosome-specific highly variable microsatellite markers from citrus species.Scientific reports · 2023Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
17 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Novel genomics-based approaches such as genome-wide association studies (GWAS) and genomic selection (GS) are expected to be useful in fruit tree breeding, which requires much time from the cross to the release of a cultivar because of the long generation time. In this study, a citrus parental population (111 varieties) and a breeding population (676 individuals from 35 full-sib families) were genotyped for 1,841 single nucleotide polymorphisms (SNPs) and phenotyped for 17 fruit quality traits. GWAS power and prediction accuracy were increased by combining the parental and breeding populations. A multi-kernel model considering both additive and dominance effects improved prediction accuracy for acidity and juiciness, implying that the effects of both types are important for these traits. Genomic best linear unbiased prediction (GBLUP) with linear ridge kernel regression (RR) was more robust and accurate than GBLUP with non-linear Gaussian kernel regression (GAUSS) in the tails of the phenotypic distribution. The results of this study suggest that both GWAS and GS are effective for genetic improvement of citrus fruit traits. Furthermore, the data collected from breeding populations are beneficial for increasing the detection power of GWAS and the prediction accuracy of GS.
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