Di Guardo, M. | Search bioRxiv

bioRxiv2021

The haplotype-resolved reference genome of lemon (Citrus limon L. Burm f.)

Lemon (Citrus limon (L.) Burm. f.) is an evergreen tree belonging to the genus Citrus. The fruits are particularly prized for their organoleptic and nutraceutical properties of the juice. Herein we report, for the first time, the release of a high-quality reference genome of the two haplotypes of lemon. The sequencing has been carried out coupling Illumina short reads and Oxford Nanopore data leading to the definition of a primary and an alternative assembly characterized by a genome size of 312.8 Mb and 324.74 Mb respectively. The analysis of the long terminal repeat (LTR) allowed the identification of 1921 regions on the primary and 1911 on the alternative assembly distributed across the nine chromosomes. Furthermore, an in-silico analysis of the microRNA genes was carried out using 246 mature miRNA and the respective pre-miRNA hairpin sequences of C. sinensis. Such analysis highlighted a high conservation between the two species with 233 mature miRNAs and 51 pre-miRNA stem-loops aligning with perfect match on the lemon genome. In parallel, total RNA was extracted from fruit, flower, leaf and root enabling the detection of 38,205 and 37,753 predicted transcripts on primary and alternative assemblies respectively. Among those, the highest and lowest number of tissue-specific transcripts were detected in flower (2.73% and 2.71% in primary and alternative assemblies respectively) and leaf (0.7% and 0.68%) while gene ontology analysis enables a more precise characterization of the expressed genes based on their function. The availability of a reference genome is an important prerequisite both for the set-up of high-throughput genotyping analysis and for functional genomic approaches toward the characterization of the genetic determinism of traits of agronomic interest.

genomics↗

bioRxiv2019

Prediction of fruit texture with training population optimization for efficient genomic selection in apple

Texture plays a major role in the determination of fruit quality in apple. Due to its physiological and economic relevance, this trait has been largely investigated, leading to the fixation of the major gene PG1 controlling firmness in elite cultivars. To further improve fruit texture, the targeting of an undisclosed reservoir of loci with minor effects is compelling. In this work, we aimed to unlock this potential with a genomic selection approach by predicting fruit acoustic and mechanical features as obtained with a TA.XTplus texture analyzer in 537 individuals genotyped with 8,294 SNP markers. The best prediction accuracies following cross-validations within the training set (TRS) of 259 individuals were obtained for the acoustic linear distance (0.64). Prediction accuracy was further improved through the optimization of TRS size and composition according to the test set. With this strategy, a maximal accuracy of 0.81 was obtained when predicting the synthetic trait PC1 in the family Gala x Pink Lady. We discuss the impact of genetic relatedness and clustering on trait variability and predictability. Moreover, we demonstrated the need for a comprehensive dissection of the complex texture phenotype and the potentiality of using genomic selection to improve fruit quality in apple. HighlightA genomic selection study, together with the optimization of the training set, demonstrated the possibility to accurately predict texture sub-traits valuable for the amelioration of fruit quality in apple.

genetics↗