Genetic Diversity and Genome-Wide Association Study of Morphological and Quality Traits in Peach Using Two Spanish Peach Germplasm Collections

Low-density SNP marker sets for genetic variation analysis and variety identification in cultivated citrus

BACKGROUND

The Citrus species are major fruit crops cultivated in the world and have complex genetic relationships due to sexual comparability between Citrus and related genera. Of these, satsuma mandarin (C. unshiu (Mak.) Marc.) and sweet orange (C. sinensis (L.) Osb.) are widely grown diploid species. In this study, genotyping by sequencing (GBS) was conducted to identify single nucleotide polymorphisms (SNPs) for investigating genetic variation in a citrus collection.

RESULTS

A total of 26,903 high-quality SNPs were detected across nine chromosomes in the 144 citrus varieties, consisting of 70 C. unshiu, 40 C. sinensis, 22 interspecific hybrids, and 12 others. Of these, a core set of 481 SNPs was filtered based on polymorphism information content and genome distribution. Both principal component analysis (PCA) and model-based clustering showed genetic differentiation between C. unshiu and C. sinensis. For interspecific hybrids, these were separated from two species in PCA, but were mixed with each species in model-based clustering. Significant genetic differentiations between three populations were also found using the pairwise Fst. In addition, interspecific hybrids showed higher level of genetic diversity relative to the C. unshiu and C. sinensis populations. With the 481 SNPs, four subsets (192, 96, 48, and 24 SNPs) were generated to evaluate their performance for variety identification. Both 192 and 96 SNP sets distinguished all 144 varieties, while the 48 and 24 SNP sets separated 134 (93.1%) and 110 (76.4%), respectively.

CONCLUSIONS

The GBS-based SNP discovery led to robust and cost-effective molecular marker sets to assess genetic variation in the cultivated citrus species with narrow genetic bases. The resulting SNP sets are a resource to enhance the phenotype-based DUS testing by developing a DNA barcode system and thus facilitate new variety breeding and protection in citrus.

Comprehensive insights on association mapping in perennial fruit crops breeding - Its implications, current status and future perspectives

In order to provide food and nutritional security for the world's rapidly expanding population, fruit crop researchers have identified two critical priorities: increasing production and preserving fruit quality during the pre- and post-harvest periods. The genetic basis of these complex, commercially important fruit traits which are uniquely regulated by polygenes or multi-allelic genes that interact with one another and the environment can be analyzed with the aid of trait mapping tools. The most interesting trait mapping approach that offers the genetic level investigation for marker-trait associations (MTAs) for these complex fruit traits, without the development of mapping population, is association mapping. This approach was used during the genetic improvement program, emphasizing the obstacles (breeding strategies adopted, generation interval, and their genomic status) pertaining to perennial fruit crops. This method of studying population diversity and linkage disequilibrium in perennial fruit crops has been made possible by recent developments in genotyping, phenotyping, and statistical analysis. Thus, the purpose of this review is to provide an overview of different trait mapping techniques, with a focus on association mapping (method, essential components, viability, constraints, and future perspective) and its advantages, disadvantages, and possibilities for breeding perennial fruit crops.

Genetic diversity, morphological and quality traits of Momordica dioica

The goal of the current study was to assess genetic variability in Momordica dioica for both qualitative and morphological features to create trait-specific lines. The correlation coefficients among twenty-three different traits of twenty-one Momordica dioica gynoecious accessions calculated and summarized by using the best linear unbiased predictor (BLUPs). The traits contribution to principal components for growth, yield and yield attributing characters positively contributed towards the PC-I were tender fruit weight (FWT), mature fruit weight (FWM), ripen fruit weight (FWR), fruit yield per plant (MFYP), fruit yield per hectare (MFPH), seeds per fruit (NSF), fruit length (FL), fruit diameter (FD), inter-nodal length (IL), fruit pedicel length (FPL), leaf width (LW), leaf length (LL) and vine length (VL). Three groups were identified; group III had the most genotypes (10), followed by cluster II (07), and cluster I (04). Group II and III had the greatest inter-cluster value (8.73811), proceeded by group III and group I (8.738105) which indicates a wider genetic base among the genotypes under study. For the twenty-three traits, different genetic traits were analyzed, including heritability (H2), genetic advance (GA), genetic advance as a percentage of mean (GAM), and phenotypic coefficient of variability and genotypic coefficient of variability (PCV & GCV). High PCV and GCV were noted respectively for the VL (26.93 and 26.24), number of stems per plant (28.12 and 21.03), LL (23.60 and 23.48), LW (21.21 and 21.09), FPL (37.53 and 36.74), FL (22.06 and 21.75), FD (22.65 and 22.60), FWT (39.77 and 49.76), FWM (51.07 and 51.01), FWR (51.97 and 51.79), fruits per plant (51.97 and 51.79), NSF (22.99 and 21.06), 100 Seed weight (141.25 and 141.25), MFYP (54.14 and 53.94) and MFYH (54.13 and 53.93). High GA as per cent grand mean was observed for VL (73.59%), number stem per plant (23.76%), FL (22.01%), FD (23.40%), FWT (24.07%), NFP (99.70%), 100 Seed weight (25.55%), MFYP (21.14%), MFYH (28.55%) and ascorbic acid (115.58%). The study provided a comprehensive of genetic variability of Momordica dioica for morphological and qualitative traits to support the development of gynoecious lines with specific traits.

Genomic exploration of Iranian almond (Prunus dulcis) germplasm: decoding diversity, population structure, and linkage disequilibrium through genotyping-by-sequencing analysis

This study focuses on the genetic diversity and population structure of Prunus dulcis (almond tree), a crucial agricultural component with widespread cultivation and commercial importance, particularly in Iran, a region with a longstanding tradition of almond cultivation. The diverse almond collection in Iran encompasses many local varieties, breeding selections, rootstocks, and international cultivars. This diversity necessitates advanced genotyping techniques to gain insights into genetic diversity, population structure, and linkage disequilibrium (LD). In this paper, genotyping-by-sequencing (GBS) was employed to analyze 62 almond germplasm samples, identifying approximately 63,537 high-quality single nucleotide polymorphisms (SNPs) distributed across the eight chromosomes of the almond genome. On average, there were 30,225 SNPs per chromosome. The analysis yielded an average polymorphism information content (PIC) of 0.315 and an expected heterozygosity (He) rate of 0.28, indicating a significant level of genetic diversity within the studied almond germplasm. The LD analysis demonstrated a rapid decline, with an average LD decay spanning approximately 300 kb for an r2 value of 0.2. This suggests substantial hybridization among the sampled almond varieties. Principal Component Analysis (PCA) and structure analysis could not differentiate genotypes based on geographical origin, providing further evidence of genetic mixing among the studied almond populations. An Analysis of Molecular Variance (AMOVA) highlighted significant genetic diversity within populations but revealed minimal differences. This comprehensive study of Iran's almond genotypes offers valuable insights for future breeding and conservation efforts, emphasizing this agriculturally significant species abundant genetic diversity and intricate population structure.