Mapping and characterization QTLs for phenological traits in seven pedigree-connected peach families.

BACKGROUND: Environmental adaptation and expanding harvest seasons are primary goals of most peach [Prunus persica (L.) Batsch] breeding programs. Breeding perennial crops is a challenging task due to their long breeding cycles and large tree size. Pedigree-based analysis using pedigreed families followed by haplotype construction creates a platform for QTL and marker identification, validation, and the use of marker-assisted selection in breeding programs. RESULTS: Phenotypic data of seven F1 low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. Three QTLs were discovered for bloom date (BD) and mapped on linkage group 1 (LG1) (172-182 cM), LG4 (48-54 cM), and LG7 (62-70 cM), explaining 17-54%, 11-55%, and 11-18% of the phenotypic variance, respectively. The QTL for ripening date (RD) and fruit development period (FDP) on LG4 was co-localized at the central part of LG4 (40-46 cM) and explained between 40 and 75% of the phenotypic variance. Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles and the presence of multiple functional alleles with different effects for a single locus for RD and FDP. CONCLUSIONS: A multiple pedigree-linked families approach validated major QTLs for the three key phenological traits which were reported in previous studies across diverse materials, geographical distributions, and QTL mapping methods. Haplotype characterization of these genomic regions differentiates this study from the previous QTL studies. Our results will provide the peach breeder with the haplotypes for three BD QTLs and one RD/FDP QTL to create predictive DNA-based molecular marker tests to select parents and/or seedlings that have desired QTL alleles and cull unwanted genotypes in early seedling stages.

Identification and characterization of QTLs for fruit quality traits in peach through a multi-family approach.

BACKGROUND: Fruit quality traits have a significant effect on consumer acceptance and subsequently on peach (Prunus persica (L.) Batsch) consumption. Determining the genetic bases of key fruit quality traits is essential for the industry to improve fruit quality and increase consumption. Pedigree-based analysis across multiple peach pedigrees can identify the genomic basis of complex traits for direct implementation in marker-assisted selection. This strategy provides breeders with better-informed decisions and improves selection efficiency and, subsequently, saves resources and time. RESULTS: Phenotypic data of seven F1 low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. One major QTL for fruit blush was found on linkage group 4 (LG4) at 40-46 cM that explained from 20 to 32% of the total phenotypic variance and showed three QTL alleles of different effects. For soluble solids concentration (SSC), one QTL was mapped on LG5 at 60-72 cM and explained from 17 to 39% of the phenotypic variance. A major QTL for titratable acidity (TA) co-localized with the major locus for low-acid fruit (D-locus). It was mapped at the proximal end of LG5 and explained 35 to 80% of the phenotypic variance. The new QTL for TA on the distal end of LG5 explained 14 to 22% of the phenotypic variance. This QTL co-localized with the QTL for SSC and affected TA only when the first QTL is homozygous for high acidity (epistasis). Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles. CONCLUSIONS: A multi-family-based QTL discovery approach enhanced the ability to discover a new TA QTL at the distal end of LG5 and validated other QTLs which were reported in previous studies. Haplotype characterization of the mapped QTLs distinguishes this work from the previous QTL studies. Identified predictive SNPs and their original sources will facilitate the selection of parents and/or seedlings that have desired QTL alleles. Our findings will help peach breeders develop new predictive, DNA-based molecular marker tests for routine use in marker-assisted breeding.

Diferentes substratos na produção de mudas de mirtileiro / Different substrates in the production of blueberry seedlings

O objetivo desse trabalho foi avaliar o efeito da composição de diferentes substratos na produção de mudas de mirtileiro. Foram utilizadas mudas da cultivar 'Georgiagem', oriundas de multiplicação in vitro. Foram utilizados sete diferentes substratos, os quais são: T1 - Plantmax® (100 por cento); T2 - Plantmax® + perlita (1:1); T3 - Solo + matéria orgânica + perlita (1:1:1); T4 - solo + casca de arroz (1:1); T5 - solo + composto industrial + vermiculita (1 :1:1); T6 - casca de acácia + solo (1:1); T7 - acícula de pinus + solo - (1:2). O substrato acícula de pinus + solo, seguido pelos substratos Plantmax®, casca de acácia + solo e casca de arroz + solo promoveram maior acúmulo de massa seca da parte aérea e raízes. Os substratos solo + composto industrial + Perlita e Solo + composto industrial + vermiculita, com pH alcalino, apresentaram menor produção de massa seca e menores concentrações de Fe, Mn, Zn, N e P. Os substratos acícula de pinus, casca de acácia + solo, casca de arroz + solo e Plantmax® com ou sem perlita, mostraram-se os mais adequados para a produção de mirtileiro, cultivar 'Georgiagem'.

The research aimed to evaluate the effect of the composition of different substrate on the production of blueberry seedlings. The seedlings used were highbush, 'Georgiagem' from in vitro multiplication. Seven different substrate were used: T1 - Plantmax® (100 percent); T2 - Plantmax® + perlita (1:1); T3 - soil + composed industrial + perlita (1:1:1); T4 - soil + rice husks (1:1); T5 - soil + composed industrial + vermiculite (1:1:1); T6 - acácia bark + soil (1:1); T7 - pine needle mulch + soil (1:2). The substrate pine needle mulch + soil, followed by the substrate Plantmax®, acácia bark + soil and soil/rice husks + soil, which promoted greater dry mass of roots and shoots. The substrate Soil + composed industrial + perlita and soil + composed industrial + vermiculite, pH alkaline, showed lower production of dry matter and lower concentrations of Fe, Mn, Zn, N and P. Pine needle mulch + soil, soil + rice husks, acácia bark + soil and the substrate Plantmax® with or without perlita g were the most suitable r for the production of blueberry seedlings, cultivar 'Georgiagem'.