Restoration over time and sustainability of Schinus terebinthifolius Raddi.

The success of recovery programs on degraded areas is dependent on the genetic material to be used, which should present heterozygosity and genetic diversity in native and recovered populations. This study was carried out to evaluate the model efficiency to enable the recovery of a degraded area of the Lower São Francisco, Sergipe, Brazil. The target species for this study was Schinus terebinthifolius Raddi. Three populations were analyzed, the recovered area, seed-tree source population, and native tree population border established to the recovered area. The random amplified polymorphic DNA (RAPD) markers were used for diversity analysis. Genetic structure was estimated to evaluate the level of genetic variability existent in each population. There was no correlation between the spatial distribution and the genetic distances for all trees of the recovered area. The heterozygosity present in the recovered population was higher than the native tree population. The seed-tree source population presents genetic bottlenecks. Three clusters were suggested (ΔK = 3) with non-genetic structure. High intra-population genetic variability and inter-population differentiation are present. However, gene flow may also introduce potentially adaptive alleles in the populations of the recovered area, and the native population is necessary to ensure the sustainability and maintenance of the populations by allelic exchange.

Genome wide selection in Citrus breeding.

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.