Fine mapping of the peach pollen sterility gene (Ps/ps) and detection of markers for marker-assisted selection

In peach, pollen sterility, expressed as absence of pollen in the anthers, segregates as an undesired trait in breeding programs. Pollen fertility screening in progenies is not a common practice mainly because it does not affect fruit set since cross-pollination is frequent. It is also a time-consuming activity that coincides with the busy pollination season. Segregation for this trait could be avoided by using molecular markers to identify appropriate parents or male sterile plants for early culling in progenies expected to segregate, thus increasing breeding efficiency. In peach, pollen sterility is determined by a recessive allele in homozygosis of the major gene, Ps/ps, located on chromosome 6. In this work, using a conventional mapping approach combined with bulked segregant analysis using resequencing data, we fine mapped Ps to a region of almost 160 kb and developed molecular markers for marker-assisted breeding. These markers were validated in plant materials from three peach breeding programs, including progenies, advanced selections, and cultivars, allowing us to determine that the frequency of the ps allele is high (0.23) and also to infer the genotypes of a large collection of cultivars and advanced breeding lines.info:eu-repo/semantics/acceptedVersio

Fine mapping of the peach pollen sterility gene (Ps/ps) and detection of markers for marker-assisted selection

Altres ajuts: CERCA Programme/Generalitat de CatalunyaIn peach, pollen sterility, expressed as absence of pollen in the anthers, segregates as an undesired trait in breeding programs. Pollen fertility screening in progenies is not a common practice mainly because it does not affect fruit set since cross-pollination is frequent. It is also a time-consuming activity that coincides with the busy pollination season. Segregation for this trait could be avoided by using molecular markers to identify appropriate parents or male sterile plants for early culling in progenies expected to segregate, thus increasing breeding efficiency. In peach, pollen sterility is determined by a recessive allele in homozygosis of the major gene, Ps/ps, located on chromosome 6. In this work, using a conventional mapping approach combined with bulked segregant analysis using resequencing data, we fine mapped Ps to a region of almost 160 kb and developed molecular markers for marker-assisted breeding. These markers were validated in plant materials from three peach breeding programs, including progenies, advanced selections and cultivars, allowing us to determine that the frequency of the ps allele is high (0.23) and also to infer the genotypes of a large collection of cultivars and advanced breeding lines

Population genetic analysis of brazilian peach breeding germplasm.

ABSTRACT Peach has great economic and social importance in Brazil. Diverse sources of germplasm were used to introduce desirable traits in the Brazilian peach breeding pool, composed mainly by local selections and accessions selected from populations developed by the national breeding programs, adapted to subtropical climate, with low chill requirement, as well as accessions introduced from several countries. In this research, we used SSR markers, selected by their high level of polymorphism, to access genetic diversity and population structure of a set composed by 204 peach selected genotypes, based on contrasting phenotypes for valuable traits in peach breeding. A total of 80 alleles were obtained, giving an average of eight alleles per locus. In general, the average value of observed heterozygosity (0.46) was lower than the expected heterozygosity (0.63). STRUCTURE analysis assigned 162 accessions splitted into two subpopulations based mainly on their flesh type: melting (96) and non-melting (66) flesh cultivars. The remaining accessions (42) could not be assigned under the 80% membership coefficient criteria. Genetic variability was greater in melting subpopulation compared to non-melting. Additionally, 55% of the alleles present in the breeding varieties were also present in the founder varieties, indicating that founding clones are well represented in current peach cultivars and advanced selections developed. Overall, this study gives a first insight of the peach genetic variability available and evidence for population differentiation (structure) in this peach panel to be exploited and provides the basis for genome-wide association studies

Caracterização de cultivares de pessegueiro e de nectarineira por marcadores moleculares

Em espécies de estreita base genética, como o pessegueiro e a nectarineira (Prunus persica (L.) Batsch), a utilização de marcadores moleculares para a caracterização de cultivares é de grande importância, além do potencial de uso para fins de proteção. As técnicas de eletroforese em gel e RAPD foram empregadas com o objetivo de caracterizar as cultivares de pessegueiro Granada, Esmeralda, Jade, Eldorado, Riograndense, Capdeboscq, Aldrighi, Precocinho, Diamante, Turmalina, Maciel, BR-1, Pepita, Coral, Chinoca, Marfim, Chiripá, Della Nona e Planalto, e as de nectarineira Dulce e Anita. Foram analisadas isoenzimas de 6-fosfogluconato desidrogenase e fosfatase ácida em pólen, peroxidase, fosfoglucoisomerase, aspartato transaminase e isocitrato desidrogenase em folhas, e malato desidrogenase, leucina aminopeptidase e fosfoglucomutase em pólen e folhas. Dos 50 primers testados, 11 foram escolhidos para análise de RAPD em folhas. As análises de similaridade e de agrupamento entre os genótipos foram feitas empregando-se o coeficiente de Jaccard e o método da média aritmética não ponderada. Apesar das diferenças detectadas nas isoenzimas de malato desidrogenase em pólen e folhas de pessegueiro e nectarineira, o baixo polimorfismo apresentado pelos demais sistemas não permitiu a caracterização de todas as cultivares por essa técnica. Os marcadores RAPD, associados ou não à eletroforese de isoenzimas, foram eficientes para caracterizar as cultivares de pessegueiro e nectarineira

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost