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1.
Front Plant Sci ; 11: 15, 2020.
Article in English | MEDLINE | ID: mdl-32161603

ABSTRACT

Forage grasses are mainly used in animal feed to fatten cattle and dairy herds, and guinea grass (Megathyrsus maximus) is considered one of the most productive of the tropical forage crops that reproduce by seeds. Due to the recent process of domestication, this species has several genomic complexities, such as autotetraploidy and aposporous apomixis. Consequently, approaches that relate phenotypic and genotypic data are incipient. In this context, we built a linkage map with allele dosage and generated novel information of the genetic architecture of traits that are important for the breeding of M. maximus. From a full-sib progeny, a linkage map containing 858 single nucleotide polymorphism (SNP) markers with allele dosage information expected for an autotetraploid was obtained. The high genetic variability of the progeny allowed us to map 10 quantitative trait loci (QTLs) related to agronomic traits, such as regrowth capacity and total dry matter, and 36 QTLs related to nutritional quality, which were distributed among all homology groups (HGs). Various overlapping regions associated with the quantitative traits suggested QTL hotspots. In addition, we were able to map one locus that controls apospory (apo-locus) in HG II. A total of 55 different gene families involved in cellular metabolism and plant growth were identified from markers adjacent to the QTLs and APOSPORY locus using the Panicum virgatum genome as a reference in comparisons with the genomes of Arabidopsis thaliana and Oryza sativa. Our results provide a better understanding of the genetic basis of reproduction by apomixis and traits important for breeding programs that considerably influence animal productivity as well as the quality of meat and milk.

2.
BMC Res Notes ; 9: 152, 2016 Mar 10.
Article in English | MEDLINE | ID: mdl-26964874

ABSTRACT

BACKGROUND: Forage grasses of the African genus Urochloa (syn. Brachiaria) are the basis of Brazilian beef production, and there is a strong demand for high quality, productive and adapted forage plants. Among the approximately 100 species of the genus Urochloa, Urochloa decumbens is one of the most important tropical forage grasses used for pastures due to several of its agronomic attributes. However, the level of understanding of these attributes and the tools with which to control them at the genetic level are limited, mainly due to the apomixis and ploidy level of this species. In this context, the present study aimed to identify and characterize molecular microsatellite markers of U. decumbens and to evaluate their cross-amplification in other Urochloa species. FINDINGS: Microsatellite loci were isolated from a previously constructed enriched library from one U. decumbens genotype. Specific primers were designed for one hundred thirteen loci, and ninety-three primer pairs successfully amplified microsatellite regions, yielding an average of 4.93 alleles per locus. The polymorphism information content (PIC) values of these loci ranged from 0.26 to 0.85 (average 0.68), and the associated discriminating power (DP) values ranged from 0.22 to 0.97 (average 0.77). Cross-amplification studies demonstrated the potential transferability of these microsatellites to four other Urochloa species. Structure analysis revealed the existence of three distinct groups, providing evidence in the allelic pool that U. decumbens is closely related to Urochloa ruziziensis and Urochloa brizantha. The genetic distance values determined using Jaccard's coefficient ranged from 0.06 to 0.76. CONCLUSIONS: The microsatellite markers identified in this study are the first set of molecular markers for U. decumbens species. Their availability will facilitate understanding the genetics of this and other Urochloa species and breeding them, and will be useful for germplasm characterization, linkage mapping and marker-assisted selection.


Subject(s)
Genetic Loci , Microsatellite Repeats/genetics , Poaceae/genetics , Polymerase Chain Reaction/methods , Genetic Markers , Models, Genetic , Phylogeny , Software
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