Frontiers in Plant SciencePlant BiologyPeer-reviewed journal article
High-resolution Linkage Map with Allele Dosage Allows the Identification of an Apomixis Region and Complex Traits in Guinea Grass (Megathyrsus maximus)
T. G. Deo, R. C. U. Ferreira, L. A. d. C. Lara, A. d. C. L. Moraes, A. Alves-Pereira, F. A. de Oliveira, A. A. F. Garcia, M. F. Santos, L. Jank, A. P. de Souza
Abstract
Forage grasses are mainly used in animal feed to fatten cattle and dairy herds. Among tropical forage crops that reproduce by seeds, guinea grass (Megathyrsus maximus) is considered one of the most productive. This species has several genomic complexities, such as autotetraploidy and apomixis, due to the process of domestication. 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 about 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 ten 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 apomixis locus by 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.
- organism: plant (other)
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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