Genetic mapping in a biparental Megathyrsus maximus (Jacq.) population with allele dosage information - Gesteira, Gabriel de Siqueira (2021)
Forage crops are widespread across farmlands worldwide and primarily used to feed livestock, consisting of an important source of economic and environmental sustainability. One of the highest yielding grasses used as a forage crop is the guineagrass (Megathyrsus maximus Jacq.), which presents high nutritional quality and tolerance to many biotic and abiotic factors. The species combines the advantage of genetic recombination through sexual crosses with the ability to fix hybrid vigor in superior genotypes and propagate them by seeds via apomixis. However, little is known about its genomic behavior, mainly due to the high complexity of its autopolyploid genome. In this work, we implemented state-of-the-art methods to construct genetic linkage maps in autopolyploid species, coupled with a multipoint Hidden Markov Model approach. The software MAPpoly can construct genetic linkage maps for ploidy levels up to 12, import data from third-party software, and export maps and genotypic conditional probabilities for further analysis. MAPpoly is easy-to-use and freely available in stable and development versions. We used MAPpoly to construct a dense and informative genetic linkage map for M. maximus using multiple dosage markers, then used a state-of-the-art method to search for QTL along the genome considering relevant traits for M. maximus breeding: canopy height and area, total yield, proportion of leaf blades, foliar and total dry matter yield, leaf and total volumetric density, regrowth capacity, and leaf elongation rate. We extracted DNA from leaf samples of a biparental mapping population containing 224 individuals and sequenced them through the GBS (Genotyping-by-Sequencing) protocol. Raw sequencing data were analyzed to find variants and call genotype dosages for both parents and all individuals in the population. We used five reference genomes of related species during the mapping process due to the absence of a reference genome for M. maximus. Then, we constructed the genetic linkage map and used phenotypic observations of selected traits to isolate the genetic component of the population performance and search for QTL regions along the genome, using a random regression model. We constructed the densest and informative linkage map for the species up to date, with 7095 markers spanning 1746.18 cM of the species genome. There was no evidence of double reduction or preferential pairing in the study population. We found ten QTL associated with seven traits that are relevant to M. maximus breeding, with narrow-sense heritabilities ranging from 0.4127 to 0.1387. The software implementation and the genetic analysis provided in this work can help untangle the genomic organization and solve uncertainties regarding M. maximus evolutionary and taxonomic placement, as well as help to assemble the species genome. The QTL analysis provides a better understanding of the complex genomic behavior involved in the genetic control of relevant traits and may be used to support marker-based selection strategies, thus increasing the efficiency of selection cycles in M. maximus breeding programs.