Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases

Abstract

Sugarcane (Saccharum spp.) is a clonally propagated outcrossing polyploid crop of great importance in tropical agriculture. Up to now, all sugarcane genetic maps had been developed using either full-sib progenies derived from interspecific crosses or from selfing, both approaches not directly adopted in conventional breeding. We have developed a single integrated genetic map using a population derived from a cross between two pre-commercial cultivars ('SP80-180' x 'SP80-4966') using a novel approach based on the simultaneous maximum-likelihood estimation of linkage and linkage phases method specially designed for outcrossing species. From a total of 1,118 single-dose markers (RFLP, SSR and AFLP) identified, 39% derived from a testcross configuration between the parents segregating in a 1:1 fashion, while 61% segregated 3:1, representing heterozygous markers in both parents with the same genotypes. The markers segregating 3:1 were used to establish linkage between the testcross markers. The final map comprised of 357 linked markers, including 57 RFLPs, 64 SSRs and 236 AFLPs that were assigned to 131 co-segregation groups, considering a LOD score of 5, and a recombination fraction of 37.5 cM with map distances estimated by Kosambi function. The co-segregation groups represented a total map length of 2,602.4 cM, with a marker density of 7.3 cM. When the same data were analyzed using JoinMap software, only 217 linked markers were assigned to 98 co-segregation groups, spanning 1,340 cM, with a marker density of 6.2 cM. The maximum-likelihood approach reduced the number of unlinked markers to 761 (68.0%), compared to 901 (80.5%) using JoinMap. All the co-segregation groups obtained using JoinMap were present in the map constructed based on the maximum-likelihood method. Differences on the marker order within the co-segregation groups were observed between the two maps. Based on RFLP and SSR markers, 42 of the 131 co-segregation groups were assembled into 12 putative homology groups. Overall, the simultaneous maximum-likelihood estimation of linkage and linkage phases was more efficient than the method used by JoinMap to generate an integrated genetic map of sugarcane.

Genetic divergence among elite sugarcane clones (Saccharum officinarum L.) based on cane yield and quality traits from Northern India

“…Considerable difficulties have been encountered in the improvement of sugarcane through hybridization due to narrow base of variation available. Thus progress in breeding of sugarcane, a highly polyploidy with chromosome number in somatic cells (2n) ranging from 80-124 in cultivated and 48-150 in wild types (Prasanna et al, 2005;Garcia et al, 2006). In sugarcane frequently aneuploid is impeded by its narrow gene pool, complex genome, poor fertility, caused by genetic recombination as well as long breeding selection cycle (Singh, 1981).…”

Progression of DNA Marker and the Next Generation of Crop Development

“…Recently, QGENE has been rewritten in the Java language and can be used for analyses of trait and QTL permutation and simulation for populations and as well as traits. Several software packages can be used for constructing linkage maps in out-crossing plant species, using full-sib families derived from two outbreed (non-inbreeding) parent plants (Garcia et al, 2006). Bayesian QTL mapping has received a lot of attention in recent years.…”

Expression Profile of Signal Transduction Components in a Sugarcane Population Segregating for Sugar Content

“…The population is comprised of 498 individuals that segregated for stem sugar content in a normal manner and was previously described by Garcia et al [12] and PapiniTerzi et al [37]. The seven plants presenting extreme values for high sugar (HS) and low sugar (LS) were selected.…”