Many plant species of great economic value (e.g., potato, wheat, cotton, and sugarcane) are polyploids. Despite the essential roles of autopolyploid plants in human activities, our genetic understanding of these species is still poor. Recent progress in instrumentation and biochemical manipulation has led to the accumulation of an incredible amount of genomic data. In this study, we demonstrate for the first time a successful genetic analysis in a highly polyploid genome (sugarcane) by the quantitative analysis of single-nucleotide polymorphism (SNP) allelic dosage and the application of a new data analysis framework. This study provides a better understanding of autopolyploid genomic structure and is a sound basis for genetic studies. The proposed methods can be employed to analyse the genome of any autopolyploid and will permit the future development of high-quality genetic maps to assist in the assembly of reference genome sequences for polyploid species.

Sugarcane is an important crop and a major source of sugar and alcohol. In this study, we performed de novo assembly and transcriptome annotation for six sugarcane genotypes involved in bi-parental crosses. The de novo assembly of the sugarcane transcriptome was performed using short reads generated using the Illumina RNA-Seq platform. We produced more than 400 million reads, which were assembled into 72,269 unigenes. Based on a similarity search, the unigenes showed significant similarity to more than 28,788 sorghum proteins, including a set of 5,272 unigenes that are not present in the public sugarcane EST databases; many of these unigenes are likely putative undescribed sugarcane genes. From this collection of unigenes, a large number of molecular markers were identified, including 5,106 simple sequence repeats (SSRs) and 708,125 single-nucleotide polymorphisms (SNPs). This new dataset will be a useful resource for future genetic and genomic studies in this species.

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.

Sugarcane microsatellites or simple sequence repeats (SSR) were developed in an economical and practical way by mining EST databases. A survey in the SUCEST (sugarcane EST) database revealed a total of 2005 clusters out of 43,141 containing SSRs. Of these, 8.2% were dinucleotide, 30.5% were trinucleotide, and 61.3% were tetranucleotide repeats. Except for dinucleotides, the CG-rich motif types were the most common. Differences in abundance of trinucleotide motif types were observed between EST-SSRs and those isolated from sugarcane genomic libraries. Among the different cDNA libraries used for EST sequencing, SSRs were more frequent in the ones derived from leaf roll (LR). Twenty-three out of 30 tested SSRs produced scorable polymorphisms in 18 sugarcane commercial clones. These EST-SSRs showed a moderate level of polymorphism with some SSRs producing unique fingerprints. The number of alleles observed among the 18 clones evaluated varied from 2 to 15, with an average of 6.04 alleles/locus. The polymorphism information content (PIC) values ranged from 0.28 to 0.90 with a mean of 0.66. The EST-SSRs screened over both parents (SP 80-180; SP 80-4966) and 6 F1 individuals produced 52 segregating markers that could potentially be used for sugarcane mapping. The EST-SSRs were found in clusters that had significant homology to proteins involved in important metabolic pathways such as sugar biosynthesis, proving that EST-SSRs are a valuable tool for the construction of a functional sugarcane map.

Expressed sequence tags (ESTs) offer the opportunity to exploit single, low-copy, conserved sequence motifs for the development of simple sequence repeats (SSRs). The authors have examined the Sugarcane Expressed Sequence Tag database for the presence of SSRs. To test the utility of EST-derived SSR markers, a total of 342 EST-SSRs, which represent a subset of over 2005 SSR-containing sequences that were located in the sugarcane EST database, could be designed from the nonredundant SSR-positive ESTs for possible use as potential genic markers. These EST-SSR markers were used to screen 18 sugarcane (Saccharum spp.) varieties. A high proportion (65.5%) of the above EST-SSRs, which gave amplified fragments of foreseen size, detected polymorphism. The number of alleles ranged from 2 to 24 with an average of 7.55 alleles per locus, while polymorphism information content values ranged from 0.16 to 0.94, with an average of 0.73. The ability of each set of EST-SSR markers to discriminate between varieties was generally higher than the polymorphism information content analysis. When tested for functionality, 82.1% of these 224 EST-SSRs were found to be functional, showing homology to known genes. As the EST-SSRs are within the expressed portion of the genome, they are likely to be associated to a particular gene of interest, improving their utility for genetic mapping; identification of quantitative trait loci, and comparative genomics studies of sugarcane. The development of new EST-SSR markers will have important implications for the genetic analysis and exploitation of the genetic resources of sugarcane and related species and will provide a more direct estimate of functional diversity.