A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Microcollinearity between autopolyploid sugarcane and diploid sorghum genomes

Abstract Background Sugarcane (Saccharum spp.) has become an increasingly important crop for its leading role in biofuel production. The high sugar content species S. officinarum is an octoploid without known diploid or tetraploid progenitors. Commercial sugarcane cultivars are hybrids between S. officinarum and wild species S. spontaneum with ploidy at ~12×. The complex autopolyploid sugarcane genome has not been characterized at the DNA sequence level. Results The microsynteny between sugarcane and sorghum was assessed by comparing 454 pyrosequences of 20 sugarcane bacterial artificial chromosomes (BACs) with sorghum sequences. These 20 BACs were selected by hybridization of 1961 single copy sorghum overgo probes to the sugarcane BAC library with one sugarcane BAC corresponding to each of the 20 sorghum chromosome arms. The genic regions of the sugarcane BACs shared an average of 95.2% sequence identity with sorghum, and the sorghum genome was used as a template to order sequence contigs covering 78.2% of the 20 BAC sequences. About 53.1% of the sugarcane BAC sequences are aligned with sorghum sequence. The unaligned regions contain non-coding and repetitive sequences. Within the aligned sequences, 209 genes were annotated in sugarcane and 202 in sorghum. Seventeen genes appeared to be sugarcane-specific and all validated by sugarcane ESTs, while 12 appeared sorghum-specific but only one validated by sorghum ESTs. Twelve of the 17 sugarcane-specific genes have no match in the non-redundant protein database in GenBank, perhaps encoding proteins for sugarcane-specific processes. The sorghum orthologous regions appeared to have expanded relative to sugarcane, mostly by the increase of retrotransposons. Conclusions The sugarcane and sorghum genomes are mostly collinear in the genic regions, and the sorghum genome can be used as a template for assembling much of the genic DNA of the autopolyploid sugarcane genome. The comparable gene density between sugarcane BACs and corresponding sorghum sequences defied the notion that polyploidy species might have faster pace of gene loss due to the redundancy of multiple alleles at each locus.