ABSTRACT
A diet rich in phytonutrients from fruit and vegetables has been acknowledged to afford protection against a range of human diseases, but many of the most popular vegetables are low in phytonutrients. Wild relatives of crops may contain allelic variation for genes determining the concentrations of these beneficial phytonutrients, and therefore understanding the genetic basis of this variation is important for breeding efforts to enhance nutritional quality. In this study, lettuce recombinant inbred lines, generated from a cross between wild and cultivated lettuce (Lactuca serriola and Lactuca sativa, respectively), were analysed for antioxidant (AO) potential and important phytonutrients including carotenoids, chlorophyll and phenolic compounds. When grown in two environments, 96 quantitative trait loci (QTL) were identified for these nutritional traits: 4 for AO potential, 2 for carotenoid content, 3 for total chlorophyll content and 87 for individual phenolic compounds (two per compound on average). Most often, the L. serriola alleles conferred an increase in total AOs and metabolites. Candidate genes underlying these QTL were identified by BLASTn searches; in several cases, these had functions suggesting involvement in phytonutrient biosynthetic pathways. Analysis of a QTL on linkage group 3, which accounted for >30% of the variation in AO potential, revealed several candidate genes encoding multiple MYB transcription factors which regulate flavonoid biosynthesis and flavanone 3-hydroxylase, an enzyme involved in the biosynthesis of the flavonoids quercetin and kaempferol, which are known to have powerful AO activity. Follow-up quantitative RT-PCR of these candidates revealed that 5 out of 10 genes investigated were significantly differentially expressed between the wild and cultivated parents, providing further evidence of their potential involvement in determining the contrasting phenotypes. These results offer exciting opportunities to improve the nutritional content and health benefits of lettuce through marker-assisted breeding.
ABSTRACT
BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a powerful tool for genome-wide transcription studies. Unlike microarrays, it has the ability to detect novel forms of RNA such as alternatively spliced and antisense transcripts, without the need for prior knowledge of their existence. One limitation of using SAGE on an organism with a complex genome and lacking detailed sequence information, such as the hexaploid bread wheat Triticum aestivum, is accurate annotation of the tags generated. Without accurate annotation it is impossible to fully understand the dynamic processes involved in such complex polyploid organisms. Hence we have developed and utilised novel procedures to characterise, in detail, SAGE tags generated from the whole grain transcriptome of hexaploid wheat. RESULTS: Examination of 71,930 Long SAGE tags generated from six libraries derived from two wheat genotypes grown under two different conditions suggested that SAGE is a reliable and reproducible technique for use in studying the hexaploid wheat transcriptome. However, our results also showed that in poorly annotated and/or poorly sequenced genomes, such as hexaploid wheat, considerably more information can be extracted from SAGE data by carrying out a systematic analysis of both perfect and "fuzzy" (partially matched) tags. This detailed analysis of the SAGE data shows first that while there is evidence of alternative polyadenylation this appears to occur exclusively within the 3' untranslated regions. Secondly, we found no strong evidence for widespread alternative splicing in the developing wheat grain transcriptome. However, analysis of our SAGE data shows that antisense transcripts are probably widespread within the transcriptome and appear to be derived from numerous locations within the genome. Examination of antisense transcripts showing sequence similarity to the Puroindoline a and Puroindoline b genes suggests that such antisense transcripts might have a role in the regulation of gene expression. CONCLUSION: Our results indicate that the detailed analysis of transcriptome data, such as SAGE tags, is essential to understand fully the factors that regulate gene expression and that such analysis of the wheat grain transcriptome reveals that antisense transcripts maybe widespread and hence probably play a significant role in the regulation of gene expression during grain development.
