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Seed oil of Lesquerella (Physaria fendelri) contains 55-60% hydroxy fatty acid (HFA) that has important industrial application. A
high throughput, large scale sequencing of transcripts from developing Lesquerella seeds was carried out by 454 pyrosequencing
to generate a database for quality improvement of seed oil and other agronomic traits. Deep mining and characterization of acyl
lipid genes were conducted to uncover candidate genes for further studies of mechanisms underlying HFA and seed oil synthesis. A
total of 651 mega bases of raw sequences from an mRNA sample of developing seeds were acquired. Bioinformatic analysis of these
sequences revealed 59,914 transcripts representing 26,995 unique genes that include nearly all known seed expressed genes. Based on
sequence similarity with known plant proteins, about 74% (19,861) genes matched with annotated coding genes. Among them, 95%
(18,868) showed highest sequence homology with Arabidopsis genes, which will allow translation of genomics and genetics findings
from Arabidopsis to Lesquerella. Using Arabidopsis acyl lipid genes as queries, we searched the transcriptome assembly and identified
615 Lesquerella genes involved in all known pathways of acyl lipid metabolism. Further deep mining the transcriptome assembly led
to identification of almost all Lesquerella genes involved in fatty acid and triacylglycerol synthesis. Moreover, we characterized the
spatial and temporal expression profiles of 15 key genes using the quantitative PCR assay. The information obtained from data mining
and gene expression profiling will provide a resource not only for the study of HFA metabolism but also for the biotechnological
improvement of HFA production in Lesquerella.
Biography
Grace Chen has obtained her PhD from University of Wisconsin at Madison and did her Postdoctoral studies from University of California, Plant Gene Expression Center. She has published more than 35 papers in reputed journals and she is globally recognized as an expert on oilseed biotechnology.