Utilizing high-throughput genomics methodologies to explore transcritomes and exomes Xiaojing Hong , University of Iowa Follow

[摘要] High-throughput genomics methodologies provide us the methods and solutions to the research fields of genomes, transcriptomes and proteomics. In my study, we utilized different high-throughput genomics methodologies to explore the exomes of human patients as well as transcriptomes of Drosophila melanogaster and Daphnia pulex . Exome sequencing, an efficient strategy to sequence the coding regions of the genome, helped us to identify potential disease causing mutations in two human diseases (Renal Agenesis and Cleft lip with or without palate). Although exome sequencing is mostly used to identify mutations underling Mendelian disorders, we chose informative pedigrees that were transmitted in Mendelian fashion for our study. Identification of new genes will be expected to significantly impact our understanding of human development and human diseases. RNA-Seq, a high-throughput sequencing technology to sequence cDNA in a sample, was utilized to explore the transcriptome of the microcrustacean Daphnia pulex . Daphnia pulex is a keystone species of freshwater ecosystems and are routinely used to determine the toxicity of aqueous solutions and to gauge the quality of inland water. Treatment of Daphnia pulex with different heavy metals followed by RNA-Seq analysis revealed us specific gene expression patterns that would provide new insights into their biological and toxicological responses to these environmental contaminants. Also these studies will help us to discover new genes that are not expressed during normal development. We also developed a new technology that utilizes microarray-based exome capture prior to RNA-Seq to faithfully annotate tissue specific transcriptomes in Drosophila melanogaster . We showed that this methodology was efficient for cataloging tissue-specific transcriptomes in which specific classes of genes or transcripts can be targeted for capture and sequence, thus reducing the significant sequencing depth normally required for accurate annotation.