Bridging expressed sequence alignments through targeted cDNA sequencing.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Identifying the complete set of genes within a genome is a significant challenge in genomic research.
• Aligning expressed sequences (RNA and EST) with genomic sequences aids gene characterization, but often results in numerous alignments needing consolidation.
• High-throughput EST sequencing is inefficient for closing alignment gaps due to its non-selective nature.

Purpose of the Study:

• To develop and validate a novel approach for bridging sequence alignments using targeted cDNA sequencing.
• To efficiently characterize novel or incomplete genes by generating overlapping sequences.

Main Methods:

• Alignment of human expressed sequences (GenBank v124) with genomic sequences (NCBI build 24) using the LEADS software system.
• Selection of 948 alignment pairs based on EST clone information and/or homology to known proteins.
• Application of reverse transcriptase PCR and sequencing to generate overlapping sequences for selected alignment pairs.

Main Results:

• Successful sequencing of 363 out of 948 targeted alignment pairs.
• Characterization of over 60 novel or incomplete human genes in UniGene build 153.
• Demonstration that the integrated strategy efficiently generates overlapping sequences.

Conclusions:

• An integrated strategy combining computational prediction and targeted experimental cDNA sequencing is effective for full genome characterization.
• This approach efficiently bridges sequence alignment gaps, enabling the identification of complete gene structures.
• The method significantly advances the ability to identify and characterize genes within complex genomes.