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06:01
Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions
Published on: January 7, 2019
More than 1,000 putative new human signalling proteins revealed by EST data mining
J Schultz1, T Doerks, C P Ponting
1[1] EMBL, Heidelberg, Germany. [2] Max-Delbrück-Center, Berlin-Buch, Germany.
Nature Genetics
|June 3, 2000
Summary
Researchers developed a new method to efficiently identify novel human signaling genes from large EST databases. This approach accelerates gene discovery and aids in cloning new signaling proteins.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Expressed Sequence Tag (EST) databases contain over 1.6 million human sequences.
- Identifying novel genes within large EST databases is challenging due to scale, sequencing errors, and low similarity between distant homologues.
Purpose of the Study:
- To develop an improved method for identifying novel human genes from EST databases.
- To facilitate the discovery and cloning of new human signaling genes and proteins.
Main Methods:
- Coupling BLAST-based searches with a domain identification protocol to filter candidate homologues.
- Large-scale analysis of 100 signaling domain families.
- In silico cloning using genomic and EST sequence data.
Main Results:
- Identified ESTs representing over 1,000 novel human signaling genes.
- Discovered ESTs for at least 106 new small GTPases, with 6 potentially new subfamilies.
- Successfully performed in silico cloning of a novel GTPase with two catalytic domains.
Conclusions:
- The developed method effectively identifies novel human signaling genes from large EST datasets.
- The identified ESTs provide a valuable resource for rapid cloning of novel human signaling proteins.
- This approach aids in the discovery of previously unidentified full-length protein sequences.
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