Yale Scientists Report Evolution Preserved in Pseudogenes
Yale scientists, using a computational approach, have found approximately 10,000 gene-like sequences or ‘pseudogenes’ in the human genome. Their work is reported in the current issue of Genome Research.
Pseudogenes are DNA sequences that have high sequence similarity with a functional gene, but are disabled or non-functional. Pseudogenes are generally not transcribed and fail to produce functional mRNA transcripts; they cannot produce protein molecules, the hallmark of functional genes.
The report of the Human Genome Project estimated that human genome contains about 30,000 functional genes. This report finds that there exists a non-functional “dead” pseudogene for every three functional “live” genes.
The paper is entitled, “Millions of Years of Evolution Preserved: A Comprehensive Catalogue of the Processed Pseudogenes in the Human Genome.”
“Our study has tremendous impact on the study of human evolution and phylogenies. The pseudogenes we discovered were actually created from ancient genes that existed in the genome of human ancestors millions of years ago,” said Zhaolei Zhang, a post-doctoral fellow and first author, working with Mark Gerstein, the Albert L Williams Associate Professor of Biomedical Informatics
A recent study suggested that existence of a pseudogene might have caused errors in a widely used tumor diagnostics assay.
Several established public and commercial genomic databases have started to incorporate the pseudogene data so they will become standard annotation.
“Pseudogenes offer snapshots of what the genes looked like millions of years ago. We can compare the sequence of these ancient genes and the genes found in the present-day mammals such as human, mouse and chimpanzee,” said Zhang. “We study how they have changed in the different species and how the changes affect the evolution of individual species.”
Other authors on the study are Paul M. Harrison an associate research Scientist at MB&B and Yin Liu a graduate student in the Computational Biology & Bioinformatics program. The work was funded by a grant from National Institute of Health to Yale Center of Excellence in Genomic Sciences. Citation: Genome Research 13: (Dec 2003)