Title |
Filtering "genic" open reading frames from genomic DNA samples for advanced annotation
|
---|---|
Published in |
BMC Genomics, June 2011
|
DOI | 10.1186/1471-2164-12-s1-s5 |
Pubmed ID | |
Authors |
Sara D'Angelo, Nileena Velappan, Flavio Mignone, Claudio Santoro, Daniele Sblattero, Csaba Kiss, Andrew RM Bradbury |
Abstract |
In order to carry out experimental gene annotation, DNA encoding open reading frames (ORFs) derived from real genes (termed "genic") in the correct frame is required. When genes are correctly assigned, isolation of genic DNA for functional annotation can be carried out by PCR. However, not all genes are correctly assigned, and even when correctly assigned, gene products are often incorrectly folded when expressed in heterologous hosts. This is a problem that can sometimes be overcome by the expression of protein fragments encoding domains, rather than full-length proteins. One possible method to isolate DNA encoding such domains would to "filter" complex DNA (cDNA libraries, genomic and metagenomic DNA) for gene fragments that confer a selectable phenotype relying on correct folding, with all such domains present in a complex DNA sample, termed the "domainome". |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 3% |
France | 1 | 3% |
Italy | 1 | 3% |
Germany | 1 | 3% |
Unknown | 33 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 27% |
Student > Ph. D. Student | 9 | 24% |
Professor > Associate Professor | 5 | 14% |
Student > Bachelor | 4 | 11% |
Unspecified | 1 | 3% |
Other | 2 | 5% |
Unknown | 6 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 16 | 43% |
Biochemistry, Genetics and Molecular Biology | 5 | 14% |
Engineering | 2 | 5% |
Environmental Science | 1 | 3% |
Computer Science | 1 | 3% |
Other | 5 | 14% |
Unknown | 7 | 19% |