Title |
Blood from a turnip: tissue origin of low-coverage shotgun sequencing libraries affects recovery of mitogenome sequences
|
---|---|
Published in |
Mitochondrial DNA Part A, October 2013
|
DOI | 10.3109/19401736.2013.840588 |
Pubmed ID | |
Authors |
F. Keith Barker, Sara Oyler-McCance, Diana F. Tomback |
Abstract |
abstract Next generation sequencing methods allow rapid, economical accumulation of data that have many applications, even at relatively low levels of genome coverage. However, the utility of shotgun sequencing data sets for specific goals may vary depending on the biological nature of the samples sequenced. We show that the ability to assemble mitogenomes from three avian samples of two different tissue types varies widely. In particular, data with coverage typical of microsatellite development efforts (∼1×) from DNA extracted from avian blood failed to cover even 50% of the mitogenome, relative to at least 500-fold coverage from muscle-derived data. Researchers should consider possible applications of their data and select the tissue source for their work accordingly. Practitioners analyzing low-coverage shotgun sequencing data (including for microsatellite locus development) should consider the potential benefits of mitogenome assembly, including internal barcode verification of species identity, mitochondrial primer development, and phylogenetics. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 17% |
United States | 1 | 17% |
United Kingdom | 1 | 17% |
Unknown | 3 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 50% |
Members of the public | 3 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 17 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 3 | 18% |
Researcher | 3 | 18% |
Professor > Associate Professor | 2 | 12% |
Student > Ph. D. Student | 2 | 12% |
Student > Bachelor | 1 | 6% |
Other | 2 | 12% |
Unknown | 4 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 59% |
Biochemistry, Genetics and Molecular Biology | 2 | 12% |
Environmental Science | 1 | 6% |
Computer Science | 1 | 6% |
Unspecified | 1 | 6% |
Other | 0 | 0% |
Unknown | 2 | 12% |