Title |
Parallel selection on gene copy number variations through evolution of three-spined stickleback genomes
|
---|---|
Published in |
BMC Genomics, August 2014
|
DOI | 10.1186/1471-2164-15-735 |
Pubmed ID | |
Authors |
Shotaro Hirase, Haruka Ozaki, Wataru Iwasaki |
Abstract |
Understanding the genetic basis of adaptive evolution is one of the major goals in evolutionary biology. Recently, it has been revealed that gene copy number variations (GCNVs) constitute significant proportions of genomic diversities within natural populations. However, it has been unclear whether GCNVs are under positive selection and contribute to adaptive evolution. Parallel evolution refers to adaptive evolution of the same trait in related but independent lineages, and three-spined stickleback (Gasterosteus aculeatus) is a well-known model organism. Through identification of genetic variations under parallel selection, i.e., variations shared among related but independent lineages, evidence of positive selection is obtained. In this study, we investigated whole-genome resequencing data from the marine and freshwater groups of three-spined sticklebacks from diverse areas along the Pacific and Atlantic Ocean coastlines, and searched for GCNVs under parallel selection. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 7 | 44% |
Unknown | 9 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 75% |
Scientists | 4 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | 5% |
Unknown | 41 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 21% |
Student > Ph. D. Student | 8 | 19% |
Student > Master | 6 | 14% |
Student > Bachelor | 4 | 9% |
Professor > Associate Professor | 3 | 7% |
Other | 8 | 19% |
Unknown | 5 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 27 | 63% |
Biochemistry, Genetics and Molecular Biology | 7 | 16% |
Nursing and Health Professions | 1 | 2% |
Computer Science | 1 | 2% |
Medicine and Dentistry | 1 | 2% |
Other | 0 | 0% |
Unknown | 6 | 14% |