| Chapter title |
Methods for Genotyping-by-Sequencing
|
|---|---|
| Chapter number | 16 |
| Book title |
Genotyping
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6442-0_16 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6440-6, 978-1-4939-6442-0
|
| Authors |
Beth A. Rowan, Danelle K. Seymour, Eunyoung Chae, Derek S. Lundberg, Detlef Weigel, Rowan, Beth A., Seymour, Danelle K., Chae, Eunyoung, Lundberg, Derek S., Weigel, Detlef |
| Abstract |
A major goal for biologists is to understand the connection between genes and phenotypic traits, and genetic mapping in experimental populations remains a powerful approach for discovering the causal genes underlying phenotypes. For genetic mapping, the process of genotyping was previously a major rate-limiting step. Modern sequencing technology has greatly improved the resolution and speed of genetic mapping by reducing the time, labor, and cost per genotyping marker. In addition, the ability to perform genotyping-by-sequencing (GBS) has facilitated large-scale population genetic analyses by providing a simpler way to survey segregating genetic variation in natural populations. Here we present two protocols for GBS, using the Illumina platform, that can be applied to a wide range of genotyping projects in different species. The first protocol is for genotyping a subset of marker positions genome-wide using restriction digestion, and the second is for preparing inexpensive paired-end whole-genome libraries. We discuss the suitability of each approach for different genotyping applications and provide notes for adapting these protocols for use with a liquid-handling robot. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 57 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 29% |
| Student > Master | 8 | 14% |
| Student > Bachelor | 7 | 12% |
| Student > Ph. D. Student | 6 | 10% |
| Student > Postgraduate | 3 | 5% |
| Other | 10 | 17% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 54% |
| Biochemistry, Genetics and Molecular Biology | 11 | 19% |
| Neuroscience | 2 | 3% |
| Arts and Humanities | 1 | 2% |
| Computer Science | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 9 | 15% |