| Chapter title |
Bioinformatics: identification of markers from next-generation sequence data.
|
|---|---|
| Chapter number | 3 |
| Book title |
Plant Genotyping
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-1966-6_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-1965-9, 978-1-4939-1966-6
|
| Authors |
Pradeep Ruperao, David Edwards, Ruperao, Pradeep, Edwards, David |
| Abstract |
With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 5% |
| Belgium | 1 | 5% |
| Unknown | 18 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 40% |
| Student > Ph. D. Student | 4 | 20% |
| Student > Master | 3 | 15% |
| Student > Bachelor | 2 | 10% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 60% |
| Biochemistry, Genetics and Molecular Biology | 4 | 20% |
| Computer Science | 2 | 10% |
| Engineering | 1 | 5% |
| Unknown | 1 | 5% |