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Mendeley readers
| Title |
High throughput SNP discovery and genotyping in grapevine (Vitis vinifera L.) by combining a re-sequencing approach and SNPlex technology
|
|---|---|
| Published in |
BMC Genomics, November 2007
|
| DOI | 10.1186/1471-2164-8-424 |
| Pubmed ID | |
| Authors |
Diego Lijavetzky, José Antonio Cabezas, Ana Ibáñez, Virginia Rodríguez, José M Martínez-Zapater |
| Abstract |
Single-nucleotide polymorphisms (SNPs) are the most abundant type of DNA sequence polymorphisms. Their higher availability and stability when compared to simple sequence repeats (SSRs) provide enhanced possibilities for genetic and breeding applications such as cultivar identification, construction of genetic maps, the assessment of genetic diversity, the detection of genotype/phenotype associations, or marker-assisted breeding. In addition, the efficiency of these activities can be improved thanks to the ease with which SNP genotyping can be automated. Expressed sequence tags (EST) sequencing projects in grapevine are allowing for the in silico detection of multiple putative sequence polymorphisms within and among a reduced number of cultivars. In parallel, the sequence of the grapevine cultivar Pinot Noir is also providing thousands of polymorphisms present in this highly heterozygous genome. Still the general application of those SNPs requires further validation since their use could be restricted to those specific genotypes. |
Mendeley readers
The data shown below were compiled from readership statistics for 265 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 5 | 2% |
| United States | 4 | 2% |
| Spain | 3 | 1% |
| Canada | 2 | <1% |
| Sweden | 2 | <1% |
| Italy | 2 | <1% |
| United Kingdom | 2 | <1% |
| Chile | 1 | <1% |
| Norway | 1 | <1% |
| Other | 10 | 4% |
| Unknown | 233 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 92 | 35% |
| Student > Ph. D. Student | 54 | 20% |
| Student > Master | 26 | 10% |
| Student > Doctoral Student | 16 | 6% |
| Student > Postgraduate | 15 | 6% |
| Other | 40 | 15% |
| Unknown | 22 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 199 | 75% |
| Biochemistry, Genetics and Molecular Biology | 27 | 10% |
| Environmental Science | 6 | 2% |
| Computer Science | 2 | <1% |
| Chemical Engineering | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 26 | 10% |