Title |
Genome-wide association studies for agronomical traits in a world wide spring barley collection
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Published in |
BMC Plant Biology, January 2012
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DOI | 10.1186/1471-2229-12-16 |
Pubmed ID | |
Authors |
Raj K Pasam, Rajiv Sharma, Marcos Malosetti, Fred A van Eeuwijk, Grit Haseneyer, Benjamin Kilian, Andreas Graner |
Abstract |
Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) provide a promising tool for the detection and fine mapping of quantitative trait loci (QTL) underlying complex agronomic traits. In this study we explored the genetic basis of variation for the traits heading date, plant height, thousand grain weight, starch content and crude protein content in a diverse collection of 224 spring barleys of worldwide origin. The whole panel was genotyped with a customized oligonucleotide pool assay containing 1536 SNPs using Illumina's GoldenGate technology resulting in 957 successful SNPs covering all chromosomes. The morphological trait "row type" (two-rowed spike vs. six-rowed spike) was used to confirm the high level of selectivity and sensitivity of the approach. This study describes the detection of QTL for the above mentioned agronomic traits by GWAS. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | <1% |
Germany | 2 | <1% |
Netherlands | 2 | <1% |
Brazil | 2 | <1% |
Spain | 2 | <1% |
Denmark | 2 | <1% |
United Kingdom | 2 | <1% |
Australia | 1 | <1% |
Sweden | 1 | <1% |
Other | 7 | 2% |
Unknown | 407 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 105 | 24% |
Researcher | 96 | 22% |
Student > Master | 56 | 13% |
Student > Doctoral Student | 32 | 7% |
Student > Bachelor | 23 | 5% |
Other | 56 | 13% |
Unknown | 63 | 15% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 292 | 68% |
Biochemistry, Genetics and Molecular Biology | 42 | 10% |
Environmental Science | 4 | <1% |
Engineering | 4 | <1% |
Computer Science | 3 | <1% |
Other | 23 | 5% |
Unknown | 63 | 15% |