Title |
Separating homeologs by phasing in the tetraploid wheat transcriptome
|
---|---|
Published in |
Genome Biology, June 2013
|
DOI | 10.1186/gb-2013-14-6-r66 |
Pubmed ID | |
Authors |
Ksenia V Krasileva, Vince Buffalo, Paul Bailey, Stephen Pearce, Sarah Ayling, Facundo Tabbita, Marcelo Soria, Shichen Wang, IWGS Consortium, Eduard Akhunov, Cristobal Uauy, Jorge Dubcovsky |
Abstract |
The high level of identity among duplicated homoeologous genomes in tetraploid pasta wheat presents substantial challenges for de novo transcriptome assembly. To solve this problem, we develop a specialized bioinformatics workflow that optimizes transcriptome assembly and separation of merged homoeologs. To evaluate our strategy, we sequence and assemble the transcriptome of one of the diploid ancestors of pasta wheat, and compare both assemblies with a benchmark set of 13,472 full-length, non-redundant bread wheat cDNAs. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 9 | 27% |
United States | 7 | 21% |
Australia | 2 | 6% |
France | 2 | 6% |
Argentina | 1 | 3% |
Sweden | 1 | 3% |
Germany | 1 | 3% |
Hong Kong | 1 | 3% |
Unknown | 9 | 27% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 19 | 58% |
Members of the public | 12 | 36% |
Science communicators (journalists, bloggers, editors) | 2 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 6 | 2% |
United States | 3 | 1% |
Italy | 2 | <1% |
Germany | 2 | <1% |
Argentina | 2 | <1% |
Sweden | 2 | <1% |
Austria | 1 | <1% |
Australia | 1 | <1% |
Brazil | 1 | <1% |
Other | 5 | 2% |
Unknown | 223 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 64 | 26% |
Researcher | 60 | 24% |
Student > Master | 21 | 8% |
Student > Bachelor | 17 | 7% |
Student > Doctoral Student | 15 | 6% |
Other | 51 | 21% |
Unknown | 20 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 174 | 70% |
Biochemistry, Genetics and Molecular Biology | 33 | 13% |
Computer Science | 11 | 4% |
Engineering | 3 | 1% |
Materials Science | 2 | <1% |
Other | 2 | <1% |
Unknown | 23 | 9% |