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Sorghum genome sequencing by methylation filtration
Authors:Bedell Joseph A  Budiman Muhammad A  Nunberg Andrew  Citek Robert W  Robbins Dan  Jones Joshua  Flick Elizabeth  Rholfing Theresa  Fries Jason  Bradford Kourtney  McMenamy Jennifer  Smith Michael  Holeman Heather  Roe Bruce A  Wiley Graham  Korf Ian F  Rabinowicz Pablo D  Lakey Nathan  McCombie W Richard  Jeddeloh Jeffrey A  Martienssen Robert A
Affiliation:1Bioinformatics, Orion GenomicsSaint Louis, MissouriUnited States of America;2Library Construction, Orion GenomicsSaint Louis, MissouriUnited States of America;3Sequencing, Orion GenomicsSaint Louis, MissouriUnited States of America;4Biomarkers, Orion GenomicsSaint Louis, MissouriUnited States of America;5Department of Chemistry and Biochemistry, University of OklahomaNorman, OklahomaUnited States of America;6Genome Center, University of CaliforniaDavis, CaliforniaUnited States of America;7The Institute for Genomic Research, RockvilleMarylandUnited States of America;8Business, Orion GenomicsSaint Louis, MissouriUnited States of America;9Cold Spring Harbor Laboratory, Cold Spring HarborNew YorkUnited States of America;University of WisconsinUnited States of America
Abstract:Sorghum bicolor is a close relative of maize and is a staple crop in Africa and much of the developing world because of its superior tolerance of arid growth conditions. We have generated sequence from the hypomethylated portion of the sorghum genome by applying methylation filtration (MF) technology. The evidence suggests that 96% of the genes have been sequence tagged, with an average coverage of 65% across their length. Remarkably, this level of gene discovery was accomplished after generating a raw coverage of less than 300 megabases of the 735-megabase genome. MF preferentially captures exons and introns, promoters, microRNAs, and simple sequence repeats, and minimizes interspersed repeats, thus providing a robust view of the functional parts of the genome. The sorghum MF sequence set is beneficial to research on sorghum and is also a powerful resource for comparative genomics among the grasses and across the entire plant kingdom. Thousands of hypothetical gene predictions in rice and Arabidopsis are supported by the sorghum dataset, and genomic similarities highlight evolutionarily conserved regions that will lead to a better understanding of rice and Arabidopsis.
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