Johns Hopkins researchers created the first nearly complete wheat bread genome.
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Johns Hopkins scientists report that they have successfully used two different gene technologies to assemble the most complete sequence of the genome to date. WHEAT, the most commonly grown varieties of wheat used in making bread.
They say, sequences in wheat genomes could help biologists not only better understand the evolutionary history of wheat, but also improve the search for more rigid, more pest-free and non -dry wheat varieties that help increase the world’s population.
“After many years of testing, we were able to produce a high-quality assembly of this challenging genome,” he said. Steven Salzberg, Ph.D., Bloomberg Distinguished Professor of Biomedical Engineering at Johns Hopkins University Whiting School of Engineering and the McKusick-Nathans Institute of Genetic Medicine at Johns Hopkins University School of Medicine.
According to Johns Hopkins scientists, bread wheat has one of the most complex genomes known to science, containing an estimated 16 billion DNA-based pairs and six copies of seven chromosome. In comparison, the human genome is about five times smaller, with about three billion base pairs and two copies of 23 chromosomes. Previously published versions of the wheat bread genome contained multiple gaps in multiple repeats of the DNA sequence.
“The repetitive nature of this genome makes it difficult to fully follow,” Salzberg said. “It’s like trying to put together a jigsaw puzzle in a landscape scene with a big blue sky. There are a lot of identical, small pieces to assemble.”
The newly compiled wheat bread genome, which costs $ 300,000 for sequencing alone, takes a year for Johns Hopkins researchers to gather 1.5 trillion raw data bases in a final assembly that 15.34 billion base pairs.
To do this, Salzberg and his tem used two different genome sequencing technologies: high-throughput short-read sequences and long-read, a molecular sequence. As its name implies, the high flow sequence produces many large DNA base pairs quickly and cheaply, even if the fragments are very short-only 150 base pairs are long. for this project. To help assemble the repetitive areas, the Johns Hopkins team used real-time, a sequencing molecule, that could read DNA because it was synthesized at a small, nano-scale well in a chip. The technology allows scientists to read up to 20,000 base pairs at a time by measuring the fluorescent signals emitted as each DNA base is copied.
Salzberg said that sequencing a genome of this size requires not only genetic skill, but also including multiple computational sources available to small research institutions around the world. The team relies heavily on the Maryland Advanced Research Computing Center, a computing center shared by Hopkins and the University of Maryland, with more than 20,000 computer cores (CPUs) and more than 20 petabytes of stored data. The tem used nearly 100 years of CPU to put together this genome.
Salzberg and his team are also involved in the collaborative effort reported in the journal NATURE to follow a generation of wheat, Aegilops tauschii, which is often called goatgrass and is still found in parts of Asia and Europe. Its genome is approximately one-third the size of the wheat bread genome, but has the same level of replication. The work, done as part of a collaborative effort between the University of California, Davis; Johns Hopkins; and the University of Georgia, took nearly four years to complete. Using order-clone genome sequencing, shotgun sequencing and optical genome mapping, the team collected the 4.3 billion nucleotides that make up the plant sequence. With this information, the remaining group identified the sequences that make up the genes responsible for specific plant characteristics.
Other researchers involved in the wheat bread study include Aleskey V. Zimin and Daniela Puiu, both members of Salzberg’s laboratory at the Center for Computational Biology at the McKusick-Nathans Institute of Genetic Medicine; Sarah Kingan and Richard Hall of Pacific Biosciences in Menlo Park, California; and Bernardo J. Clavijo of the Earlham Institute in Norwich, United Kingdom.
This work was supported in part by the National Science Foundation (IOS-1238231 and IOS-1444893) and the National Human Genome Research Institute (R01 HG006677).
None of the authors reported any competing or conflicting interests related to the research.
* This release was edited on November 29 2017 to correct the compliance information and assembly technology used in this research.