Browsing by Author "Soorni, Aboozar"

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    Assessment of Genetic Diversity and Population Structure in Iranian Cannabis Germplasm
    Soorni, Aboozar; Fatahi, Reza; Haak, David C.; Salami, Seyed Alireza; Bombarely, Aureliano (Nature Publishing Group, 2017-11-15)
    Cannabis sativa has a complex history reflected in both selection on naturally occurring compounds and historical trade routes among humans. Iran is a rich resource of natural populationswhich hold the promise to characterize historical patterns of population structure and genetic diversity within Cannabis. Recent advances in high-throughput DNA sequencing technologies have dramatically increased our ability to produce information to the point that it is now feasible to inexpensively obtain population level genotype information at a large scale. In the present investigation, we have explored the use of Genotyping-By-Sequencing (GBS) in Iranian cannabis. We genotyped 98 cannabis samples 36 from Iranian locations and 26 accessions from two germplasm collections. In total, 24,710 high-quality Single Nucleotide Polymorphisms (SNP) were identified. Clustering analysis by Principal Component Analysis (PCA) identified two genetic clusters among Iranian populations and fineSTRUCTURE analysis identified 19 populations with some geographic partitioning. We defined Iranian cannabis in two main groups using the results of the PCA and discovered some strong signal to define some locations as population according to fineSTRUCTURE analyses. However, single nucleotide variant analysis uncovered a relatively moderate level of variation among Iranian cannabis.
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    Organelle_PBA, a pipeline for assembling chloroplast and mitochondrial genomes from PacBio DNA sequencing data
    Soorni, Aboozar; Haak, David C.; Zaitlin, David; Bombarely, Aureliano (Biomed Central, 2017-01-07)
    Background The development of long-read sequencing technologies, such as single-molecule real-time (SMRT) sequencing by PacBio, has produced a revolution in the sequencing of small genomes. Sequencing organelle genomes using PacBio long-read data is a cost effective, straightforward approach. Nevertheless, the availability of simple-to-use software to perform the assembly from raw reads is limited at present. Results We present Organelle-PBA, a Perl program designed specifically for the assembly of chloroplast and mitochondrial genomes. For chloroplast genomes, the program selects the chloroplast reads from a whole genome sequencing pool, maps the reads to a reference sequence from a closely related species, and then performs read correction and de novo assembly using Sprai. Organelle-PBA completes the assembly process with the additional step of scaffolding by SSPACE-LongRead. The program then detects the chloroplast inverted repeats and reassembles and re-orients the assembly based on the organelle origin of the reference. We have evaluated the performance of the software using PacBio reads from different species, read coverage, and reference genomes. Finally, we present the assembly of two novel chloroplast genomes from the species Picea glauca (Pinaceae) and Sinningia speciosa (Gesneriaceae). Conclusion Organelle-PBA is an easy-to-use Perl-based software pipeline that was written specifically to assemble mitochondrial and chloroplast genomes from whole genome PacBio reads. The program is available at https://github.com/aubombarely/Organelle_PBA