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Ryan McCormick

Ryan McCormick

Advisor: Dr. John E. Mullet

Department of Biochemistry & Biophysics
2128 TAMU

College Station , TX 77843-2128

Education:

  1. B.S. Biology, Texas A&M University 2009
  2. M.S. Biology, Texas A&M University 2012

Biography:

Entered Program in 2012

See curriculum vitae here (updated 2013): https://drive.google.com/file/d/0B9S7nr_CWEh-Y3Y4alJXUUJFZms/edit?usp=sharing

Research Project:

Sorghum bicolor is a valuable plant crop used commercially for grain, forage, sugar, and bioenergy production. Increasing yields for these applications without increasing input from natural resources is necessary to sustainably meet future demand. The generation of superior plant cultivars that produce more without increased input is facilitated by methods that can rapidly and accurately acquire plant genotypic and phenotypic data, and our work focuses on development and application of genomic and phenomic methods. One product of our ongoing work in analyzing sorghum genomic sequence data is the Recalibration and Interrelation of genomic sequence data with the GATK (RIG) workflow. This variant calling workflow provides a means by which different sources of genomic sequence data can be interrelated and used to inform the modern machine learning techniques implemented within the Broad Institute's Genome Analysis Toolkit (GATK). This workflow readily interrelates genomic sequence data to generate accurate variant call sets that can be used to dissect the genetic basis of agriculturally important traits such as maturity, height, and grain yield. Additionally, to increase the rate at which germplasm can be evaluated, we are exploring the application of image-based phenotyping methods. One of our approaches is the use of computer vision techniques to acquire three dimensional reconstructions of sorghum plants; these reconstructions can be used to measure phenotypes and used as input to crop modeling applications. Future efforts will continue to develop and apply these methods to the genetic dissection of agriculturally important traits. This work will facilitate the rapid and accurate acquisition of the data necessary to increase the rate of crop improvement.

Broader Impacts of Research Project: 

Projected increases in global population and affluency demand that agricultural production increases by 60% between 2007 and 2050. Meeting this demand without further depleting limited natural resources is necessary to maintain food security, energy security, and environmental health. As the world's fifth most produced cereal crop and a promising bioenergy crop, Sorghum bicolor is a valuable agricultural crop used commercially for grain, forage, sugar, and bioenergy production. Our work aims to employ high throughput genotyping with image-based phenotyping to increase the rate at which the genetic regulation of important agricultural traits can be determined.