Adjunct Assistant Professor
In recent years, technological advances in fields such as sequencing have transformed certain aspects of biology into an information-based discipline.
To make this abundance of data—often called Big Data—useful to researchers and breeders, it needs to be organized and made accessible. Towards this goal, the Mueller lab designs and implements databases that assist scientists in their research and plant breeders in more efficient crop improvement.
Our databases and software make transcriptomic, genotypic and phenotypic data from thousands of experiments accessible to the public, often focusing on under-researched staple crops from food-insecure regions. A method called Genomic Selection that uses high-throughput genotyping technologies, such as genotyping-by-sequencing (GBS), and large phenotyping data sets allows for rapid prediction of desirable traits in new plant crosses.
Based on these tools, the Mueller laboratory collaborates on a variety of different projects. With the Nextgen Cassava project, we have created Cassavabase, a database specifically designed for cassava breeders in Africa. We coordinate the Solanaceae Genomics Network—a compilation of all the genetic information known about solanaceous plants, such as tomato, petunia and Nicotiana. We are also developing breeding databases for yam, sweet potato and the cooking banana and we work with the Genomic and Open-source Breeding Informatics Initiative (GOBII) to streamline crop breeding for five staple crops—wheat, rice, maize, sorghum and chickpea. Finally, the Mueller group is involved in multiple genome sequencing projects, including tomato, coffee, petunia and Nicotania benthamiana.