Research

 

Trait Identification and Genetics

Genome-wide association studies

Purdue Contemporary SRWW germplasm: We have assembled > 400 soft red winter wheat (SRWW) ever produced by the small grains breeding program over the last few decades. These are all crosses made after 1980 but the parental lines, themselves, are mainly from Purdue breeding program. They represent germplasm developed by elite x elite crosses. This Purdue panel is being genotyped using next-gen sequencing methods. Our objective is to characterize Fusarium head blight (FHB) resistance in this germplasm using field and greenhouse approaches. We will also characterize agronomic traits. A preliminary yield trial conducted for a subset of these materials to increase seed and evaluate winter hardiness is depicted below. 

 

 

Hyperspectral aerial image taken from Purdue panel preliminary trial 2017 by remote sensing team led by Dr. Melba Crawford.

Hyperspectral aerial image taken from Purdue panel preliminary trial 2017 by remote sensing team led by Dr. Melba Crawford.

 

United State SRWW Historical Panel: We have assembled >300 historical and contemporary SRWW accessions (named US Wheat History, USWH panel) by sampling from US genebank in Aberdeen, ID. This panel includes accessions grown in a long range of time from 200 years through recent releases of 2015 in United State. Therefore, this collection represents lines that were released before and after the introduction of height reducing (Rht) genes during the Green Revolution. This panel is unique for studying historical events such as loss and gains of favorable alleles using population genetics techniques and genotyping-by-sequencing data.

 

We grown USWH panel in row-plots in ACRE and performed genomewide association studies for kernel weight. This study, identified several (including QKWpur-7A.1) loci with implications in kernel weight. 

 

The Manhattan plot (left) showing the significance level of marker trait associations (MTA), and in particular QKWpur-7A.1, for KW in a panel of 279 historical panel (A). The discovery phenotype was from grain samples grown in ACRE, West Lafayette, IN. The validation data was from grain samples independently grown in totally different environment in Aberdeen ID.Nine MTAs were identified (1:9) and the number of favorable alleles at these MTAs were profiled. The graph (right) shows increases in kernel weight from lines that have only one favorable allele (Q1), all the way to lines that have up to nine favorable alleles for kernel weight.

The Manhattan plot (left) showing the significance level of marker trait associations (MTA), and in particular QKWpur-7A.1, for KW in a panel of 279 historical panel (A). The discovery phenotype was from grain samples grown in ACRE, West Lafayette, IN. The validation data was from grain samples independently grown in totally different environment in Aberdeen ID. Nine MTAs were identified (1:9) and the number of favorable alleles at these MTAs were profiled. The graph (right) shows increases in kernel weight from lines that have only one favorable allele (Q1), all the way to lines that have up to nine favorable alleles for kernel weight.

 

We analyzed controlled-environment grown seedling root traits using roll-ups and WinRHIZO and were able to characterize phenotypic distribution and genetics of main root axis, root branching, and root dry matter.

 

 

The Manhattan plot shows the significance of marker-trait associations for length of seminal axis root. The use of anchor sequence 1000bp upstream and downstream of the polymorphic site facilitated a blast search against genomic DNA and identifying the genomic scaffold that houses the polymorphic site. Genes in the vicinity of the polymorphic site can be further studied for any possible relationship with the trait of interest

The Manhattan plot shows the significance of marker-trait associations for length of seminal axis root. The use of anchor sequence 1000bp upstream and downstream of the polymorphic site facilitated a blast search against genomic DNA and identifying the genomic scaffold that houses the polymorphic site. Genes in the vicinity of the polymorphic site can be further studied for any possible relationship with the trait of interest.

 

We received the seed and genotype data for the SRWW elite panel from Dr. Sneller and Dr. Brown-Guedira, respectively. This is a publically available resource that was developed by NIFA-supported Triticeae CAP project. We are in the process of measuring traits beyond standard nursery traits. We identified grain yield QTL that were stable between the two replicates of 2017. 

 

Two layouts of 13 column x 24 rows were planted side-by-side in ACRE to evaluate grain yield and yield components. For grain yield marker trait associations were stably identified in the two replicates individually and in the average dataset.

Two layouts of 13 column x 24 rows were planted side-by-side in ACRE to evaluate grain yield and yield components. For grain yield marker trait associations were stably identified in the two replicates individually and in the average dataset.

 

Trait identification and development

Besides genome-wide association studies, we conduct field-based research to characterize nitrogen use efficiency and to develop skills and algorithms to phenotype breeding nurseries faster and cheaper. Our collaborators at Purdue Precision Management Zone and the Department of Electrical Engineering, expert in remote sensing technologies, create a multidisciplinary learning environment for our students.

 

RGB (top) and NDVI (bottom) images of wheat nursery, located within Precision Management Zone of ACRE in 2017 taken over five time points. The images were taken using a RedEdge® MicaSense sensor.

RGB (top) and NDVI (bottom) images of wheat nursery, located within Precision Management Zone of ACRE in 2017 taken over five time points. The images were taken using a RedEdge® MicaSense sensor.

 

We are also very interested in efficiency traits. Many research groups focus on phenotyping underground traits from only structural and shape perspectives. We are keen to learn more about how efficient a large root is compared to a short root.

 

Contact us if you think your research interest is in alignment with research described above and you are willing to join our laboratory.

This is a kid version of teaching scientific methods

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