Soybean genetic linkage maps represent the order of known molecular genetic markers along a given chromosome, which provide an insight into the organization of the genome. A high resolution genetic map will allow us to identify candidate genes underlying a QTL, conduct association mapping, identify syntenic regions among legume species, and assist in molecular breeding. Especially, a high resolution genetic map is also a useful tool to evaluate and utilize the current soybean sequence assembly.

Soybean BAC-based physical maps provide useful resources for effective and high-throughput gene and QTL cloning, EST mapping, marker development, genome sequencing, and comparative genomics research. Soybean physical maps for “Forrest” and “Williams 82” representing southern and northern U.S. soybean germplasm base have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps. More than 2,000 genetic markers and 5,000 gene-based STS markers have been anchored onto the Williams 82 physical map but only a limited number of markers has been anchored to the Forrest physical map. We are using a Forrest x Williams 82 mapping population containing 1,025 F8 RILs to construct a reference genetic map. Our approach involves selection of a core set of this mapping population using SSR markers followed by high-resolution mapping using SNP markers with customized Illumina 1,536-GoldenGate arrays.

We use several types of genetic markers in our laboratory, these include:  Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), Single Feature Polymorphism (SFP), and Indels (Insertion and Deletion Marker).  In addition to the public SNP markers, we have generated extensive polymorphic marker resources (SSR, SFP, Indels, and SNP) that will be used for the genetic mapping in this population. We have developed thousands of genome-wide SNP markers by Solexa high throughput sequencing technology. Combined with advanced mapping populations, we will target genes of interest and specific traits with these SNP markers.  Our goals are to understand the genetic basis of QTLs underlying economically important traits and to develop high throughput marker-assisted selection methods for soybean improvement.

 

Our goals are to understand the genetic basis of QTLs underlying economically important traits and to develop high-throughput marker-assisted selection methods for breeding application.

Soybean Cyst Nematode (SCN) Mapping:
Our laboratory is collaborating with other soybean cyst nematode (SCN) researchers at the University of Missouri.  We are conducting evaluations of exotic soybean germplasm for broad-based resistance to multi-HG types of SCN, developing genetic populations for the identification and mapping of novel quantitative trait loci (QTL)/gene(s), and developing of near-isogenic lines (NILs) through marker-assisted breeding (MAB). Our goals are:  1) to dissect QTL regions and discover candidate genes in the QTL regions conditioning resistance to multi-HG types of SCN.  These efforts include novel and known QTL (the rhg1 and Rhg4 loci); 2) to clone and characterize identified candidate genes using functional analysis and genetic transformation approaches in attempts to enhance the understanding and elucidation of the mechanism of host plant resistance to SCN; and 3) to develop gene-based genetic markers (SNP and Indels), which will be employed for the fine-mapping and map-based QTL cloning.  

Following the discovery and mapping of novel QTL underlying resistance to multi-SCN HG types in several unique soybean PIs, currently our laboratory is focusing on the development of NILs using marker-assisted backcrossing. And based on information from whole genome sequence assembly (Glymax1, http://www.phytozome.net), we are in process of developing candidate gene-based genetic markers aiming to fine-mapping and positional cloning of these genes.

Drought tolerance with an emphasis on root growth and development:
Research is focused on evaluation of genetic diversity of root traits and drought responses. Contrasting parental lines will be crossed to develop segregating populations for QTL mapping and used for functional genomics studies.

Seed composition traits:
Research is in progress on QTL mapping and candidate gene analysis for oil traits, isoflavones and secondary metabolites (e.g. sapponins). A coordinated United Soybean Board (USB) project on marker-assisted backcrossing for mid oleic acid trait in soybean is underway.