Association mapping of iron deficiency chlorosis loci in soybean (Glycine max L. Merr.) advanced breeding lines

Abstract

Association mapping is an alternative to mapping in a biparental population. A key to successful association mapping is to avoid spurious associations by controlling for population structure. Confirming the marker/trait association in an independent population is necessary for the implementation of the marker in other genetic studies. Two independent soybean populations consisting of advanced breeding lines representing the diversity within maturity groups 00, 0, and I were screened in multi-site, replicated field trials to discover molecular markers associated with iron deficiency chlorosis (IDC), a major yield-limiting factor in soybean. Lines with extreme phenotypes were initially screened to identify simple sequence repeat (SSR) markers putatively associated with the IDC. Marker data collected from all lines were used to control for population structure and kinship relationships. Single factor analysis of variance (SFA) and mixed linear model (MLM) analyses were used to discover marker/trait associations. The MLM analyses, which include population structure, kinship or both factors, reduced the number of markers significantly associated with IDC by 50% compared with SFA. With the MLM approach, three markers were found to be associated with IDC in the first population. Two of these markers, Satt114 and Satt239, were also found to be associated with IDC in the second confirmation population. For both populations, those lines with the tolerance allele at both these two marker loci had significantly lower IDC scores than lines with one or no tolerant alleles.

Development and Application of Molecular Markers to Breed Common Bean (Phaseolus vulgaris L.) for Resistance to Common Bacterial Blight (CBB) — Current Status and Future Directions

“…Merr.) two markers, Satt114 and Satt239, were found to be associated with iron deficiency chlorosis loci using advance breeding lines (Wang et al, 2008). In rice (Oryza sativa L.), microsatellite markers associated with yield and its components were identified in a variety trial, and many of them were located in regions where QTL had previously been identified (Agrama et al, 2007).…”

“…A Mixed Linear Model (MLM) approach has been developed to account for multiple levels of relatedness simultaneously as determined by kinship estimates based on a set of random genetic markers . This model has been proven useful in genome-wide association studies to control the biases that may be caused by population structure and relatedness in other species e.g., maize (Zea mays L.) , rice (Wang et al, 2008). Another issue for association mapping is reliability, an issue of particular concern when the goal is to discover marker/trait associations that have broad application.…”

Natural variation in iron use efficiency and mineral remobilization in cucumber (Cucumis sativus)

“…Many alkaline soils also have high bicarbonate concentration (Mengel 1994;Rogovska et al 2007), which can inhibit Fe uptake Mengel 1994). Leaf chlorosis is a classical Fe deficiency sign, and negatively impacts yield in certain crops, such as soybean in the upper Midwest USA (O'Rourke et al 2007;Wang et al 2008). Under low Fe availability conditions, plants increase Fe uptake gene expression and protein activity (Morrissey and Guerinot 2009), which in dicot species includes ferric reductases (Jeong and Connolly 2009), iron transporters (Vert et al 2002), and H + -ATPases (Santi and Schmidt 2009).…”

Genomic selection of seed weight based on low-density SCAR markers in soybean

“…To identify more general molecular markers for MAS, association mapping in a natural population was developed for screening molecular markers, which are related to desired traits of crops. QTL for important traits in soybean have been identified by AM using SSR markers, including those related to protein content and iron deficiency (e.g., Wang et al, 2008;Jun et al, 2008). Importantly, however, AM cannot resolve problems of small-effect genes and multi-gene interaction, which has limited the application of AM in soybean.…”