An updated ‘Essex’ by ‘Forrest’ linkage map and first composite interval map of QTL underlying six soybean traits

Abstract

DNA marker maps based on single populations are the basis for gene, loci and genomic analyses. Individual maps can be integrated to produce composite maps with higher marker densities if shared marker orders are consistent. However, estimates of marker order in composite maps must include sets of markers that were not polymorphic in multiple populations. Often some of the pooled markers were not codominant, or were not correctly scored. The soybean composite map was composed of data from five separate populations based on northern US germplasm but does not yet include 'Essex' by 'Forrest' recombinant inbred line (RIL) population (E x F) or any southern US soybean cultivars. The objectives were, to update the E x F map with codominant markers, to compare marker orders among this map, the Forrest physical map and the composite soybean map and to compare QTL identified by composite interval maps to the earlier interval maps. Two hundred and thirty seven markers were used to construct the core of the E x F map. The majority of marker orders were consistent between the maps. However, 19 putative marker inversions were detected on 12 of 20 linkage groups (LG). Eleven marker distance compressions were also found. The number of inverted markers ranged from 1 to 2 per LG. Thus, marker order inversions may be common in southern compared to northern US germplasm. A total of 61 QTL among 37 measures of six traits were detected by composite interval maps, interval maps and single point analysis. Seventeen of the QTL found in composite intervals had previously been detected among the 29 QTL found in simple interval maps. The genomic locations of the known QTL were more closely delimited. A genome sequencing project to compare Southern and Northern US soybean cultivars would catalog and delimit inverted regions and the associated QTL. Gene introgression in cultivar development programs would be accelerated.

Identification of Loci Underlying Seed Yield in Recombinant Inbred and Near Isogeneic Soybean Lines Derived from Flyer by Hartwig

“…However, at genomic regions where gaps between adjacent markers were greater than 10 cM in the map associations 0.005>P>0.0005 were accepted as a potentially significant association. Precedents (Hnetkovsky et al, 1996;Chang et al, 1997;Njiti et al, 1997;Kassem et al, 2006) have shown these criteria to be valid in later maps (Meksem et al, 2001a;Njiti et al, 2002;Yuan et al, 2002;Triwitaykorn et al, 2005;Ruben et al, 2006).…”

“…For example, Orf et al (1999a,b) identified QTL for seed yield in different linkage groups A2, B1, B2, D1a+Q, D1b+W, D2, F, J, L, and M of the soybean genome. Other authors identified QTL for yield on linkage groups C2, H, M (Specht et al, 1999), F (Reyna and Sneller 2001), J, L, M (Mansur et al, 1993(Mansur et al, , 1996, and N (Kassem et al, 2006) of the soybean genome. Three QTL for yield were found on linkage groups C1, I, and K using 136 SSR markers and a RIL population of Essex × Forrest (E × F) (Yuan et al, 2002).…”

“…sem et al, 2006) have major effects on yield potential in many segregating populations. DNA molecular markers have been used extensively to identify and screen for QTL that underlie soybean seed yield and yield components (Mansur et al, 1994;Mansur et al, 1996;Orf et al, 1999b;Yuan et al, 2002;Kassem et al, 2006). The yield QTL identified to date are large genomic regions where at least two distinct alleles have been shown to influence yield.…”

QTL mapping for yield components and agronomic traits in a Brazilian soybean population

“…Although several QLT related to grain yield have been described in the scientific literature, maybe only a few of them have already been confirmed (Kassem et al 2006, Bernardo 2008, Sebastian et al 2010. QTL, which have already been selected in breeding programs and/or transferred to new cultivars are rare (Ainsworth et al 2012).…”

Translational Genomics in Agriculture: Some Examples in Grain Legumes

“…(Kassem et al, 2006) For instance, BSA was used for mapping of Fusarium wilt (FW) resistance with RAPD markers in the case of pigeonpea (Kotresh et al, 2006). On the other hand, in order to understand the complex nature of drought tolerance in chickpea, precise phenotypic data for 20 different root traits was analyzed using a QTL mapping approach.…”