The first genetic transcript map of the soybean genome was created by mapping one SNP in each of 1141 genes in one or more of three recombinant inbred line mapping populations, thus providing a picture of the distribution of genic sequences across the mapped portion of the genome. Singlenucleotide polymorphisms (SNPs) were discovered via the resequencing of sequence-tagged sites (STSs) developed from expressed sequence tag (EST) sequence. From an initial set of 9459 polymerase chain reaction primer sets designed to a diverse set of genes, 4240 STSs were amplified and sequenced in each of six diverse soybean genotypes. In the resulting 2.44 Mbp of aligned sequence, a total of 5551 SNPs were discovered, including 4712 single-base changes and 839 indels for an average nucleotide diversity of u ¼ 0.000997. The analysis of the observed genetic distances between adjacent genes vs. the theoretical distribution based upon the assumption of a random distribution of genes across the 20 soybean linkage groups clearly indicated that genes were clustered. Of the 1141 genes, 291 mapped to 72 of the 112 gaps of 5-10 cM in the preexisting simple sequence repeat (SSR)-based map, while 111 genes mapped in 19 of the 26 gaps .10 cM. The addition of 1141 sequence-based genic markers to the soybean genome map will provide an important resource to soybean geneticists for quantitative trait locus discovery and map-based cloning, as well as to soybean breeders who increasingly depend upon marker-assisted selection in cultivar improvement.

Cultivated soybean (Glycine max L.) cv. Dunbar (PI 552538) and wild G. soja (PI 326582A) exhibited significant differences in root architecture and root-related traits. In this study, phenotypic variability for root traits among 251 BC2F5 backcross inbred lines (BILs) developed from the cross Dunbar/PI 326582A were identified. The root systems of the parents and BILs were evaluated in controlled environmental conditions using a cone system at seedling stage. The G. max parent Dunbar contributed phenotypically favorable alleles at a major quantitative trait locus on chromosome 8 (Satt315-I locus) that governed root traits (tap root length and lateral root number) and shoot length. This QTL accounted for >10% of the phenotypic variation of both tap root and shoot length. This QTL region was found to control various shoot- and root-related traits across soybean genetic backgrounds. Within the confidence interval of this region, eleven transcription factors (TFs) were identified. Based on RNA sequencing and Affymetrix expression data, key TFs including MYB, AP2-EREBP and bZIP TFs were identified in this QTL interval with high expression in roots and nodules. The backcross inbred lines with different parental allelic combination showed different expression pattern for six transcription factors selected based on their expression pattern in root tissues. It appears that the marker interval Satt315–I locus on chromosome 8 contain an essential QTL contributing to early root and shoot growth in soybean.

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The germplasm pool for North American soybean [Glycine max (L.) Merr.] is narrow, and identifying novel and useful genetic diversity is time consuming and expensive. The objective of this research was to develop an early‐generation population screening method to select diversity × elite populations. The F2 high‐parent heterosis (F2 heterosis) was used as a tool to identify populations with the greatest potential for producing high‐yielding lines in subsequent generations. For Set 1 populations, six populations were selected for significantly positive F2 heterosis, and six were selected for significantly negative F2 heterosis. When these populations were advanced into plant row yield trials, five out of six populations with positive F2 heterosis had the highest average yield for the top 5% of the lines, and five out of six populations with negative F2 heterosis had the lowest average yield for the top 5% of the lines. For Set 2, two populations with the highest positive F2 heterosis value had significantly higher average population yield and average top 5% selection yield compared with two populations with negative F2 heterosis. Differences in combining ability were evident in both sets of populations, as two populations with one parent in common may have opposite classifications for F2 heterosis. Using F2 heterosis as an early‐generation population selection tool may enable the focus of resources to identify which populations have the best opportunity to develop high‐yielding lines with unique diversity. These data will need to be verified in replicated yield testing over multiple years and locations.