Selective Genotyping for Marker Assisted Selection Strategies for Soybean Yield Improvement

  • Benjamin D. Fallen Clemson University, Advanced Plant Technology Center, Clemson Pee Dee REC, 2200 Pocket Rd., Florence, SC 29506, USA.
  • Fred L. Allen University of Tennessee, Department of Plant Sciences, 2431 Joe Johnson Dr., Knoxville, TN 37996, USA.
  • Dean A. Kopsell University of Tennessee, Department of Plant Sciences, 2431 Joe Johnson Dr., Knoxville, TN 37996, USA.
  • Arnold M. Saxton University of Tennessee, Department of Plant Sciences, 2431 Joe Johnson Dr., Knoxville, TN 37996, USA.
  • Leah McHale Ohio State University, Department of Horticulture and Crop Science, 2021 Coffey Rd., Columbus, OH 43210, USA.
  • J. Grover Shannon University of Missouri, Division of Plant Sciences, Delta Center, P.O. Box 160, Portageville, MO 63873, USA.
  • Stella K. Kantartzi Southern Illinois University, Department of Plant, Soil Science and Agricultural Systems, 1205 Lincoln Drive, Carbondale, IL 62901, USA.
  • Andrea J. Cardinal Syngenta Seeds, 3054 Cornwallis Rd., Research Triangle Park, NC 27709, USA.
  • Perry B. Cregan Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center – West, USDA, ARS, Beltsville, MD 20705, USA.
  • David L. Hyten Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center – West, USDA, ARS, Beltsville, MD 20705, USA; Current address: DuPont Pioneer, 8305 NW 62nd Ave., PO Box 7060, Johnston, IA 50131-7060, USA.
  • Vincent R. Pantalone University of Tennessee, Department of Plant Sciences, 2431 Joe Johnson Dr., Knoxville, TN 37996, USA.
Keywords: Genomic selection, epistasis, predictive breeding, QTL analysis

Abstract

Using molecular markers in soybean [Glycine max (L.) Merr.] has lead to the identification of major loci controlling quantitative and qualitative traits that include: disease resistance, insect resistance and tolerance to abiotic stresses. Yield has been considered as one of the most important quantitative traits in soybean breeding. Unfortunately, yield is a very complex trait and most yield quantitative trait loci (QTL) that have been identified have had only limited success for marker assisted selection (MAS). The objective of this study was to identify QTL associated with soybean seed yield in preliminary yield trials grown in different environments and to evaluate their effective use for MAS using a yield prediction model (YPM), which included epistasis. To achieve this objective, 875 F5:9 recombinant inbred lines (RIL) from a population developed from a cross between two prominent ancestors of the North American soybean (Essex and Williams 82) were used. The 875 RIL and check cultivars were divided into four groups based on maturity and each group was grown in Knoxville, TN and one other location that had an environment in which the maturity group (MG) was adapted to be grown. Each RIL was genotyped with >50,000 single nucleotide polymorphic markers (SNPs) of which 17,232 were polymorphic across the population. Yield QTL were detected using a single factor (SF) analysis of variance (ANOVA) and composite interval mapping (CIM). Based on CIM, 23 yield QTL were identified. Twenty-one additional QTL were detected using SF ANOVA. Individually, these QTL explained from 4.5% to 11.9% of the phenotypic variation for yield. QTL were identified on all 20 chromosomes and five of the 46 QTL have not been previously reported. This study provides new information concerning yield QTL in soybean and may offer important insights into MAS strategies for soybean.

Published
2017-06-15
Section
ARTICLES