Plant Genetics, Genomics, and Biotechnology 2018-01-21T02:44:29-05:00 Abdelmajid Kassem Open Journal Systems <p>Plant Genetics, Genomics, and Biotechnology is an Open Access, peer-reviewed international journal that publishes original research articles, short communications, and review articles in all fields of Plant Genetics, Genomics, and Biotechnology.</p> Introduction of High Throughput and Cost Effective SNP Genotyping Platforms in Soybean 2018-01-21T02:44:29-05:00 Jiazheng Yuan Zixiang Wen Cuihua Gu Dechun Wang <p>We presented here the application of two in-plate SNP (single nucleotide polymorphism) genotyping platforms for soybean plants [Glycine max (L.) Merr.], KASP® (Kompetitive Allele Specific PCR genotyping, LGC Genomics) and TaqMan® (Life Technologies) respectively. These two systems offer us an ability to determine the genotypes of 384 individual samples accurately and efficiently by allele specific PCR in a single plate using typical PCR conditions. Both of the systems require small quantity of genomic DNA obtained from a simple DNA extraction. The genomic sequences containing target SNPs can easily be used as a basic blueprint to design the probes and primers of KASP® and TaqMan® assays whether the sequences are obtained from the genome sequence of soybean William 82 (Wm82.a2.v1), Illumina Soy50k SNPs, or parallel resequencing. Moreover, we listed the pros and cons of the two systems and explained the principles behind the platforms. The high call rate and clear clustering separation of the SNPs can be readily obtained from these platforms without conducting any assay optimization processes. These platforms can routinely be performed on 96/384-well plate format with or without an automation procedure. Therefore, these platforms are especially suitable for the SNP genotyping on a particular trait with a large sample size, gene fine mapping, and marker assisted selection. Further, they require little hands-on experience and achieve per-site and per-individual costs below that of current SSR, AFLP, RFLP, and SNP chip technologies. The platforms can be used for genotyping on a wide range of organisms due to their simplicity and flexibility of handling. Meanwhile, we also especially presented some of the advantages using KASP® SNP genotyping pipeline, which was cost effective in the selection of allele specific assay and therefore, efficiently facilitated the soybean genotyping across large numbers (thousands or more) of individual lines for a great range of markers (hundreds to thousands) in our laboratory.</p> 2017-06-15T03:40:14-04:00 Copyright (c) 2017 Plant Genetics, Genomics, and Biotechnology Selective Genotyping for Marker Assisted Selection Strategies for Soybean Yield Improvement 2018-01-21T02:44:29-05:00 Benjamin D. Fallen Fred L. Allen Dean A. Kopsell Arnold M. Saxton Leah McHale J. Grover Shannon Stella K. Kantartzi Andrea J. Cardinal Perry B. Cregan David L. Hyten Vincent R. Pantalone <p>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 &gt;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.</p> 2017-06-15T04:05:55-04:00 Copyright (c) 2017 Plant Genetics, Genomics, and Biotechnology