Gao L.,National Center for Soybean Improvement |
Gao L.,Key Laboratory of Biology and Genetic Improvement of Soybean |
Gao L.,National Key Laboratory for Crop Genetics and Germplasm Enhancement |
Gao L.,Nanjing Agricultural University |
And 28 more authors.
Plant Disease | Year: 2015
Soybean mosaic virus (SMV), belonging to the genus Potyvirus of the family Potyviridae, has a relatively narrow host range almost exclusively confined to leguminous hosts. While disease management through genetic transformation can be an effective approach, soybean remains recalcitrant to routine genetic transformation. In this context, it is important to identify new hosts for SMV that can be used to develop effective transgenic resistance strategies. Transformation in Nicotiana benthamiana is simple and highly efficient; hence, here we demonstrate the infectivity of SMV strain SC7 in N. benthamiana plants. To identify an SMV strain infectious in N. benthamiana, we mechanically inoculated N. benthamiana plants with 37 isolates from 21 (SC1 to SC21) SMV strains. Plants inoculated with isolates of strain SC7 produced mosaic symptoms on leaves. However, N. benthamiana plants inoculated with the 20 other SMV strains showed no visible symptoms. Furthermore, soybean cv. Nannong 1138-2 inoculated with sap prepared from symptomatic N. benthamiana leaves showed typical SMV mosaic symptoms 2 weeks after inoculation. In addition, SMV was detected in symptomatic N. benthamiana and soybean leaves by RT-PCR, DAS-ELISA, and further identified by sequencing. Together, the results indicate that N. benthamiana plants could support multiplication of SMV strain SC7. The findings of this study would be useful for the investigation of SMV resistance using the model plant N. benthamiana. © 2015 The American Phytopathological Society.
Korir P.C.,Nanjing Agricultural University |
Korir P.C.,National Center for Soybean Improvement |
Korir P.C.,National Key Laboratory for Crop Genetics and Germplasm Enhancement |
Zhao T.,Nanjing Agricultural University |
And 5 more authors.
Frontiers of Agriculture in China | Year: 2010
To determine an appropriate indicator and a suitable stage for evaluating tolerance of soybeans to aluminum (Al) toxin is one of the keys to effective breeding for the trait. Seventeen accessions selected as tolerant from a previous test program by using average membership index (FAi) as indicator, plus one tolerant (PI.416937) and one sensitive (NN1138-2) check, were assayed in sand culture pot experiments, totaling four experiments, each for evaluation at V3, V5, V7 and V9 stage, respectively, each in a randomized complete block design with three replications, and each genotype exposed to two Al levels (0 and 480 μM). The relative values of shoot dry weight (RSDW), root dry weight (RRDW), total plant dry weight (RTDW), total root length (RTRL) and total root surface area (RRSA) as the tolerance indicators as well as FAi were compared. All the indicators showed significant variation in Al tolerance among genotypes over and across the leaf stages, but Genotype × Stage interactions were significant only for RTRL and RRSA, indicating that they were less stable among stages than RTDW, RSDW and RRDW. Among the latter three, RTDW was chosen as the major indicator of Al tolerance due to its relatively better stability, higher correlation with other indicators and easier measuring procedure than the others. The seedling age applicable for screening was not definitive, but V5 appeared to compromise between time spent resulting from screening the relatively older seedlings at later stages and low variation among genotypes at a younger stage. The differences of Al tolerance among the tested accessions were further detected by using RTDW, and superior Al tolerant accessions identified were PI.509080 (South Korea), N23533 and N24282 (Northeast China) and PI.159322 (USA), comparable to the putative tolerant check PI.416937 (Japan) at all vegetative stages. © 2010 Higher Education Press and Springer-Verlag Berlin Heidelberg.
Li H.,Nanjing Agricultural University |
Li H.,National Center for Soybean Improvement |
Li H.,National Key Laboratory for Crop Genetics and Germplasm Enhancement |
Zhao T.,Nanjing Agricultural University |
And 13 more authors.
Euphytica | Year: 2011
The relative importance of various types of quantitative trait locus (QTL) conferring oil content and its fatty acid components in soybean seeds was assessed through testing a recombinant inbred line (RIL) population (derived from KF1 × NN1138-2) in randomized blocks experiments in 2004-2006. The contents of oil and oleic, linoleic, linolenic, palmitic and stearic acids were determined with automatic Soxhlet extraction system and gas chromatography, respectively. Based on the established genetic linkage map with 834 markers, QTLNetwork2. 0 was used to detect QTL under the genetic model composed of additive, additive × additive (epistasis), additive × year and epistasis × year effects. The contributions to the phenotypic variances of additive QTL and epistatic QTL pairs were 15.7% (3 QTL) and 10.8% (2 pairs) for oil content, 10.4% (3 QTL) and 10.3% (3 pairs) for oleic acid, 11.6% (3 QTL) and 8.5% (2 pairs) for linoleic acid, 28.5% (7 QTL) and 7.6% (3 pairs) for linolenic acid, 27.0% (6 QTL) and 16.6% (7 pairs) for palmitic acid and 29.7% (5 QTL) and 4.3% (1 pair) for stearic acid, respectively. Those of additive QTL by year interaction were small and no epistatic QTL pair by year interaction was found. Among the 27 additive QTL and 36 epistatic QTL (18 pairs), three are duplicated between the two QTL types. A large difference was found between the genotypic variance among RILs and the total variance of mapped QTL, which accounted for 52.9-74.8% of the genotypic variation, much larger than those of additive QTL and epistatic QTL pairs. This part of variance was recognized as that due to a collection of unmapped minor QTL, like polygenes in biometrical genetics, and was designated as collective unmapped minor QTL. The results challenge the breeders for how to pyramid different types of QTL. In addition, the present study supports the mapping strategy of a full model scanning followed by verification with other procedures corresponding to the first results. © 2011 Springer Science+Business Media B.V.