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Deciphering the Genetic Architecture of Plant Height in Soybean Using Two RIL Populations Sharing a Common M8206 Parent.
Sunday, 2019/10/06 | 07:04:44
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Cao Y, Li S, Chen G, Wang Y, Bhat JA, Karikari B, Kong J, Gai J, Zhao T Plants (Basel). 2019 Sep 26;8(10). pii: E373. doi: 10.3390/plants8100373. AbstractPlant height (PH) is an important agronomic trait that is closely related to soybean yield and quality. However, it is a complex quantitative trait governed by multiple genes and is influenced by environment. Unraveling the genetic mechanism involved in PH, and developing soybean cultivars with desirable PH is an imperative goal for soybean breeding. In this regard, the present study used high-density linkage maps of two related recombinant inbred line (RIL) populations viz., MT and ZM evaluated in three different environments to detect additive and epistatic effect quantitative trait loci (QTLs) as well as their interaction with environments for PH in Chinese summer planting soybean. A total of eight and 12 QTLs were detected by combining the composite interval mapping (CIM) and mixed-model based composite interval mapping (MCIM) methods in MT and ZM populations, respectively. Among these QTLs, nine QTLs viz., QPH-2, qPH-6-2MT, QPH-6, qPH-9-1ZM, qPH-10-1ZM, qPH-13-1ZM, qPH-16-1MT, QPH-17 and QPH-19 were consistently identified in multiple environments or populations, hence were regarded as stable QTLs. Furthermore, Out of these QTLs, three QTLs viz., qPH-4-2ZM, qPH-15-1MT and QPH-17 were novel. In particular, QPH-17 could detect in both populations, which was also considered as a stable and major QTL in Chinese summer planting soybean. Moreover, eleven QTLs revealed significant additive effects in both populations, and out of them only six showed additive by environment interaction effects, and the environment-independent QTLs showed higher additive effects. Finally, six digenic epistatic QTLs pairs were identified and only four additive effect QTLs viz., qPH-6-2MT, qPH-19-1MT/QPH-19, qPH-5-1ZM and qPH-17-1ZM showed epistatic effects. These results indicate that environment and epistatic interaction effects have significant influence in determining genetic basis of PH in soybean. These results would not only increase our understanding of the genetic control of plant height in summer planting soybean but also provide support for implementing marker assisted selection (MAS) in developing cultivars with ideal plant height as well as gene cloning to elucidate the mechanisms of plant height.
See: https://www.mdpi.com/2223-7747/8/10/373/htm
Figure 2: Distribution of QTLs on genetic map for plant height in the MT population (here only the genetic map around QTLs is shown). Red graphics represent the QTLs were detected by CIM method. Black graphics represent the QTLs were detected by MCIM method, and the filled graphics represent QTLs with additive effect, while the hollow graphics represent QTLs with non-additive effect. Black dotted lines represent that there are epistatic interaction effects between two connected QTLs.
Figure 3: Distribution of QTLs on genetic map for plant height in the ZM population (here only the genetic map around QTLs is shown). Red graphics represent the QTLs were detected by CIM method. Black graphics represent the QTLs were detected by MCIM method, and the filled graphics represent QTLs with additive effect, while the hollow graphics represent QTLs with non-additive effect. Black dotted lines represent that there are epistatic interaction effects between two connected QTLs. |
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