Spanish
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Frontiers in Plant Science 2016

RNA-Seq Analysis of Differential Gene Expression Responding to Different Rhizobium Strains in Soybean (Glycine max) Roots.

Solo los usuarios registrados pueden traducir artículos
Iniciar sesión Registrarse
El enlace se guarda en el portapapeles.
Songli Yuan
Rong Li
Shuilian Chen
Haifeng Chen
Chanjuan Zhang
Limiao Chen
Qingnan Hao
Zhihui Shan
Zhonglu Yang
Dezhen Qiu

Palabras clave

Abstracto

The root nodule symbiosis (RNS) between legume plants and rhizobia is the most efficient and productive source of nitrogen fixation, and has critical importance in agriculture and mesology. Soybean (Glycine max), one of the most important legume crops in the world, establishes a nitrogen-fixing symbiosis with different types of rhizobia, and the efficiency of symbiotic nitrogen fixation in soybean greatly depends on the symbiotic host-specificity. Although, it has been reported that rhizobia use surface polysaccharides, secretion proteins of the type-three secretion systems and nod factors to modulate host range, the host control of nodulation specificity remains poorly understood. In this report, the soybean roots of two symbiotic systems (Bradyrhizobium japonicum strain 113-2-soybean and Sinorhizobium fredii USDA205-soybean)with notable different nodulation phenotypes and the control were studied at five different post-inoculation time points (0.5, 7-24 h, 5, 16, and 21 day) by RNA-seq (Quantification). The results of qPCR analysis of 11 randomly-selected genes agreed with transcriptional profile data for 136 out of 165 (82.42%) data points and quality assessment showed that the sequencing library is of quality and reliable. Three comparisons (control vs. 113-2, control vs. USDA205 and USDA205 vs. 113-2) were made and the differentially expressed genes (DEGs) between them were analyzed. The number of DEGs at 16 days post-inoculation (dpi) was the highest in the three comparisons, and most of the DEGs in USDA205 vs. 113-2 were found at 16 dpi and 21 dpi. 44 go function terms in USDA205 vs. 113-2 were analyzed to evaluate the potential functions of the DEGs, and 10 important KEGG pathway enrichment terms were analyzed in the three comparisons. Some important genes induced in response to different strains (113-2 and USDA205) were identified and analyzed, and these genes primarily encoded soybean resistance proteins, NF-related proteins, nodulins and immunity defense proteins, as well as proteins involving flavonoids/flavone/flavonol biosynthesis and plant-pathogen interaction. Besides, 189 candidate genes are largely expressed in roots and\or nodules. The DEGs uncovered in this study provides molecular candidates for better understanding the mechanisms of symbiotic host-specificity and explaining the different symbiotic effects between soybean roots inoculated with different strains (113-2 and USDA205).

Únete a nuestra
página de facebook

La base de datos de hierbas medicinales más completa respaldada por la ciencia

  • Funciona en 55 idiomas
  • Curas a base de hierbas respaldadas por la ciencia
  • Reconocimiento de hierbas por imagen
  • Mapa GPS interactivo: etiquete hierbas en la ubicación (próximamente)
  • Leer publicaciones científicas relacionadas con su búsqueda
  • Buscar hierbas medicinales por sus efectos.
  • Organice sus intereses y manténgase al día con las noticias de investigación, ensayos clínicos y patentes.

Escriba un síntoma o una enfermedad y lea acerca de las hierbas que podrían ayudar, escriba una hierba y vea las enfermedades y los síntomas contra los que se usa.
* Toda la información se basa en investigaciones científicas publicadas.

Google Play badgeApp Store badge