با همکاری مشترک دانشگاه پیام نور و انجمن بیوتکنولوژی جمهوری اسلامی ایران

نوع مقاله : علمی پژوهشی

نویسندگان

1 گروه زراعت و اصلاح نباتات، دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران

2 گروه زیست‌شناسی سیستم‌ها، پژوهشگاه بیوتکنولوژی کشاورزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

چکیده

آرایش سیستم ریشه و صفات مرتبط با آن برای جذب رطوبت از خاک‌های عمیق اهمیت زیادی دارند. اطلاعات مربوط به QTLهای مرتبط با آرایش سیستم ریشه‌ای برنج از مقالات و پایگاه داده‌های مرتبط جمع‌آوری شدند. متاآنالیز در سطح کل ژنوم روی این QTLها با استفاده از داده‌های 28 مطالعه مستقل مکان‌یابی QTL در 38 جمعیت مختلف برنج انجام شد. از میان 312 ناحیه QTL که روی نقشه ژنتیکی مرجع قرار گرفتند، 84 و 228 ناحیه QTL به‌ترتیب در شرایط عادی رطوبتی و تنش خشکی شناسایی‌شده بودند. پس از انتقال‌QTL ها روی نقشه توافقی، متاآنالیز QTL با به کارگیری نرم‌افزار BioMercator انجام شد. در مجموع تعداد 69 ناحیه MQTL معنی‌دار روی 12 کروموزوم برنج شناسایی شدند. نواحی MQTL شامل 5 تا 32 QTL اولیه و منعکس‌کننده QTLهای متعدد برای سه تا پنج صفت مرتبط با آرایش ریشه بودند. پس از بررسی فواصل اطمینان و تعداد QTLهای اولیه برای هر یک از نواحی MQTL، 23 ناحیه به‌عنوان مهم‌ترین نواحی MQTL گزینش و ژن‌های واقع در محدوده این MQTLها شناسایی شدند. از جمله ژن‌های کاندیدای دخیل در آرایش سیستم ریشه برنج که در نواحی MQTL قرار داشتند می‌توان به ژن‌هایی از خانواده‌های WRKY، ARF، IAA، EXPA، WOX، HOX، YUCCA، RHL و NAC اشاره کرد. جایگاه 60 MQTL با موقعیت‌SNPهای گزارش‌شده در مطالعات ارتباطی کل ژنوم (GWAS) برای صفات ریختی ریشه در برنج همپوشانی داشتند. ژن‌های منتخب امیدبخش و نواحی MQTL می‌توانند برای مهندسی ژنتیک و به‌نژادی مبتنی بر MQTL با هدف بهبود پتانسیل عملکرد، پایداری و کارایی در محیط‌های مواجه با کم‌آبی در برنج مورد استفاده قرار گیرند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Identification of genomic regions associated with root system architecture in rice using meta˗analysis of QTL

نویسندگان [English]

  • Parisa Daryani 1
  • Hadi Darzi Ramandi 2
  • Sara Dezhsetan 1
  • Zahra-Sadat Shobbar 2

1 Department of Agronomy & Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.

2 Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.

چکیده [English]

The root system architecture and the related traits are important factors for moisture uptake from deep soils. Information on QTLs controlling rice root system architecture was collected from the related papers and databases. A genome-wide meta-analysis was conducted on the QTLs using data from 28 independent QTL mapping studies in 38 different rice populations. Among the 312 QTL regions that were mapped on the reference genetic map, 84 and 228 QTL regions were identified under normal moisture conditions and drought stress, respectively. After projection and displaying the QTLs on the reference consensus map, the meta-QTL analysis was performed using BioMercator software version 4.2. A total of 69 significant MQTLs regions were detected on the 12 rice chromosomes. The identified meta-QTL regions included 5-32 initial QTLs and reflecting multiple QTLs for 3-5 traits associated with root architecture. After evaluating the confidence intervals and the number of initial QTLs for each meta-QTL region, 23 meta-QTL regions were selected as the most important ones and the genes located in the MQTL regions were identified. WRKY, ARF, IAA, EXPA, WOX, HOX, YUCCA, RHL and NAC were among the important candidate genes involved in rice root system architecture, which were located in the MQTL regions. Interestingly, 60 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The promising candidate genes and MQTLs can be used for genetic engineering and MQTL-assisted breeding of root traits to improve yield potential, stability and efficiency in water deficit environments for rice.

کلیدواژه‌ها [English]

  • Candidate genes
  • Drought stress
  • MQTL regions
  • Root morphological traits
  • GWAS
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