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the 4th international edition and 13th Iranian Conference on Bioinformatics
international edition and Iranian Conference on Bioinformatics
صفحه اصلی
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4th international edition and 13th Iranian Conference on Bioinformatics
Phylogenetic and In Silico Analysis of SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) Gene Family in Crops
نویسندگان :
Amin Nasirpour
1
Abbasali Emamjomeh
2
Nasibe Chenarani
3
1- Laboratory of Computational Biotechnology and Bioinformatics (CBB), Department of Bioinformatics, Faculty of Basic Sciences, University of Zabol, Zabol, Iran
2- Department of Plant Breeding and Biotechnology (PBB), Faculty of Agriculture, University of Zabol, Zabol, Iran
3- Post-doctoral researcher، Agricultural Biotechnology Research Institute of IRAN (ABRII), Karaj
کلمات کلیدی :
Phylogenetic Analysis،In Silico Characterization،Transcription Factors،Computational Pipeline
چکیده :
The SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) genes represent a crucial transcription factor family in plants. We have developed a systematic bioinformatics pipeline for identification and characterization of SPL gene family in crop plants, using safflower (Carthamus tinctorius L.) as a case study. Our computational workflow combined sequence similarity searches and domain prediction algorithms to identify 44 SBP domain-containing sequences. In silico characterization using machine learning-based approaches revealed diverse protein architectures with sequences ranging from 60 to 7994 amino acids. Motif analysis using MEME identified conserved patterns ranging from 6 to 49 amino acids, while subcellular localization predictions demonstrated nuclear targeting for 60.7% of proteins. Evolutionary relationships were investigated through Maximum Likelihood phylogenetic reconstruction, revealing distinct patterns when compared with model plants like Arabidopsis and rice. Gene Ontology analysis highlighted significant overrepresentation of DNA binding (57.1%) and glycosyltransferase activity (35.7%). This integrative computational framework demonstrates the power of bioinformatics in understanding gene family evolution and can be applied to various crops.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.5.0