ایجاد درخت ژنی با استفاده از واگرایی کولبک-لیبلر روی ژن‌های موثر بر تولید شیر در گاو شیری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه علوم دامی، دانشکده علوم کشاورزی، دانشگاه گیلان

2 استاد گروه علوم دامی، دانشکده علوم کشاورزی، دانشگاه گیلان

3 استادیار گروه علوم دامی، دانشکده علوم کشاورزی، دانشگاه یاسوج

4 استادیار گروه مهندسی برق، دانشکده فنی، دانشگاه گیلان

5 دانشیار موسسه تحقیقات علوم دامی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج

چکیده

نظریه­ اطلاعات، شاخه­ای از ریاضیات است که با مهندسی ارتباطات، زیست­شناسی و پزشکی هم­پوشانی دارد. هدف از بررسی حاضر ارائه روشی جهت خوشه­بندی تعدادی از ژن­های موثر روی تولید شیر در گاو شیری با استفاده از الگوریتمی متکی بر واگرایی کولبک­­ -­ لیبلر بود. در این پژوهش بعد از استخراج توالی DNA ژن‌ و اگزون‌های موثر بر تولید شیر در گاو شیری، فراسنجه آنتروپی در مراتب یک تا چهار برای هر ژن و اگزون‌های هر ژن محاسبه شد. جهت استخراج فاصله میان ژن‌ها از یکدیگر، از واگرایی کولبک - لیبلر در سه روش مختلف استفاده شد. روش‌های اول و دوم مبتنی بر همترازی ولی روش سوم غیر مبتنی بر همترازی و بر پایه آنتروپی نسبی ژن‌ها بود. نتایج هر سه روش واگرایی کولبک - لیبلر روی توالی DNA ژن‌ها و اگزون‌ها با استفاده از هفت روش معمولSingle ،Complete ،Average ،Weighted ، Centroid،  Medianو KMeansخوشه‌بندی شدند. تجمیع نتایج هر خوشه‌بندی که با الگوریتم AdaBoost انجام شد، و خود نوعی درخت ژنی را تداعی کرد، نشان داد که روش سوم، خوشه‌بندی معقولی را از نظر زیستی برای مجموعه‌ای از ژن‌ها حاصل نمود چرا که با نتایج حاشیه­نویسی ژنومی ژن‌های حاصل ازGeneMANIA  مطابقت داشت. این اعتقاد وجود دارد که روش ارائه شده برای ایجاد درخت ژنی می‌تواند با سایر روش‌های متکی بر توالی DNA ژن‌ها جهت خوشه­بندی مجموعه‌ای از ژن‌ها، رقابت نماید و لذا می‌تواند در گروه‌بندی ژن‌های سایر گو‌نه‌ها نیز بکار رود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Gene tree construction using Kullback-Leibler divergence on milk governing genes in dairy cattle

نویسندگان [English]

  • H. Dehghanzadeh 1
  • S. Z. Mirhoseini 2
  • M. Ghaderi-Zefrehei 3
  • H. Tavakoli 4
  • S. Esmaeilkhaniyan 5
1 Ph.D Student, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
2 Professor, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3 Assistant Professor, Department of Animal science, Faculty of Agricultural Sciences, University of Yasouj, Yasouj, Iran
4 Assistant Professor, Department of Electrical Engineering, Faculty of Electrical Engineering, University of Guilan, Rasht, Iran
5 AsAssociate Professor, Department of Biotechnology, Animal Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
چکیده [English]

Information theory is a branch of mathematics that overlaps with communications, biology. The aim of the current study was to provide a method for clustering a number of Milk Governing Genes in Dairy Cattle using an algorithm based on Kullback-Leibler divergence. In this study, after retrieving gene and exon DNA sequences affecting milk yield in dairy cattle, the entropy in orders one to four was calculated. In order to extract gene distances, Kullback-Leibler divergence over three different methods was calculated. The first and second methods were based on the genes alignment but the third method was based on non-alignment and the relative entropy of the genes. The results of each method of Kullback-Leibler divergence over DNA and exon sequences were entered as input into 7 general clustering algorithms: Single, Complete, Average, Weighted, Centroid, Median and K-Means. Integrated result of each clustering algorithm due to AdaBoost algorithm, which implied as gene tree, indicated that the third method was based on the relative entropy of the genes, biologically grouped set of genes as it was proved by their gene annotation using GeneMANIA. We believe that the proposed method might be used with other DNA based clustering competitive methods and therefore, it can be used to group set of genes in other species.

کلیدواژه‌ها [English]

  • Information theory
  • Gene clustering
  • Dairy cattle
  • Kullback-Leibler divergence
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