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Insect Genomics pp 45–57Cite as

Integrated Modeling of Structural Genes Using MCuNovo

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1858))

Abstract

Correct modeling of protein-coding genes based on genome and cDNA data is a prerequisite for functional studies. Various programs such as MAKER, Cufflinks, Oases, and Trinity have been developed, each with advantages and drawbacks. Manual integration of different models for a single gene is cumbersome and becomes a daunting task for 14,000–18,000 genes in a typical holometabolous insect. We developed methods to evaluate the output of MAKER, Cufflinks, Oases and Trinity and select the best models to constitute the MCOT1.0 set for Manduca sexta, a biochemical model insect. To apply these methods in other organisms, we improved the algorithm (designated MCuNovo Gene Selector) and automated the data processing. In this chapter, we describe background information of algorithm development and how to prepare and run this program.

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Acknowledgments

This study is supported by NIH grants GM58634 and AI112662. This work was approved for publication by the Director of Oklahoma Agricultural Experimental Station and supported in part under project OKLO2450.

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Authors and Affiliations

  1. Department of Entomology and Plant Pathology, Oklahoma State University, Stillwater, OK, USA

    Xiaolong Cao & Haobo Jiang

Authors
  1. Xiaolong Cao
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  2. Haobo Jiang
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Corresponding author

Correspondence to Haobo Jiang .

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Editors and Affiliations

  1. Division of Biology, Kansas State University, Manhattan, NY, USA

    Susan J. Brown

  2. Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA

    Michael E. Pfrender

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Cao, X., Jiang, H. (2019). Integrated Modeling of Structural Genes Using MCuNovo. In: Brown, S., Pfrender, M. (eds) Insect Genomics. Methods in Molecular Biology, vol 1858. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8775-7_5

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  • DOI: https://doi.org/10.1007/978-1-4939-8775-7_5

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8774-0

  • Online ISBN: 978-1-4939-8775-7

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