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      Integrated Analysis of Transcriptome and Proteome to Reveal Pupal Color Switch in Papilio xuthus Butterflies

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          Abstract

          Pupal color polyphenism in Papilio butterflies, including green, intermediate, or brown, is an excellent study system for understanding phenotypic plasticity. Previous studies suggested that development of brown pupae may be controlled by a hormone called pupal-cuticle-melanizing-hormone (PCMH) which is synthesized and secreted from brain-suboesophageal ganglion and prothoracic ganglion complexes (Br-SG-TG1) during the pre-pupa stage. However, detailed molecular mechanisms of neuroendocrine regulation in pupal color development remain unknown. In this study, we integrated the expression profiles of transcriptome and proteome at pre-pupa stages [2 h after gut purge (T1) and 3 h after forming the garter around the body (T2)] and pigmentation stages [10 h after ecdysis (T3) and 24 h after ecdysis (T4)] to identify important genes and pathways underlying the development of green and brown pupa in the swallowtail butterfly Papilio xuthus. Combined comparisons of each developmental stage and each tissue under green and brown conditions, a total of 1042 differentially expressed genes (DEGs) and 430 different abundance proteins (DAPs) were identified. Weighted gene co-expression network analysis (WGCNA) and enrichment analysis indicate that these DEGs were mainly related to oxidation-reduction, structural constituent of cuticle, and pigment binding. Soft clustering by Mfuzz and enrichment analysis indicate that these DAPs are mainly involved in tyrosine metabolism, insect hormone biosynthesis, and melanogenesis. By homologous alignment, we further identified those genes encoding neuropeptides (51), GPCRs (116), G-proteins (8), cuticular proteins (226), chitinases (16), and chitin deacetylases (8) in the whole genome of P. xuthus and analyzed their expression profiles . Although we identified no gene satisfying with hypothesized expression profile of PCMH, we found some genes in the neuropeptide cascade showed differentially expressed under two pupal color conditions. We also found that Toll signaling pathway genes, juvenile hormone (JH) related genes, and multiple cuticular proteins play important roles in the formation of selective pupal colors during the prepupal-pupal transition. Our data also suggest that both green and brown pupa include complex pigment system that is regulated by genes involved in black, blue, and yellow pigments. Our results provide important insights into the evolution of pupal protective colors among swallowtail butterflies.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                03 February 2022
                2021
                : 12
                : 795115
                Affiliations
                [1] 1 State Key Laboratory of Genetic Resources and Evolution , Kunming Institute of Zoology , Chinese Academy of Sciences , Kunming, China
                [2] 2 Kunming College of Life Science , University of Chinese Academy of Sciences , Kunming, China
                [3] 3 School of Ecology and Environment , Northwestern Polytechnical University , Xi’an, China
                Author notes

                Edited by: Li Zhang, Chinese Institute for Brain Research, Beijing (CIBR), China

                Reviewed by: Shuai Zhan, Chinese Academy of Sciences (CAS), China

                Tong-Xian Liu, Northwest A and F University, China

                Tingting Zhang, Shanxi University, China

                *Correspondence: Wen Wang, wwang@ 123456mail.kiz.ac.cn ; Xue-Yan Li, lixy@ 123456mail.kiz.ac.cn

                This article was submitted to Evolutionary and Population Genetics, a section of the journal Frontiers in Genetics

                Article
                795115
                10.3389/fgene.2021.795115
                8852814
                d1f03238-51d8-4fdc-ad61-bc309115a8de
                Copyright © 2022 He, Dong, Hu, Liu, Zhang, Liu, Zhao, Wan, Wang and Li.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 October 2021
                : 22 December 2021
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32070482 31621062
                Funded by: Yunnan Provincial Science and Technology Department , doi 10.13039/501100008871;
                Award ID: 202105AC160039
                Categories
                Genetics
                Original Research

                Genetics
                pupal color polyphenism,pcmh,papilio xuthus,neuroendocrine system,toll signaling pathway,juvenile hormone related genes,cuticular proteins

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