0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genomes of the cosmopolitan fruit pest Bactrocera dorsalis (Diptera: Tephritidae) reveal its global invasion history and thermal adaptation

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Graphical abstract

          Highlights

          • The present study achieves a large-scale SNP dataset, a total of 512 genomes comprising 487 B. dorsalis and 25 B. carambolae.

          • B. dorsalis originates from the Southern India with three invasion routes worldwide, mainly facilitated by human activities.

          • CYP6a9 is identified that enhance the thermal adaptation of B. dorsalis and thus boost its invasion to temperate regions.

          • The gene function is further verified using the RNAi technology.

          Abstract

          Introduction

          The oriental fruit fly Bactrocera dorsalis is one of the most destructive agricultural pests worldwide, with highly debated species delimitation, origin, and global spread routes.

          Objectives

          Our study intended to (i) resolve the taxonomic uncertainties between B. dorsalis and B. carambolae, (ii) reveal the population structure and global invasion routes of B. dorsalis across Asia, Africa, and Oceania, and (iii) identify genomic regions that are responsible for the thermal adaptation of B. dorsalis.

          Methods

          Based on a high-quality chromosome-level reference genome assembly, we explored the population relationship using a genome-scale single nucleotide polymorphism dataset generated from the resequencing data of 487 B. dorsalis genomes and 25 B. carambolae genomes . Genome-wide association studies and silencing using RNA interference were used to identify and verify the candidate genes associated with extreme thermal stress.

          Results

          We showed that B. dorsalis originates from the Southern India region with three independent invasion and spread routes worldwide: (i) from Northern India to Northern Southeast Asia, then to Southern Southeast Asia; (ii) from Northern India to Northern Southeast Asian, then to China and Hawaii; and (iii) from Southern India toward the African mainland, then to Madagascar, which is mainly facilitated by human activities including trade and immigration. Twenty-seven genes were identified by a genome-wide association study to be associated with 11 temperature bioclimatic variables. The Cyp6a9 gene may enhance the thermal adaptation of B. dorsalis and thus boost its invasion, which tended to be upregulated at a hardening temperature of 38 °C. Functional verification using RNA interference silencing against Cyp6a9, led to the specific decrease in Cyp6a9 expression, reducing the survival rate of dsRNA-feeding larvae exposed to extreme thermal stress of 45 °C after heat hardening treatments in B. dorsalis.

          Conclusion

          This study provides insights into the evolutionary history and genetic basis of temperature adaptation in B. dorsalis.

          Related collections

          Most cited references74

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

            Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              fastp: an ultra-fast all-in-one FASTQ preprocessor

              Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Adv Res
                J Adv Res
                Journal of Advanced Research
                Elsevier
                2090-1232
                2090-1224
                24 December 2022
                November 2023
                24 December 2022
                : 53
                : 61-74
                Affiliations
                [a ]College of Plant Protection, China Agricultural University, Beijing 100193, China
                [b ]Key Laboratory of Surveillance and Management for Plant Quarantine Pests, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
                [c ]Royal Museum for Central Africa, Invertebrates Section and JEMU, Tervuren B3080, Belgium
                [d ]Department of Fruit Science, Punjab Agricultural University, Ludhiana, Punjab, India
                [e ]Centre for Insect Systematics, Department of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor Darul Ehsan, Malaysia
                [f ]Institute of Plant Quarantine, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
                [g ]CIRAD UMR PVBMT, Ambatobe, Madagascar
                [h ]Ministry of Agriculture, Animal Husbandry and Fisheries, Paramaribo, Suriname
                [i ]School of Life Science and Technology, Bandung Institute of Technology, Bandung 40132, Indonesia
                [j ]National Agriculture Quarantine & Inspection Authority, Port Moresby, Papua New Guinea
                [k ]Apiculture Research Institute, P.O. Box 32-40302, Marigat, Kenya
                [l ]Crop Protection Directorate, Dakar, Senegal
                [m ]Department of Agriculture, Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, Mardan, Pakistan
                Author notes
                [* ]Corresponding author at: College of Plant Protection, China Agricultural University, Beijing 100193, China; Key Laboratory of Surveillance and Management for Plant Quarantine Pests, Ministry of Agriculture and Rural Affairs, Beijing 100193, China. lizh@ 123456cau.edu.cn
                [1]

                Retired.

                Article
                S2090-1232(22)00291-0
                10.1016/j.jare.2022.12.012
                10658297
                36574947
                bc456843-0677-4770-ae27-72d318a43866
                © 2023 The Authors. Published by Elsevier B.V. on behalf of Cairo University.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 17 September 2022
                : 29 November 2022
                : 19 December 2022
                Categories
                Original Article

                bactrocera dorsalis,chromosome-level genome assembly,invasion routes and history,resequencing,species delimitation,thermal adaptation

                Comments

                Comment on this article