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      Deciphering the population structure and genetic basis of growth traits from whole-genome resequencing of the leopard coral grouper ( Plectropomus leopardus)

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          Abstract

          The leopard coral grouper ( Plectropomus leopardus) is a species of significant economic importance. Although artificial cultivation of P. leopardus has thrived in recent decades, the advancement of selective breeding has been hindered by the lack of comprehensive population genomic data. In this study, we identified over 8.73 million single nucleotide polymorphisms (SNPs) through whole-genome resequencing of 326 individuals spanning six distinct groups. Furthermore, we categorized 226 individuals with high-coverage sequencing depth (≥14×) into eight clusters based on their genetic profiles and phylogenetic relationships. Notably, four of these clusters exhibited pronounced genetic differentiation compared with the other populations. To identify potentially advantageous loci for P. leopardus, we examined genomic regions exhibiting selective sweeps by analyzing the nucleotide diversity ( θπ) and fixation index ( F ST) in these four clusters. Using these high-coverage resequencing data, we successfully constructed the first haplotype reference panel specific to P. leopardus. This achievement holds promise for enabling high-quality, cost-effective imputation methods. Additionally, we combined low-coverage sequencing data with imputation techniques for a genome-wide association study, aiming to identify candidate SNP loci and genes associated with growth traits. A significant concentration of these genes was observed on chromosome 17, which is primarily involved in skeletal muscle and embryonic development and cell proliferation. Notably, our detailed investigation of growth-related SNPs across the eight clusters revealed that cluster 5 harbored the most promising candidate SNPs, showing potential for genetic selective breeding efforts. These findings provide a robust toolkit and valuable insights into the management of germplasm resources and genome-driven breeding initiatives targeting P. leopardus.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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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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              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
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                Author and article information

                Contributors
                Journal
                Zool Res
                Zool Res
                ZR
                Zoological Research
                Science Press (16 Donghuangchenggen Beijie, Beijing 100717, China )
                2095-8137
                18 March 2024
                : 45
                : 2
                : 329-340
                Affiliations
                [1 ] MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences/Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Qingdao, Shandong/Sanya, Hainan 266100/572025, China
                [2 ] Hainan Seed Industry Laboratory, Sanya, Hainan 572025, China
                [3 ] Southern Marine Science and Engineer Guangdong Laboratory, Guangzhou, Guangdong 511458, China
                Author notes

                #Authors contributed equally to this work

                Article
                zr-45-2-329
                10.24272/j.issn.2095-8137.2023.270
                11017084
                38485503
                ce8714bc-e81c-41c4-85b9-539ecf9d4615
                Copyright © 2024 Editorial Office of Zoological Research, Kunming Institute of Zoology, Chinese Academy of Sciences.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 August 2023
                : 10 October 2023
                Funding
                This study was supported by the National Key Research and Development Program of China (2022YFD2400501), Key R&D Project of Hainan Province (ZDYF2021XDNY133), Project of Sanya Yazhouwan Science and Technology City Management Foundation (SKJC-2020-02-009), PhD Scientific Research and Innovation Foundation of Sanya Yazhou Bay Science and Technology City (HSPHDSRF-2022-02-007) and Young Elite Scientists Sponsorship Program by CAST (2023QNRC001)
                Categories
                Article

                plectropomus leopardus,whole-genome resequencing,growth,haplotype reference panel,single nucleotide polymorphisms

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