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      ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat ( Scatophagus argus)

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          Abstract

          Background

          Scatophagus argus is a popular farmed fish in several countries of Southeast Asia, including China. Although S. argus has a highly promising economic value, a significant lag of breeding research severely obstructs the sustainable development of aquaculture industry. As one of the most important economic traits, growth traits are controlled by multiple gene loci called quantitative trait loci (QTLs). It is urgently needed to launch a marker assisted selection (MAS) breeding program to improve growth and other pivotal traits. Thus a high-density genetic linkage map is necessary for the fine mapping of QTLs associated with target traits.

          Results

          Using restriction site-associated DNA sequencing, 6196 single nucleotide polymorphism (SNP) markers were developed from a full-sib mapping population for genetic map construction. A total of 6193 SNPs were grouped into 24 linkage groups (LGs), and the total length reached 2191.65 cM with an average marker interval of 0.35 cM. Comparative genome mapping revealed 23 one-to-one and 1 one-to-two syntenic relationships between S. argus LGs and Larimichthys crocea chromosomes. Based on the high-quality linkage map, a total of 44 QTLs associated with growth-related traits were identified on 11 LGs. Of which, 19 significant QTLs for body weight were detected on 9 LGs, explaining 8.8–19.6% of phenotypic variances. Within genomic regions flanking the SNP markers in QTL intervals, we predicted 15 candidate genes showing potential relationships with growth, such as Hbp1, Vgll4 and Pim3, which merit further functional exploration.

          Conclusions

          The first SNP genetic map with a fine resolution of 0.35 cM for S. argus has been developed, which shows a high level of syntenic relationship with L. crocea genomes. This map can provide valuable information for future genetic, genomic and evolutionary studies. The QTLs and SNP markers significantly associated with growth-related traits will act as useful tools in gene mapping, map-based cloning and MAS breeding to speed up the genetic improvement in important traits of S. argus. The interesting candidate genes are promising for further investigations and have the potential to provide deeper insights into growth regulation in the future.

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          Most cited references 57

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          Mapping genes for complex traits in domestic animals and their use in breeding programmes.

          Genome-wide panels of SNPs have recently been used in domestic animal species to map and identify genes for many traits and to select genetically desirable livestock. This has led to the discovery of the causal genes and mutations for several single-gene traits but not for complex traits. However, the genetic merit of animals can still be estimated by genomic selection, which uses genome-wide SNP panels as markers and statistical methods that capture the effects of large numbers of SNPs simultaneously. This approach is expected to double the rate of genetic improvement per year in many livestock systems.
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            SLAF-seq: An Efficient Method of Large-Scale De Novo SNP Discovery and Genotyping Using High-Throughput Sequencing

            Large-scale genotyping plays an important role in genetic association studies. It has provided new opportunities for gene discovery, especially when combined with high-throughput sequencing technologies. Here, we report an efficient solution for large-scale genotyping. We call it specific-locus amplified fragment sequencing (SLAF-seq). SLAF-seq technology has several distinguishing characteristics: i) deep sequencing to ensure genotyping accuracy; ii) reduced representation strategy to reduce sequencing costs; iii) pre-designed reduced representation scheme to optimize marker efficiency; and iv) double barcode system for large populations. In this study, we tested the efficiency of SLAF-seq on rice and soybean data. Both sets of results showed strong consistency between predicted and practical SLAFs and considerable genotyping accuracy. We also report the highest density genetic map yet created for any organism without a reference genome sequence, common carp in this case, using SLAF-seq data. We detected 50,530 high-quality SLAFs with 13,291 SNPs genotyped in 211 individual carp. The genetic map contained 5,885 markers with 0.68 cM intervals on average. A comparative genomics study between common carp genetic map and zebrafish genome sequence map showed high-quality SLAF-seq genotyping results. SLAF-seq provides a high-resolution strategy for large-scale genotyping and can be generally applicable to various species and populations.
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              2b-RAD: a simple and flexible method for genome-wide genotyping.

              We describe 2b-RAD, a streamlined restriction site-associated DNA (RAD) genotyping method based on sequencing the uniform fragments produced by type IIB restriction endonucleases. Well-studied accessions of Arabidopsis thaliana were genotyped to validate the method's accuracy and to demonstrate fine-tuning of marker density as needed. The simplicity of the 2b-RAD protocol makes it particularly suitable for high-throughput genotyping as required for linkage mapping and profiling genetic variation in natural populations.
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                Author and article information

                Contributors
                chpsysu@hotmail.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                3 April 2020
                3 April 2020
                2020
                : 21
                Affiliations
                [1 ]ISNI 0000 0001 0685 868X, GRID grid.411846.e, Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), Guangdong Research Center on Reproductive Control and Breeding Technology of Indigenous Valuable Fish Species, , Fisheries College, Guangdong Ocean University, ; Zhanjiang, 524088 China
                [2 ]Food and Environmental Engineering Department, Yangjiang Polytechnic, Yangjiang, 529566 China
                Article
                6658
                10.1186/s12864-020-6658-1
                7126399
                32245399
                © The Author(s). 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funding
                Funded by: the National Key R&D Program of China
                Award ID: 2018YFD0901203
                Award Recipient :
                Funded by: the National Natural Science Foundation of China
                Award ID: 31702326
                Award ID: 41706174
                Award Recipient :
                Funded by: the Natural Science Foundation of Guangdong Province
                Award ID: 2019A1515010958, 2018B030311050
                Award ID: 2019A1515012042
                Award Recipient :
                Funded by: Guangdong Ocean University Cultivating Fund Project for Excellent Doctoral Dissertations
                Award ID: 201830
                Award Recipient :
                Funded by: Young Creative Talents Project of Guangdong Province Universities and Colleges
                Award ID: 2017GkQNCX092
                Award Recipient :
                Funded by: Special key projects of Guangdong science and Technology Department's science and technology innovation strategy
                Award ID: 2018B030311050
                Award Recipient :
                Funded by: Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang)
                Award ID: ZJW-2019-06
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

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