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      A high-density linkage map construction in guava ( Psidium guajava L.) using genotyping by sequencing and identification of QTLs for leaf, peel, and pulp color in an intervarietal mapping population

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          Abstract

          Psidium guajava L. is an important fruit crop in the tropical and subtropical regions of the world. The advanced breeding methods are not employed for important commercial traits like peel and pulp color, seed hardiness, fruit size, etc., due to the scarcity of genome-wide molecular markers and high-density linkage maps. In this study, we employed single-nucleotide polymorphism (SNP) markers and identified quantitative trait loci (QTL) regions that are associated with color traits of leaf, peel, and pulp in the guava intervarietal mapping population. The mapping population was developed from the contrasting genotypes of fruit and leaf color. Variations in color among the segregating hybrids were recorded both visually and using a Color reader. A high-density linkage map of guava was constructed using the SNP markers from genotyping by sequencing (GBS) of 150 hybrid individuals of the cross ‘Arka Poorna’ (green) x ‘Purple Local’ (purple). The integrated linkage map consisted of 1426 SNPs mapped on 11 linkage groups (LG), spanning a total distance of around 730 cM with an average of 129.6 markers per LG. Through QTL analysis for color traits, a minor QTL region was identified for visually scored leaf color and peel color on LG1, whereas a major QTL was detected for pulp color in LG4. The Hunter color values (L* and, a*) also had major QTLs with overlapping marker intervals for leaf and peel colors, establishing the association of SNP markers to the trait. The QTLs harbored genes and transcription factors involved in lycopene and anthocyanin pigment biosynthesis. This is the first report of a high-density linkage map based on SNP markers in guava and QTL mapping for color characters in leaf, fruit peel and pulp. The genotyping information generated in this study can aid in genetic engineering and marker-assisted breeding in guava.

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

          Shifu Chen, Yanqing Zhou, Yaru Chen … (2018)
          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.
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            A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

            Robert Elshire, Jeffrey C. Glaubitz, Qi-ying Sun … (2011)
            Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.
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              ShinyGO: a graphical gene-set enrichment tool for animals and plants

              Steven Xijin Ge, Dongmin Jung, Runan Yao … (2019)
              Gene lists are routinely produced from various omic studies. Enrichment analysis can link these gene lists with underlying molecular pathways and functional categories such as gene ontology (GO) and other databases. To complement existing tools, we developed ShinyGO based on a large annotation database derived from Ensembl and STRING-db for 59 plant, 256 animal, 115 archeal and 1678 bacterial species. ShinyGO’s novel features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for the retrieval of pathway diagrams and protein–protein interaction networks. ShinyGO is an intuitive, graphical web application that can help researchers gain actionable insights from gene-sets. http://ge-lab.org/go/. Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Malarvizhi Mathiazhagan: Role: Role: Role: Role: Role:
                Dayanandhi Elangovan: URI : https://loop.frontiersin.org/people/173913Role: Role: Role:
                Vasugi Chinnaiyan: Role: Role: Role: Role:
                Kodthalu Seetharamaiah Shivashankara: URI : https://loop.frontiersin.org/people/2628441Role: Role: Role:
                Darisi Venkata Sudhakar Rao: Role: Role:
                Kundapura Venkataramana Ravishankar: URI : https://loop.frontiersin.org/people/1756185Role: Role: Role: Role: Role:
                Journal
                Journal ID (nlm-ta): Front Plant Sci
                Journal ID (iso-abbrev): Front Plant Sci
                Journal ID (publisher-id): Front. Plant Sci.
                Title: Frontiers in Plant Science
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 1664-462X
                Publication date (Electronic): 27 February 2024
                Publication date Collection: 2024
                Volume: 15
                Electronic Location Identifier: 1335715
                Affiliations
                [1] 1 Division of Basic Sciences, ICAR-Indian Institute of Horticultural Research , Bengaluru, India
                [2] 2 Centre for Post-graduate Studies, Jain (Deemed-to-be) University , Bengaluru, India
                [3] 3 Division of Fruit Crops, ICAR-Indian Institute of Horticultural Research , Bengaluru, India
                [4] 4 Division of Post Harvest Technology and Agricultural Engineering, ICAR-Indian Institute of Horticultural Research , Bengaluru, India
                Author notes

                Edited by: Nelson Marmiroli, University of Parma, Italy

                Reviewed by: Manosh Kumar Biswas, University of Leicester, United Kingdom

                Lohithaswa Hirenallur Chandappa, University of Agricultural Sciences, Bangalore, India

                *Correspondence: Kundapura Venkataramana Ravishankar, kv_ravishankar@ 123456yahoo.co.in
                Article
                DOI: 10.3389/fpls.2024.1335715
                PMC ID: 10927721
                PubMed ID: 38476683
                SO-VID: b0256d98-c7e2-4466-8407-391e3cc7e7df
                Copyright © Copyright © 2024 Mathiazhagan, Elangovan, Chinnaiyan, Shivashankara, Sudhakar Rao and Ravishankar
                License:

                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
                Date received : 09 November 2023
                Date accepted : 12 February 2024
                Page count
                Figures: 7, Tables: 6, Equations: 0, References: 62, Pages: 16, Words: 7176
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The financial support received from Rashtriya Krishi Vikas Yojana (RKVY) project, “Centre for excellence in genomic assisted selection for developing processing guava” (Grant ID-KA/RKVY-HORT2022/1299).
                Categories
                Subject: Plant Science
                Subject: Original Research
                Custom metadata
                section-in-acceptance Plant Biotechnology

                ScienceOpen disciplines: Plant science & Botany
                Keywords: guava,genotyping by sequencing,snp markers,linkage map,leaf color,peel color,pulp color,quantitative trait loci
                Data availability:
                ScienceOpen disciplines: Plant science & Botany
                Keywords: guava, genotyping by sequencing, snp markers, linkage map, leaf color, peel color, pulp color, quantitative trait loci

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