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      Population-scale peach genome analyses unravel selection patterns and biochemical basis underlying fruit flavor

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          Abstract

          A narrow genetic basis in modern cultivars and strong linkage disequilibrium in peach ( Prunus persica) has restricted resolution power for association studies in this model fruit species, thereby limiting our understanding of economically important quality traits including fruit flavor. Here, we present a high-quality genome assembly for a Chinese landrace, Longhua Shui Mi (LHSM), a representative of the Chinese Cling peaches that have been central in global peach genetic improvement. We also map the resequencing data for 564 peach accessions to this LHSM assembly at an average depth of 26.34× per accession. Population genomic analyses reveal a fascinating history of convergent selection for sweetness yet divergent selection for acidity in eastern vs. western modern cultivars. Molecular-genetics and biochemical analyses establish that PpALMT1 (aluminum-activated malate transporter 1) contributes to their difference of malate content and that increases fructose content accounts for the increased sweetness of modern peach fruits, as regulated by PpERDL16 (early response to dehydration 6-like 16). Our study illustrates the strong utility of the genomics resources for both basic and applied efforts to understand and exploit the genetic basis of fruit quality in peach.

          Abstract

          Longhua Shui Mi (LHSM) is a representative of the Chinese Cling peaches that have been central in global peach genetic improvement. Here, the authors assemble the genome of LHSM and show convergent selection for sweetness yet divergent selection for acidity in eastern vs. western cultivars through population genomics analyses.

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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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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                quanj@vip.sina.com
                weijianhua@baafs.net.cn
                xiehua@baafs.net.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                14 June 2021
                14 June 2021
                2021
                : 12
                : 3604
                Affiliations
                [1 ]Beijing Agro-Biotechnology Research Center, Academy of Agriculture and Forestry Sciences/Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing, China
                [2 ]GRID grid.418260.9, ISNI 0000 0004 0646 9053, Beijing Academy of Forestry and Pomology Sciences, Beijing Academy of Agriculture and Forestry Sciences, ; Beijing, China
                [3 ]GRID grid.469586.0, Institute of Pomology, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, ; Nanjing, China
                Author information
                http://orcid.org/0000-0001-6123-4992
                http://orcid.org/0000-0001-9969-8944
                http://orcid.org/0000-0003-2867-4114
                Article
                23879
                10.1038/s41467-021-23879-2
                8203738
                34127667
                e4c1e72d-982f-4521-aaa0-2dfa1a604887
                © The Author(s) 2021

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 February 2021
                : 17 May 2021
                Funding
                Funded by: This research was supported by the National Key Research and Development Program (grant no. 2018YFD1000200) and the Financial Special Foundation (grant no. KJCX201907-2), the Innovation Capacity Building Foundation (grant no. KJCX20210432), and the Youth Foundation (grant no. QNJJ202120) from Beijing Academy of Agriculture and Forestry Sciences.
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                © The Author(s) 2021

                Uncategorized
                agricultural genetics,genetic association study,genomics,plant evolution
                Uncategorized
                agricultural genetics, genetic association study, genomics, plant evolution

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