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      Genomic diversity, population structure, and genome-wide association reveal genetic differentiation and trait improvements in mango

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          Abstract

          Mango ( Mangifera indica L.) has been widely cultivated as a culturally and economically significant fruit tree for roughly 4000 years. Despite its rich history, little is known about the crop’s domestication, genomic variation, and the genetic loci underlying agronomic traits. This study employs the whole-genome re-sequencing of 224 mango accessions sourced from 22 countries, with an average sequencing depth of 16.37×, to explore their genomic variation and diversity. Through phylogenomic analysis, M. himalis J.Y. Liang, a species grown in China, was reclassified into the cultivated mango group known as M. indica. Moreover, our investigation of mango population structure and differentiation revealed that Chinese accessions could be divided into two distinct gene pools, indicating the presence of independent genetic diversity ecotypes. By coupling genome-wide association studies with analyses of genotype variation patterns and expression patterns, we identified several candidate loci and dominant genotypes associated with mango flowering capability, fruit weight, and volatile compound production. In conclusion, our study offers valuable insights into the genetic differentiation of mango populations, paving the way for future agronomic improvements through genomic-assisted breeding.

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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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            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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              RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

              Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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                Author and article information

                Contributors
                Journal
                Hortic Res
                Hortic Res
                hr
                Horticulture Research
                Oxford University Press
                2662-6810
                2052-7276
                July 2024
                01 July 2024
                01 July 2024
                : 11
                : 7
                : uhae153
                Affiliations
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                Panzhihua Academy of Agricultural and Forestry Sciences , Panzhihua, Sichuan 617061, China
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                Panzhihua Academy of Agricultural and Forestry Sciences , Panzhihua, Sichuan 617061, China
                Panzhihua Academy of Agricultural and Forestry Sciences , Panzhihua, Sichuan 617061, China
                Liangshan Academy of Forest and Grassland , Xichang, Sichuan 615000, China
                Liangshan Academy of Forest and Grassland , Xichang, Sichuan 615000, China
                Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences , Haikou, Hainan 571100, China
                Bioinformatics and Analytics Core, University of Missouri , Columbia, MO 65201, USA
                National Key Laboratory for Tropical Crop Breeding, Sanya 572024, China; Key Laboratory of Tropical Fruit Biology, Ministry of Agriculture & Rural Affairs; Key Laboratory for Postharvest Physiology and Technology of Tropical Horticultural Products of Hainan Province, South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences , Zhanjiang, Guangdong 524091, China
                College of Agriculture, Henan University , Zhengzhou, Henan 450046, China
                Author notes
                Corresponding authors. E-mail: xuwentian@ 123456catas.cn ; kyc@ 123456henu.edu.cn

                These authors contributed equally to this work.

                Article
                uhae153
                10.1093/hr/uhae153
                11246242
                39006000
                dbdf3be6-4aa2-4c49-98a7-6fb60ce1420c
                © The Author(s) 2024. Published by Oxford University Press on behalf of Nanjing Agricultural University.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 January 2024
                : 23 May 2024
                : 01 July 2024
                Page count
                Pages: 11
                Funding
                Funded by: funder-nameChina Agriculture Research System of MOF and MARA;
                Award ID: CARS-31
                Funded by: funder-nameGuangdong Province Seed Industry Revitalization Project;
                Award ID: 2022-NPY-00-030
                Funded by: funder-nameNational Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 32360727
                Funded by: funder-nameHainan Province Key Research and Development Plan;
                Award ID: ZDYF2022XDNY255
                Funded by: funder-nameHainan Provincial Natural Science Foundation of China;
                Award ID: 322CXTD524
                Funded by: funder-nameNatural Science Foundation of Guangdong Province, DOI 10.13039/501100003453;
                Award ID: 2021A1515010966
                Categories
                Article
                AcademicSubjects/SCI01210
                AcademicSubjects/SCI01140

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