Literature DB >> 33431939

Discovery of SNPs and InDels in papaya genotypes and its potential for marker assisted selection of fruit quality traits.

Dieimes Bohry1, Helaine Christine Cancela Ramos2, Pedro Henrique Dias Dos Santos2, Marcela Santana Bastos Boechat2, Fernanda Abreu Santana Arêdes2, Adriana Azevedo Vimercati Pirovani2, Messias Gonzaga Pereira2.   

Abstract

Papaya is a tropical and climacteric fruit that is recognized for its nutritional benefits and medicinal applications. Its fruits ripen quickly and show a drastic fruit softening, leading to great post-harvest losses. To overcome this scenario, breeding programs of papaya must invest in exploring the available genetic variation to continue developing superior cultivars with improved fruit quality traits. The objective of this study was to perform a whole-genome genotyping (WGG) of papaya, predict the effects of the identified variants, and develop a list of ripening-related genes (RRGs) with linked variants. The Formosa elite lines of papaya Sekati and JS-12 were submitted to WGG with an Illumina Miseq platform. The effects of variants were predicted using the snpEff program. A total of 28,451 SNPs having Ts/Tv (Transition/Transversion) ratio of 2.45 and 1,982 small insertions/deletions (InDels) were identified. Most variant effects were predicted in non-coding regions, with only 2,104 and 138 effects placed in exons and splice site regions, respectively. A total of 106 RRGs were found to be associated with 460 variants, which may be converted into PCR markers to facilitate genetic mapping and diversity studies and to apply marker-assisted selection (MAS) for specific traits in papaya breeding programs.

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Year:  2021        PMID: 33431939      PMCID: PMC7801719          DOI: 10.1038/s41598-020-79401-z

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  34 in total

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Review 3.  Molecular and genetic regulation of fruit ripening.

Authors:  Nigel E Gapper; Ryan P McQuinn; James J Giovannoni
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Journal:  BMC Genomics       Date:  2015-10-05       Impact factor: 3.969

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Journal:  Sci Rep       Date:  2018-09-28       Impact factor: 4.379

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10.  QTL Analyses in Multiple Populations Employed for the Fine Mapping and Identification of Candidate Genes at a Locus Affecting Sugar Accumulation in Melon (Cucumis melo L.).

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Journal:  Front Plant Sci       Date:  2017-09-26       Impact factor: 5.753

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  1 in total

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Journal:  Genes (Basel)       Date:  2021-11-25       Impact factor: 4.096

  1 in total

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