ArticleBreeding science2020
Identification of a SNP and development of a PCR-based allele-specific marker of the sporulation-deficient (sporeless) trait of the Tamogitake 108Y2D mutant using next-generation sequencing.
Article in Breeding science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 3 citations in OpenAlex.
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6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
The mass scattering of basidiospores during the cultivation of edible mushrooms causes serious problems, such as allergic reactions in workers. Sporulation-deficient (sporeless) cultivars would be very useful for preventing these issues. We aimed to identify the single-nucleotide polymorphism (SNP) that is responsible for the single dominant sporeless mutation of the Tamogitake 108Y2D mutant using next-generation sequencing (NGS) and TILLING technology and to develop an allele-specific PCR marker for sporeless breeding. By comparing the sequences of the wild-type and its mutant genomes, we identified 685 mutation loci in gene regions and pinpointed one SNP only consistent with sporeless phenotype for 105 segregants, i.e., a C to T located at position 1,950 of the exonic region of a putative fungal transcription factor that generated a stop codon. We developed an allele-specific marker based on the identified SNP, and its high practicality was validated using tests against progenies from several hybrids and wild isolates from different geographical origins. Thus, the allele-specific PCR marker developed here will be useful for marker-assisted selection in the breeding of the sporeless trait of this mushroom. Furthermore, the technical success of SNP identification and marker development based on NGS genome data can help achieve efficient mutation breeding in mushrooms.
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