Quantitative trait loci mapping for free amino acid content using an albino population and SNP markers provides insight into the genetic improvement of tea plants

Rong Huang , Jun-Ya Wang , Ming-Zhe Yao , Chun-Lei Ma , Liang Chen

Horticulture Research ›› 2022, Vol. 9 ›› Issue (1) : uhab029

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Horticulture Research ›› 2022, Vol. 9 ›› Issue (1) :uhab029 DOI: 10.1093/hr/uhab029
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Quantitative trait loci mapping for free amino acid content using an albino population and SNP markers provides insight into the genetic improvement of tea plants
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Abstract

Free amino acids are one of the main chemical components in tea, and they contribute to the pleasant flavor, function, and quality of tea, notably the level of theanine. Here, a high-density genetic map was constructed to characterize quantitative trait loci (QTLs) for free amino acid content. A total of 2688 polymorphic SNP markers were obtained using genotyping-by-sequencing (GBS) based on 198 individuals derived from a pseudotestcross population of “Longjing 43”× “Baijiguan”, which are elite and albino tea cultivars, respectively. The 1846.32 cM high-density map with an average interval of 0.69 cM was successfully divided into 15 linkage groups (LGs) ranging from 93.41 cM to 171.28 cM. Furthermore, a total of 4 QTLs related to free amino acid content (theanine, glutamate, glutamine, aspartic acid and arginine) identified over two years were mapped to LG03, LG06, LG11 and LG14. The phenotypic variation explained by these QTLs ranged from 11.8% to 23.7%, with an LOD score from 3.56 to 7.7. Furthermore, several important amino acid metabolic pathways were enriched based on the upregulated differentially expressed genes (DEGs) among the offspring. These results will be essential for fine mapping genes involved in amino acid pathways and diversity, thereby providing a promising avenue for the genetic improvement of tea plants.

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Rong Huang, Jun-Ya Wang, Ming-Zhe Yao, Chun-Lei Ma, Liang Chen. Quantitative trait loci mapping for free amino acid content using an albino population and SNP markers provides insight into the genetic improvement of tea plants. Horticulture Research, 2022, 9 (1) : uhab029 DOI:10.1093/hr/uhab029

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