BMC Plant Biology (Dec 2018)

Genome-wide association study discovered favorable single nucleotide polymorphisms and candidate genes associated with ramet number in ramie (Boehmeria nivea L.)

  • Kunmei Chen,
  • Mingbao Luan,
  • Heping Xiong,
  • Ping Chen,
  • Jikang Chen,
  • Gang Gao,
  • Kunyong Huang,
  • Aiguo Zhu,
  • Chunming Yu

DOI
https://doi.org/10.1186/s12870-018-1573-1
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 10

Abstract

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Abstract Background Ramie (Boehmeria nivea L.) is one of the most important natural fiber crops and an important forage grass in south China. Ramet number, which is a quantitative trait controlled by multigenes, is one of the most important agronomic traits in plants because the ramet number per plant is a key component of grain yield and biomass. However, the genetic variation and genetic architecture of ramie ramet number are rarely known. Results A genome-wide association study was performed using a panel of 112 core germplasms and 108,888 single nucleotide polymorphisms (SNPs) detected using specific-locus amplified fragment sequencing technology. Trait-SNP association analysis detected 44 significant SNPs that were associated with ramet number at P < 0.01. The favorable SNP Marker20170–64 emerged at least twice in the three detected stages and was validated to be associated with the ramie ramet number using genomic DNA polymerase chain reaction with an F1 hybrid progeny population. Comparative genome analysis predicted nine candidate genes for ramet number based on Marker20170–64. Real-time quantitative polymerase chain reaction analysis indicated that six of the genes were specific to upregulation in the ramie variety with high ramet number. These results suggest that these genes could be considered as ramet number-associated candidates in ramie. Conclusions The identified loci or genes may be promising targets for genetic engineering and selection for modulating the ramet number in ramie. Our work improves understanding of the genetics of ramet number in ramie core germplasms and provides tools for marker-assisted selection for improvement of agricultural traits.

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