Combined use of Specific Length Amplified Fragment Sequencing (SLAF-seq) And Bulked Segregant Analysis (BSA) For Rapid Identification of Genes Influencing Fiber Content of Hemp (Cannabis sativa L.)

Abstract

\n Hemp (Cannabis sativa L.), an ancient crop, is a significant source of high-quality fiber that primarily caters to the textile industry worldwide. Compared to other fiber crops, hemp is an environmentally friendly fiber crop which requires fewer pesticides and purifies the soil during cultivation. Fiber content is a crucial quantitative trait for evaluating fiber yield in hemp. Understanding the genetic mechanisms involved in hemp breeding is essential for improving yield. In this study, to investigate these underlying mechanisms, we developed 660 F1 plants from a cross between Jindao-15(high fiber content fiber-use variety)and Fire No.1༈low fiber content fiber-use variety༉, and thirty plants each with high and low fiber content were selected from 305 monoecious plants of this population according to 5 %-10 % of population size for quantitative traits. The DNA from these plants was extracted to establish two bulk DNA pools. The DNA was then subjected to the restriction digestion by the enzymes RsaI and HaeIII to obtain 314–364 bp digestion fragments and subjected to sequencing using specific length amplified fragment sequencing (SLAF-seq). Then, each fragment was labeled with specific SLAF tags, and single nucleotide polymorphisms (SNPs) were identified to determine the candidate regions related to fiber content through marker association analysis of genotype frequency differences between the mixed pools of DNA. The gene annotation results identified the candidate genes responsible for the fiber content of hemp. In this study, we successfully developed 368,404 SLAF tags, which led to the detection of 389,687 SNPs. These SNPs were then subjected to the SNP-Index correlation algorithm, which revealed four candidate regions related to fiber content traits on Chromosome 1, with a length of 8.68 Mb and containing 389 annotated genes. We found that 199 non-synonymous mutations which change the amino acids sequences existed in the parent population. The annotation information and the comparison results identified 15 genes that were highly likely to modulate the fiber content of hemp. Further, qPCR validation identified six genes (LOC115705530, LOC115705875, LOC115704794, LOC115705371, LOC115705688 and LOC115707511) that were highly positively correlated with influencing the hemp fiber content. These genes were involved in the transcription regulation, auxin and water transportion, one carbon and sugar metabolism. Thus, our study highlights the importance of the combined use of SLAF-Seq and Bulked Segregant analysis (BSA) to locate genes related to hemp fiber content rapidly. Hence, our study provides novel mechanistic inputs for the fast identification of genes related to important agronomic traits of hemp and other crops catering to the textile industry.