High-resolution genetic map construction and QTL analysis of important ber traits in kenaf using RAD-seq

Quantitative trait locus (QTL) mapping is a useful method for revealing the mechanism of complex genetic traits and identifying new genomic information to accelerate crop improvement. In the present study, 154 F 2:3 strains and their parents were used for restriction site-associated DNA sequencing, single-nucleotide polymorphism (SNP) identication, and genetic map construction. After ltering based on stringent ltering standards, 297.5 Gb of clean data were obtained. Further, 5,191 polymorphic SNP markers were identied from each sample, of which 1,997 polymorphic SNP markers were successfully mapped onto 18 different linkage groups. Six QTLs (QPH, QFBW, QDBW, QFW, QFT, and QFC) were identied based on the genetic map using the multiple QTL mapping (MQM) method, which were then assigned to three linkage groups, LG16, LG8, and LG3. QPH, QFBW, QDBW, and QFW were related to ber yield, while QFT and QFC were related to ber quality. This is the rst study of its kind to map QTL of ber yield and ber quality, which will facilitate further understanding of the molecular genetic basis of these traits. However, there are limitations regarding the utilization of this map because several large gaps remain in some linkage groups. Therefore, additional markers need to be developed to further narrow these regions. The results showed that the three agronomic characters were closely related. Moreover, QDBW and QFW1 were located in the same region in LG8 and were closely associated with the same SNP marker un_56233383. These results showed that ber yield and quality-related genes may have pleiotropic effects. The SNP markers un_59437998 and un_56233383 were closely linked to ber yield agronomic trait, suggesting that the two SNP markers can be candidate molecular markers for determining the ber yield during breeding.


Introduction
Kenaf (Hibiscus cannabinus L.) is an important natural ber crop. The main purpose of kenaf planting is to harvest bast bers. Kenaf bers can be used as textile materials, carpet backing, packing materials, paper pulp, and biocomposite materials (Li et  protection, the demand for natural ber is increasing worldwide. Kenaf ber is an important natural ber; therefore, improving both the quality and yield of the ber is an essential task in kenaf breeding.
It is common knowledge that the agronomic traits of ber yield and quality are controlled by polygenes. It is di cult to further increase the ber yield and quality using traditional breeding strategies, such as hybrid breeding, which are the main methods currently used to improve these traits. Marker-assisted selection breeding is an e cient method to improve both ber yield and quality.
In kenaf, the rst genetic linkage map was constructed in 2011 using sequence-related ampli ed polymorphism (SRAP), inter simple sequence repeats (ISSR), and random ampli ed polymorphic DNA (RAPD) markers, which comprised 307 loci (Chen et al. 2011). Due to the limitation of the number of traditional markers when constructing the genetic linkage map, the map cannot achieve su cient resolution for quantitative trait locus (QTL) mapping or map-based cloning. However, single-nucleotide polymorphism (SNP) markers, which are widely distributed in plant genomes, have been previously used to construct genetic maps and map QTLs in many crops, such as jute, upland cotton, alfalfa, Hawthorn, The combination of next-generation sequencing technology (NGS) and restriction enzyme digestion has facilitated the development of SNP markers and genotyping processes ).
Restriction site-associated DNA sequencing (RAD-seq) is an e cient method to develop SNP markers for high-throughput genotyping, and does not require a reference genome. To date, RAD sequencing has been used to construct high-density linkage maps and QTL maps for important agronomic traits in many species, such as barley and Barbarea vulgaris (Chutimanitsakun et al. 2011;Liu et al. 2019). However, high-density genetic linkage maps have been constructed for kenaf using RAD-seq technology.
In this study, we developed a high-density genetic linkage map with SNP markers, using an F 2:3 population derived from a cross between Taihong763 ( ) and F71 ( ). This is the rst attempt to use SNP markers to construct high-density genetic linkage maps. We rst identi ed six QTLs for both ber yield and quality agronomic traits based on this genetic map. These results will be fundamental for markerassisted gene selection in kenaf breeding programs.

Plant material
A tall female parent Taihong763 with a plant height of 466 cm and a short male parent F71 with a plant height (360 cm) were supplied by the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences. Hybridization occurred between Taihong763 ( ) and F71 ( ), which were planted in Changsha, in Hunan Province during the summer of 2017. The hybrid seeds were harvested, and these were planted in eight rows (each row was 10 m long, 0.6 m apart) and self-pollinated to produce the F2 generation in Sanya, Hainan Province, in 2019. In 2020, we selected 154 F 2:3 plant strains and planted them in Changde, Hunan Province. The two parents and the 154 F 2:3 plant strains were used to construct highdensity genetic linkage map and to map QTLs. Young leaf tissues from the two parents and 154 F 2:3 plant strains were collected for genomic DNA extraction.

Fiber yield and ber quality phenotypic measurements and analysis
The F 2:3 population was planted in Changde, Hunan, in the summer of 2020. Ten individual plants of each F 2:3 plant strain were randomly selected for measuring their agronomic traits. The following six agronomic traits related to ber yield and quality were investigated in this study: plant height (PH), fresh bast weight (FBW), dry bast weight (DBW), ber weight (FW), ber strength, (FS), and ber count (FC). pH was measured in mature plants as the distance (cm) from the root to the top of the plant. FBW was determined based on the weight (g) of the whole plant's fresh bast. DBW was determined by the weight (g) of the whole plant's dry bast. FW was measured as the weight (g) of the whole plant's bast ber. FS (N/tex) was measured using an Instron 3350 instrument. FC (N) was measured using an OFDA 2000 instrument. SPSS software (version 21.0) was used for statistical analysis of phenotypic data. The eld trial experiments were performed in Changde, Hunan, in the summer of 2020, following completely random block design with three replications. The average value was calculated as the nal phenotypic value.

DNA extraction, RAD library construction and sequencing
Young leaves from F 2:3 individuals and their parents were collected and used to extract genomic DNA following the manufacturer's protocol of the Plant Genomic DNA extraction Kit (Tiangen Biotech, Beijing, China). DNA concentration and purity were assessed using a NanoPhotometer® NP 80 spectrophotometer (IMPLEN, CA, USA).
The RAD-seq library was developed based on a previously described protocol (Baird et al. 2008;Guo et al. 2015). Genomic DNA of the F 2:3 strains and their parents were digested by EcoRI (New England Biolabs, Ipswich, MA, USA) and were then ligated to a P1 adapter containing a nucleotide barcode for individual labeling. The digested DNA and the P1 adapter from different samples were pooled together and randomly sheared. The 400-700 bp fragments were selected and ligated with the P2 adapter. Several rounds of PCR ampli cation were performed to enrich the adapter-ligated DNA fragments, and DNA fragments within the 400-700 bp range were selected and puri ed for library construction. The quali ed library was sequenced on HiSeq4000 platform using the PE150 strategy.

SNP discovery and genotyping
The raw data were segregated to each individual of the F 2:3 population or the parents according to their nucleotide barcodes. The raw reads were ltered to the trimmed P1 and P2 adapter sequences, and the low quality sequences were removed, according to the standards described by Nie et al. (2017). SNP identi cation and genotyping were performed using the Stacks software ). The SNPs of the two parents and individuals of the F 2:3 population were identi ed by aligning the clean reads to the reference RAD tags. Polymorphic SNPs were selected according to the following stringent ltering standards: (a) homozygous sites with polymorphism between parents were screened, (b) the loci with missing parental information were ltered out, and (c) the loci with >10% unidenti ed nucleotides were removed from the offspring population. Genotypes of each F 2:3 plant strain were obtained by comparing these genotypes with the parental genotypes. Polymorphic SNP markers, which conformed to the above standards and with <10% missing data among the 154 F 2:3 strains, were used to construct the genetic map.

Genetic linkage map construction
Polymorphic SNP markers with more than a 10% deletion rate in the F 2:3 plant strains were removed and further ltered using the parameters of segregation distortion (p < 0.01). The value of logarithm of odds (LOD) ranged from 2.0 to 20.0 using the maximum likelihood method. Joinmap 4.1 software was used to separate ltered markers into 18 linkage groups. The distance between the polymorphic SNP markers was then calculated using Kosambi mapping function. MapChart 2.2 software was used to draw the visualized linkage map (Voorrips 2002).

QTL mapping and analysis
The ber yield and quality data were used to map QTLs based on the high-density genetic map using MapQTL6.0 (Van Ooijen and Kyazma 2009). A multiple QTL mapping (MQM) model was used to scan the QTLs. A permutation test (1000 replications) at 5% level of signi cance was conducted to achieve the LOD threshold, which was in turn used to determine the existence of QTLs. QTLs were detected with an LOD threshold of ≥4.0. Moreover, the location of the QTL was determined according to its peak LOD location and the surrounding region over the score threshold. The analysis results indicated the additive effects of QTLs and explanation rate of phenotypic variation by QTLs.

Phenotypic analyses of ber yield and quality traits
Fiber yield and quality phenotypic data showed continuous positive distribution or positively skewed distribution (Fig. 1). As shown in Fig. 1, the six agronomic traits are quantitative traits controlled by multiple genes. Transgressive segregation in the F 2:3 population was observed for the six traits, which suggested that there were allelic genes, which had positive effects on the six agronomic traits. The correlation analysis (Table 1) showed that there was a positive correlation between FW and PH, FBW, and DBW (p < 0.01). This is because the kenaf ber originates from the bast of the plant, and the FW is closely related to the bast weight. Taller the plant, more is the weight of the ber. There was also a positive correlation between the FW and FS (p < 0.01). However, there was a negative correlation between FW and FC (p < 0.01). There was no correlation between the FS and FC.

Rad Sequencing And Genotyping
There were 156 RAD-seq libraries that were constructed from 154 F 2:3 strains and their parents, which were then sequenced on the Illumina HiSeq4000 platform. A total of 305.93 Gb of raw data were obtained and assigned to each sample according to their nucleotide barcode. After ltering and trimming the adapter sequence and removing the low-quality sequences, 297.5 Gb of clean data were obtained. There were 196,389 RAD tags that were found and used as reference tags. The SNP loci of each sample were identi ed. According to stringent ltering standards, 5,191 polymorphic SNP markers were identi ed and used to construct the genetic map. The number of SNP markers in each sample is shown in Table S1.

Genetic Linkage Map Construction
After ltering, 1,997 polymorphic SNP markers were successfully mapped onto 18 different linkage groups ( LG12, and the minimum gap length was 0.504 cM, which occurred in LG18. According to these results, the linkage distance distribution and resolution in this genetic map were much better than the genetic map constructed using SRAP, ISSR, and RAPD markers.

Fiber Yield And Quality Qtl Analysis
The ber yield and quality-related traits, which showed a continuous distribution (Fig. 1), were controlled by polygenes. Overall, six QTLs (QPH, QFBW, QDBW, QFW, QFT, and QFC) were detected with the genetic map using the MQM method (Fig. 2, Table 3). Among the six QTLs, QPH, QFBW, QDBW, and QFW were associated with ber yield, and QFT and QFC were associated with ber quality. On LG16, two QTLs (Q1 and Q2) were detected, QPH1 and 2, QFBW2, and QFW3 were located at the same locus (Q1), and QFC was located at the Q2 locus. QPH, with two closely related markers (un_59437998 and un_24745703), explained 13.8% and 13.5% of the PH phenotypic changes, respectively. QFBW, with two closely related markers (un_37170711, un_59437998), explained 10.7% and 11.9% of the FBW phenotypic changes, respectively. QFW, with closely related marker un_59437998, explained 10.5% of the phenotypic variance of the FW. QFC, with closely related marker un_25677623, could explain 12.3% of the phenotypic variance of the FC. On LG8, one QTL was identi ed, and QDBW and QFW 1 and 2 were located at the same locus (Q3). QDBW, with the closely related marker un_56233383, could explain 11.8% of the phenotypic variance of the DBW. QFW, with two closely related markers un_56233383 and un_36391475, could explain 14.7% and 14.0% of the phenotypic variance of the FW, respectively.  Riaz et al. 2004). However, the genetic linkage maps constructed using traditional molecular markers have a lower resolution and lower genome coverage than the genetic map constructed using SNP markers. With the development of sequencing technology, RAD-seq technology has been used for identifying SNPs and constructing genetic maps without a reference genome. To date, there have been no reports on a high-density genetic linkage map of kenaf, which was constructed using SNP markers obtained by RAD-seq. In this study, we developed a large number of SNP markers with the RADseq method and constructed a SNP genetic map for kenaf. There are 5,191 polymorphic SNP markers, which were obtained from 154 F 2:3 offspring and two kenaf parents. Of the polymorphic SNP markers, 1,997 SNP markers were successfully segregated to 18 linkage groups, corresponding to 18 chromosomes of kenaf. Compared with previously published genetic map with 307 loci constructed using ISSR, SRAP, and RAPD markers (Chen et al. 2011), the marker number and quality of the present genetic map achieved a new milestone. Moreover, the current version of the genetic map can be used for QTL mapping and locating important genes of kenaf. However, many large gaps remain in some linkage groups that may limit its application in some aspects. Therefore, we need to develop additional markers to further narrow the gaps in these regions.
The main purpose of kenaf planting is to harvest bast bers. Therefore, continuously improving ber yield and quality are important breeding targets for kenaf. QTLs of agronomic traits related to yield have been detected in many crops, such as rice and maize (Shi et al. 2020;Yang et al. 2020). However, there are no previous reports on ber yield QTLs in kenaf. In the present study, we found six QTLs of ber yield and quality based on the genetic map. These six QTLs were assigned to three linkage groups, namely LG3, LG8, and LG16. QPH1, QDBW2, and QFW3 were located in the same region in LG16 and were closely associated with the same SNP marker un_59437998. The results showed that the three agronomic characters were closely related. Moreover, QDBW and QFW1 were located in the same region in LG8 and were closely associated with the same SNP marker un_56233383. These results showed that ber yield and quality-related genes may have pleiotropic effects. The SNP markers un_59437998 and un_56233383 were closely linked to ber yield agronomic trait, suggesting that the two SNP markers can be candidate molecular markers for determining the ber yield during breeding.
To the best knowledge of the authors, this is the rst study of its kind to perform QTL mapping for both ber yield and ber quality. Six QTLs were identi ed that were assigned to three linkage groups, namely LG3, LG8, and LG16, among which QPH, QFBW, QDBW, and QFW were related to ber yield, and QFS and QFC were related to ber quality. The QTLs obtained in the present study will facilitate further understanding of the molecular genetic basis of these traits.

Statements And Declarations
Ethics approval and consent to participate: NA Consent for publication: NA 25. Zhang F, Kang J, Long R, Yu LX, Wang Z, Zhao Z, Zhang T, Yang Q (2019) High-density linkage map construction and mapping QTL for yield and yield components in autotetraploid alfalfa using RADseq.BMC Plant Biol19:165 2 . Zhao Y, Zhao Y, Guo Y, Su K, Shi X, Liu D, Zhang J (2020) High-density genetic linkage-map construction of hawthorn and QTL mapping for important fruit traits.PLoS One15:e0229020 Figure 1 Phenotypic distribution of six traits among the 154 F2:3 strains