Genetic mapping of QTL for three root-related traits in wheat (Triticum aestivum)

Abstract A well-developed root system plays a positive role in wheat yield. Here, we identified quantitative trait loci (QTL) for total root length (TRL), root average diameter (RD) and number of root tips (RTN) based on the previously developed genetic map of a recombinant inbred line (RIL) population in bread wheat and phenotype data from two individual trials. A stable and major QTL, Qtrl-AS-5A for TRL was detected explaining 17.19 to 17.78% of the phenotypic variation. It was physically located at 680.66-683.25 Mb (∼2.59 Mb interval) on chromosome arm 5AL. Two stably expressed QTLs for RD, Qrd-AS-4A and Qrd-AS-6B, were identified. The phenotype variances explained for them were between 5.11 to 5.43% and 17.42 to 22.40%, respectively. They were physically located at 621.74 Mb-621.93 Mb (∼0.19 Mb) on 4AL and 624.01 − 624.78 Mb (∼0.77 Mb) on 6BL, respectively. One unstably expressed QTL for RN was identified only. Genetic analysis suggested that the two major and stably expressed QTLs, Qtrl-AS-5A and Qrd-AS-6B, were not likely associated with plant height and anthesis date. Comparison analysis indicated that they may be novel loci. Several candidate genes which were mainly expressed in roots were also obtained. Collectively, these results provided several major and stably expressed QTLs for root traits and they should have breeding potential.


Introduction
Bread wheat (Triticum aestivum L.) is one of the most important food crops. Due to the huge consumption, the annual yield of wheat must increase 1.6% to fulfil the burden of food security by 2050 [1].
To date, a large number of studies have mainly focussed on wheat above-ground parts including grain, spike, plant height and tiller. The roots, as important underground organs taking up water and nutrients from soil, also play key roles in the growth and development in crops [2,3]. Appropriately manipulating crop roots has great potential in improving yield [4]. Root system mainly includes root length, root diameter, number of root tips and others. Root length affects the spatial distribution of roots. Root diameter is associated with the capacity to permeate soil and drought tolerance. Root tip belongs to a dynamic section in the root structure [5][6][7]. Thus, genetic dissection of root system and researches on the underlying mechanisms are essential for wheat breeding.
Due to the difficulties of root recovery and evaluating root traits in situ, indoor hydroponic cultivation methods combined with digital imaging were used to study root traits of seedlings and genetic loci associated with root growth and development were identified [6,[8][9][10][11][12][13][14][15][16]. For instance, Ma et al. [13] identified 15 QTLs on 8 chromosomes including four major ones based on a total of 186 recombinant inbred lines (RILs) derived from a cross between Tibetan semi-wild wheat accession Q1028 and wheat cultivar Zhengmai 9023. Li et al. [10] detected 18 QTLs for 8 root traits on 9 chromosomes in a RIL population. Xu et al. [16] identified 12 stable chromosomal regions associated with root traits on chromosomes 1 D, 2 A, 4 A, 4B, 5B, 6 D, and unmapped markers based on a genome-wide association study of 196 wheat accessions from the Huang-Huai Wheat Region of China. Additionally, some genes associated with wheat root traits have been reported based on reverse genetics methods including TaZFP34 [17], lateral organ boundaries (LOB) family member TaMOR [18], TaEXPB23 [19] and LATERAL ROOT DENSITY [20].
Considering the key roles of roots in plant growth and development in wheat, it is necessary to excavate stable and major loci related to root traits which might be pyramided in wheat breeding. Here, we attempt to detect QTLs for three root traits from a RIL population towards providing gene sources for wheat improvement.

Population materials
A RIL population derived from the cross of 'AS985472'/'Sumai 3′(AS) was used in this study and it included 94 F8 lines [21]. 'AS985472' is a stable wheat line; 'Sumai 3′ is well known to be highly resistant to Fusarium head blight [22].

Root traits measurement
A previously reported hydroponic culture system [6,15] was adopted to analyse the target traits of wheat seedling roots. The detailed method of the culture analysis was described previously [10]. The experiment was repeated two times with four plants per line in each trial. Fifteen seeds with similar size from each line were selected and germinated. Four plants were transferred to plastic trays (50 cm × 40 cm × 30 cm). Hoagland's nutrient solution was applied and was replaced twice a week. An air pump was used to supply oxygen for the seedlings [23]. After four weeks, root traits were measured.
The Epson Expression 11000 XL was used to scan the root system. The scanned images were further analysed using Win-RHIZO (Ottawa, ON, Canada). Total root length (TRL, the total length for all the roots including primary and lateral roots cm/plant), root average diameter (RD, the average diameter of all the roots from a single measured plant, cm/plant) and number of root tips (RTN, the total tips of all the roots from a single measured plant, n/plant) were obtained.

Agronomic traits measurement
The agronomic traits including anthesis date (AD), spike length (SL), spikelet number per spike (SNS), plant height (PH), flag leaf width (FLW) and flag leaf length (FLL) were measured previously [21]. Specifically, AD was the time interval from the sowing date to that when more than 50% of the plants of a line flowered. After anthesis, FLW (the widest section of the flag leaf, cm) and FLL (the length from the base to the top of the flag leaf, cm) was measured. PH was the distance from the base to the top of the main spike (excluding awns). SL was the length of the main spike of an individual plant (excluding awns). SNS was the number of spikelets per spike from the main tiller. The best linear unbiased prediction (BLUP) of agronomic traits from multiple environments calculated using SAS version 8.0 (Cary, North Carolina) was used for further analysis.

Data analysis
The IBM SPSS Statistics 25 (Armonk, NY, USA) was employed for Pearson's correlation, frequency distribution, BLUP, standard error and the Student's t-test (p < 0.05).

QTL identification
The previously constructed genetic linkage map using the 1978 DArT markers [24] was adopted for QTL analysis. QTL analysis was carried out as described previously [25]. QTLs that were identified in at least two trials (including mean value) and explained more than 10% of the phenotypic variation were regarded as major ones.

Predicated genes in the interval of QTL
Sequences of the DArT markers were used to blast against 'Chinese Spring' genome sequences (IWGSC RefSeq v1.0) to determine the physical intervals of the identified QTLs. Predicted genes located between the flanking markers, their expression patterns and function annotations were retrieved from the Triticeae Multi-omics Center [26].

Phenotype evaluation
The TRL of AS985472 ranged from 591.22 to 605.38 mm and Sumai 3 ranged from 529.14 to 586.44 mm. AS985472 showed significantly longer TRL than Sumai 3 in a trial ( Table 1). The TRL of AS RILs ranged between 152.1 and 1111.6 mm. The RD of AS985472 ranged from 0.31 to 0.33 cm and Sumai 3 ranged from 0.27 to 0.29 mm. AS985472 also showed significantly lager RD than Sumai 3 in two trials. The RD of AS RILs ranged between 0.24 and 0.36 mm. The RN of AS985472 ranged from 1168.00 to 1387.00 and Sumai 3 ranged from 1065.00 to 1127.50. AS985472 had significantly more RN than Sumai 3 in two trials. The RN of AS RILs ranged between 362.30 and 2784.50. Continuous variation and bidirectional transgressive segregation of TRL, RD and RN were both observed in the RIL population. An approximately normal distribution for these three traits was observed, indicating that they were poly-genically inherited ( Figure 1).

Correlation of root traits and agronomic traits
TRL was significantly and positively correlated with PH (R = 0.401, p < 0.01, Table 2). RD was significantly and negatively correlated with FLW (R=-0.291), SL (R=-0.261) and SNS (R=-0.257). No significant correlation was detected between RN and other traits (Table 3).

QTL analysis
QTL analysis combined with the previously constructed linkage map and measured data of three root traits from two trials and the mean value in this study identified 5 QTLs. They were physically located on chromosomes 2 A, 4 A, 5 A, 7 A and 6B. The LOD scores for these QTLs ranged from 2.53 to 10.34. The phenotype variance explained (PVE) ranged from 4.48 to 22.40% (Table 3).
For TRL, only one QTL, Qtrl-AS-5A, was detected, and it can be detected in both of the two trials and the mean value. It explained 17.19 to 17.78% of the phenotypic variation. The LOD score was in the range of 2.53 − 2.69. It was treated as a major QTL ( Figure 2, Table 3). The positive allele at this QTL on increasing TRL was from Sumai 3 ( Figure 2). It was located at 680.66-683.25 Mb (~2.59 Mb) on 5AL of CS genome with 37 predicted genes in this interval ( Figure 2).
For RD, three QTLs were identified and they were Qrd-AS-2A, Qrd-AS-4A and Qrd-AS-6B. Qrd-AS-2A was identified in only one trial and it explained 4.48% of the phenotypic variation. The positive allele at this QTL was from AS985472. Qrd-AS-4A can be detected in two trials and the mean value. However, the PVE ranged from 5.11 to 5.43%. The LOD score ranged from 3.08 to 3.68. The positive allele of this QTL was contributed by AS985472 as well. Eight genes can be predicted in this interval (621.74 Mb-621.93 Mb, ~0.19 Mb, Figure 3) on 4AL. Qrd-AS-6B can be identified in both trials and the mean value. The PVE ranged from 17.42 to 22.40% and LOD score ranged from 7.22 to 10.34 suggesting that it was a major and stably expressed QTL. The positive allele of this QTL was from Sumai 3. This QTL was located between 624.01 to 624.78 Mb (~0.77 Mb) on 6BL with five genes in this interval (Figure 4).  For RN, only one QTL with 17.59% of PVE that can be expressed in only one trial was identified. The positive allele of this QTL was from Sumai 3.

Effects of major QTLs on other agronomic traits
To detect the possible correlations of the two major and stably expressed QTLs with other agronomic traits, the RILs were classified into two groups (without heterozygous lines) according to the genotypes of the flanking markers of the target QTLs. For Qtrl-AS-5A of TRL, the group carrying increased alleles from Sumai 3 had significantly higher SL and SNS than that carrying alleles from AS985472. No significant differences were detected between these two groups for FLL, FLW, AD and PH (Supplemental Figure S1). For Qrd-AS-6B of RD, the lines with allele from AS985472 were not significantly different from those with that from Sumai 3 for all of the surveyed traits (Supplemental Figure S2).

Expression patterns of predicated genes in the intervals where the stably expressed QTLs were mapped
In the physical interval of Qtrl-AS-5A, 37 genes were predicated. Of them, six (TraesCS5A02G519700, Tra e s C S 5 A 0 2 G 5 2 0 6 0 0 , Tra e s C S 5 A 0 2 G 5 2 1 0 0 0 , TraesCS5A02G521600, TraesCS5A02G521700 and TraesCS5A02G521800) were mainly expressed in roots (Supplemental Figure S3a). In the interval of Qrd-AS-4A, three of the 8 genes (TraesCS4A02G341000, TraesCS4A02G341600 andTraesCS4A02G341700) were mainly expressed in roots (Supplemental Figure S3b). In the interval of Qrd-AS-6B, TraesCS6B02G355700 was mainly expressed in roots ( Figure S3c).

Discussion
Given that the root system supports aerial growth and development of plants and is critical for yield, identifying, characterizing and genetic mapping more important QTLs for root traits will be useful to provide genetic resources for wheat improvement. Here, the DArT markers-based constructed linkage map combined with two trials were employed to detect 5 QTLs for three root traits. Three stably expressed QTLs were obtained. Correlation analysis suggested that they may be not associated with AD and PH. Predicted genes in the intervals where the stable QTLs were mapped will be helpful for further fine mapping of these QTLs. These identified QTLs might be useful in wheat breeding.
To date, numerous QTLs for TRL, RN and RD have been detected in bread wheat, however, only several ones can be found on chromosomes 5 A, 4 A and 6B. To further identify whether the presently detected QTLs are novel, we systematically compared them with previously reported ones. For instance, Luo et al. [12] identified a minor QTL for TRL, QTrl-5A, under three treatments with 3.35% of PVE. It was genetically mapped between 24.5 and 35.5 cM corresponding to a 9.22 Mb of physical interval (26.43-35.65 Mb) on 5AS. Alemu et al. [27] used genome-wide association analysis to identify a QTL for TRL, EPdwTRL-5A with IWA3196 as a significant marker, and it was located at 9.84 Mb on 5AS. Maccaferri et al. [7] identified two QTLs for TRL with IWA7361 and IWB66282 as the most associated markers on 5 A, and their physical positions were 82.44 Mbp and 547.06 Mb, respectively. The presently identified Qtrl-AS-5A was far away from these previously identified QTLs, suggesting it may be a novel one. Maccaferri et al. [7] also identified a QTL for RD, QTrd.ubo-6B, with IWB49257 as the most associated marker, and it was mapped 587.39 Mbp on 6B. Fan et al. [28] identified a major and stably expressed QTL for RD, QRd-6B, based on a RIL population, and it was mapped between 715.85 Mbp and 720. 19 Mbp. These results further indicated that Qrd-AS-6B for RD is likely different from the previously reported ones. As for the interval of the minor QTL Qrd-AS-4A for RD, no other QTLs were identified to our knowledge. Additionally, we only identified one QTL for RN in this study and we think it may be not stable. Further experiments should be conducted to confirm its effects.
A significant and positive correlation between TRL and PH was detected being consistent with the results from Ma et al. [13]. Interestingly, the positive allele of Qtrl-AS-5A for TRL has increased effects on improving SL and SNS. These results suggested that TRL has an important role in increasing the aboveground biomass production [10]. The results that RD showed negative correlation with FLW, SL and SNS are worth further studying. Interestingly, our results suggested that Qtrl-AS-5A for TRL and Qrd-AS-6B for RD were neither correlated with AD nor PH, indicating that they may have different roles in regulating growth and development of a plant. Further field work is needed to characterize the effects of these two major QTLs on other agronomic traits.
Of the predicated candidate genes in the intervals where the stably expressed QTL was located, five, three and one, respectively, for Qtrl-AS-5A, Qrd-AS-4A and Qrd-AS-6B were mainly expressed in roots suggesting their possible roles in root growth and development ( Supplemental Figure S3). For example, TraesCS5A02G521000 encodes an O-methyltransferase which was previously reported to be associated with salt tolerance in barley roots [29]. TraesCS4A02G341700 encodes a protein kinase-like protein. Receptor-like protein kinases (RLKs) have been reported to be important components in cellular processes and have functions in regulating Arabidopsis root hair development [30]. Therefore, these genes will be useful for the subsequent work of fine mapping and gene cloning.

Conclusions
Three root traits including TRL, RD and RN of a RIL mapping population were surveyed in two trials. Correlations between these traits and several agronomic traits were detected. Based on the previously constructed linkage map using the DArT markers, three stable QTLs were identified on chromosome arms 4AL, 5AL and 6BL. Comparison of physical maps suggested that they are likely novel loci. The two major QTLs Qtrl-AS-5A for TRL and Qrd-AS-6B for RD were not correlated to PH and AD, highlighting their possible breeding potential.

Data availability statement
All data generated or analysed during this study are included in this article and its supplementary information files; further inquiries can be directed to the corresponding author.

Disclosure statement
No potential conflict of interest was reported by the authors.

Funding
This study was supported by the Open Project from the Ecological Security and Protection Key Laboratory of Sichuan Province (ESP1608, ESP1801), the Scientific Research Initiation Project of Mian Yang Normal University (QD2019A13).