Acta agriculturae Slovenica, 117/3, 1–14, Ljubljana 2021 doi:10.14720/aas.2021.117.3.2167 Original research article / izvirni znanstveni članek Marker-trait association study for root-related traits in chickpea (Cicer arietinum L.) Zahra SHEKARI 1 , Zahra TAHMASEBI 1, 2 , Homayoun KANOUNI 3 , Ali Asherf MEHRABI 1 Received April 11, 2021; accepted June 16, 2021. Delo je prispelo 11. aprila 2021, sprejeto 16. junija 2021 1 Agronomy and Plant Breeding Department, Agricultural College, Ilam University, Ilam, Iran 2 Corresponding author, e-mail: z.tahmasebi@ilam.ac.ir 3 Research Associate, Field and Horticultural Crops Reseach Unit, Agricultural and Natural Resources Research and Education Center of Kurdistan, Agricultural Research, Education and Extension Organization, Iran Marker-trait association study for root-related traits in chick- pea (Cicer arietinum L.) Abstract: Root structure modification can improve important agronomic traits including yield, drought toler - ance and nutrient deficiency resistance. The aim of the pres- ent study was to investigate the diversity of root traits and to find simple sequence repeat (SSR) markers linked to root traits in chickpea (Cicer arietinum L.). This research was per - formed using 39 diverse accessions of chickpea. The results showed that there is significant variation in root traits among chickpea genotypes. A total of 26 alleles were detected 26 polymorphic bands were produced by 10 SSR markers in the eight linkage groups (LG). The results indicated that there is substantial variability present in chickpea germplasm for root traits. By analyzing the population structure, four subpopula- tions were identified. PsAS2, AF016458, 16549 and 19075 SSR markers on LG1, LG3, LG2 and LG1 linkage group respec- tively were associated with root traits. The research findings provide valuable information for improving root traits for chickpea breeders. Key words: linkage groups; drought tolerance; popula- tion structure; SSR markers; subpopulations; variation Raziskava povezave genskih označevalcev in lastnosti korenin pri čičerki (Cicer arietinum L.) Izvleček: Sprememba zgradbe korenin lahko izboljša pomembne agronomske lastnosti vključno s pridelkom, strpnost za sušo in odpornost na pomanjkanje hranil. Namen raziskave je bil preučiti raznolikost lastnosti korenin in najti enostavne označevalce ponavljajočih se zaporedij (SSR) pove- zanih z lastnostmi korenin pri čičerki (Cicer arietinum L.). Raziskava je bila opravljena na 39 različnih akcesijah čičerke. Rezultati so pokazali, da obstaja značilna spremenljivost v lastnostih korenin med genotipi čičerke. Celokupno je bilo ugotovljeno 26 alelov. 10 SSR označevalcev je dalo 26 poli- morfnih prog v osmih povezanih skupinah (LG). Izsledki so pokazali, da obstaja v dednem materialu čičerke znatna vari- abilnost v lastnostih korenin. Z analizo zgradbe populacije so bile ugotovljene štiri podpopulacije. PsAS2, AF016458, 16549 in 19075 SSR označevalci v LG1, LG3, LG2 in LG1 povezanih skupinah so bili povezani z lastnostmi korenin. Ugotovitve raziskave prispevajo žlahtniteljem čičerke pomembne infor - macije za izboljšanje lastnosti korenin. Ključne besede: povezane skupine ; toleranca na sušo; zgradba populacije; SSR označevalci; podpopulacije; variabil- nost Acta agriculturae Slovenica, 117/3 – 2021 2 Z. SHEKARI et al. 1 INTRODUCTION Chickpea (Cicer arietinum L., 2n = 16) as a third major legume in the world widely used for food and fodder. Numerous biotic and abiotic stresses affect the production and yield of chickpea of which drought is one of the most important abiotic constraints. Drought causes heavy production losses, about 45–50  % in chickpea (Ahmad et al., 2005). For drought management, genetic improvement over crop options for better adaptation to drought can be a sustainable and low-cost solution. But, it is very difficult to understand the maintenance of potential yield under drought stress, due to the different mecha- nisms used by plants to maintain growth under limited water resource, (Tuberosa & Salvi, 2006). The major challenges in identifying drought tolerance genotypes is drought interaction with the environment and its quantitative inheritance (Varshney et al., 2014). Root structure modification can improve impor - tant agronomic traits including yield, drought tolerance and nutrient deficiency resistance (Tuberosa et al., 2002; Beebe et al., 2006; Ghanem et al., 2011). Despite, ap- proximately small populations and inaccurate pheno- typing cause it difficult to make large scale use of root genetic information in plant breeding (de Dorlodot et al., 2007). From now, correct phenotyping and char - acterization of root traits is necessary for translating novel physiological and genetic progresses into a con- ception of the role of root systems in increasing yield and productivity (especially in dry environments). The effect of diverse root features on drought tolerance were found to be high under final drought stress condition, mainly in environment where plant only confide in the stored soil water (Ludlow & Muchow, 1990; Kashiwagi et al., 2006; Passioura, 2006; Wasson et al., 2014). For example, Kirkegaard et al. (2007) indicated using root traits and soil moisture assessments in the field, that a 30 cm enhance in root depth increased the uptake of 10 mm more underground soil moisture and thus in- creased the yield by 0.5 t ha -1 grain yield. it also was demonstrated that Large root system effect on shoot biomass production and harvest index (HI) under ter - minal drought stress (Kashiwagi et al., 2006; Zaman- Allah et al., 2011). Although plant breeders are aware of the worth of the root system offering, but due to the low heritability of root traits, high variation in expression in different soils and soil moisture environments, and the difficulty of measuring these traits in the field has been less pay attention to these traits selection (Tuberosa et al., 2002; Malamy, 2005; Gaur et al., 2008). Genetic diversity has been investigated using di- verse types of  DNA markers, including SSR in chickpea (Sefera et al., 2011; Keneni et al., 2012; Ghaffari et al., 2014; Hajibarat et al., 2015). DNA markers have been found for many agronomic traits (Thudi et al., 2014a). Majority of the breeding attempts made in chick- pea have been, and are being, focused on improving yield, resistance to diseases like Ascochyta blight and Fusarium wilt (Varshney et al., 2014a) and on tolerance to various abiotic stresses (such as drought (Varshney et. al., 2014; Jaganathan et al., 2015), cold (Mugabe et. al., 2019) and heat tolerance (Jha et al., 2018)). How- ever even with the value of root traits and their criti- cal roles in drought and heat adaptation in chickpea ( Maphosa et. al., 2020), their genetic control has been less studied. Consequential associations between mark- ers and quantitative traits led to the identification of locus significantly associated with drought tolerance. The root phenotyping problems has reduced the iden- tity of root trait genomic locus in chickpea thus the aim of this research was to identify of the SSR markers as- sociated with root-related traits in a various chickpea germplasm. 2 MATERIAL AND METHODS Plant material contains 39 chickpea genotypes, in- cluding accessions from ICARDA (International Center for Agricultural Research in the Dry Areas) chickpea germplasm (Table 1). These entries were selected based on the results of previous drought tolerance trials in Kabuli type chickpea genotypes. 2.1 GENOTYPING 2.1.1 DNA extraction and SSR primers, PCR and aga- rose gel electrophoresis Genomic DNA was extracted from young leaflets of chickpea genotypes plant leaves (4 plants of each genotypes) using a CTAB method according Doyle and Doyle (1987) with a slight modification. On the basis of their locations on the eight linkage groups (LGs) of the integrated genetic linkage map of chickpea (Cicer arietinum L.), altogether 10 SSR markers were select (Sefera et al., 2011) (Table 2). PCR was carried out in a 14 μl reaction mixture that contain 100 ng of DNA, 100 pmol of each primer (forward and reverse), 7μl of Cin- naGen PCR master mix, 2 X (0.08 units μl -1 Taq DNA polymerase in reaction buffer, 3 mmol MgCl 2 , and 1.6 mmol dNTPs). The amplifications were performed with a Thermal Cycler (Applied Bio Rad, Foster City, CA, Acta agriculturae Slovenica, 117/3 – 2021 3 Marker-trait association study for root-related traits in chickpea (Cicer arietinum L.) USA), with an initial denaturation at 94 0 C for 240 sec that was followed by 10 cycles of: at 94 0 C for 30 s, 45 s at annealing temperature (Ta) (Table 2), 120 s at 72 0 C, and then was followed by 25 cycles of: 30 s at 94 0 C, 45 s at Ta, 120 s at 72 0 C and a final extension step at 72 0 C for 420 s In 2.5 % agarose gel by 1X TBE running buffer, amplified fragments were resolved and quantity one software (Bio-Rad, CA 94547, USA) analyzed images. Table 1: The list of genotypes used in the present study Pedigree Genotype Name NO. X04TH62/X03TH-130XFLIP97-116 FLIP97-706C 1 X04TH65/X03TH-133XFLIP96-154 FLIP03-77C 2 X04TH65/X03TH-133XFLIP96-154 FLIP03-130C 3 X04TH65/X03TH-133XFLIP96-154 FLIP06-158C 4 X04TH66/X03TH-134XFLIP97-116 FLIP07-19C 5 X04TH66/X03TH-134XFLIP97-116 FLIP07-20C 6 X04TH66/X03TH-134XFLIP97-116 FLIP07-22C 7 X04TH67/X03TH-135XFLIP99-34 FLIP07-28C 8 X04TH67/X03TH-135XFLIP99-34 FLIP07-31C 9 X04TH76/X03TH-144XFLIP97-116 FLIP07-44C 10 X04TH77/X03TH-145XFLIP99-34 FLIP07-239C 11 X04TH79/X03TH-147XFLIP96-154 FLIP07-261C 12 X04TH110/X03TH-178XFLIP97-116 FLIP07-280C 13 X04TH110/X03TH-178XFLIP97-116 FLIP08-46C 14 X04TH114/X03TH-182XFLIP97-116 FLIP08-200C 15 X04TH115/X03TH-183XFLIP99-34 FLIP09-70C 16 X04TH117/X03TH-185XFLIP96-154 FLIP09-81C 17 X04TH123/FLIP97-205XFLIP97-116 FLIP09-85C 18 X04TH124/FLIP97-229XFLIP99-34 FLIP09-90C 19 X04TH126/FLIP98-229XFLIP96-154 FLIP09-98C 20 X04TH129/FLIP98-233XFLIP99-48 FLIP09-148C 21 X05TH7/X04TH-126XFLIP01-18 FLIP09-149C 22 X05TH106/FLIP97-131XFLIP00-14 FLIP09-189C 23 X05TH106/FLIP97-131XFLIP00-14 FLIP09-191C 24 X05TH106/FLIP97-131XFLIP00-14 FLIP09-192C 25 X05TH106/FLIP97-131XFLIP00-14 FLIP09-194C 26 X05TH131/FLIP97-118XFLIP00-17 FLIP09-214C 27 X05TH152/FLIP98-107XUC27 FLIP09-216C 28 X04TH31/X03TH-31XFLIP97-116 FLIP09-218C 29 X06TH100/FLIP02-47XFLIP98-230 FLIP09-219C 30 ILC482 ILC482 31 X79TH101/ILC 523 X ILC 183 FLIP 82-150C 32 X85 TH143/ILC 629 x FLIP 82-144C FLIP88-85C 33 X89TH258/ (FLIP 85-122CXFLIP 82-150C)/FLIP 86-77C FLIP93-93C 34 X04TH12/X03TH-12XFLIP99-48 FLIP07-180C 35 X04TH40/X03TH-40XFLIP99-34 FLIP09-88C 36 X04TH50/X03TH-50XFLIP99-34 FLIP09-115C 37 X04TH53/X03TH-53XFLIP97-116 FLIP09-337C 38 X04TH59/X03TH-59XFLIP99-48 FLIP09-386C 39 Acta agriculturae Slovenica, 117/3 – 2021 4 Z. SHEKARI et al. 2.2 PHENOTYPING 2.2.1 Root sample extraction and processing The experiment was conducted in Glasshouse at Ilam university. The average daily temperature was 25/16  0 C (day/night), and the humidity was 70 %. Ex- periment was carried out in completely randomized design (CRD) with four replications. The seeds of each genotype were sown in split drain pipes (SDP) with 60 cm height and 10 cm diameter. The soil used in SDP was a mixture of sand and Jons Innes No-2 (1:1 ratio). Each SDP was put together with a single plant. The plants were harvested 30 days after germination. Plants were harvested on 35 day after germination based on taproot length increments for the growth period (Chen et al., 2017). 2.2.1 Root-related traits Chickpea root samples were taken to record root traits. Using a water shower, the soil was separated from the roots and then the fresh mass of the roots was meas- ured. Then, by floating the root samples in water in a tray, organic debris and weed roots were removed man- ually from chickpea roots. The fresh soil and roots were thereupon dried in an oven at 65 °C for 72 hours and the percentage of soil and root moisture was obtained. The root characteristics are showed in Table 3. 2.3 STATISTICAL ANALYSIS Analysis of variance was performed with the SAS 9.2 software to evaluate the factor ‘GENOTYPE”. The genotype means were compared by a Duncan’s multiple range post hoc test and used for the association analy- ses. 2.4 ASSOCIATION ANALYSES The polymorphism information content (PIC) value was calculated using PIC = 1-Σ (P ij ) 2 (Where Pij is the frequency of jth allele in ith primer and summation extends over ‘n’ patterns) (Nei , 1973) for each primer. PIC describe content of ‘gene diversity’ . NTSYSpc 2.02e was used to compute Jaccard simi- larity coefficients to report genetic relationships among Table 2: The list of genotypes used in the present study Annealing temperature ( 0 C) Linkage Group Primer sequences(5’-3’) Marker name NO. 57.75 LG1 F:CACGAGTACAACATGGAGTGAAG R: CAAGCTCAACCTCCTCATACC 19075 1 55.6 LG3 F:CATGCATGGAGTTGGAAGAG R: GTCCCAAAATGCAGCCAATA 18363 2 55.7 LG2 F:CAATGAGATGCTGGCGATAA R: GTTCGGTGTTGTGGGTTTTT 16549 3 58.2 LG4 F:GCTACTGGAGGAGGCTTTCA R: GCCTTCTACACAACGGCTTC C24 4 58.9 LG1 F: CTAATCACACGTTTAGGACCGG R: CGAAATCCAAACCGAACCTAATCC PsAS2 5 53.95 LG6 F:AATTAATGCCAATCCTAAGGTATT R: GGTTGCACTATTTTCGTTCTC PSAB60 6 54.9 LG 5 F:ATGGTTGTCCCAGGATAGATAAR: GAAAACATTGGAGAGTGGAGTA PD23 7 57.55 LG7 F: AGCCCAAGTTTCTTCTGAATCC R: GAAAACATTGGAGAGTGGAGTA PSAD147 8 57.35 LG 8 F:CGCCCTTCATCATCATCTTC R: AAATTCGCAGAGCGTTTGTTAC 17605 9 57 LG 3 F:CGCCCTTCATCATCATCTTC R: CGAATCTTGGCCATGAGAGTTGC AF016458 10 Acta agriculturae Slovenica, 117/3 – 2021 5 Marker-trait association study for root-related traits in chickpea (Cicer arietinum L.) the chickpea genotypes. Also using this software and based on genetic distances, cluster analysis was carried out using the unweighted pair-group (UPGMA) meth- od and the dendrograms were drawn (Rohlf, 2000). The marker–trait association between the SSR markers and each of root related traits tested using TASSEL 4.0. (Bradbury et al., 2007). General linear model (GLM) and mixed linear model (MLM) ap- proaches used for association analysis. Covariates in GLM and MLM analyses were the corresponding Q values. Manhattan plots present association between a SSR marker and phenotypic trait that was significant at p ≤ 0.05. STRUCTURE version 2.3.4 used for determine the population structure of the 39 accessions using the Bayesian clustering method (Pritchard et al., 2000). The STRUCTURE analysis separated the population based on ΔK method (Evanno et al., 2005). Table 3: The root related trait measured in the present study No. Trait Formula Unit of measurement References 1 Root length (RL) Total RL of each sample was measured using a ruler. cm - 2 Root fresh mass (RFM) The fresh weight of the roots was measured with a digital scale to the nearest thousandth g - 3 Root dry mass (RDM) The roots were kept for oven drying at 70 ◦C for 72 h (to constant mass) then was estimated. g Ramamoorthy et al., 2017 4 Dry mass of plant shoots (SDM) The shoots were kept for oven drying at 70 ◦C for 72 h (to constant mass) then SDW was estimated g Ramamoorthy et al., 2017 5 Root volume (RV) cm 3 - 6 Root area (RA) cm 2  Akhavan et al., 2012 7 Root fineness (RF) cm root /root fresh mass Hajabbasi, 2001 8 Root diameter (Rd) cm Schenk & Barber, 1979 9 root length (SRL) Specific cm root length cm -3 soil volume Mahanta et al., 2014 10 Root water content (RWC) g Lovelli et al., 2012 11 Root length density (RLD) cm RL cm -3 soil volume Mahanta et al., 2014 12 Specific root volume (SRV) g RDW cm -3 soil volume) Hasanabadi et al., 2010 13 Root tissue density (RTD) g RDW× cm 3 soil volume Paula & Pausas, 2011 14 Root volume density (RVD) cm m -3 Hajabbasi, 2001 15 Root area density (RAD) cm 2 cm -3 Akhavan et al., 2012 16 Root density (RD) g cm -3 Akhavan et al., 2012 B =water and root volume, C = water volume, SQRT = root square Acta agriculturae Slovenica, 117/3 – 2021 6 Z. SHEKARI et al. 3 RESULTS 3.1 ANALYSIS OF ROOT TRAITS DATA Root morphological traits differed significantly among genotypes. All of 16 measured root related traits differed significantly among genotypes (p ≤ 0.001) (Ta- ble 4). The average root length was 50.69 cm and ranged from 27 to 72 cm (Table 5). The variation (Coef. Var. ) in RL among genotypes was 20.7 % (Table 5). Root volume (RV) and root fresh mass (RFM) varied sig- nificantly among genotypes (Table 5). RV ranged from 3.75 cm 3 (FLIP07-28C) to 22 cm 3 (FLIP07-31C), with an average root volume of 11.5 cm 3 . The root fresh mass (RFM) averaged 10.93 g across all genotypes. RFM var - ied among genotypes and ranged from 2.69 g (FLIP07- 28C) to 22.52 g (FLIP09-192C). Root dry mass (RDM) was 0.15 g (ILC482) to 3.93g (FLIP09-192C) (average 1.33 g). The average leaf dry mass (LDM) was 0.91g, ranging from 0.17 g (FLIP07-31C) to 2.28 g (FLIP09- 192C), and root fineness (RF) ranged from 2.07 FLIP97-706C to 13 (FLIP88-85C) (mean 4.95 cm root / root fresh mass). The average specific root length (SRL) was 50.37 cm and ranged from 15 cm (FLIP97-706C) to 238.71 cm (FLIP 82-150C). Root water content (RWC) averaged 8.30 g across all genotypes. RWC ranged from 2.58 (FLIP07-31C) to 30.88 (FLIP07-20C). The average root tissue density (RTD) ranging from 0.61 (ILC482) to 86.53 (FLIP07-31C) (mean 16.47 g RDW × cm 3 soil volume). Root diameter (Rd) ranged from 0.038 cm (FLIP88-85C) to 0.27 cm (FLIP09-192C), with an aver - age root volume of 0.12 cm. The average root area (RA) was 83.69  cm 2 and ranged from 36.83 cm 2 (FLIP07- 28C) to 127.68 cm 2 (FLIP07-31C). The average root density(RD) was 0.52 g cm -3 and ranged from 0.29 g cm -3 (ILC482) to 0.71 g cm -3 (FLIP07-31C). Root length density (RLD) ranging from 0.05 (FLIP07-28C) to 0.13 (FLIP07-20C) (mean 0.094 cm RL cm -3 soil volume). The average specific root volume (SRV) was 0.0025 g RDM cm -3 soil volume and ranged from 0.0028 (ILC482) to 0.0073 g RDM cm -3 soil volume (FLIP09- 192C). Root volume density (RVD) ranged from 0.0050 cm m -3 (FLIP07-28C) to 0.042 cm m -3 (FLIP09-192C), with an average RVD of 0.020 cm m -3 . Root area den- sity (RAD) averaged across all genotypes 82.14 cm 2 cm - 3 . RAD ranged from 30.20 cm 2 cm -3 (FLIP07-28C) to 129.19 cm 2 cm -3 (FLIP09-192C). 3.2 SSR MARKER SCREENING AND GENETIC DIVERSITY ASSESSMENT Using the SSR marker system the genetic diver - sity of 39 chickpea genotypes analyzed. Detected alleles were 26. 2-3 bands with an average number of 2.6 al- leles per locus observed. AF016458، 17605، PSAD147، 19075، 16549 and PD23 had 3 alleles. All of the amplification products (100 %) showed polymorphism, denoted high variation among chick- pea accessions at the DNA level. Size of fragments pro- duced varied from 110 to 150 bp (Table 6). The high- est PIC was for primer 16549 and PSAD147 (0.54) and the lowest PIC was for the primer C24 (0.38). Hence, primer 16549 and PSAD147 were effective and useful markers for determining the genetic differences among the chickpea genotypes (Table 6). The cluster analysis showed that the 39 accessions were divided into five clusters (Fig. 1). The first cluster included FLIP97-706C and FLIP03-77C. The second cluster included only FLIP09-148C. The third cluster in- cluded FLIP09-85C, FLIP09-90C, FLIP09-98C, FLIP09- 115C, FLIP09-337C and FLIP09-386C. The forth cluster included FLIP03-130C, FLIP09-214C, FLIP09-216C, FLIP09-218C, FLIP09-219C, ILC482, FLIP 82-150C, FLIP88-85C, FLIP93-93C, FLIP07-180C and FLIP09- 88C. The fifth cluster included FLIP06-158C, FLIP07- 20C, FLIP07-239C, FLIP07-280C, FLIP08-200C, FLIP09-149C, FLIP09-189C, FLIP09-191C and FLIP09- 192C. 3.3 POPULATION STRUCTURE The marker segregation data was used for the pop- ulation clustering, the STRUCTURE analysis separated the population into four cluster (Fig. 2). The 39 chick- pea genotypes were grouped in to four subpopulations, as viewed in STRUCTURE analysis (Fig. 2). Genotypes 39, 38, 20, 19, 18 and 37, respectively, were named as FLIP09-386C, FLIP09-337C, FLIP09- 98C, FLIP09-90C, FLIP09-85C and FLIP09-115C, re- spectively. Genotypes 31, 32, 33, 28, 30, 27, 29, 26 and 34 respectively with the letters ILC482, FLIP 82-150C, FLIP88-85C, FLIP09-216C, FLIP09-219C, FLIP09- 214C, FLIP09-218C, FLIP09 -194C and FLIP93-93C belonged to the second subpopulation. Genotypes 13, 11, 12, 14, 16, 6, 17, 15, 8, 5, 7, 9 and 10 respectively with the names FLIP07-280C, FLIP07-239C, FLIP07-261C, FLIP08-46C, FLIP09-70C, FLIP07-20C, FLIP09-81C, FLIP08-200C, FLIP07-28C, FLIP07-19C, FLIP07-22C, FLIP07-31C and FLIP07-44C were in the third sub- population and genotypes 23, 3, 24, 25, 22, 2 , 1, 4, 35, 36 and 21 respectively with the letters FLIP09-189C, FLIP03-130C, FLIP09-191C, FLIP09-192C, FLIP09- 149C, FLIP03-77C, FLIP97-706C, FLIP06-158C, FLIP07-180C, FLIP09 -88C and FLIP09-148C were also included in the fourth subpopulation (Figure 2). Acta agriculturae Slovenica, 117/3 – 2021 7 Marker-trait association study for root-related traits in chickpea (Cicer arietinum L.) Figure 1: A dendrogram based on SSR markers of the 39 chickpea genotypes by UPGMA method Figure 2: Genetic relatedness of 39 genotypes of chickpea with 10 SSR primer combinations as analyzed by the STRUCTURE program 3.4 ASSOCIATION ANALYSIS The markers with minor allele frequency less than 5 %, remove so 21 marker loci retained for association analysis (Table 7). As in table 7 seen, AF016458 signifi- cantly associated with root fresh masst, root diameter, root volume density, root area, root length density, root area density, root length and root flavor. The 16549 marker was significantly associated to root fresh mass, root volume density, root area, root volume, root fine- ness and root area density. Significant associations were observed to the marker 19075 with root flavor. PsAS2 was significantly associated with root flavor, root volume density, root area, root volume, root fresh mass and root area density. 4 DISCUSSION Several putative root traits contributing to drought Acta agriculturae Slovenica, 117/3 – 2021 8 Z. SHEKARI et al. Table 4: Analysis of variance of root morphological traits in 39 chickpea genotypes Mean square Degree of freedom Source of variation Rd RA RD RLD SRV RVD RAD RL RV RFM RDM LDW RF SRL RWC RTD 0.005** 1193.69** 0.027** 0.001 ** 0.000 004** 0.0001** 1308.67** 399.72** 40.71** 48.61** 1.26** 0.69** 10.72** 4018.71** 30.67** 387.26** 38 genotype 0.0007 55.13 0.001 0.000 02 0.0000 001 0.00001** 54.59 7.95 2.90 2.97 0.04 0.03 0.84 73.50 2.97 16.65 113 Experimental error RL: Root length, RFM: Root fresh mass, RDM: Root dry mass, DMS: Dry mass of plant shoots, RV: Root volume, RA: Root area, RF: Root fineness, Rd: Root diameter, SRL: specific root length RWC: Root water content, RLD: Root length density, SRV: Specific root volume, RTD: Root tissue density, RVD: Root volume density, RAD: Root area density, RD: Root density. **: significant at 0.01 Table 5:. Descriptive statistics of 16 measured root traits in 39 chickpea genotypes grown in a greenhouse condition Variable Mean SE Mean Coef. Var. (%) Minimum Maximum RL (cm) 50.69 0.85 20.7 27 72 RV (cm 3 ) 11.30 0.29 32.1 3.75 22 RFM (g) 10.93 0.31 35.14 2.69 22.52 RDM (g) 1.33 0.051 47.85 0.15 3.93 LDW (g) 0.91 0.036 49.98 0.17 2.28 RF (cm root /root fresh mass 4.95 0.15 38.41 2.07 13 SRL (cm) 50.37 3.02 74.17 15 238.71 RWC (g) 8.30 0.31 46.22 2.58 30.88 RTD (g RDM× cm 3 soil volume) 16.47 0.95 71.70 0.61 86.53 Rd (cm) 0.12 0.0036 37.91 0.038 0.27 RA (cm 2 ) 83.69 1.52 22.41 36.83 127.68 RD (g cm -3) 0.52 0.0074 17.56 0.29 0.71 RLD (cm RL cm -3 soil volume) 0.094 0.0016 20.75 0.05 0.13 SRV (g RDM cm -3 soil volume) 0.0025 0.000095 47.85 0.0028 0.0073 RVD (cm m -3) 0.020 0.00058 35.14 0.0050 0.042 RAD (cm 2 cm -3) 82.14 1.57 23.70 30.20 129.19 RL: Root length, RFM: Root fresh mass, RDM: Root dry mass, DMS: Dry massof plant shoots, RV: Root volume, RA: Root area, RF: Root fineness, Rd: Root diameter, SRL: Specific root length C: Root water content, RLD: Root length density, SRV: Specific root volume, RTD: Root tissue density, RVD: Root volume density, RAD: Root area density, RD: Root density Acta agriculturae Slovenica, 117/3 – 2021 9 Marker-trait association study for root-related traits in chickpea (Cicer arietinum L.) Table 6: The number and size range of bands produced by the SSR primers among the 39 chickpea genotypes Polymorphism information content (PIC) Number of observed alleles Marker name 0.57 3 19075 0.47 2 18363 0.66 3 16549 0.38 2 C24 0.48 2 PsAS2 0.48 2 PSAB60 0.59 3 PD23 0.66 3 PSAD147 0.65 3 17605 0.54 3 AF016458 0.55 2.6 Mean Table 7: Marker-trait associations with MLM and GLM models Traits Marker name No. of Associations P . value R 2 (%) MLM GLM Root fresh mass PsAS2 2 0.047 0.039 44.9 Root fresh mass AF016458 3 - 0.042 44.1 Root fresh mass 16549 3 0.021 0.038 45.2 Root diameter AF016458 3 0.042 0.045 34.8 Root volume density 16549 3 0.025 0.037 45 Root volume density AF016458 3 - 0.048 42.2 Root volume density PsAS2 2 0.047 0.039 44.8 Root flavor AF016458 3 0.039 0.025 37.2 Root flavor 16549 3 0.039 0.042 32.5 Root flavor 19075 2 0.034 0.046 31.7 Root flavor PsAS2 2 - 0.044 32 Root area AF016458 3 - 0.038 40.1 Root area PsAS2 2 0.046 0.016 49 Root area 16549 3 0.027 0.014 49.9 Root length density AF016458 3 0.038 0.029 31.7 Root volume 16549 3 0.050 0.017 51.6 Root volume PsAS2 2 0.029 0.019 50.9 Root area density 16549 3 0.036 0.025 46.2 Root area density AF016458 3 0.041 0.019 48.9 Root area density PsAS2 2 - 0.026 45.9 Root length AF016458 3 0.049 0.030 31.6 resistance in chickpea has been found (Benjamin and Nielsen, 2006; Fukai et al., 1995; Ali et al., 2005; Kashi- wagi et al., 2008). Phenotypic selection for root traits is difficult because of the laborious, time-consuming and destructive methods involved in root studies (Gaur et al., 2008). An effort has been made in this study to identify the markers showed association with root traits in chickpea using a diverse set of genotypes. All of the measured root related traits differed significantly among genotypes (p ≤ 0.001) (Table 4). The variation (Coef. Var ) in all root-related traits (17.56-74.17 % (Ta- ble 5)) observed in the genotypes in the present study justifies its use for association analysis. Breseghello & Sorrells (2006) suggested use of diverse genotypes for the purpose of association mapping. FLIP09-192C had the highest root fresh mass, root dry mass, the average leaf dry mass, root diameter, the average specific root volume, root volume density and root area density and FLIP07-31C had the highest root Acta agriculturae Slovenica, 117/3 – 2021 10 Z. SHEKARI et al. In this research, a total of 26 alleles with a mean of 2.6 alleles per locus were found. Also, the mean PIC value was 0.55 (Table 6). So that according to indicated genetic diversity among cultivated chickpea genotypes was lesser than the wild chickpea genotypes (Ghaffari et al., 2014 and Hajibarat et al., 2015) and the wild chick- pea species showed greater PIC value and number of al- lele count per locus (Upadhyaya et al. (2008) and Ghaf- fari et al. (2014)). The 39 genotypes used for association analysis were split in to four distinct subpopulations at K = 4 (Fig. 2). Genotypes in a subpopulation often have simi- lar pedigrees (Table 1). The presence of subpopulations within a population can be due to reasons such as the different geographical origin of the genotypes, natural or human selection, or genetic drift (Flint-Garcia et al., 2003; Buckler & Thornsberry, 2002). In the present study, a total of 10 SSR markers have been used for genotyping the 39 chickpea The microsat- ellite markers showing association with root traits were detected using TASSEL software. A total of 21 marker- trait association have been found in this study at p < 0.05. The markers, PsAS2, AF016458, 16549 and 19075 on LG1, LG3, LG2, LG1 linkage group respectively was linked with root fresh mass root diameter, root volume density, root area, root length density, root area density, root length and root flavor. Several QTLs controlling root traits have been re- ported (Kale et. al., 2015; Gaur et al., 2008; Varshney et al., 2014). Chandra et al. (2004) reported that a SSR marker, TAA 170, was associated with root mass and root length under drought stress in chickpea. Li et al. (2018) found that several SNPs from auxin-related genes were associated with yield and yield-related traits under drought condition. H6C-07 (on LG3) and H5G01 (on LG4) markers found that associated with QTLs for many drought-related traits (Hamwieh et al., 2013). Thudi et al. (2014b) discovered over 200 SSR, DArT, and SNP markers associated with drought-related traits. The most of highly expressed ESTs encoded proteins involved in cellular organization, protein metabolism, signal transduction, and transcription in the chickpea under drought stress (Jain & Chattopadhyay, 2010). The role of hypothetical abscissic acid and stress ripening (ASR) protein NP_001351739.1 in mediating drought responses as a transcription factor were recognized in chickpea (Sachdeva et al., 2020). A “QTL-hotspot” con- taining quantitative trait loci (QTL) for several root and drought tolerance traits was transferred through mark- er assisted backcrossing into JG 11, a leading variety of chickpea (Cicer arietinum L.) in India from the donor parent ICC 4958. some introgression lines were identi- fied that may be released as improved variety with en- hanced drought tolerance (Varshney et al., 2013). 5 CONCLUSIONS In conclusion, this study demonstrated the exist- ence of genetic diversity exists in the current chickpea germplasm for root traits. The present study has helped in identification of significant marker-trait associations on LG1, LG2 and LG3. This shows that these chromo- somes are potential candidate ones for emphasizing fu- ture studies. The research findings provide valuable in- formation for marker-assisted selection improving root traits after validation for chickpea breeders. 6 ACKNOWLEDGMENTS This study was supported by Ilam University. Chickpea accessions were obtained from Agricultural and Natural Resources Research and Education Center of Kurdistan, Sanandaj, Iran. Conflict of interest: The authors declare that they have no conflict of interest. Authors’ Contributions: Zahra Shekari: Collection of experimental data. Zahra Tahmasebi: supervision of the study and writing of manuscript. Homayon Kanoni: review of the manuscript. Ali Asherf Mehrabi: molecu- lar and statistical analysis. 7 REFERENCES Ahmad, F., Gaur, P ., & Croser, J. (2005). Chickpea (Cicer arieti - num L.). In ‘Genetic resources, chromosome engineering and crop improvement–grain legumes’.(Eds R Singh, P Jauhar) pp. 185–214. https://doi.org/10.1201/9780203489284.ch7 Akhavan, S., Shabanpour, M., & Esfahani, M. (2012). Soil com- paction and texture effects on the growth of roots and shoots of wheat. Journal of Water and Soil, 26(3), 727–735. doi: 10.22067/JSW .V0I0.14941. Beebe, S. E., Rojas‐Pierce, M., Yan, X., Blair, M. 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