Genome-wide association mapping of seed oligosaccharides in chickpea

Abstract

Chickpea (Cicer arietinum L.) is one of the major pulse crops, rich in protein, and widely consumed all over the world. Most legumes, including chickpeas, possess noticeable amounts of raffinose family oligosaccharides (RFOs) in their seeds. RFOs are seed oligosaccharides abundant in nature, which are non-digestible by humans and animals and cause flatulence and severe abdominal discomforts. So, this study aims to identify genetic factors associated with seed oligosaccharides in chickpea using the mini-core panel. We have quantified the RFOs (raffinose and stachyose), ciceritol, and sucrose contents in chickpea using high-performance liquid chromatography. A wide range of variations for the seed oligosaccharides was observed between the accessions: 0.16 to 15.13 mg g^-1 raffinose, 2.77 to 59.43 mg g^-1 stachyose, 4.36 to 90.65 mg g^-1 ciceritol, and 3.57 to 54.12 mg g^-1 for sucrose. Kabuli types showed desirable sugar profiles with high sucrose, whereas desi types had high concentrations RFOs. In total, 48 single nucleotide polymorphisms (SNPs) were identified for all the targeted sugar types, and nine genes (Ca_06204, Ca_04353, and Ca_20828: Phosphatidylinositol N-acetylglucosaminyltransferase; Ca_17399 and Ca_22050: Remorin proteins; Ca_11152: Protein-serine/threonine phosphatase; Ca_10185, Ca_14209, and Ca_27229: UDP-glucose dehydrogenase) were identified as potential candidate genes for sugar metabolism and transport in chickpea. The accessions with low RFOs and high sucrose contents may be utilized in breeding specialty chickpeas. The identified candidate genes could be exploited in marker-assisted breeding, genomic selection, and genetic engineering to improve the sugar profiles in legumes and other crop species.

Introduction

Chickpea (Cicer arietinum L.) is one of the founder crops domesticated between 9,000–11,000 years ago and is an important ancient legume grown and consumed all over the globe (Lev-Yadun et al., 2000). As a legume crop, it is often grown as rotational crops with cereals to enhance yield because of their ability to fixing atmospheric nitrogen (Graham and Vance, 2003). Chickpea is rich in carbohydrates (60-65%), protein (20-22%), fat (6%), and rich in dietary fiber, as well as minerals (phosphorus, calcium, magnesium, iron, and zinc) and vitamins (β-carotene, thiamin, riboflavin, and niacin) (Jukanti et al., 2012). The major pulse grain constituents are carbohydrates, based on their polymeric structure that can be classified as monosaccharides (ribose, fructose, and glucose), disaccharides (sucrose, maltose, melibiose), oligosaccharides (raffinose, stachyose, verbascose, ajugose, and ciceritol) and polysaccharides (Chibbar et al., 2010). Among the oligosaccharides, α-galacto-oligosaccharides (α-GOS) are known as raffinose family oligosaccharides (RFOs) (Sosulski et al., 1982). The major RFOs found in chickpea include raffinose, stachyose, and verbascose. However, ciceritol does not belong to the RFOs since its structure is different from α-GOS and can rapidly undergo a hydrolysis process, so unlike raffinose and stachyose, ciceritol does not cause flatulence in humans and animals (Quemener and Brillouet, 1983).

RFOs are the single most deterrent factor for the rapid adoption of legumes in mainstream food usage in humans and animals (Delumen, 1992; Elango et al., 2022a). Humans and animals lack the enzyme α-galactosidase to degrade α-galactosides (RFOs), which results in the accumulation of undigested RFOs in the large intestine of the digestive system, which ultimately causes flatulence and abdominal discomforts due to the production of flatulent gases by colonic bacteria through fermenting the un-digested RFOs present in the guts (Calloway and Murphy, 1968; Sosulski et al., 1982; Singh, 1985; Han and Baik, 2006). Though, RFOs have been reported to have a beneficial effect on gut microflora (Van den Ende, 2013; Su et al., 2019), and play a role in seed germinability and biotic and abiotic stress tolerance in crop plants (Gulewicz et al., 2002; Taji et al., 2002; Nishizawa-Yokoi et al., 2008; Dobrenel et al., 2013; Van den Ende, 2013; Gangl and Tenhaken, 2016; Yan et al., 2022). However, we do not know what the right concentration is needed to benefit humans, animals, and plants concerning RFOs.

Food processing can eliminate RFOs at varying degrees and significantly increase dietary fraction availability in food (Jood et al., 1985; Egbe and Akinyele, 1990; Aguilera et al., 2009). However, these techniques often come with trade-offs; most techniques are time-consuming, lead to loss of nutrients, and sometimes have consumer acceptability issues. Therefore, identifying sources of variation for developing desirable sugar-type cultivars through crop breeding is very important. Screening and identification of low RFOs have been carried out in many economically important legume crops such as lentil (Tahir et al., 2011), chickpea (Raja et al., 2015; Gangola et al., 2016), pea (Peterbauer et al., 2003), soybean (Blackman et al., 1992; Dierking and Bilyeu, 2008; Obendorf and Górecki, 2012), mung bean and urd bean (Souframanien et al., 2014), whereas, very limited efforts have been taken toward the identification of genomic regions associated with RFOs in crop plants. In this context, our study aims to identify the genetic factors responsible for seed oligosaccharides in chickpea through genome-wide association mapping using the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) mini-core collection.

Materials and methods

Plant materials

The chickpea mini-core collection consisting of 211 accessions from 24 countries (Asia, Africa, Europe, North, and South American regions) was obtained from the genetic resources division of International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), India (Upadhyaya and Ortiz, 2001). Field experiments were performed in a randomized complete block design (RCBD) with three replications in the 2010 winter season at the Department of Pulses (11.0232° N latitude, 76.9293° E longitude, 426.72 m altitude), Tamil Nadu Agricultural University (TNAU), Coimbatore, India. Each accession was grown in a single row in a 3 m long plot. Seeds from each replicate of individual accessions were harvested at physiological maturity and stored at 4°C until analysis was performed. A standard agronomic package of practices was followed to achieve the best crop establishment.

Sugar extraction and quantification

The seeds of each chickpea accession were grounded, and the flours were used to extract soluble sugars. One gram of flour samples was taken into a screw cap vial and mixed with 10 ml of 50% ethanol, and vortexed briefly. After adding ethanol, samples were shaken horizontally using a water bath shaker maintained at 50° C for 30 min at 100 rpm. The incubated vial was centrifuged at 4000 rpm for 5 min, then 5 ml of supernatant was taken and mixed with 7 ml of acetonitrile (high-performance liquid chromatography (HPLC)-grade) to precipitate the soluble proteins. The mixture (5 ml supernatant + 7 ml acetonitrile) was incubated at room temperature for two hours. After incubation, the mixture was centrifuged at 3670 g for 5 min, and one ml aliquot of the supernatant was collected. The collected supernatant was dried at 50°C and resuspended with 500 μl 65% HPLC-grade acetonitrile and filtered through a 0.2 μm membrane filter and transferred to HPLC vials. Standards of sucrose, raffinose, and stachyose were purchased from Sigma-Aldrich, Bengaluru, India and ciceritol was purchased from Clearsynth, Hyderabad, India. Three different concentrations, 1.25 mg ml^-1, 2.5 mg ml^-1, and 5.0 mg ml^-1, were prepared and included in each batch of samples to obtain the standard curve. The concentration of different sugars (sucrose, raffinose, stachyose, and ciceritol) was determined using the HPLC (Shimadzu, Kyoto, Japan), which consisted of an LC20AD pump and a RID-10A refraction index detector. Sugar concentrations were determined using the peak area of the sample in comparison with standards.

Marker-trait association analyses

We performed genome-wide association mapping analysis using 673,115 single nucleotide polymorphisms (SNPs), where the SNP calls for 211 genotypes were obtained from Varshney et al. (2019). As reported in Varshney et al. (2019), for calling SNPs, the clean reads were mapped on to the reference genome of chickpea genotype CDC Frontier using SOAP2. We then used SOAPsnp3 to calculate the likelihood of all possible genotypes for each sample. In order to filter out low-quality variants, the loci with sequencing depth higher than 10,000 and lower than 400, mapping times higher than 1.5, or quality scores lower than 20, were filtered out. The loci with estimated allele frequency not equal to 0 or 1 were determined as SNPs. After obtaining the SNPs, we also determined the genotype of each individual at the SNP locus by assigning the most likely genotype from the SOAPsnp3 result of each sample. We have used the Fixed and random model Circulating Probability Unification (FarmCPU) model (Liu et al., 2016) in the Genome Association and Prediction Integrated Tool (GAPIT3) package (Wang and Zhang, 2021) to identify significant marker-trait associations (MTAs). GAPIT estimated the allelic effect for the significant SNPs identified. Sign (+/-) of the allelic effect estimate is relative to the alphabetical order of the nucleotides. MTAs were selected for p-value <10^-5. Gene annotations were determined from the reference genome of chickpeas released in 2013 (Varshney et al., 2013). Genes within the flanking regions of 50kb upstream and downstream of the significantly called SNPs were collected first, and among them, only the genes already annotated in the chickpea genome with predicted function or found orthologs in other model plants were selected as candidate genes. Distance from the SNP (bp) is calculated as the distance from the SNP location to the start site of the upstream or downstream genes. If the SNP is located within a gene, the distance is calculated as the distance to the start site of the gene.

Results

Phenotypic variation and correlations among seed oligosaccharides

We have observed wide variations for all sugars measured in the ICRISAT chickpea mini-core collection. Among the morphotypes, Kabuli-type chickpeas exhibited higher sucrose and total sugar contents. In contrast, the desi-type chickpeas showed higher RFOs (raffinose and stachyose) and ciceritol contents in seeds (Figure 1). Mini-core collection showed wide seed oligosaccharide variations: 0.16 to 15.13 mg g^-1, 2.77 to 59.43 mg g^-1, 4.36 to 90.65 mg g^-1, 3.57 to 54.12 mg g^-1 for raffinose, stachyose, ciceritol, and sucrose with an average of 4.61, 28.02, 34.48, and 23.11 mg g^-1 flour sample, respectively (Table 1). We have observed significant positive correlations among seed oligosaccharides measured: sucrose, ciceritol, and stachyose have strong positive correlations with total sugars; moderate correlations were observed between sucrose and ciceritol, and ciceritol and stachyose (Figure 2). Whereas raffinose had a low level of positive correlations with all other seed oligosaccharides (Figure 2).

Figure 1

Figure 2

Marker trait associations

Genome-wide association mapping identified 48 SNPs associated with the seed oligosaccharide contents in chickpeas (Table 2). The largest number of associated markers (12) were detected on chromosome 4 (Table 2), and there were 16 SNPs found to be significantly associated with raffinose content in chickpea, which is the most associated markers compared with other three sugars: 7 SNPs for ciceritol and stachyose respectively, and 9 SNPs for sucrose, and 8 SNPs for total sugar content in chickpea (Table 2; Figure 3).

Figure 3

Probable candidate genes

We identified 80 probable candidate genes for all the seed oligosaccharides measured in this study (Table 2). Among them, nine genes were recognized with annotated functions highly associated with sugar biosynthesis and transportation. Four genes that are important components in inositol biosynthesis: two associated with stachyose (Ca_06204: phosphatidylinositol N-acetylglucosaminyltransferase; Ca_04353: Type I inositol 1,4,5-trisphosphate 5-phosphatase), and two associated with sucrose (Ca_20828: inositol-polyphosphate phosphatase; Ca_10185: UDP-glucose dehydrogenase) have been identified as probable candidates for seed oligosaccharide biosynthesis in chickpeas (Table 2). There were also three candidate genes identified playing an important role in RFOs transportation: two of the genes (Ca_17399 and Ca_22050) are associated with raffinose content, and the other gene (Ca_11152) is linked with total sugar content in chickpea seeds, and all of them encodes remorin protein, which regulates the carbohydrate translocation in plants. The other group of important genes identified in our study includes Ca_14209 (associated with two traits: ciceritol and total sugar contents) and Ca_27229 (associated with raffinose content), and both genes encode UDP-glucose dehydrogenase (UGD) and likely interfere with RFOs biosynthesis as a competitor for the upstream precursor compound (Joët et al., 2009).

A candidate gene Ca_23689 harboring SNP Ca4_43438450 was associated with raffinose content, and GO annotation indicates gene Ca_23689 encodes structural constituent of the cell wall (Table 2). A precedent study has discovered that over-expression of raffinose synthase (rfs) resulted in increased biomass and total cellulose content in the cell wall (Unda et al., 2017). Gene Ca_03642 was associated with chickpea stachyose content in seed (Table 2). The GO term functional annotation suggests that gene Ca_03642 involves intracellular protein transport, vesicle-mediated transport, and membrane fusion. Studies have demonstrated that stachyose is the primary photoassimilate and transport sugar in legumes (Peterbauer et al., 2001; Qiu et al., 2015). Another gene, Ca_09762, which is predicted as involved in calcium ion transmembrane transport, was also associated with stachyose content (Table 2). Meanwhile, we identified another SNP locus (Ca6_2510863) in the gene Ca_10383 associated with sucrose content in chickpea seed, and the functional prediction of gene Ca_10383 is ATP hydrolysis coupled proton transport. A previous study suggested that stachyose and sucrose may also be accumulated in the vacuole by stachyose and Sucrose/H⁺ antiporter mechanisms, which is an ATPase energized vacuolar uptake process (Keller, 1992).

Two SNP loci (Ca_46225454 in gene Ca_21541 and Ca5_1870839 in gene Ca_26715) were associated with ciceritol content in chickpea seeds (Table 2). Gene Ca_21541 is predicted as a TPX2 (targeting protein for Xklp2) family protein. SNP Ca_46225454 is also adjacent to a sequence fragment ortholog of AT5G40690, which encodes for methyltransferase activity. Ciceritol is the end product of the inositol methylation process, which explains the role of the identified SNP Ca_46225454 in ciceritol biosynthesis in chickpeas. Gene Ca_26715 is an endochitinase A-like protein. Chitinase is known to protect plants against abiotic and biotic stresses (de Las Mercedes Dana et al., 2006; Karlsson and Stenlid, 2008; Xin et al., 2021; Zhang et al., 2022). The association between endochitinase and ciceritol content in chickpea suggests a metabolic link between the ciceritol pathway and the pathway leading to biotic and abiotic resistance. Two SNPs were identified for total sugar content: SNP Ca4_17208915 in gene Ca_05402 and Ca5_1870839 in gene Ca_26715. Gene Ca_05402 involves ATP hydrolysis coupled proton transport. Gene Ca_26715 is predicted as an A-like endochitinase (Table 2).

Discussion

Breeding specialty chickpeas

Identification of germplasm lines with good nutritional quality parameters is key for developing cultivars for different end users. In this study, we have identified varying sugar profile accessions that could be exploited as a base in breeding specialty chickpeas. Especially the accessions with high sucrose (ICC 12564 and ICC 9137) and low RFOs (ICC 6263 and ICC 13816) are desirable for making delicacies like hummus, besan laddoo, Mysore Pak, besan barfi, Puran Poli, and other confectionaries without refined sugars and or artificial sweetening agents. The low RFO lines could be exploited in human and animal food and feed industries. Stachyose and raffinose are considered the most undesirable oligosaccharides present in chickpea. The low stachyose and raffinose accessions ICC 13816 and ICC 6263 can be used in breeding programs as a unique germplasm resource to develop chickpea varieties with improved nutrient utilization and digestibility. The chickpea mini-core collection also shows a considerable amount of variation for ciceritol among accessions. It is believed that these compounds play an important role in protecting plants and seeds against drought stress (Keller and Ludlow, 1993). Ciceritol, a new trisaccharide do not correlate with flatulence, was found high in chickpea accessions reported by Quemener and Brillouet (1983) and Xiaoli et al. (2008). Further research indicated that ciceritol also plays an important role in improving gut health by enhancing the growth of Lactobacillus, Enterococcus, and Bifidobacterium spp in addition to the production of short-chain fatty acids and is used as a potential source of prebiotics (Zhang et al., 2017). Therefore, increasing ciceritol relatively decreases the flatus potential of chickpea.

Seed oligosaccharide candidates

There are four genes - two associated with stachyose (Ca_06204: phosphatidylinositol N-acetylglucosaminyltransferase; Ca_04353: Type I inositol 1,4,5-trisphosphate 5-phosphatase) and two associated with sucrose (Ca_20828: inositol-polyphosphate phosphatase; Ca_10185:UDP-glucose dehydrogenase) – have been recognized as indispensably involved in various signaling pathways in plants via mediating the phospholipidation and phosphatization of Myo-inositol and its derivatives like sucrose and RFOs. Studies reported the crosstalk linkage between inositol signaling and sugar metabolism in plants (Saddhe et al., 2021; Lou et al., 2007; Yang et al., 2007). In 2008, Ananieva et al. (2008) discovered the in-vitro interactions between the myo-inositol polyphosphate 5-phosphatase (5PTase13) and the sucrose nonfermenting-1-related kinase (SnRK1.1) and identified 5PTase13 regulated SnRK1 activity under different sugar conditions. Plant SnRK1 is known for its key role at the interface among sugar metabolism, stress signaling, and other physiological developmental processes like seed germination and seedling growth (Radchuk et al., 2006; Baena-González et al., 2007; Jossier et al., 2009; Hulsmans et al., 2016; Elango et al., 2022b). SnRK1 has been identified in higher plants and two other subfamilies – SnRK2 and SnRK3 (Halford and Hey, 2009). Purcell et al. (1998) demonstrated that SnRK1 plays an essential role in the regulation of Suc synthase expression in potatoes (Solanum tuberosum), and later Tiessen et al. (2003) recognized that SnRK1 also regulates starch biosynthesis. The same finding about SnRK1’s role involved in starch synthesis was also identified in pollen grains of barley (Hordeum vulgare) (Zhang et al., 2001). Our findings indicate that in chickpea, the stachyose and sucrose biosynthesis is mediated by various kinds of inositol-polyphosphate phosphatase, potentially through their regulation of SnRK families. Additionally, the genes involved in the RFO biosynthetic pathway have been identified in soybean (Glycine max) and common bean (Phaseolus vulgaris). de Koning et al. (2021) identified three galactinol synthase (GolS) genes in common bean, named PvGolS1, PvGolS2, and PvGolS3. GolS crosslinks between inositol and RFO biosynthesis, and GolS are the primary checkpoint for RFO biosynthesis via inositols (Sengupta et al., 2015).

We also found that three candidate genes encode for remorin protein – two genes (Ca_17399 and Ca_22050) are associated with raffinose content, and the other gene (Ca_11152) is linked with total sugar content in chickpea seeds. RFOs serve as a major transport form of carbohydrates in the vascular system in plants (Ayre et al., 2003; Johnson et al., 2020; Ren et al., 2021). Remorin is a kind of plant-specific membrane-bound protein and has been identified in Arabidopsis thaliana, Nicotiana tabacum, Medicago truncatula, and Lycopersicon esculentum (Watson et al., 2003; Bariola et al., 2004; Marmagne et al., 2004; Mongrand et al., 2004; Sazuka et al., 2004; Nelson et al., 2006; Valot et al., 2006). In Arabidopsis, 16 genes have been identified in the REM family, and among them, REM1.2, REM1.3, and REM1.4 from the REM1 subfamily were found to exist ubiquitously in the majority of the tissues (Huang et al., 2019). Previous studies demonstrated that remorin proteins are localized in the plasma membrane and plasmodesmata of phloem companion cells and regulate photoassimilate translocation via reducing plasmodesmata permeability in the symplastic system in rice (Oryza sativa) (Gui et al., 2014). As an example, in rice, over-expressed remorin gene gsd1-D in the dominant mutant (grain setting defect1-Dominant) showed a grain setting-deficient phenotype of reduced grain setting rate, reversible accumulation of carbohydrate in leaves, and reduced synthesis of soluble sugar concentration in phloem exudates (Gui et al., 2014).

Three candidate genes are also identified as UDP-glucose dehydrogenase (UGD) – gene Ca_14209 is simultaneously associated with two traits (ciceritol and total sugar contents). The other two genes are Ca_27229 (associated with raffinose content) and Ca_10185 (associated with sucrose content). UGD is a key enzyme in carbohydrate metabolism and has been identified in soybean (Glycine max), maize (Zea mays L.), cotton (Gossypium hirsutum), and Arabidopsis (Arabidopsis thaliana) (Kärkönen et al., 2005; Kohlberger et al., 2018; Jia et al., 2021). The overexpression of UDG-coding gene PeUGDH4 in Arabidopsis leads to a significant increase in hemicellulose synthesis (Yang et al., 2020), indicating its critical role in plant cell wall synthesis. UGD converts UDP-glucose to UDP-glucuronic acid, providing the precursor for hemicellulose and pectin biosynthesis - the two confound components in the primary cell wall matrix (Oka and Jigami, 2006). And later, UGD has also been identified to be highly involved in the secondary cell wall construction in Moso bamboo (Phyllostachys edulis) (Yang et al., 2020). Besides being incorporated into the cell wall, the remainder forms of carbohydrates can be small molecule oligosaccharides such as RFOs. The RFOs biosynthesis pathways started with UDP-galactose being converted to UDP-galacturonic acid (UDP-GalA) by UG4E UDP-glucose 4′-epimerase; or alternatively UDP-glucose being converted to myo-inositol (Karner et al., 2004; Joët et al., 2009). Then both UDP-GAL and myo-inositol can be the precursors of the galactinol biosynthesis by galactinol synthase GolS (Keller and Pharr, 1996). Galactinol is believed to be the only known galactosyl donor to RFOs (Sprenger and Keller, 2000). In summary, the cell wall polysaccharide (CWP) and RFOs biosynthesis pathways are interconnected but also competitive for the upstream precursor UDP-glucose. The increase in UGD activity could lead to the increased production of CWP; however, at the same time, it could diminish RFOs and other carbohydrates production.

Conclusion

The present study identified potential candidate genes regulating the biosynthesis and transport of seed oligosaccharides in chickpea. We have identified 48 SNPs associated with five sugar types. Nine genes (Ca_06204, Ca_04353, and Ca_20828: Phosphatidylinositol N-acetylglucosaminyltransferase; Ca_17399 and Ca_22050: Remorin proteins; Ca_11152: Protein-serine/threonine phosphatase; Ca_10185, Ca_14209, and Ca_27229: UDP-glucose dehydrogenase) were identified as potential candidate genes for sugar metabolism and transport in chickpea. The accessions with low RFOs and high sucrose contents may be utilized in breeding specialty chickpeas. The identified candidates could be exploited in marker-assisted breeding, genomic selection, and genetic engineering to improve the sugar profiles in legumes and other crop species.

Funding

The open access publication fees for this article were covered by the Iowa State University Library.

Publisher’s note

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