Scholars Academic Journal of Biosciences Abbreviated Key Title: Sch Acad J Biosci ISSN 2347-9515 (Print) | ISSN 2321-6883 (Online) Journal homepage: http://saspublisher.com/sajb/ Biology Relationship between Digitaria Exilis Stapf and its Wild Relatives Based on Morphological and Genetic Approaches Ablaye Ngom1*, Mame Samba Mbaye1, Oumar Diack2, Madiop Gueye1, Kandioura Noba1 1 Laboratoire de Botanique et Biodiversité, Département de Biologie Végétale, Université Cheikh Anta Diop, Sénégal Centre d'Études Régional pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS), Institut Sénégalais de Recherches Agricoles, Sénégal 2 DOI: 10.36347/SAJB.2019.v07i11.006 | Received: 13.11.2019 | Accepted: 20.11.2019 | Published: 29.11.2019 *Corresponding author: Ablaye Ngom Abstract Original Research Article White fonio (Digitaria exilis Stapf), a neglected crop in West African countries, is considered as a strategic source for nutrition and food security and a potential source to generate significant financial returns for farmers. Fonio has agronomic potentialities and adaptation to drought conditions that make it deserve special attention as well as its wild relatives which have interesting genetic traits for its improvement. The objective of this study was to evaluate the relationship between white fonio and its wild relatives based on agro-morphological traits and SSR markers. A total of 25 accessions belonging to 10 species and provided from the Herbaria of DAKAR and IFAN and from our collections were analyzed. Morphological and SSR similarity between species was calculated and the correlation between morphological and genetic variation was analyzed by the Mantel test. The results showed three main classes for each method used and a closely relationship between D. exilis and D. longiflora phenotypically and genetically compared to other studied Digitaria species. Mantel test revealed positive correlation between the two marker systems (r = 0.39, p = 0.013). Therefore, the techniques of molecular biology, such as the use of SSR markers, are effective tools to better understand genetic diversity within te genus Digitaria. Keywords: Genetic diversity, phenotypic traits, SSR markers, Digitaria longiflora, fonio. Copyright @ 2019: This is an open-access article distributed under the terms of the Creative Commons Attribution license which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use (NonCommercial, or CC-BY-NC) provided the original author and source are credited INTRODUCTION White fonio (Digitaria exilis Stapf) is known for its importance in human nutrition due to its nutritional and therapeutic qualities that make this cereal a strategic source of nutrition [1-5]. These properties generate significant financial returns for farmers and, significantly, for women, who are traditionally involved in processing and marketing [6, 5]. It contributes to food security, a growing concern in West Africa where it is grown. Despite the importance of this crop to traditional agriculture in this region, research efforts to improve the crop are still inadequate. Consequently, the crop remains primitive facing diverse agronomical problems which, contribute notably to grain yield lost [7, 8]. Even so, its wild relatives which are a source of genes for adaptation and resistance can be used to increase the yields of its production through a process of improvement [9]. However, the relationship between fonio and its wild relatives is poorly known despite the existence of a genus Monograph [10] and several taxonomic studies [11-13]. Based on morphological characters [14], have made a significant contribution to understanding phylogenetic relationships within the genus. However, this study did not take into account this important cultivated species as well as wild species, considered until now, as the closest ones. Genetically, various molecular biology techniques such as the use of Randomly Amplified Polymorphic DNA (RAPD) [15], Amplifed Fragment Length Polymorphism (AFLP) [3], Inter-Simple Sequence Repeat (ISSR) [16] markers and cytological studies have allowed to understanding the relationships between cultivated and wild species in the genus Digitaria. But, the use of new methods such as SSR markers is valuable for a better understanding of their relationships. In fact, SSR markers are becoming the marker of choice for fingerprinting and genetic diversity studies for a wide range of plants [17]. Microsatellites markers are a powerful tool to quantify genetic diversity within crop species and genetic relationships among species because of their high polymorphism, abundance, and codominant inheritance [18]. By the way, [19] showed a high transferability of microsatellite loci developed for D. exilis to other wild for which there is little genomic resources available. This study aims to evaluate the relationship between white fonio and its wild relatives on the basis of morphological and molecular characters, using SSR © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 416 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 markers, for more targeted use of wild genetic resources in fonio improvement and their better conservation. MATERIALS AND METHODS Morphological Characterization In this study, a total of 27 accessions belonging to 10 Digitaria species was analyzed. Accessions are consisted of herbarium samples conserved in the Herbaria of DAKAR and IFAN (Senegal) and also fresh material from our collections (Table-1). Morphological data were obtained from direct study of specimens and, when information was not available, from literature sources [20, 21]. A total of 25 traits (Table-2) were scored including 7 vegetative traits, 15 from the inflorescence and 3 traits from the seed. All characters are recorded in a summary table (presence by 1 and absence by 0) comprising 56 modalities and the 10 species. The binary matrix obtained was used to calculate the morphological similarity matrix between species using Jaccard’s coefficient [22], with PAST software, version 2.17c [23]. A dendrogram was generated from the similarity matrix by the unweighted pair-group method using arithmetic averages (UPGMA) [24] in XLSTAT software, version 2018.7 [25]. The cophenetic correlation coefficient was calculated in order to estimate how well the dendrogram represents its corresponding similarity matrix. Correlation coefficient was used to estimate the genetic distance between species. Table-1: Accessions of Digitaria used for morphological and molecular characterization Species Extraction code Country of origin Collection number Digitaria acuminatissima Stapf** Digitaria acuminatissima Stapf** Digitaria acuminatissima Stapf Digitaria acuminatissima Stapf* Digitaria aristulata Stapf** Digitaria aristulata Stapf Digitaria aristulata Stapf Digitaria ciliaris Koel. Digitaria ciliaris Koel. Digitaria ciliaris Koel. Digitaria delicatula Stapf** Digitaria delicatula Stapf Digitaria delicatula Stapf Digitaria delicatula Stapf* Digitaria exilis Stapf** Digitaria exilis Stapf** Digitaria exilis Stapf* Digitaria exilis Stapf* Digitaria exilis Stapf Digitaria horizontalis Willd.** Digitaria horizontalis Willd.** Digitaria horizontalis Willd. Digitaria horizontalis Willd.* Digitaria horizontalis Willd.* Digitaria longiflora Pers.** Digitaria longiflora Pers.* Digitaria longiflora Pers. Digitaria longiflora Pers. Digitaria perrottetii Stapf Digitaria perrottetii Stapf Digitaria perrottetii Stapf Digitaria ternata Stapf** Digitaria ternata Stapf** Digitaria ternata Stapf** Digitaria ternata Stapf* Digitaria ternata Stapf* Digitaria velutina Beauv.** Digitaria velutina Beauv.** Digitaria velutina Beauv.* Digitaria velutina Beauv. Digitaria velutina Beauv.* CIRAD-16 CIRAD-49 IF-Dacu1 IF-Dacu2 CIRAD-33 IF-Dari1bis IF-Dari2 S-Fs-I103 S-Fs-I107 S-Fs-I113 CIRAD-31 Dk-Ddel1 Dk-Ddel2 Dk-Ddel3 CIRAD-30 CIRAD-38 IF-Dex5 IF-Dex6 IF-Dex9 CIRAD-22 CIRAD-50 Dk-Dho3 DK-Dho5 IF-Dho3 CIRAD-26 DK-Dlon5 IF-Dlon11 S-Fs-I46 Dk-Dper1 Dk-Dper2 Dk-Dper3 CIRAD-15 CIRAD-85 CIRAD-92 DK-Dter1 IF-Dter1 CIRAD-60 CIRAD-91 IF-Dvel-4 IF-Dvel-5 IF-Dvel-6 Niger Mali Chad Senegal Senegal Senegal Senegal Senegal Senegal Senegal Senegal Senegal Senegal Senegal Senegal Mali Guinea Guinea Nigeria Ivory Coast Senegal Senegal Senegal Ivory Coast Senegal Mali Senegal Senegal Senegal Senegal Cameroon Zimbabwe Zimbabwe Senegal Mali Democratic Republic of Congo Zimbabwe Senegal Sierra - Leone Senegal 5879 bis 34716 1528 15042 14301 14865 13715 16907 16898 16951 13501 19408 2126 2795 2796 9523 a 35500 584 285 283 11404 17858 6829 17900 10056 3623 5354 66950 67460 2293 15005 41357 67457 171 200 244 * Accessions not used for the molecular characterization ** Accessions not used for the morphological characterization Herbarium/ Collection CIRAD CIRAD IFAN IFAN CIRAD IFAN IFAN Personal collection Personal collection Personal collection CIRAD DAKAR DAKAR DAKAR CIRAD CIRAD IFAN IFAN IFAN CIRAD CIRAD DAKAR DAKAR IFAN CIRAD DAKAR IFAN Personal collection DAKAR DAKAR DAKAR CIRAD CIRAD CIRAD DAKAR IFAN CIRAD CIRAD IFAN IFAN IFAN Table-2: Morphological traits and their descriptions used for Digitaria’ species characterization © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 417 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 Traits Stubble height Stubble nodes pubescence Stubble internodes pubescence Sheath pubescence Ligule height Ligule pubescence Limb pubescence Racemes disposition Racemes rhachis Spikelets grouping Spikelets pubescence Spikelets’ hair type Pedicels roughness Pedicels pubescence Lower glume presence Relative length of upper glume Number of veins of the upper glume Upper glume pubescence Relative length of the lower lemma Number of veins of the lower lemma Lower lemma pubescence Relative length of the upper lemma Fruit shape Fruit length Fruit color Molecular Characterization An overall sample of 30 accessions was selected including 6 accessions from the Herbarium of DAKAR, 6 accessions from the Herbarium of IFAN, 14 other accessions acquired from collections of the Herbarium of CIRAD in France and 4 accessions from personal collection (Table 1). Each species is represented by 3 accessions. DNA from fresh material was extracted following the protocol of [26]. For dry material, some modifications were performed (2% of sodium bisulphite in the lysis buffer). DNA were quantified on a spectrophotometer and diluted to a working concentration of 25 ng/μl. A set of eight SSR loci [27] were selected on the basis of their polymorphism (Table 3). Forward Description < 100 cm; x ≥ 100 cm glabrous; hairy glabrous; hairy glabrous; hairy between 0 and 1.5 mm; ˃ 1.5 mm glabrous; hairy glabrous; hairy digitate; subdigitate; whorled triquetrous winged; triquetrous not winged by 2; by 3; by 4 glabrous; hairy appressed; clavate; verrucose scabrous; smooth glabrous; hairy absent; present shorter than the spikelet; equal to the spikelet 3-veined; 5-veined glabrous; hairy shorter than the spikelet; equal to the spikelet 5-veined; 7-veined; 9-veined glabrous; hairy shorter than the spikelet; equal to the spikelet elliptic to linear; oblong; egg-shaped ≤ 1 mm; between 1 and 2 mm; ˃ 2 mm brown; other colors primers were tagged with a 5'-M13 universal sequence [28]. PCR was conducted in a 10 μl final volume with a buffer (10X), MgCl2 (50 mM), dNTP (2 mM), forward primer (10 mM), reverse primer (10 mM), BSA (10 mg/ml), Taq (2 U/μl), DNA (3.5 ng) and H20. PCR conditions were as follows: 4 min at 94°C, 10 Touchdown cycles (94°C/30 s, 60°C down to 50°C per cycle allowing specific annealing/90 s, 72°C/30 s), followed by 30 classics cycles (94°C/30 s, 58°C /90 s, and 72°C / 30 s) and final extension for 10 min at 72°C. PCR products were run on an ABI Prism 3500 (Applied Biosystems) with GS600LIZ as size standard. Genotyping data were scored and checked using GeneMapper software (version 5., Applied Biosystems). Number of alleles per locus (Na), as well as amplification percentage and percentage of polymorphic loci for each species were calculated using GenAlEx version 6.5 [29]. Table-3: Characteristics of the 8 single amplification site SSR markers developed in Digitaria exilis [27] © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 418 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 Locus De-07 De-14 De-17 De-24 De-34 De-36 De-37 De-38 Forward primers (5′–3′) TCATGGTGTTTCACTTAATCC CGAGACCTGATTTGTTTAGC GTAACGAACATCGGGTGA CCTCGATAATGCGTTTGT ACTAACAACCAGCGGTGA GAAGACAGCCCATTGTTAGA TGAACAAATTCCTCTTGCTC AAAACGAAAACCAAATCTCA Reverse primers (5′–3′) AAATAGATGCCAATCACACC CAAGTCTTTGATTTCCGTCT CTGATGGCAAGGATGTGT CAGCATTTTAATTGTTCACG CTAGCAGTGTTTCAATGTGC AGACATTGCCAAGAAAATTG TGGCAATGTTCCATAAAGA AGCCCAAGAAGTATTGCTAA For molecular analysis, matrix of binary data was constructed with rows equal to species, and columns equal to alleles found in the different loci. The body matrix contained zeros and ones, corresponding to the absence or presence of alleles. As for the morphological analysis, the binary matrix obtained was used to calculate the SSR similarity matrix between species using Jaccard’s coefficient (Jaccard 1908), with PAST software, version 2.17c [23]. A dendrogram was also generated from the similarity matrix using the UPGMA clustering method in XLSTAT software. A cophenetic correlation coefficient was measured as indicated. As far as that goes, correlation coefficient was used to estimate the genetic distance between species. The levels of correlation between the morphological and SSR similarity matrices were determined using the Mantel test with 10000 permutations (Mantel, 1967) using XLSTAT. This procedure examines the matrix correspondence by taking the 2 matrices together and plotting one against the other, element by element. RESULTS Morphological Analysis Out of the 25 qualitative traits observed, ten characters were found to be almost constant. They are shared by nine out of ten species studied and are related to the internodes pubescence, ligule height, the limb pubescence, racemes disposition, spikelet pubescence, pedicels pubescence, number veins of the upper glume and its pubescence, relative length and the pubescence of the lower lemma. Indeed, the internodes are often glabrous, the ligule not exceeding 1.5 mm, the limb pubescent, the racemes digitated, the spikelets pubescent, the pedicels glabrous, the upper glume 3-veined, the upper glume pubescent and the lower Repeat motif (GT)8 (TGCG)3 (GT)6 (CT)18 (AC)11 (CA)8 (TTC)29 (CA)6 Na 2 3 2 5 3 6 22 3 GenBank accession no. JN587188 JN587195 JN587198 JN587205 JN587215 JN587217 JN587218 JN587219 lemma as long as the spikelet and pubescent. After these, the most commonly recorded characters are the absence of hair in the sheath (except in D. aristulata and D. velutina), the upper glume which is shorter than the spikelet (except in D. exilis and D. longiflora) and the lower lemma 7-nerved (except for D. delicatula and D. ternata). For similarities among the Digitaria species, the generate dendrogram (UPGMA) grouped the species sharing similar phenotypic features. The cluster analysis revealed three main classes in which the species are grouped on the basis of characters from the vegetative and reproductive system (Fig-1). The first class was distinguished by two groups: one comprising D. aristulata and the other represented by D. delicatula and D. ternata. The second main class was represented by D. exilis and D. longiflora. The third main class grouped all of the remaining species into two groups: one consisted of D. acuminatissima and D. perrottetii and the other represented by D. ciliaris, D. horizontalis, and D. velutina. The cophenetic correlation coefficient of this cluster analysis was r = -0.931. Table 4 shows the results of correlation coefficient between species. The correlation coefficient ranged from -0.14 to 0.79 for all pair-wise combinations, confirming the wide morphological diversity of species for the traits under study (Table 4). The minimum correlation coefficient of -0.14 was recorded between D. exilis and D. perrottetii while the highest of 0.79 was observed between D. ciliaris and D. horizontalis. It is remarkable to note a weak linear relationship, whether positive or negative, between D. exilis and the other species. Despite this weakness, the correlation between D. exilis and D. longiflora, which was 0.25, was stronger compared to the relationship between the cultivated species and the other wild relatives. © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 419 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 Fig-1: UPGMA cluster analysis on the basis of the morphological data Table-4: Correlation matrix based on phenotypic traits for all pair-wise comparisons of Digitaria exilis and its wild species 1 2 3 4 5 6 7 8 9 10 D. acuminatissima D. aristulata D. ciliaris D. delicatula D. exilis D. horizontalis D. longiflora D. perrottetii D. ternata D. velutina 1 1 0.32 0.43 0.36 -0.04 0.57 0.21 0.47 0.14 0.50 2 3 4 5 6 7 8 9 10 1 0.18 0.46 -0.07 0.25 0.11 0.07 0.11 0.32 1 0.29 0.04 0.79 0.14 0.40 0.00 0.64 1 -0.04 0.36 0.22 0.32 0.50 0.14 1 0.18 0.25 -0.14 -0.04 -0.11 1 0.28 0.47 0.14 0.71 1 0.18 0.07 0.07 1 0.25 0.47 1 0.21 1 Molecular Analysis A total of 51 alleles are found in the 30 individuals studied. In this study, 13 alleles (25.49% of the total) were found in D. exilis, of which 3 alleles (ie 5.88% of the total) are specific to it. 47 alleles (ie 92.16% of the total) were detected in wild species of which 38 alleles (ie 74.51% of the total) are absent in D. exilis. Finally, 10 alleles (19.61% of the total) were detected in both D. exilis and other wild species. The number of alleles detected was variable between loci. The largest number, 13 alleles, was found at the De-37 locus followed by the De-38 locus with 9 alleles. Two alleles were the lowest number and were found at the De-14 locus. The average number of alleles per locus was 6.38 (Fig-2). Fig-2: Number and distribution of alleles in SSR loci (De-07 to De-38) As for phenotypic study, the cluster analysis showed three main classes (Fig-3). The first class included D. aristulata, D. ciliaris, D. horizontalis, D. perrottetii and D. velutina. The second class was composed by D. acuminatissima and D. delicatula. The latest was represented by D. exilis, D. longiflora and D. ternata. The cophenetic correlation coefficient of this cluster analysis was r = -0.89. Table 5 shows the results of correlation coefficient between species. The correlation coefficient ranged from -0.16 to 0.57 for all pair-wise combinations, confirming the wide morphological diversity of species for the traits under study. The minimum correlation coefficient of -0.16 was recorded between D. longiflora and D. velutina while the highest of 0.57 was observed between D. acuminatissima and D. delicatula followed by D. horizontalis and D. perrottetii. A weak linear relationship was observed between D. exilis and the other species. Indeed, the correlation between D. exilis and D. longiflora of 0.40 was the strongest. © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 420 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 Fig-3: UPGMA cluster analysis on the basis of the molecular data Table-5: Correlation matrix based on molecular traits for all pair-wise comparisons of Digitaria exilis and its wild species 1 2 3 4 5 6 7 8 9 10 D. acuminatissima D. aristulata D. ciliaris D. delicatula D. exilis D. horizontalis D. longiflora D. perrottetii D. ternata D. velutina 1 1 0,18 0,25 0,57 0,07 0,12 0,17 0,17 0,28 0,18 2 3 4 5 6 7 8 9 10 1 0,04 0,28 0,00 0,28 -0,05 0,12 -0,06 0,11 1 0,20 0,13 0,38 0,02 0,07 -0,05 0,17 1 0,16 0,19 0,19 0,24 0,27 0,07 1 0,16 0,40 0,04 0,19 0,00 1 0,04 0,55 -0,04 0,28 1 -0,05 0,01 -0,16 1 0,01 0,12 1 0,06 1 DISCUSSION The results from phenotypic data revealed that D. exilis is closer to D. longiflora. These results corroborate those obtained by [30-36] who considered D. longiflora as the species from which D. exilis is derived. Moreover [37], includes D. exilis in the group of D. longiflora because of their resemblance by many characters. D. longiflora seems to have the particularity of supporting more varied soil types [38]. As for the proximity of D. delicatula and D. ternata, it also confirms the infrageneric classification of the genus Digitaria [10]. As proof, they belong to the same Section “Clavipilae” characterized by ternate spikelets with the presence of appressed clavate hairs [39, 40]. Regarding to D. acuminatissima, D. ciliaris, D. horizontalis, D. perrottetii and D. velutina, they constitute a fairly complex group sharing many common traits and which are mostly discriminated from reproductive characters [41]. Their grouping in the Section “Sanguinales” by [37] in the Flora of Tropical Africa attests to this proximity. In molecular characterization, the very high percentage of alleles (74.51%) specific to wild species coupled to the correlation coefficient between species revealed the high variability and also the complexity of the Digitaria species. These results are in concordance with those of [16] highlighting a high genetic divergence between the cultivated D. exilis and the other wild species, taxonomically distant. Generally, this great interspecific variability is a guarantee of a great capacity to face up to the variations of the environment. The analysis of the molecular data also reveals proximity between D. exilis, D. longiflora and D. ternata. Findings of [42, 43, 15], based on the use of RAPD markers, consolidate our results since they consider D. longiflora as the ancestor of D. exilis. As for D. ternata, it also has a close relationship with D. exilis although it is considered as the species from which D. iburua derives. D. aristulata, D. ciliaris, D. horizontalis, D. perrottetii and D. velutina appear to be distant from the cultivated species. However, as noted with the morphological data, the relationships between them seem to be complex. These species, particularly D. ciliaris, D. horizontalis and D. velutina, have been defined as closely related forming a group in which it is difficult to identify phenotypically. The results of the Mantel tests (r = 0.39, p = 0.013, 10000 permutations) showed positive relationship between morphological and molecular diversity. However, this value is not very significant probably due to the absence of linkage between the loci that control some of the studied morphological characters and the evaluated markers or the limited number of SSR markers used. It can be explained also by the fact that the morphological characters are determined by a few alleles, whose genotype does not correlate with the overall marker scores for the lines [44]. © 2019 Scholars Academic Journal of Biosciences | Published by SAS Publishers, India 421 Ablaye Ngom et al., Sch Acad J Biosci, Nov, 2019; 7(11): 416-423 CONCLUSION The results of this study have highlighted the genetic diversity within the genus Digitaria. With a positive and relatively significant correlation between morphological traits and molecular markers, these findings showed that molecular data could resolve the taxonomic difficulties associated with morphological traits. A better understanding the genetic diversity of Digitaria species by analyzing more SSR markers and by considering a larger number of species is important for the identification of species with interesting agronomic traits that are useful for improvement of fonio. 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