Genetic Diversity and population structure of Selected tef Core Germplasm Lines Based on Microsatellite Markers

Abstract

Tef is an indigenous and important food, feed and cash crop to the small-holder Ethiopian farmers. Knowledge of the natural genetic composition of the crop provides the option to further exploit its genetic potential through breeding. However, there are insufficient reports on the genetic variability of Ethiopian tef using a medium-throughput marker system. Hence, the current study was designed to evaluate the genetic variability of released and core germplasm which were collected earlier. Eighty-one tef genotypes collected from eight Ethiopian ecological zones and release variety were targeted using 14 SSR markers. The study ensued a total of 122.43 alleles through the entire loci and populations. All the used microsatellite loci were highly polymorphic with PIC ranging from 0.96 to 0.98 and mean of 0.976. The analysis showed the presence of high allelic diversity ranging from 0.94 to 0.97 with overall mean of 0.96. The molecular variance analysis indicated the existence of large genetic differentiation (FIS and FIT=0.87) with 86% and 13% of the total variation accounted by among genotypes within population and across from all population respectively. Whereas low genetic differentiation among population (FST=0.014. which accounts 1 %.) was observed. Multivariate analysis like clustering, and PCoA, analysis did not cluster genotypes into distinct groups according to their geographical areas of population. This is due to presumably gene flow among populations. The information of this study may be used as input for breeders in selecting breeding materials.

Introduction

Tef is well known as an indigenous and important food, feed and cash crop to the small-holder Ethiopian farmers.  Among the cereals, tef covers 2.93 million hectares of land and this is equivalent to 27.8% of the total area allocated to cereal crop cultivation in Ethiopia (CSA, 2021). The same source indicates that the annual grain production of 5.51 million tons makes tef third following maize and wheat with 10.56 and 5.78 million tons, respectively.

 In Ethiopia, tef grain is mainly used for making ‘injera’ and sometimes for making porridge, unraised bread (‘kita’), and local alcoholic drinks, called ‘tela’ and ‘katikala’. In general, tef is considered to be a highly nutritious grain having protein content in the range of 8 to 11 percent, similar to other more common cereals such as wheat (Baye et al., 2014), balanced amino acids with high lysine content (Jansen et al., 1962), and high iron content (Mengesh ,1966; Costanza et al., 1979). It has also got significantly higher calcium content than most major grains (Vohwinkel et al., 2002). Besides, tef straw is the most appreciated feed for cattle, while it also serves as a binding material to reinforce mud used for plastering the walls of huts and local grain storage facilities called gotera, and also as bedding material, mulch and fuel source. Moreover, tef grains are free of gluten which causes celiac disease. It is also a good alternative diet for diabetic people due to its low glycemic index as compared to most other cereals (Saturni et al., 2010).

Eragrostis tef (Zucc.) Trotter belongs to the class: Liliopsida, order: Poale, family: Poaceae, subfamily: Chloridodeae, genus: Eragrostis (Smale et al., 1996). It is allotetraploid (2n =4x= 40) originating from the hybridization of two distinct species followed by diploidization Cannarozzi et al. (2014). 

Every individual is genetically unique by nature. Hence conservation of this unique ness is to maintain genetic diversity at many levels and to provide tools for population monitoring and assessment that can be used for conservation planning. Genetic diversity is generally defined as the extent of genotypic variability existing in a group of individuals. It provides opportunity for plant breeders to develop new and improved cultivars with desirable characteristics, which include both farmer-preferred traits (yield potential and large seed, etc.) and breeders preferred traits (pest and disease resistance and photosensitivity, etc.). It gives species that the ability to adapt to changing environments, including new pests and diseases and new climatic conditions, such as global warming. Hence assessment of genetic diversity in germplasm collections and genetic relationships among breeding materials is therefore essential in crop improvement strategies.

The indigenous tef genetic resources have been and will continue to be the major source of variability for its genetic improvement. In the early 1990s, a core tef germplasm set of 320 selected representative lines was established based on phenotypic evaluation and characterization of over 2255 tef germplasm collections (Ketema et al., 1993). Some studies detected tef genetic diversity at the molecular level using various types of DNA markers such as AFLP (Mulu Ayele et al., 1999; Bai et al., 1999), RAPD (Bai et al., 2000), ISSR (Assefa et al., 2003a), SSR (Zeid et al., 2012; Tesfaye et al., 2018; Fikre et al., 2018 and Jifar et al., 2020) and SNP (Girma et al., 2014). Among these, the studies so far indicate SSR markers are polymorphic in tef genotypes comparably (Girma et al., 2014)

A number of methods have been developed over the past decades for the assessment of genetic diversity in tef germplasm accessions, breeding lines and populations. This implies considerable progress in improving tef and developed and released more than 51 improved tef varieties (Chanyalew et al., 2021). However, the productivity of tef with its national average yield of 1.88 t/ha is still extremely low compared to other cereals (CSA, 2021). Among the major issues which cause low productivity are lodging, abiotic stresses such as drought and acidity, and biotic stresses (diseases and insect pests) (Assefa et al., 2015). 

Therefore, germplasm screening and varietal development with the  molecular markers in tef have been described as still insufficient (Misgana et al., 2018). Besides, conventional cereal breeding is time-consuming and very dependent on environmental conditions. Hence breeding a new variety takes between eight and twelve years and even then, the release of improved variety cannot be guaranteed. Hence, breeders are extremely interested in molecular markers. 

 Characterization and evaluation of core germplasm collections using SSR markers would be vital for enhancing genetic gain from tef breeding. The productivity of tef should be enhanced to compete with other more productive cereals. Consequently, this study is initiated with the aim of generating useful information by molecular diversity analysis for designing effective and efficient tef breeding strategies.

Materials And Methods

Plant Materials

The experimental plant materials for both the field and laboratory experiments comprised a total of 81 genotypes including 74 core germplasm lines and seven released varieties obtained from the working collections at the National Tef Research Program of DZARC. The germplasm materials originated from previous collections made from different areas of Ethiopia (Table 1)

Table 1. List of experimental tef genotypes

DNA Isolation and Purification 

About 20-30 seeds of each of the 81 tef genotypes were planted in plastic pots comprising the combination of sand, forest soil, and compost. The plants were grown in the greenhouse at National Agricultural Biotechnology Research Center (NABRC), Holetta, Ethiopia. 

Leaf samples were collected from a single plant of four-week-old seedlings. Hundred milligrams of fresh leaves were placed in 2 ml autoclaved and labeled Eppendorf tubes and freeze-dried for 24 hours at −40 °C, and then lyophilized. The samples were then ground using Geno Grinder (MM-200, Retsch) for 3 min. The genomic DNA was extracted from the ground fresh leaf samples using plant DNA extraction protocol based on the method of Diversity Array Technology (DArT) with some minor modification. Then, the DNA pellets were air dried and dissolved in 100 μl of TE buffer.

The quality and concentration of genomic DNA was checked with nano drop spectrophotometer (ND-8000, Thermos scientific). The level of DNA purity was determined by the 260/280 absorbance ratio. Further, the quality of DNA was tested using 1% (w/v) agarose gel and electrophoresis was carried out on horizontal electrophoresis set up (JYSPBT) using a standard DNA ladder. Hyper Ladder TM IV with known reference band to quantify the DNA amount and visualized using gel documentation, 3UV- Tran’s illuminator (Bio-Doc).

Those high band intensity, lesser smear, and high concentration were selected for PCR analysis and were stored in the refrigerator (4 ºC) till the PCR. 

 Microsatellite Primer Selection and Optimization

Twenty-five microsatellite primer-pairs previously developed by Zeid et al. (2011) were used for initial screening for amplification, polymorphism, and specificity to target loci. Fourteen markers that showed clear band and polymorphism were selected (Table 2). Concurring to the manufacturer's instruction, they were dissolved utilizing nuclease-free,water to a final concentration of 100mol/µl.

Table 2. Description of screened microsatellite makers that were used in the diversity analysis of 81 tef genotypes

PCR and Gel Electrophoresis 

DNA amplification was performed in 12.5 μl reaction volume containing 6.25 μl, GoTaq®Red Master Mix (supplemented with all PCR reaction components, MgCl₂, PCR buffer, dNTPs, and Taq DNA polymerase), 0.5 μl forward primer and reverse primer, 3.25 μl nuclease-free water and 2 μl genomic DNA. The PCR was carried out using thermal cycler Gene Amp® PCR system 9700 (Applied Biosystems, USA) programmed at an initial denaturation at 95°C for 2 minutes followed by denaturation at 95°C for 30 seconds, annealing at 51.3°C up to 61.3°C depending on the primer used for 1 minute, extension at 72°C for 30 seconds and final elongation at 72°C for 5 minutes for 37 cycles. Before fragment analysis, amplification of the PCR products was checked on a 2% (w/v) agarose gel and visualized using gel documentation 3UV-transilluminator (Bio-Doc).

Data Analyses

Fragment scoring and data analyses were based on allelic forms. Clearly resolved and unambiguous fragments were scored for each locus using Gel analyzer 19.1 software. Then the allelic forms data of all entries combined were subjected for statistical analysis. Genetic diversity parameters of the 81 tef genotypes were analyzed using GenAlex version 6.5 (Peakall and Smouse, 2015) software package. Genetic diversity parameters considered in this study were number of effective alleles per locus (Ne), Shannon information index (I), fixation index (F) (Nei, 1978), gene flow (Nm), and percent polymorphism (% P). The number of alleles per locus (Na), polymorphic information content (PIC), observed (Ho), and expected (He) heterozygosity were analyzed using Power Marker v3, 25 (Liu and Muse, 2005) software package.

 Furthermore, AMOVA was used to estimate F-statistics such as genetic differentiation (F_ST), fixation index or inbreeding coefficient (F_IS), and overall fixation index (F_IT) to compare the genetic structure among and within populations. The AMOVA procedures were done using Gene Alex version 6.5 (Peakall and Smouse, 2015) software package. To examine the degree of pair-wise population of F_ST and Nm values among the study materials were computed according to Nei’s (1978) using Gen Alex version 6.5 (Peakall and Smouse, 2015) software package.

Cluster analysis was carried out by using the UPGMA algorithm in DARwin version 6 software (Perrier and Jacquemoud Collet, 2010). A dendrogram for 81 tef test genotypes was then generated based on the dissimilarity matrix to visualize the pattern of a cluster within and among the selected tef germplasm lines and varieties. In addition, the population structure and admixture patterns of the 81 germplasm and release varieties were determined by the Bayesian model-based clustering method (Pritchard et al., 2000) using the Structure ver. 2.3.1 software. 

Principal Coordinate Analysis (PCoA) was done using the Jaccard’s index to further validate the complementarity of clustering pattern revealed by the dendrogram using GenAlex version 6.5 (Peakall and Smouse, 2015) software package. The first three axes were used to plot the three-dimensional PCoA with STATISTICA version 6.0 software (Hammer et al., 2001)

Results

Molecular Genetic Diversity

In this study, the overall of 122.43 alleles were detected across the genome of 81 genotypes as revealed by 14 microsatellite loci. The number of alleles noticed ranged from 6.11 (CNLTS5) to 12.4 (CNLTS463) with a mean number of 8.75 alleles per locus through the genome of the entire populations. On the other hand, from all loci there was high inbreeding coefficient (f>0.5) except loci CNLTS 463 (0.3021) (Fig 1). In addition, the heterozygosity of the studied materials ranged from 0.to 0.69 with overall mean of 0.1457. 

Relatively the markers CNLTS463, CNLTS22, CNLTS27, and CNLTS20 have high heterozygosity and Shannon´s index. The germplasm showed the highest genetic differentiation (F_st = 0.27) and the lowest value of gene flow (Nm =0.69) from CNLTS458 (Fig 1). 

Four of the microsatellite loci (CNLTS22, CNLTS25, CNLTS27 and CNLTS463) did not significantly deviated from the HW-equilibrium over the entire populations.And  the overall polymorphic information, from all the microsatellite loci utilized was found profoundly instructive (0.96-0.98) (Fig.1)

Analysis of Molecular Variance 

The analysis of molecular variance (AMOVA) showed that 1% of the total genetic variation and low genetic differentiation (F_ST = 0.014) for the variation among populations, 86% among genotypes within populations and 13% variation among genotypes across all populations (Table 4). This study confirmed genetic differentiation (F_IS =0.870) of genotypes within population and (F_IT=0.872) among genotypes across all population (From 81 genotypes=one large grouped) with a small value of overall genetic differentiation coefficient (p = 0.001) (Table 4).     

On the other side, released varieties and core germplasm collection of overall genetic differentiation coefficient among the population (p = 0.832), Fst=-0.004 and gene flow (Nm: 0) were observed (Table 4). A total genetic variation of 87% and 13% were explained by within populations and among genotypes across all populations respectively (Table 4). 

Table 4: AMOVA results of 81 tef genotypes evaluated using 14 SSRs

Where, df = degree of freedom, SS=sum of squares, MS=mean squares and Nm=gene flow, FST=inbreeding coefficient among population, FIS=inbreeding coefficient with population, FIT=inbreeding coefficient of within groups (across all population=one)

 Genetic Distance and Gene Flow Among Populations

The pairwise population genetic distance and gene flow for both core germplasm and released varieties of tef genotypes are presented in (Table 5). The pairwise Fst standard genetic differentiation among populations varied from (0.000-0.036) which means 0,000 in   between Wollo and Wellega, Gojam and Wollo ,Gojam and Wellega, Wollo and released varieties, Wellega and released varieties  and  0.036  shows in between Arsi and Wellega. 

Table 5: Fst values (below diagonal) and gene flow (above the diagonal) among tef genotypes originating from nine sources

JIM=Jimma, TG =Tigray, GOJ= Gojam, WO= Wollo, WEL=Wellega, ES= East Shoa, WS= West Shoa, AR=Arsi and R. Var=Released Variety 

Allelic Diversity Among Populations

The number of observed alleles (Na) was higher for accessions collected from East Shoa, West Shoa and Wollo with values of 18.857, 12.57 and 10.714, respectively (Fig 2). Similarly, the germplasms from East Shoa, West Shoa and Wollo in that order have the highest numbers of effective alleles with 16.756, 11.592 and 9.732 and Shannon’s information indices with 2.855, 2.436 and2.306, and numbers of private alleles with 13.071, 8.500 and6.357. (Fig 2)

Small number of observed heterozygosity were observed for all of the populations. However, relatively high number of heterozygosity were noted for the lines from Jimma (0.193), Released varieties (0.19) Wellega (0.16) Tigray (1.5) and E.shoa (1.5) and the (Fig 2). And all core germplasm tef collection of populations used in this study showed similar value in percentage of polymorphism (100), except the materials originated from Arsi. (Fig 2)

Population Structure Analysis

 Cluster Analysis 

Cluster analysis based on UPGMA method clustered the 81 tef genotypes into three major groups consisting of 52%, 44% and 4% of the genotypes in clusters 1, 2 and 3, respectively (Figure.1A). It was observed that the genotypes in cluster 1 comprised in total of genotypes per population:16/25 from East Shoa, 4/7 from released varieties, 6/11 from Wollo, 3/4 from Wellega, 3/4 from Gojam, 1/5 from Arsi, 1/16 from Jimma, 3/4 from Tigray and 5/15 from West Shoa. 

The genotypes in second cluster included 10 from West Shoa, 4 from Arsi, 7 from East Shoa, 2 from Wollo, 3 from the 7 released varieties 1 of the 4 from Tigray, and 4 from Jimma. On the other hand, only 3 of the germplasm lines from Wollo are grouped in cluster 3

Principal Coordinate Analysis

PCoA showed that the first three coordinates count in anti clockwise direction  explained 93.34% of the gross genetic variation. The gross variation explained was 65.45%, 22.93% and 4.96% by the first, second, and third principal coordinates, respectively (Fig. 3). 

Population Structure

The most function of structure in population hereditary qualities is the recognizable proof of hereditarily homogeneous bunches of individuals based on modular value of ΔK. These are determined by Bayesian algorithm implemented in the software STRUCTURE based on true number of cluster (K) suggested by Evanno et al. (2005). In this study the algorithm allows estimating the true number of clusters at (K=4) (Figure 3a) in the sample of 81 individuals included in the study. Which means that these samples (81 individuals) come from four ancestors. But the bar plot appeared that there is no clear geographic origin-based organizing of population this is what indicates there is admixture of tef genes. 

Discussion

Allelic Variance from Loci in Populations 

The allele number that found in this study relatively closer to the earlier reports with ranges of 8 to 23 (Zeid et al., 2012). However, these were different when compared to the reports of total number of alleles (164) using 10 SSR (Tesfaye et al., 2016), 168 allels using 10 SSR (Jifar et al., 2020) and, 52 using 9 SSR markers (Fikre et al., 2018). In the other case, the genetic distance in the present study is relatively high but with a narrower range than those reported by Zeid et al. (2012) 0.75-0.94 and Tesfay et al. (2016) 0.65-0.94. This shows the marker used from this study have high polymorphism and results to detect the differentiation of genotypes appropriately.

Regarding to inbreeding coefficient all loci show f>0.5 except loci CNLTS 463(0.3021). And as compared to the expected heterozygosity, the observed heterozygosity is less. This is dissimilar from the report of higher heterozygosity (Fikre et al., 2018). The cause is the differences in test genotypes used in the studies and due to the fact that tef is autogamous and improvement of tef using intra-specific crossing has not been yet exploited from most of the germplasm collections that included from this study. Here in even though the observed heterozygosis and genetic differentiation is not in line with the high range heterozygosity of in previous study of Fikre et al. (2018), the loci CNLTS463, CNLTS22, CNLTS27 and CNLTS20 have relatively high genetic variation in all the test genotypes. This gives chanced for breeders to alleles that are linked for desirable traits and then helps to establish new breeding strategy. 

In the other case, four of the microsatellite loci (CNLTS22, CNLTS25, CNLTS27 and CNLTS463) did not significantly deviate from the HW-equilibrium over the entire test genotypes. This may be due to gene flow or inbreeding as it implies genetic drift within populations. This in turn reduces or increases the amount of genetic diversity within the gene pool (Kleinhans et al., 2019). In terms of the general polymorphic data, all the microsatellite loci utilized were found profoundly instructive (0.96-0.98) and all loci have greater than 0.5. The range is different from the previous reports of 0.75 to 0.91 (Zeid et al., 2012); 0.67 to 0.94 (Tesfaye et al., 2016), and 0.36 to 0.93 (Jifar et al., 2020). 

Besides the markers used in the study are highly informative, and have high allelic variation in loci that are distributed within tef core germplasms and released varieties. Consequently, these markers would be useful for further genetic analysis diversity and interrelationships as well as linkage map and QTL mapping. And the study indicates private alleles are parallel with the number of genotypes within a population. This line with the study of Jifar et al. (2020), and the observed high number of private alleles will be important for further improvement of the tef crop. 

 Compared to the expected heterozygosity, low observed heterozygosity values were observed from all the test genotypes. However, relatively high heterozygosity occurred for germplasm lines from Jimma and Tigray, and also released varieties. Hence a good differentiation of genes may be from those populations. This will be source of good traits which help to design breeding program.

 Genetic Differentiation of the Population 

low genetic differentiation of among population from this study is due high variation of the genotypes within population. This has little bet discrepancy with the study of Jifar et al. (2020) and Tadesse et al. (2021) which is 3% and 5% respectively. But majority of the variation, is described among genotypes within one population and secondly explained by the distinction of among genotypes across all populations (within 81 genotypes =within a large group). These results show little bet high variation within population as compared to in earlier tef studies depicted Jifar et al. (2020), Tadesse et al. (2021) respectively. While it shows low variation of genotypes across all population comparing to the study of Jifar et al., (2020); Tadesse et al. (2021).

The Fst value ranged from 0 to 0.05 is considered as low, 0.05 to 0.15 moderate, and 0.15 to 0.25 large and greater than 0.25 very large genetic differentiations (Wright, 1951). Comparing to this, the current results showed low F_ST, (0.000-0.036)) genetic differentiation in pair of population which is low. While high genetic differentiation (within population and among individuals of genotypes across all populations have been observed in this study. The low genetic differentiation among populations is may be due to   presence of high gene flow that led to high genetic differentiation within population. Those which have high gene differentiation of genotypes within population and among genotypes across all populations provides ample opportunities to select lines having good potentials to adapt different environments (Bekana et al., 2021).  

On the other hand, in this study, the overall genetic differentiation of released variety versus core germplasm collections is very low among the population and the gene flow is (Nm: 0). Here in absence of gene flow is because of new varieties were released recently whereas, the core germplasm was collected earlier around 1994 (Berhe, 1995). 

Clustering and Population Structure Analysis 

Cluster analysis is used to establish the relationships among the genotypes based on their distance matrix. Based on this, the UPGMA method, the study confirms the reports of Fikre et al. (2018) and Tadesse et al. (2021), who obtained three clusters of the tef test genotypes whereas Jifar et al. (2020) obtained 5 clusters for 144 genotypes. Here indicates the number of genotypes and its diversity that used from study have influenced the number of clusters. And the patterns of grouping of the genotypes through all clusters obviously showed the existence of moderate to significant gene flow along geographical borders. This is due to contiguity and interchange of germplasm resources. Besides, for small seeded crops like tef, it is very hard to maintain truly pure seed stocks because admixtures can occur during any step of the seed production and handling process unless extreme care is practiced (Zeid et al., 2012). 

On the other case the cluster of collected core germplasm versus release variety, the released varieties are distributed from different clusters and sub clusters rather than forms one cluster except Tesfa and Eba. This indicates, the variety may be developed for different parents which found in different agro ecologies whereas the variety Tesfa and Eba may have similar parents. 

The most function of structure in population hereditary qualities is the recognizable proof of hereditarily homogeneous bunches of individuals. In PCoA of in this study  showed that individuals make three groups with  three coordinates explained 93.34% of the genetic variation. The gross variation explained in this study is unlike from the previous study of Fikre et al. (2016), 29% of gross variation 12%, 10%,7% Tadesse et al. (2021); 30.72% explained 13.13 %, 9.20%, 8.39% and Teshome (2019) 14.85% of the total variation explained  5.57%, 4.95% and 4.33%  . 

In the other case, based on Bayesian algorithm ,the structure of the individuals clustered into four since the algorithm allows estimating the true number of clusters at (K=4) (Figure 3a) in the sample of 81 individuals based on suggested by Evanno et al. (2005).Which means that these samples come from four ancestors. But the bar plot appeared in the admixture indicates the used sample of individuals are admixture and requires revision for its collection.  

Conclusion And Recommendation

In conclusion, sufficient genetic variation offers alternatives from which selections are made for improvement of crop. A success in crop improvement depends  on the quantity of genetic variation that exist in the genetic materials and selection for genetically superior genotypes.

In this study higly polymorphic and informative markers were used .Hence larger number of allels are generated.  Among these, there may have  private  allels which might be linked to important agronomic traits. And it  indicates there is relatively high heterozygosity occurred for germplasm lines which is found in  Jimma ,Tigray and released varieties .Those may have allels which linked to good traits which help to design breeding program. While  we observed lower heterozygosity than  expected heterozygosity. To increase hetezygosity,  artificial intracross and a broad variablity through artificial intercrossing should be supported by in vitro embryo rescue. And induced mutation will aslo help to increase the variablity of tef. As the population structure indicates from this study the genotypes found in all population are admixture which come from four ancestors. Hence re-collect the genotypes based on its origin may be good to conserve

The study did not cover all admistrative zones due to lack of the passport data.To facillitate the breeding for diffrenet environment, core germplasm collection should be revised and collected based on agroecologies

Declarations

Acknowledgements

The principal author acknowledges the assistance and support of the Ethiopian Institute of Agricultural Research (EIAR), Debre Zeit Agricultural Research Center and its staff, Holetta National Agricultural Biotechnology Research Center and its staff, Mr. Obssi Desalegn, Dr.Solomon Chanyalew, Prof.Gabriel Schaaf and his PhD student Yeshambel Emwedih,at Rhenish Friedrich Wilhelm University of Bonn, and Wagaw Sendeku (PhD) Student at Addis Ababa University.

Author contributions

Kebebew A. and Derejaw T. conceived the study; Derejaw.T did the whole lab work, data analysis and drafted the manuscript; Tileye F. and Kebebew A. give suggestion follow up the work and revised the manuscript; all authors reviewed the manuscript and gave final approval for publication

Funding 

funding provided for working was by Ethiopian institution agricultural research and Addis Ababa university.

Conflict of Interest          

No conflict of interest.

Data Availability Statement

The data that support the findings of this study are openly available in the Science Data Bank at https://www.doi.org/ [DOI 10.57760/science dB. j00143.00070] and Addis Ababa university library 

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