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Brazilian Journal of Botany

, Volume 41, Issue 3, pp 699–709 | Cite as

Genetic diversity and population structure of Urochloa grass accessions from Tanzania using simple sequence repeat (SSR) markers

  • S. O. Kuwi
  • M. Kyalo
  • C. K. Mutai
  • A. Mwilawa
  • J. Hanson
  • A. Djikeng
  • S. R. GhimireEmail author
Open Access
Original Article

Abstract

Urochloa (syn.—Brachiaria s.s.) is one of the most important tropical forages that transformed livestock industries in Australia and South America. Farmers in Africa are increasingly interested in growing Urochloa to support the burgeoning livestock business, but the lack of cultivars adapted to African environments has been a major challenge. Therefore, this study examines genetic diversity of Tanzanian Urochloa accessions to provide essential information for establishing a Urochloa breeding program in Africa. A total of 36 historical Urochloa accessions initially collected from Tanzania in 1985 were analyzed for genetic variation using 24 SSR markers along with six South American commercial cultivars. These markers detected 407 alleles in the 36 Tanzania accessions and 6 commercial cultivars. Markers were highly informative with an average polymorphic information content of 0.79. The analysis of molecular variance revealed high genetic variation within individual accessions in a species (92%), fixation index of 0.05 and gene flow estimate of 4.77 showed a low genetic differentiation and a high level of gene flow among populations. An unweighted neighbor-joining tree grouped the 36 accessions and six commercial cultivars into three main clusters. The clustering of test accessions did not follow geographical origin. Similarly, population structure analysis grouped the 42 tested genotypes into three major gene pools. The results showed the Urochloa brizantha (A. Rich.) Stapf population has the highest genetic diversity (I = 0.94) with high utility in the Urochloa breeding and conservation program. As the Urochloa accessions analyzed in this study represented only 3 of 31 regions of Tanzania, further collection and characterization of materials from wider geographical areas are necessary to comprehend the whole Urochloa diversity in Tanzania.

Keywords

Apomixis Brachiaria Carbon sequestration Polyploid Principal coordinate analysis Private alleles 

1 Introduction

Urochloa (syn.—Brachiaria s.s.) that consists of about 100 species is among the most widely cultivated tropical forage grass in South America, Australia and East Asia and has been recognized for high yield, nutritional content and wider adaptability to diverse ecological niches (Miles et al. 1996). Urochloa is a tropical warm season forage native to Africa and was first introduced to Australia in about 1800 (Barnard 1969) and subsequently into tropical South America during the mid-nineteenth century (Parsons 1972). Urochloa is resistant to drought, insect pests and diseases and competes effectively with other plant species and quickly covers the ground (Stomayor-Rios et al. 1960). Urochloa produces a yearly dry forage yield of 5–36 t/ha depending on soil fertility, soil moisture content and fertilizer application (Bogdan 1977). The forage is palatable and highly nutritious contributing to a significant increase in livestock milk and meat production. Moreover, Urochloa sequesters carbon, enhances N use efficiency through a biological nitrification inhibition process and subsequently reduces greenhouse gas emission and groundwater pollution (Subbarao et al. 2009; Danilo et al. 2014; Arango et al. 2014).

Low livestock productivity is a common feature across sub-Saharan Africa (SSA) contributed largely by shortage of quality feed particularly during the dry seasons. Though not a tradition, farmers have started growing improved forages to support the emerging livestock sector in the region. Recently, Urochloa has emerged as one of the important forage options among smallholder farmers of Africa (Ghimire et al. 2015). However, the wider adoption of Urochloa grass in Africa is constrained by unavailability of seeds, lack of improved agronomic practices and nonexistence of a variety suitable for wide-ranging environments. The varieties currently introduced to Africa were developed in Australia and tropical America from the African germplasm. The commercial cultivation of these varieties developed elsewhere can lead to an elevated risk of pests and diseases, and of poor adaptation to other biotic and abiotic stresses. Therefore, the need for Africa-based Urochloa breeding program accommodating natural genetic diversity in the region has been recently realized with the aim to develop varieties suitable to different production environments.

The characterization of genetic diversity of a population is necessary for better use of genetic resources in breeding and biodiversity conservation programs. Therefore, knowledge of genetic diversity of the available germplasm is essential in selecting materials for cultivation or parents for cultivar development. The genetic diversity can be assessed using different tools including DNA markers (Kapila et al. 2008). Molecular markers are valuable tools for characterization and evaluation of genetic diversity within and between species and populations. Different molecular markers such as random amplified polymorphic DNA (RAPD), inter-simple sequence repeats (ISSR), simple sequence repeats (SSR) and amplified fragment length polymorphism (AFLP) have been used to assess the genetic diversity in plant species (Balasaravanan et al. 2003; Khan et al. 2005; Terzopoulos et al. 2005) of which the simple sequence repeats (SSR) are preferred due to ease of application, high reproducibility, rapid analysis, low cost, easy scoring patterns and higher allelic diversity (Chen et al. 1997). The SSR markers are codominant markers that can detect both homozygote and heterozygote individuals and are distributed throughout the genome (McCouch et al. 1997). Knowing the degree of genetic differences among Urochloa genotypes is useful to organize a working collection and to select genotypes for crossing and conservation (Mendes-Bonato et al. 2006). Despite the importance of Urochloa, limited information is available on biology and genetic diversity of the genus, which has severely constrained the breeding and conservation efforts. Therefore, this study was conducted to assess the genetic diversity and population structure of Tanzanian Urochloa accessions from the historical collection maintained at the Field Genebank of the International Livestock Research Institute (ILRI), Ethiopia. The result of this study would be highly useful in a Urochloa improvement and conservation program.

2 Materials and methods

Source of plant materials

– A total of 36 Urochloa accessions originally collected from Tanzania and six commercial cultivars (Basilisk, Humidicola, Llanero, MG4, Mulato II and Piata) were included in this study (Table 1). The Genbank accessions were collected from natural populations from the Iringa, Mbeya and Ruvuma regions of Tanzania (Fig. 1) during 1985 and since then maintained in ILRI’s Forage Field Genebank at Zwai, Ethiopia. Fresh young leaf samples were collected, dried in silica gel and transported to the Biosciences eastern and central Africa—International Livestock Research Institute (BecA-ILRI) Hub, Nairobi, Kenya, for subsequent analysis. Leaf samples of six commercial cultivars were collected from pasture evaluation plots at ILRI Headquarters, Nairobi, Kenya.
Table 1

Details of Urochloa accessions and commercial cultivars used in the study

S. no

Accession

Other ID #

Species

Variety

Origin

Region

Latitude

Longitude

Collection year

1

ILCA-814

CIAT 26386

U. brizantha

NA

Tanzania

Iringa

− 8.89

33.98

1985

2

ILCA-726

CIAT 26370

U. brizantha

NA

Tanzania

Iringa

− 7.9501

35.56

1985

3

ILCA-731

CIAT 26371

U. brizantha

NA

Tanzania

Iringa

− 8.3298

35.3104

1985

4

ILCA-869

CIAT 26397

U. brizantha

NA

Tanzania

Mbeya

− 8.5

33.4

1985

5

ILCA-717

CIAT 26407

U. humidicola

NA

Tanzania

Iringa

− 7.78

35.75

1985

6

ILCA-10871

U. decumbens

Basilisk

Uganda

NA

NA

NA

NA

7

ILCA-12470

U. humidicola

Llanero

Zambia

NA

NA

NA

NA

8

ILCA-828

CIAT 26389

U. brizantha

NA

Tanzania

Mbeya

− 8.92

33.39

1985

9

ILCA-821

CIAT 26388

U. brizantha

NA

Tanzania

Mbeya

− 8.82

33.84

1985

10

ILCA-849

CIAT 26393

U. brizantha

NA

Tanzania

Mbeya

− 9.35

33.67

1985

11

CIAT 16125

U. brizantha

Piata

NA

NA

NA

NA

12

ILCA-758

U. jubata

NA

Tanzania

Ruvuma

− 10.77

35.13

1985

13

ILCA-767

CIAT 26380

U. brizantha

NA

Tanzania

Ruvuma

− 10.3718

35.5573

1985

14

ILCA-781

CIAT 26381

U. brizantha

NA

Tanzania

Ruvuma

− 10.0266

35.3737

1985

15

ILCA-785

CIAT 26384

U. brizantha

NA

Tanzania

Iringa

− 9.28

34.38

1985

16

ILCA-732

CIAT 26434

U. ruziziensis

NA

Tanzania

Iringa

− 8.3298

35.3104

1985

17

ILCA-829

CIAT 26423

U. humidicola

NA

Tanzania

Mbeya

− 8.93

33.27

1985

18

ILCA-728

CIAT 26411

U. humidicola

NA

Tanzania

Iringa

− 7.9501

35.56

1985

19

ILCA-727

CIAT 26438

U. bovonei

NA

Tanzania

Iringa

− 7.9501

35.56

1985

20

ILCA-735

CIAT 26414

U. humidicola

NA

Tanzania

Iringa

− 8.5853

35.3122

1985

21

ILCA-822

CIAT 26422

U. humidicola

NA

Tanzania

Mbeya

− 8.82

33.84

1985

22

ILCA-853

CIAT 26427

U. humidicola

NA

Tanzania

Mbeya

− 9.48

33.7

1985

23

ILCA-864

CIAT 26430

U. humidicola

NA

Tanzania

Mbeya

− 9.55

33.76

1985

24

ILCA-832

CIAT 26424

U. humidicola

NA

Tanzania

Mbeya

− 9.0549

33.1715

1985

25

ILCA-857

CIAT 26428

U. humidicola

NA

Tanzania

Mbeya

− 9.57

33.83

1985

26

CIAT  36087

U. hybrid

Mulato-II

Colombia

NA

NA

NA

NA

27

ILCA-810

CIAT 26385

U. brizantha

NA

Tanzania

Mbeya

− 8.91

33.56

1985

28

ILCA-756

CIAT 26404

U. brizantha

NA

Tanzania

Ruvuma

− 10.76

35.16

1985

29

ILCA-769

CIAT 26439

U. bovonei

NA

Tanzania

Ruvuma

− 10.1543

35.4718

1985

30

ILCA-815

CIAT 26420

U. humidicola

NA

Tanzania

Iringa

− 8.89

33.98

1985

31

ILCA-734

CIAT 26413

U. humidicola

NA

Tanzania

Iringa

− 8.4303

35.3511

1985

32

ILCA-819

CIAT 26421

U. humidicola

NA

Tanzania

Iringa

− 8.91

33.98

1985

33

ILCA-782

CIAT 26382

U. brizantha

NA

Tanzania

Ruvuma

− 9.82

35.3

1985

34

ILCA-760

CIAT 26378

U. brizantha

NA

Tanzania

Ruvuma

− 10.88

35.01

1985

35

ILCA-744

CIAT 26416

U. humidicola

NA

Tanzania

Iringa

− 9.0392

34.8211

1985

36

ILCA-736

CIAT 26415

U. humidicola

NA

Tanzania

Iringa

− 8.5798

35.324

1985

37

ILCA-863

CIAT 26396

U. brizantha

NA

Tanzania

Mbeya

− 9.55

33.76

1985

38

ILCA-718

CIAT 26408

U. humidicola

NA

Tanzania

Iringa

− 7.6006

35.5495

1985

39

ILCA-761

CIAT 26379

U. brizantha

NA

Tanzania

Ruvuma

− 11.04

34.92

1985

40

CIAT  26646

U. brizantha

MG4

Trinidad

NA

NA

NA

NA

41

ILCA-812

CIAT 26405

U. brizantha

NA

Tanzania

Mbeya

− 8.8

33.64

1985

42

CIAT  679

U. humidicola

Humidicola

South Africa

NA

NA

NA

NA

NA not available

Fig. 1

Map of Tanzania showing the origin of Urochloa accessions. Purple, blue and green colors in map represent Mbeya, Iringa and Ruvuma regions, respectively. (Color figure online)

Genomic DNA extraction

– Genomic DNA was extracted from dried leaves using Zymo extraction kit (Zymo Research, USA) according to manufacturer’s instructions. The quality, quantity and integrity of DNA were estimated using the NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA) and visualized in 1% agarose gel (w/v) stained with 0.25X GelRed under ultraviolet light (UVP BioImaging Systems, Upland, CA). The DNA was adjusted to the final concentration of 20 ng/μl and stored at − 20 °C until further use.

PCR amplification and capillary electrophoresis

– A total of 24 SSR markers initially developed for U. ruziziensis Germain & Evrard with the proven transferability to other Urochloa species were used in the study (Silva et al. 2013; Table 2). Primers were optimized for appropriate annealing temperature using gradient PCR. Thereafter, multiplex PCR was used to amplify genomic DNA using AccuPower® PCR PreMix without dye (Bioneer, Republic of Korea). PCR amplification was performed in a final reaction volume of 10 μl containing 40 ng genomic DNA, 0.09 μM of each forward and reverse primer (labeled with different fluorescent dyes: 6-FAM, VIC, NED and PET), 0.5 μM MgCl2 and 7.2 μl sterile water. The PCR amplifications were performed in a GeneAmp PCR System 9700 thermocycler (Applied Biosystems, Foster City, CA) using the following PCR cycling conditions: initial denaturation at 95 °C for 3 min, followed by 35 cycles of 94 °C for 30 s, annealing at 58/59 °C for 1 min, extension at 72 °C for 2 min and final extension at 72 °C for 20 min and hold at 15 °C. The amplicons were separated in 2% agarose gel stained with 0.25× GelRed and run for 45 min at 100 V. A cocktail (LH) of 15 μl GeneScan™500LIZ size standard (Applied Biosystems, USA) and 1 ml Hi-Di-formamide was prepared for capillary electrophoresis. Multiplexed PCR product (1.5 μl) was mixed with 9 μl of LH, denatured at 95 °C for 3 min and snap-chilled on ice for 5 min. The samples were then subjected to capillary electrophoresis at the Segolip Unit of BecA-ILRI HuU.
Table 2

SSR markers used for the genetic diversity study of Tanzania Urochloa accessions and commercial varieties

(adapted from Silva et al. 2013)

Marker

Forward primer sequence

Reverse primer sequence

Annealing temperature (°C)

Expected product size range (bp)

Repeat motif

Br0012

ACTCAAACAATCTCCAACACG

CCCCACAAATGGTGAATGTAAC

59

144–196

(AT)8

Br0028

CATGGACAAGGAGAAGATTGA

TGGGAGTTAACATTAGTGTTTTT

58

111–197

(TA)8

Br0029

TTTGTGCCAAAGTCCAAATAG

TATTCCAGCTTCTTCTGCCTA

59

132–178

(AG)14

Br0031

CCCCCATTTAACACCATAGTT

GCTCAAAATGCAATGTACGTG

59

139–179

(AT)9

Br0067

TTAGATTCCTCAGGACATTGG

TCCTATATGCCGTCGTACTCA

59

130–171

(AT)9

Br0076

CCTAGAATGCGGAAGTAGTGA

TTACGTGTTCCTCGACTCAAC

59

120–262

(AT)7

Br0087

TTCCCCCACTACTCATCTCA

AACAGCACACCGTAGCAAGT

58

229–261

(GA)9

Br0092

TTGATCAGTGGGAGGTAGGA

TGAAACTTGTCCCTTTTTCG

59

200–295

(AT)6

Br0100

CCATCTGCAATTATTCAGGAAA

GTTCTTGGTGCTTGACCATT

58

229–286

(AT)11

Br0115

AATTCATGATCGGAGCACAT

TGAACAATGGCTTTGAATGA

59

231–315

(AT)6

Br0117

AGCTAAGGGGCTACTGTTGG

CGCGATCTCCAAAATGTAAT

59

233–345

(TA)5

Br0118

AGGAGGTCCAAATCACCAAT

CGTCAGCAATTCGTACCAC

59

237–321

(CT)11

Br0156

CATTGCTCCTCTCGCACTAT

CTGCAGTTAGCAGGTTGGTT

58

223–279

(CA)6

Br0130

TCCTTTCATGAACCCCTGTA

CATCGCACGCTTATATGACA

58

199–299

(CT)14

Br0149

GCAAGACCGCTGTTAGAGAA

CTAACATGGACACCGCTCTT

58

231–299

(AT)11

Br0152

ATGCTGCACTTACTGGTTCA

GGCTATCAATTCGAAGACCA

58

233–301

(TC)11

Br0214

GCCATGATGTTTCATTGGTT

TTTTGCACCTTTCATTGCTT

59

231–286

(AC)7

Br0203

CGCTTGAGAAGCTAGCAAGT

TAGCCTTTTGCATGGGTTAG

58

208–310

(GA)8

Br0212

ACTCATTTTCACACGCACAA

CGAAGAATTGCAGCAGAAGT

58

248–330

(CA)5

Br0213

TGAAGCCCTTTCTAAATGATG

GAACTAGGAAGCCATGGACA

58

212–337

(CA)7

Br0122

TCTGGTGTCTCTTTGCTCCT

TCCATGGTACCTGAATGACA

58

241–358

(AT)8

Br0235

CACACTCACACACGGAGAGA

CATCCAGAGCCTGATGAAGT

59

239–330

(TC)9

Br3002

GCTGGAATCAGAATCGATGA

GAACTGCAGTGGCTGATCTT

59

143–187

(AAT)7

Br3009

AGACTCTGTGCGGGAAATTA

ACTTCGCTTGTCCTACTTGG

58

116–199

(AAT)10

Data analysis

– Forty-two Urochloa genotypes consisting five species: U. bovonei (Chiov.) Robyns, U. brizantha (A. Rich.) Stapf, U. jubata (Fig. & De Not.) Stapf, U. humidicola (Rendle) Schweick, U. ruziziensis Germain & Evrard and six Urochloa cultivars were grouped into six populations for the genetic diversity study. The descriptive statistics for SSR markers were computed with PowerMarker v.3.25 software (http://www.powermarker.net). The population diversity description, principal coordinate analysis (PCoA) and analysis of molecular variance (AMOVA) were performed using GenAlEx v6.41 (Peakall and Smouse 2006). The neighbor-joining method (NJ) was used to generate the dendrogram using Darwin v.6.0.010 (Perrier and Jacquemoud-Collet 2006). One thousand bootstrap replicates were used to determine branch support in the consensus tree. Structure v.2.3.4 (Pritchard et al. 2000) was used to infer the population structure and ancestry of samples based on Bayesian statistics. The parameter set for this analysis used the admixture model, and batch runs with correlated and independent allele frequencies among inferred populations were tested with burn-in and run length of 50,000 and 100,000, respectively. All other parameters were set to default values. A batch job with values of K ranging from 1 to 10 was set up, with ten independent runs for each successive K. This procedure clusters individuals into populations and estimates the proportion of membership in each population for every individual. The K value was determined by the log probability of data [(Ln P(D)] based on the rate of change in Ln P(D) between successive K. The optimum K value was predicted following the simulation method (Evanno et al. 2005) using the web-based software Structure Harvester v.0.6.92 (Earl and Von Holdt 2012).

3 Results

SSR polymorphism and genetic diversity

– A total of 407 alleles ranging in size from 111 to 345 bp were detected (Tables 2, 3). The number of alleles scored per locus varied from 5 (Br0067) to 40 (Br0028) with an average of 16.96 alleles across all loci. The PIC value varied from 0.64 (Br0213) to 0.95 (Br0235) with an average of 0.79 per locus (Table 3).
Table 3

Diversity indices for 24 microsatellite markers

SSR locus

N A

N DA

I

H O

H E

PIC

Br0012

9

9

0.86

0.50

0.35

0.85

Br0029

11

10

0.73

0.42

0.26

0.71

Br0031

9

9

0.67

0.50

0.36

0.66

Br0067

5

5

0.84

0.17

0.11

0.82

Br0076

9

9

0.81

0.50

0.33

0.80

Br0087

22

16

0.75

0.43

0.31

0.74

Br0092

7

7

0.76

0.50

0.30

0.74

Br0115

16

12

0.95

0.66

0.44

0.95

Br0117

8

8

0.74

0.50

0.31

0.73

Br0118

12

11

0.70

0.42

0.24

0.68

Br0212

17

13

0.95

0.57

0.44

0.95

Br0214

16

12

0.93

0.88

0.66

0.92

Br0235

31

23

0.95

0.71

0.55

0.95

Br3002

11

9

0.87

0.63

0.46

0.86

Br0028

40

19

0.79

0.65

0.48

0.78

Br0100

13

13

0.73

0.63

0.44

0.72

Br0122

10

9

0.78

0.42

0.26

0.76

Br0130

18

11

0.76

0.67

0.47

0.75

Br0149

13

12

0.67

0.50

0.32

0.66

Br0152

29

19

0.73

0.69

0.43

0.73

Br0156

38

22

0.85

0.74

0.55

0.85

Br0203

22

15

0.80

0.56

0.36

0.79

Br0213

6

6

0.66

0.50

0.32

0.64

Br3009

35

23

0.81

0.70

0.49

0.80

Mean

16.96 ± 10.43

12.74 ± 5.32

0.80 ± 0.09

0.56 ± 0.15

0.38 ± 0.12

0.79 ± 0.09

NA number of alleles, NDA number of different alleles, I Shannon index, HO observed heterozygosity, HE expected heterozygosity

Population genetic diversity

– The genetic diversity indices for Urochloa populations are summarized in Table 4. The average number of effective alleles (NE), number of private alleles (NP) and percentage of polymorphic loci (%PL) across all loci ranged from 0.34–2.74, 0.08–1.53 and 17.19–68.75%, respectively, in the studied populations. The observed heterozygosity (HO) was in the range of 0.17–0.69, with a mean of 0.49. The high-level diversity was observed in U. brizantha population (I = 0.94) and a low-level diversity in U. bovonei population (I = 0.12). The observed heterozygosity was higher than expected for all populations.
Table 4

Summary of population genetic diversity indices averaged over 24 SSR markers

Population

N

N A

N E

N P

I

H O

H E

%PL

U. brizantha

17

3.50

2.74

1.53

0.94

0.69

0.47

68.75

U. humidicola

15

2.70

2.37

1.03

0.77

0.58

0.40

57.81

U. bovonei

2

0.94

0.69

0.22

0.25

0.31

0.17

31.25

U. ruziziensis

1

0.34

0.34

0.08

0.12

0.17

0.09

17.19

U. jubata

1

0.59

0.59

0.28

0.21

0.30

0.15

29.67

Urochloa Cultivars

6

1.61

1.48

0.66

0.52

0.46

0.30

46.88

Mean

8.4

1.89

1.64

0.76

0.56

0.49

0.31

41.93

SE (±)

0.13

0.12

0.10

0.12

0.03

0.03

0.02

7.90

N number of accessions, NA number of alleles, NE number of effectives alleles, I information index, HO observed heterozygosity, HE expected heterozygosity, NP number of private alleles, %PL percentage of polymorphic loci

Genetic distance

– The pairwise genetic distance and population matrix of Nei unbiased genetic identity were presented in Table 5. Among four populations analyzed (excluding U. ruziziensis and U. jubata), U. bovonei and commercial cultivar populations were distantly related (3.186), whereas U. brizantha and U. humidicola populations were the most closely related (1.639). Similarly, genetic identity was the highest between U. brizantha and U. humidicola populations (0.194) and the lowest between U. bovonei and commercial cultivar populations (0.041).
Table 5

Pair-wise genetic distance based on shared allele (below diagonal) and genetic identity among Urochloa populations (above diagonal)

Population

U. brizantha

U. humidicola

U. bovonei

Cultivars

U. brizantha

0.194

0.048

0.097

U. humidicola

1.639

0.055

0.067

U. bovonei

3.044

2.893

0.041

Cultivars

2.333

2.709

3.186

Analysis of molecular variance

– Analysis of molecular variance (AMOVA) of 42 Urochloa genotypes showed that only 3% of the total variation in the population was due to differences among individual accessions. Differences within individual accessions in a population contributed 94% of total variation, and 5% was due to the differences among the Urochloa populations (Table 6). There was a low genetic differentiation in the total populations (FST = 0.05) as evidenced by high level of gene flow estimate (Nm = 4.77).
Table 6

Analysis of molecular variance (AMOVA) of populations of Urochloa accessions and cultivars based on 24 SSR loci

Source

Degree of freedom

Sum of squared

Mean of squared

Estimated variance

Variation (%)

P values

Among populations

4

96.841

24.210

0.712

5

0.001

Among individuals

37

517.754

13.993

0.407

3

0.084

Within individuals

42

553.500

13.179

13.179

92

0.001

Total

83

1168.095

 

14.298

100

 

FST = 0.05; Nm = 4.77

FST Fixation index, Nm Number of migration per generation

Population structure

– The principal coordinate analysis (PCoA) bi-plot showed no distinct clustering pattern for 42 Urochloa genotypes studied (Fig. 2). The variations explained by axes 1 and 2 were 26.09 and 10.78%, respectively. An unweighted neighbor-joining dendrogram depicting genetic relationships among the Urochloa accessions and commercial cultivars showed three major clusters (Fig. 3). Of the 42 individuals including the commercial cultivars, 19, 18 and 5 individuals were grouped together in cluster I, II and III, respectively. Most of the accessions from U. brizantha and one commercial cultivar (MG4) grouped in cluster I, whereas most of accessions from U. humidicola, two accessions of U. bovonei and two commercial cultivars (Humidicola and Piata) grouped in cluster II. Three commercial cultivars (Basilisk, Llanero and Mulato II) and one available accession U. ruziziensis formed the cluster III. Overall topology of the dendrogram indicated the presence of three lineages in the Urochloa populations studied. A similar pattern was observed on Bayesian model-based clustering algorithm implemented in STRUCTURE software. The method of Evanno et al. (2005), implemented in STRUCTURE, predicted K = 3 to be the most likely number of clusters (Fig. 4).
Fig. 2

Principal coordinate analysis (PCoA) bi-plot showing the clustering of 36 Urochloa accessions from Tanzania and six commercial cultivars. Percentages of variation explained by the first two axes (1, 2) are 26.09 and 10.78%, respectively. (Color figure online)

Fig. 3

An unweighted neighbor-joining tree of 42 Urochloa genotypes (36 Tanzanian accessions and six commercial cultivars) using the simple matching similarity coefficient based on 24 microsatellite markers. The populations are color-coded as shown in the tree. (Color figure online)

Fig. 4

a Analysis performed in STRUCTURE 2.2.3 using admixture model with correlated allele frequencies. The clustering profile obtained for K = 3 is displayed as indicated by different colors. b Each of the 42 individuals is represented by a single column broken into colored segments with lengths proportional to each of the K inferred gene pools. Three major clusters of individuals were identified and are indicated by red, green and blue colors (CI = 17, CII = 10 and CIII = 15), and bars with two colors represent individuals that share allelic pools. Membership coefficients (y-axis) are indicated, which were used to allocate individuals into clusters. (Color figure online)

4 Discussion

Genetic diversity assessment is an essential component of any Urochloa breeding and conservation program. Microsatellites are among the most widely used DNA markers for many purposes such as diversity, genome mapping and variety identification (da Silva 2005). These markers have been used to study genetic diversity in different plant species (Singh et al. 2004; Joshi and Behera 2006). In this study, the extent and pattern of genetic variation among 36 Tanzanian Urochloa accessions were evaluated and their genetic relationships with six Urochloa cultivars were examined using 24 SSR markers. The SSR markers used in the study were subsets of previously published markers (Silva et al. 2013) with high polymorphic information content (PIC) values, elevated allele detection profile and proven transferability to multiple Urochloa species.

The average number of alleles (16.96) detected in this study was higher than that reported by Jungmann et al. (2010), Bianca et al. (2011), Silva et al. (2013) and Pessoa-Filho et al. (2015), who reported average numbers of alleles of 7.33, 4.22, 12.3 and 9 using 172 U. brizantha, 11 U. ruziziensis, 63 African Ruzigrass and 58 U. humidicola accessions with 15, 30, 15 and 27 SSR markers, respectively. The mean PIC value for SSR markers was high (0.79) compared to previous studies (Sousa et al. 2010; Bianca et al. 2011; Silva et al. 2013) showing high discriminating ability of these markers among tested genotypes. The detection of more alleles and high PIC values in this study could have been attributed to high diversity in Tanzanian Urochloa accessions, use of primers with high allele detection ability, high PIC values and proven transferability to multiple Urochloa species or a combination thereof. The high number of alleles detected in this study signifies high genetic variations among test Urochloa accessions in consistent with high genetic diversity index (0.67–0.95) (Table 3). The result is not surprising as Tanzania is within the region that represents a center of diversity for Urochloa species. Moreover, these 36 Tanzanian Urochloa accessions represent five distinct species (Table 1).

All the diversity indices are measured in this study, including the numbers of private alleles were high for U. brizantha population, whereas U. bovonei and U. ruziziensis populations had lower values (Table 4). As the number of different alleles and the number of private alleles depend heavily on sample size (Szpiech et al. 2008), a high number of accessions in U. brizantha population might have largely contributed to such results. Despite similar sample size of U. jubata and U. ruziziensis, the U. jubata accession had a slightly higher number of private alleles and a higher percentage of polymorphic loci, signifying that factors other than sample size also contribute to diversity indices. The observed heterozygosity was higher than expected heterozygosity for all studied Urochloa populations suggesting presence of many equally frequent alleles and the high genetic variability in the populations indicating high value of these genetic resources in Urochloa improvement and conservation program. Mixing of two previously isolated Urochloa populations could be another possibility for higher observed heterozygosity than expected.

Genetic distance is the measure of the allelic substitutions per locus that have occurred during the separate evolution of two populations or species (Woldesenbet et al. 2015). The Nei unbiased genetic distance between U. brizantha and U. humidicola was smaller, while larger genetic distance was observed between U. bovonei and the commercial cultivars. The genetic closeness of two populations could be due to interspecific hybridization that has occurred throughout their evolution, which favors allele sharing (Cidade et al. 2013). The large genetic distance observed between U. bovonei and commercial cultivars could be attributed by lack of genetic similarity as five commercial cultivars used in this species are from three species (U. brizantha, U. decumbens Stapf and U. humidicola), while commercial cultivar, Mulato II, is a product of three-way cross of U. brizantha, U. decumbens and U. ruziziensis. Two species, i.e., U. jubata and U. ruziziensis, were not included in this analysis due to insufficient sample size.

The AMOVA test showed major and significant (92%; P = 0.001) contribution of within-individual difference to a total variation, whereas among-individual and among-population differences contributed 3 and 5%, respectively. The high level of genetic variation within species observed in our study was similar to that reported for Ruzigrass (Pessoa-Filho et al. 2015). These results are also in agreement with other studies (Bianca et al. 2011; Garcia et al. 2013; Teixeira et al. 2014). The high level of genetic variation within individual in a population could be attributed to genetic drift, mutation and environment conditions (Young et al. 2000). As the Urochloa population/species in this study are composed of genotypes originating from different locations with different geographical and environment conditions, a high within-population difference was expected. There was a low genetic variation among Urochloa accessions in consistent with the high genetic indices as evidenced by relatively low fixation index (FST = 0.05) among populations and high number of migration (Nm = 4.7) per generation (Slatkin 1981; Caccone 1985; Walples 1987). A low genetic differentiation among Urochloa populations was anticipated because of apomictic mode of reproduction, polyploidy-triggered meiotic anomalies obstructing sexual reproduction and dispersion of plant propagules by migratory herbivores and birds. Of five Urochloa species analyzed in this study, four (U. brizantha, U. humidicola, U. bovonei and U. jubata) are polyploid (Boldrini et al. 2009; Bianca et al. 2011) and U. ruziziensis is diploid with sexual mode of reproduction (Pessoa-Filho et al. 2015). Polyploid plants can effectively colonize and occupy different habitats favoring no genetic differentiation among Urochloa populations (De Wet 1980). This has also been observed in other apomictic polyploid forages such as Paspalum notatum Fluegge (Cidade et al. 2013).

In PCoA, no distinct clusters were observed; however, STRUCTURE and the unweighted neighbor-joining algorithm analyses consistently revealed three major clusters (Figs. 3, 4). Cluster I was mainly composed of U. brizantha accessions (15 out of 17), while most U. humidicola accessions (12 out of 15) were found in cluster II and 3 of 6 commercial cultivars were found in cluster III. Two accessions of U. bovonei and one of U. jubata were found in cluster II, but in different sub clusters. Although U. ruziziensis was found in cluster III, it is a bit far from the rest of accessions (Fig. 3). This is as expected because it is only one accession included in this study with diploid genome and sexual mode of reproduction. The accessions included in the study grouped together irrespective of their geographical origin indicating accessions from different geographical regions share the allelic pool (Sousa et al. 2010). However, a little admixture of accessions from different allelic pools was observed in all clusters showing possible interspecific hybridization that might have occurred during the evolution favoring allele sharing, or could be due to the error while assigning species. This study revealed a high genetic diversity in Tanzanian Urochloa accessions compared to six commercial Urochloa cultivars. The SSR markers used in this study were highly informative to assess genetic diversity in Urochloa species. The Urochloa accessions did not cluster according to the geographical regions but clustered by their genetic background. The accessions belonging to U. brizantha were more diverse than those from other four species and commercial cultivars, which can be tapped and used in conservation and breeding programs, especially in developing improved Urochloa varieties and hybrids that can produce high biomass and withstand well to biotic and abiotic environmental conditions. The cultivars and sexual diploid U. ruziziensis from cluster III can be used in future crosses with other accessions from cluster I and II depending on their ploidy to obtain heterosis in the progeny. As the Urochloa accessions analyzed in this study represent only 3 of 31 regions of Tanzania, collecting Urochloa germplasm from a wider geographical area is necessary to catalog the genetic variation of Urochloa in the country.

Notes

Acknowledgements

This project was supported by the BecA-ILRI Hub through the Africa Biosciences Challenge Fund (ABCF) Program. The ABCF Program is funded by the Australian Department for Foreign Affairs and Trade (DFAT) through the BecA-CSIRO partnership; the Syngenta Foundation for Sustainable Agriculture (SFSA); the Bill & Melinda Gates Foundation (BMGF); the UK Department for International Development (DFID); and the Swedish International Development Cooperation Agency (Sida). The support of Asheber Tegegn in collecting experimental materials from Field Genebank of ILRI, Ethiopia, and Segolip Unit in genotyping is duly acknowledged.

Authors’ contributions

SOK, SRG, AD, AM, JH designed the study; SOK, CKM, MK conducted lab experiments; SOK, MK, SRG analysed the data; SOK, SRG wrote the manuscript, and AD, AM, JH reviewed the manuscript. SRG supervised the research project.

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© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Tanzania Livestock Research InstituteDodomaTanzania
  2. 2.The Bioscience eastern and central Africa - International Livestock Research Institute HubNairobiKenya
  3. 3.International Livestock Research InstituteAddis AbabaEthiopia

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