Literature DB >> 25889143

Microsatellite markers for Urochloa humidicola (Poaceae) and their transferability to other Urochloa species.

Jean C S Santos1, Mariana A Barreto2, Fernanda A Oliveira3, Bianca B Z Vigna4, Anete P Souza5,6.   

Abstract

BACKGROUND: Urochloa humidicola is a warm-season grass commonly used as forage in the tropics and is recognized for its tolerance to seasonal flooding. This grass is an important forage species for the Cerrado and Amazon regions of Brazil. U. humidicola is a polyploid species with variable ploidy (6X-9X) and facultative apomixis with high phenotypic plasticity. However, this apomixis and ploidy, as well as the limited knowledge of the genetic basis of the germplasm collection, have constrained genetic breeding activities, yet microsatellite markers may enable a better understanding of the species' genetic composition. This study aimed to develop and characterize new polymorphic microsatellite molecular markers in U. humidicola and to evaluate their transferability to other Urochloa species.
FINDINGS: A set of microsatellite markers for U. humidicola was identified from two new enriched genomic DNA libraries: the first library was constructed from a single sexual genotype and the second from a pool of eight apomictic genotypes selected on the basis of previous results. Of the 114 loci developed, 72 primer pairs presented a good amplification product, and 64 were polymorphic among the 34 genotypes tested. The number of bands per simple sequence repeat (SSR) locus ranged from 1 to 29, with a mean of 9.6 bands per locus. The mean polymorphism information content (PIC) of all loci was 0.77, and the mean discrimination power (DP) was 0.87. STRUCTURE analysis revealed differences among U. humidicola accessions, hybrids, and other Urochloa accessions. The transferability of these microsatellites was evaluated in four species of the genus, U. brizantha, U. decumbens, U. ruziziensis, and U. dictyoneura, and the percentage of transferability ranged from 58.33% to 69.44% depending on the species.
CONCLUSIONS: This work reports new polymorphic microsatellite markers for U. humidicola that can be used for breeding programs of this and other Urochloa species, including genetic linkage mapping, quantitative trait loci identification, and marker-assisted selection.

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Year:  2015        PMID: 25889143      PMCID: PMC4365966          DOI: 10.1186/s13104-015-1044-9

Source DB:  PubMed          Journal:  BMC Res Notes        ISSN: 1756-0500


Findings

Background

Urochloa humidicola (Rendle) Morrone & Zuloaga (syn. Brachiaria humidicola (Rendle) Schweick.), commonly known as koronivia grass, is a perennial tropical grass native to eastern Africa that was introduced to Brazil in the 1950s [1,2]. U. humidicola is an apomictic polyploid species with variable levels of ploidy (6X–9X) [3-7]. In Brazil, the grasses of the genus Urochloa occupy 85% of the cultivated pasture areas [8]. U. humidicola is cultivated as forage in several tropical regions worldwide and is particularly recognized for its tolerance to poorly draining soils, seasonal flooding, and infertile acidic soils [9]. For this reason, this species has been largely exploited in the tropics as a forage option over other Urochloa grasses, mostly in the African savannas and similar environments, such as the Brazilian Cerrado [7]. The development and adoption of new U. humidicola cultivars with a broad genetic base are crucial for the diversification of forage pastures in the tropics, primarily because there are few cultivars of this species in Brazil (Tully, Llanero, and BRS Tupi). However, the development of new cultivars must be a dynamic process, providing cultivars with high nutritional value, increased biotic and abiotic resistance, and economic competitiveness. Molecular markers are important tools to the progress of breeding programs, and their utilization would favor a more dynamic development of new cultivars of this species. However, there is a lack of information about the U. humidicola genome. Indeed, little or nothing is known about the number of genes, distribution of gene families, abundance and diversity of retro-elements, QTL localization of traits of economic importance, genome colinearity with model species, or abundance of repetitive sequences. Molecular markers are widely used in the fingerprinting of cultivars, the detection of genetic diversity in evaluating population structure in the mapping genes of interest, and in the selection of elite genotypes in breeding programs. SSR markers, in particular, are often used due to their codominant and multi-allelic characteristics [10]; moreover, they are highly site specific and transferable to related species [11]. Some microsatellite markers have already been developed for U. humidicola [12,13] and have been used for germplasm diversity studies [7,13], with all of them from the same microsatellite-enriched library constructed from genotype H016. Moreover, our research group identified four different gene pools among U. humidicola accessions; genotype H031 was found to be completely different from all other accessions, which was verified by a population structure analysis and by the fact that 18.5% of the tested markers did not amplify in this accession [7]. As a large number of markers are necessary for molecular breeding programs, our goal was to isolate and characterize new polymorphic microsatellite markers for U. humidicola genotype H031 (accession 12) to ensure that its genome was well represented by the new set of markers and also different accessions that belong to different gene pools and to test the transferability of these markers to four other Urochloa species (U. brizantha, U. decumbens, U. ruziziensis, and U. dictyoneura). The results were compared with previously reported data [12,13].

Methods

The plant material for library construction and marker validation was obtained from young leaves from several Urochloa genotypes. For the first library (Lb-1) construction, a single sexual genotype (H031) was used. For the second library (Lb-2) construction, a pool of eight apomictic genotypes (H010, H013, H015, H034, H041, H043, H101, and H108) was used. For marker validation, 34 genotypes were selected, consisting of 20 U. humidicola germplasm accessions, six intra-specific hybrids, and eight Urochloa accessions, as represented by two different accessions from each of the following species: U. brizantha, U. decumbens, U. ruziziensis, and U. dictyoneura. These genotypes were selected based on the four gene pools found by a previous study [7], from which two genotypes were selected from each gene pool. All of the accessions used are from the Urochloa germplasm collection maintained at Embrapa Beef Cattle, Campo Grande, MS, Brazil. They have been personally identified by S. A. Renvoize, from the Royal Botanic Gardens, Kew, UK and their identity have been confirmed by C. B. do Valle when transferred to Brazil [9]. The annotation numbers, accession numbers (as recorded in Embrapa Beef Cattle (EBC) and Center for Tropical Agriculture (CIAT)), genotypes, and species identifications are shown in Table 1. Genomic DNA was extracted from freeze-dried leaf samples using the CTAB method [14]. The DNA samples were evaluated on a 1% agarose gel and quantified by comparison to known quantities of uncut λ phage DNA (Invitrogen, Carlsbad, CA, USA).
Table 1

Genotypes of and four species of the genus used for the characterization and transferability analyses of new microsatellite markers

AN CIAT BRA EBC Genotype Species
1161814821H004germplasm accession U. humidicola
2161824839H005germplasm accession U. humidicola
3168674863H006germplasm accession U. humidicola
4168714901H008germplasm accession U. humidicola
5168804952H010germplasm accession U. humidicola
6168824979H012germplasm accession U. humidicola
7168865011H013germplasm accession U. humidicola
8261415088H015germplasm accession U. humidicola
9261495118H016germplasm accession U. humidicola
10168774928H023germplasm accession U. humidicola
11168945070H030germplasm accession U. humidicola
12261465100H031germplasm accession U. humidicola
13264136131H035germplasm accession U. humidicola
14264326203H041germplasm accession U. humidicola
15168844995H044germplasm accession U. humidicola
16NANAH048germplasm accession U. humidicola
17NA1929H107germplasm accession U. humidicola
1867052208H112germplasm accession U. humidicola
1961331449H125germplasm accession U. humidicola
2063690370H126germplasm accession U. humidicola
21--20hybrid U. humidicola
22--45hybrid U. humidicola
23--184hybrid U. humidicola
24--215hybrid U. humidicola
25--264hybrid U. humidicola
26--320hybrid U. humidicola
2716162-B057germplasm accession U. brizantha
2816467-B166germplasm accession U. brizantha
2916499004481D009germplasm accession U. decumbens
3026300004707D028germplasm accession U. decumbens
3126163005568R102germplasm accession U. ruziziensis
3226174005614R104germplasm accession U. ruziziensis
3316186007889DT157germplasm accession U. dictyoneura
3416188007901DT159germplasm accession U. dictyoneura

NA: not available, AN: annotation number, CIAT: Center for Tropical Agriculture, BRA: codes from EMBRAPA, EBC: codes from EMBRAPA Beef Cattle.

Genotypes of and four species of the genus used for the characterization and transferability analyses of new microsatellite markers NA: not available, AN: annotation number, CIAT: Center for Tropical Agriculture, BRA: codes from EMBRAPA, EBC: codes from EMBRAPA Beef Cattle. Genomic DNA was restriction digested with Afa I (Invitrogen), enriched in microsatellite fragments using (CT)8 and (GT)8 probes, and then used to construct a microsatellite-enriched library following the protocol of Billotte et al. [15]. The enriched microsatellite fragments were cloned into pGEM-T (Promega, Madison, WI), and the ligation products were used to transform Escherichia coli XL1-Blue competent cells. All 94 clones from both libraries were sequenced with an ABI 377 automated sequencer (Applied Biosystems, Foster City, CA) using the BigDye terminator cycle sequencing kit (Applied Biosystems, Foster City, CA). The microsatellites were identified using MISA software [16]. Only mono-nucleotides with twelve or more repeats, di-nucleotides with six or more repeats, tri-nucleotides with four or more repeats, and tetra-, penta-, and hexa-nucleotides with three or more repeats were considered. Primer pairs were designed using the Primer Select 5.01 software (DNASTAR Inc.) and the Primer3Plus software [17]. Polymerase chain reactions (PCRs) were carried out as previously described [12]. The amplification products were resolved by electrophoresis through 3% agarose gels prior to vertical electrophoresis through 6% denaturing polyacrylamide gels. The gels were then silver stained [18], and the product sizes were determined by comparison to a 10-bp DNA ladder (Invitrogen, Carlsbad, CA). Polyploid microsatellite genotyping is difficult due to the closeness of fragment sizes, stutter peaks observed and allele overlap due to multiple alleles of the same size. Few methods have been developed to overcome allele overlapping and estimate the allele frequencies, such as the estimation of alleles based on the electropherogram peak ratios [19] or the statistical estimation of allele frequencies [20]. However, for the present study work, we restricted the project to describe the new SSR markers, which were visually scored based on the presence (1) or absence (0) of a band in the polyacrilamide gels for each of the Urochloa genotypes. PIC (Polymorphic Information Content) [21] and DP (Discriminatory Power) [22] values were calculated to estimate polymorphisms at each locus. The microsatellite scores for the 34 individuals were evaluated using a model-based method with Bayesian clustering approach in STRUCTURE software version 2.2 [23-25]. The admixture model was tested with 200,000 replicates for burn-in and 100,000 replicates for Markov Chain Monte Carlo (MCMC) processes through ten iterations (runs). The numbers of clusters (K) were tested from 2 to 20. The optimal number of clusters was estimated using the ΔK value, as previously described [26], and the final graphs were visualized using the STRUCTURE HARVESTER software [27]. The individuals were grouped into clusters according to the association coefficient (Q) proportion of each allelic pool in an individual. A joint analysis (Lb-c) was performed with the data from the polymorphic loci derived from the new libraries Lb-1 and Lb-2. Data from a previous study [12] that used SSRs developed from accession 9 (H016) were used to compare the three libraries. The data were reanalyzed under the same parameters as those used for the new libraries, resulting in Lb-3. Another joint analysis (Lb-ct) was performed with data from the three libraries together (Lb-1, Lb-2, and Lb-3). The results obtained by STRUCTURE software were permuted by CLUMPP software [28], and the figures were generated using DISTRUCT software [29].

Results

Microsatellite enrichment success for the U. humidicola DNA libraries was 79.0% for Lb-1 and 61.2% for Lb-2. From all of the sequenced clones, 183 microsatellites were identified. Di-nucleotide repeats were the most abundant class of microsatellites detected, representing 76.4% and 72.7% of the loci for Lb-1 and Lb-2, respectively, followed by mono-nucleotide and tetra-nucleotide repeats. Perfect microsatellites were the most abundant (Table 2).
Table 2

Characterization of new microsatellite-enriched libraries from

Library Lb-1 Lb-2
Total clones sequenced86.080.0
Sequences containing microsatellites (%)79.061.2
Total number of SSRs identified106.077.0
Type of repeat (%)
By nucleotide stringMono-nucleotides12.76.5
Di-nucleotides76.472.7
Tri-nucleotides1.95.2
Tetra-nucleotides5.611.6
Penta-nucleotides2.83.9
Hexa-nucleotides0.90.0
By formPerfect79.180.6
Imperfect9.31.6
Perfect Compound5.89.7
Imperfect Compound5.88.1
Characterization of new microsatellite-enriched libraries from Of the 114 SSR primer pairs designed and tested, 72 were successfully amplified in U. humidicola genotypes, and 64 SSRs were polymorphic. A description of the number of alleles per locus and PIC and DP values for both the U. humidicola accessions and Urochloa accessions is presented in Table 3. The loci BhUNICAMP68 to BhUNICAMP108 are derived from Lb-1, and the loci BhUNICAMP109 to BhUNICAMP139 are derived from Lb-2. Based on the allelic frequencies estimated by STRUCTURE software, 36.43% of the alleles are rare (frequency < 0.05), 60.06% are intermediate alleles (0.05 < frequency < 0.30), and 3.50% are abundant alleles (frequency > 0.30).
Table 3

Characterization of the 72 polymorphic SSR markers developed for

SSR locus GenBank accession number Repeat motif Ta (°C) a Primer sequences (5′-3′) Urochloa species accessions* U. humidicola accessions**
Size range (bp) A b PIC c A b PIC c DP d
BhUNICAMP068KM068303(CACACC)4(CA)17 58.5F_CCACAAACGTGAACACATACA R_AGGGACGGAAACACCCTTAG226-261100.87100.870.95
BhUNICAMP069KM068304(TC)25 64.5F_GAGGAACTCCTTTGGGTAGA R_TTCAGAGAGAGGATGGTATAGAG285-30020.3620.360.58
BhUNICAMP070KM068305(GT)9 65F_CCCCGGTCTCGACCTATC R_GAGGCTGCCCCCTTACTC174-214120.8460.780.54
BhUNICAMP071KM068306(AC)11 65F_CGCAACGAAGCTCCAATAG R_CGATCGCAAGCGTGTATCTA160-228110.86110.860.94
BhUNICAMP072KM068307(GT)7 56.5F_CCCCATGTAAACAACCGTAGA R_CCATGGTTGACCGCTAGAA174-18630.5630.560.85
BhUNICAMP073KM068308(TG)10 60F_TGAACATGTGAATGCCCACT R_ATTGCAGGATGCGGACTCTA240-304100.85100.850.94
BhUNICAMP074KM068309(CT)6 58.5F_ACGAACGATCCGACCAACTA R_TGCTTACGAGACGGCATAGA231-25570.8170.810.92
BhUNICAMP075KM068310(TC)22 50F_TGAATGCTTTTGTCCTGGTATC R_ACGTGCAGCAGCAACAGTA148-236280.95240.950.98
BhUNICAMP076KM068311(AC)18 51.5F_CCGATGGTCAAAGGTCAGTT R_GGTGGGCATATACCATGTTT206-234100.84100.840.66
BhUNICAMP077KM068312(AC)7 65F_CGGGAAGTCCTACTCCGTAA R_GGAGCTCAAGGTAGGGATTG212-23080.8380.830.93
BhUNICAMP078KM068313(GT)7 58.5F_ACCAGTGCACGTCTGAAAGA R_CGATCACTGCTGCGTCATA216-21820.3520.350.52
BhUNICAMP079KM068314(AG)12G(GA)17 62.5F_GGATTGAAAGTTGGAGCACA R_GCATGCTGTGAAGGAGGTTA180-222170.92170.920.96
BhUNICAMP080KM068315(GA)26 50F_CAAGCCTCTTCATGCAAGTAAC R_TGTCATACCCCCATGATTAAGA176-230220.93210.930.93
BhUNICAMP081KM068316(AGC)5ACAAT(CA)11 55F_CTGGCATGGGTCCCTTTAC R_TCTTCTTCCTCCAGCCACAT160-17950.7550.750.95
BhUNICAMP082KM068317(CA)23 60F_TTGCCGGGAACAGTTATACA R_GAAGCTCTATCAAACAGCCCT157-19290.8290.820.92
BhUNICAMP083KM068318(AG)22 56.5F_AAACATGCACCGTCATAACT R_GGGCTTGATTCATTTGTTA152-19060.6840.680.77
BhUNICAMP084KM068319(TG)15 65F_GGCGAAGACCATACCCTGTA R_TGCTGGTGGAAGAAGATGAA159-18290.8090.800.96
BhUNICAMP085KM068320(GT)9 60F_CGATTTATCGACGACCGAGT R_CCTTACTCGCAGGTCTGTCC158-17150.7650.760.64
BhUNICAMP086KM068321(TC)19 65F_AGTTGAATGGGCTGAACCAT R_TGCACTTCCAGGATCAGACA238-326100.82100.820.93
BhUNICAMP087KM068322(GT)10 50F_GGCCATTTCTAGCCAAACAA R_CCTTACTCGCAGGTCTGTCC24010.0010.000.00
BhUNICAMP088KM068323(TG)12 65F_AGAGGTTCCATGGACATTGC R_CTCATCAACAGACGCCTGAA17810.0010.000.00
BhUNICAMP089KM068324(AC)7 65F_CCGGATAGAAGGTCTGAACG R_AGTCGTCGAAGCGAGCTCTA17510.0010.000.00
BhUNICAMP090KM068325(CA)10 65F_CAGAGTAAGCTTCCGGGACA R_CGATTTATCGACGACCGAGT200-300120.85110.850.91
BhUNICAMP091KM068326(AC)8 65F_CTTGTGCCACTTCCACCTTT R_TCGTGTGGACACTTCCTCTG120-15090.8390.830.95
BhUNICAMP092KM068327(TG)6 65F_ATGCCTTGCTCCCACTAACA R_TAAATGCTCCAGCGACCTTC135-168110.85110.850.91
BhUNICAMP093KM068328(AAG)4 65F_GGAGCGCTAATTTCGTTCAG R_CCTCCGTTCTCGCTAATGAC23010.0010.000.00
BhUNICAMP094KM068329(TG)7 65F_TTGGAGCTTTCCCTAGCTCA R_GAACAAGAAGGGAGGAAGCA272-29040.3140.310.39
BhUNICAMP095KM068330(TC)16(TG)14 65F_GGGTTGGCCTACACACTGAT R_CGCACGACATTGATACCTTG268-32060.7560.750.92
BhUNICAMP096KM068331(TC)8TT(TC)40 65F_TGTTCTGCTCACTGGTTTGG R_TCAGCTCTCTACGGCTGGAT157-255110.87110.870.95
BhUNICAMP097KM068332(GT)6 65F_GCGAGCTACCGAGGTATTTG R_ACGTCAATGTCGAGCTTCCT129-14850.6950.690.80
BhUNICAMP098KM068333(GT)10(G)18 65F_GGACTGGTCGTCTTTCCATC R_GCTTTCTGCAAGCGGTAGAT250-31290.8590.850.95
BhUNICAMP099KM068334(CA)10TG(GA)10 65F_TTTGTGGCACCTGCAGAATA R_CGCTTCGTGCTGACAGATTA124-174160.91160.910.99
BhUNICAMP100KM068335(TG)12 65F_GCGCCATGGTTTCATCTATT R_GGTGGTTCCTCGTGTGAGAT178-21970.7970.790.98
BhUNICAMP101KM068336(TG)28 65F_GGTAAAGAAGGGCCGGACT R_GCATGGCATGTTCCTACTGA128-184140.89120.890.97
BhUNICAMP102KM068337(GCGA)4 65F_TGGTGGGCTCCACTATCTCT R_TCCGCCATCTCTCCTCTCT224-260120.89120.890.94
BhUNICAMP103KM068338(CT)22 65F_AGCTCTCCCGCCTCTCTCT R_CATCCACACCGTCTCTCTCA100-156140.91140.910.96
BhUNICAMP104KM068339(TG)26 60F_ACGACGACCTAATGGGTGAA R_ACCCAGCAACAAATCTCGTC190-274150.87130.870.96
BhUNICAMP105KM068340(AC)10ATACACACACAC(AG)53 50F_CTCCATCACGTGCTTGCTAA R_GTGTGATCGGCTGGAGATTT100-176300.93290.930.98
BhUNICAMP106KM068341(TTTGT)3 50F_GCTGTTCGGAGAGGAATCTG R_ATGAGAGGAGGGAAGGAAGG135-15580.7970.790.91
BhUNICAMP107KM068342(GA)18 50F_GGGTCAGTGTCGTCTCAGTTT R_CAGATTCCTCTCCGAACAGC118-190260.94260.940.98
BhUNICAMP108KM068343(CT)16 65F_TTGCCATTACTGGATCTGGA R_GCGCCACCCATAACTTAAA112-160140.85130.850.94
BhUNICAMP109KM068344(GT)9 60F_AGCGAGTCAAGCACAAGGAT R_GGGTCCAATCTCCCTCTCTC186-22690.8290.820.93
BhUNICAMP110KM068345(TG)8 65F_TCTGCATCCACTAGGCTCAG R_TCCTCCACCTTCTTTCCGTA148-16440.3940.390.46
BhUNICAMP111KM068346(TG)27 65F_AACTCCGACTATCTTCCAGTTGA R_AATGCATGGGTAGGATCTGC250-330150.89150.890.96
BhUNICAMP112KM068347(AC)26 65F_GACCAAACCCTCCGAAGTTA R_GGTTGCAACTACACGACCAG246-300100.81100.810.94
BhUNICAMP113KM068348(CGTG)3 63F_AACTTCGAGAGGTTCGTCCA R_ACCGGCAATCTATCCGTGT144-17930.4530.450.51
BhUNICAMP114KM068349(CT)21 63F_TATACAAGGCGCATCCACAA R_GCTCTTTCCTCACGCTGTTC200-266150.89150.890.96
BhUNICAMP115KM068350(AC)27(AT)7 60F_CTTCCTGCCAATAAGCGAAG R_CGAGCTTCCAGATTCTTTGG24010.0010.000.00
BhUNICAMP116KM068351(TG)8 65F_CTCCGCACCGCTTAAATTAG R_GTTGGAAATGGTGCTTCCAC288-30630.5230.520.62
BhUNICAMP117KM068352(TGA)7 65F_CCAACTGAACGGCCATACTT R_CCCACAAAGGAACCCTGAT290-30040.6140.610.77
BhUNICAMP118KM068353(AG)9 50F_CTGCATAACTTTCAGCCATCTC R_TTGGCACAACTGGAACGTAG14910.0010.000.00
BhUNICAMP119KM068354(AAG)7 65F_AAGGGCGTGATGTTCTGAAG R_AGGCCAAACGAATTTCTCAA189-20440.6640.660.82
BhUNICAMP120KM068355(AT)8ACACACACACG(CA)9 65F_TCCAGCAGTGTGTTCCTCAG R_ACCAGGAGTGCATAGCCAAG190-20060.7160.710.75
BhUNICAMP121KM068356(TC)12 65F_CGCTACTGCTGCACACAAAT R_CTGAGTGCGCCGTATGTTTA170-19560.7160.710.92
BhUNICAMP122KM068357(GT)15 65F_AGGAAGGCTCGCACTCACTA R_CCAAAGGCGGTGGTTAGATA200-315140.90140.900.95
BhUNICAMP123KM068358(TTA)4 65F_CCAAACTCTAGCTTTCACAGCA R_TTGGATCCACGTCAAACAAG28010.0010.000.00
BhUNICAMP124KM068359(AG)23 65F_TTGGAGTTGCTGGGCTATTT R_GAACCAAGCATAAGGCAACA218-320120.85100.850.95
BhUNICAMP125KM068360(GT)8GAATGTGTGT(GA)7 65F_TGTTATCAGTGCAGGTGTTGG R_GAGGCTGACGAAAGCTCAAC258-28070.8170.810.93
BhUNICAMP126KM068361(AC)10 65F_GGGAACCCAGGGTATCGTAT R_CTCTCCCAGCGTCTTTCCTT21010.0010.000.00
BhUNICAMP127KM068362(GT)6 65F_CCACCATTGCTTCCAGAGTAA R_ATTCGCCTCTCCTAGCACAA272-32070.6970.690.91
BhUNICAMP128KM068363(GA)3765F_TGCCTGGAGACTGAGAAAGG R_CCTGCAGCAGACCTTCACAT150-240170.91170.910.98
BhUNICAMP129KM068364(AC)7ATGAA(CATG)3(CA)22 63F_TGTGTTTAGACCGCCAACAA R_TTATCGGCTCCCATTCACTC207-310110.84100.840.95
BhUNICAMP130KM068365(AC)7 63F_ACGCAGGAGAACTGCGTATC R_ATGGGATCCAACCGAACATA236-300120.79110.790.87
BhUNICAMP131KM068366(AC)7(A)16 60F_CATCAGATGCCTCAAACAGC R_GCAGGTGTGCAGCAAATAGA184-238140.87140.870.93
BhUNICAMP132KM068367(TG)7(T)29 50F_TCACTAGTGCGTCTGCTGCT R_GCACTCCATTGCAGACCTAAG184-19640.5330.530.63
BhUNICAMP133KM068368(TG)10 50F_CATGACTTATGTCCTTGGTGGA R_TCGACAGTGGAGCCACAA114-162190.89160.890.97
BhUNICAMP134KM068369(CCGG)3 60F_CAAACGGAGGAAGAGAGACG R_GGTGTCAATGCAGCCAAGTA114-13590.7550.750.83
BhUNICAMP135KM068370(AG)27 65F_CATGAGCCATCTCGTTGTTG R_TGCATTGACTTGACGTCTCC176-260140.9090.900.91
BhUNICAMP136KM068371(AC)9(ACAA)3 50F_TCCTGGTAAAGTTCCTCGTCA R_ACAACAATGCACGTCGAGAA225-29070.7560.750.93
BhUNICAMP137KM068372(GA)23 65F_TAGGTTTGGGTGGCACTAGG R_CTCCATGCTGCGTTGCTAT258-320110.8590.850.91
BhUNICAMP138KM068373(T)12 60F_TGCTCATGTGGGTCACATTT R_TGTGTGCCTGTGTGATGCTA270-28850.7050.700.95
BhUNICAMP139KM068374(AAAAG)3 65F_TCCTTTCTTTGAGCCGAGAG R_GCTGATGCTGACATCAAGGA248-29460.6750.670.97
Total average10.260.779.600.770.87
Lb-1 average11.050.7910.480.790.87
Lb-2 average9.180.758.400.750.86

*Species evaluated: Urochloa humidicola (Rendle) Morrone & Zuloaga, Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster, Urochloa decumbens (Stapf) R.D. Webster, Urochloa dictyoneura (Figure & De Not.) Veldkamp, Urochloa ruziziensis (R. Germ. & C.M. Evrard) Crins.

**Hybrids included.

Amplification temperature (°C).

Maximum number of alleles observed.

Polymorphism Information Content.

Discrimination Power.

Characterization of the 72 polymorphic SSR markers developed for *Species evaluated: Urochloa humidicola (Rendle) Morrone & Zuloaga, Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster, Urochloa decumbens (Stapf) R.D. Webster, Urochloa dictyoneura (Figure & De Not.) Veldkamp, Urochloa ruziziensis (R. Germ. & C.M. Evrard) Crins. **Hybrids included. Amplification temperature (°C). Maximum number of alleles observed. Polymorphism Information Content. Discrimination Power. A survey of the potential transferability of the microsatellite markers from U. humidicola to other Urochloa species identified that 61.11% of the 72 markers resulted in amplified PCR products in at least one U. brizantha genotype, 58.33% were amplified in U. decumbens, 59.72% were amplified in U. ruziziensis, and 69.44% were amplified in U. dictyoneura. The number of successfully amplified genotypes per number of genotypes tested per species is shown in Table 4.
Table 4

Cross-amplification of the 72 SSR markers among other species

Transferability a,b
SSR locus U. brizantha U. decumben U. ruziziensis U. dictyoneura
BhUNICAMP0680/20/20/20/2
BhUNICAMP0690/20/20/20/2
BhUNICAMP0702/22/22/22/2
BhUNICAMP0710/20/20/22/2
BhUNICAMP0721/21/20/21/2
BhUNICAMP0730/20/20/22/2
BhUNICAMP0740/20/20/20/2
BhUNICAMP0752/22/22/22/2
BhUNICAMP0762/22/22/21/2
BhUNICAMP0772/22/22/22/2
BhUNICAMP0781/20/21/21/2
BhUNICAMP0792/22/22/21/2
BhUNICAMP0802/21/22/21/2
BhUNICAMP0810/20/20/20/2
BhUNICAMP0822/20/21/21/2
BhUNICAMP0831/21/21/22/2
BhUNICAMP0842/22/22/22/2
BhUNICAMP0852/22/22/22/2
BhUNICAMP0862/22/22/22/2
BhUNICAMP0872/22/22/22/2
BhUNICAMP0882/22/22/22/2
BhUNICAMP0890/20/20/20/2
BhUNICAMP0902/22/22/22/2
BhUNICAMP0910/20/20/22/2
BhUNICAMP0920/20/20/22/2
BhUNICAMP0930/20/20/20/2
BhUNICAMP0942/22/21/22/2
BhUNICAMP0950/20/20/20/2
BhUNICAMP0962/22/21/22/2
BhUNICAMP0972/22/22/22/2
BhUNICAMP0980/20/20/20/2
BhUNICAMP0990/20/20/20/2
BhUNICAMP1000/20/20/20/2
BhUNICAMP1012/22/22/22/2
BhUNICAMP1020/20/20/20/2
BhUNICAMP1032/21/22/22/2
BhUNICAMP1042/22/22/22/2
BhUNICAMP1052/22/22/22/2
BhUNICAMP1062/22/22/22/2
BhUNICAMP1072/22/22/21/2
BhUNICAMP1082/22/22/21/2
BhUNICAMP1092/22/22/22/2
BhUNICAMP1102/22/22/22/2
BhUNICAMP1112/22/22/22/2
BhUNICAMP1122/22/22/22/2
BhUNICAMP1130/20/20/20/2
BhUNICAMP1140/20/20/20/2
BhUNICAMP1150/20/20/20/2
BhUNICAMP1162/22/22/22/2
BhUNICAMP1170/20/20/22/2
BhUNICAMP1180/20/20/20/2
BhUNICAMP1190/20/20/20/2
BhUNICAMP1202/22/22/22/2
BhUNICAMP1212/22/22/22/2
BhUNICAMP1220/20/20/20/2
BhUNICAMP1230/20/20/22/2
BhUNICAMP1242/22/22/20/2
BhUNICAMP1250/20/20/20/2
BhUNICAMP1262/22/22/22/2
BhUNICAMP1270/20/20/20/2
BhUNICAMP1280/20/20/20/2
BhUNICAMP1292/22/22/20/2
BhUNICAMP1302/22/22/22/2
BhUNICAMP1312/22/22/22/2
BhUNICAMP1320/20/20/22/2
BhUNICAMP1332/22/22/22/2
BhUNICAMP1342/22/22/22/2
BhUNICAMP1352/22/22/22/2
BhUNICAMP1362/22/21/22/2
BhUNICAMP1372/22/22/22/2
BhUNICAMP1380/20/20/22/2
BhUNICAMP1392/22/22/22/2
Total44424350
Amplification %61,1158,3359,7269,44

Number of successfully amplified genotypes/Number of tested genotypes.

Nomenclatural classification: Urochloa humidicola (Rendle) Morrone & Zuloaga, Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster, Urochloa decumbens (Stapf) R.D. Webster, Urochloa dictyoneura (Figure & De Not.) Veldkamp, Urochloa ruziziensis (R. Germ. & C.M. Evrard) Crins.

Cross-amplification of the 72 SSR markers among other species Number of successfully amplified genotypes/Number of tested genotypes. Nomenclatural classification: Urochloa humidicola (Rendle) Morrone & Zuloaga, Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster, Urochloa decumbens (Stapf) R.D. Webster, Urochloa dictyoneura (Figure & De Not.) Veldkamp, Urochloa ruziziensis (R. Germ. & C.M. Evrard) Crins. The population structure analysis based on SSR allelic data showed differentiation among the U. humidicola accessions, hybrids, and other Urochloa species. The STRUCTURE analysis for Lb-1 and Lb-2 and the joint analysis of data from both libraries (Lb-c) showed K = 18, K = 17, and K = 17 allelic pools, respectively, with each one represented by a different color in Figure 1. Clusters I to V were composed of U. humidicola accessions. Cluster VI was composed of two U. humidicola accessions (accessions 9 and 12) and six hybrids derived from a controlled cross between these two accessions. The other Urochloa species were grouped into Clusters VII and VIII for Lb-1 and Lb-c and in Cluster VII for Lb-2.
Figure 1

Analysis performed with STRUCTURE software. Lb-1: Library constructed from a sexual accession (H031), Lb-2: Library constructed from a pool of eight apomictic accessions, Lb-3: Library constructed from an apomictic accession (H016) [12], Lb-c: Joint analysis of Lb-1 and Lb-2, Lb-ct: Joint analysis of Lb-1, Lb-2, and Lb-3. Each of the 34 genotypes is represented by a single column divided into colored segments with lengths proportional to each of the allelic pools inferred by K through Evanno method [24]. Each K is represented by a different color and Lb-1 presented K = 18, Lb-2 K = 17, Lb-c K = 17, Lb-3 K = 15, and Lb-ct K = 18. The individuals were grouped into clusters according to the Q proportion of each allelic pool in an individual. Eight clusters were identified for Lb-1, Lb-c, Lb-3, and Lb-ct (I to VIII) and seven clusters for Lb-2 (I to VII). The left scale indicates the association coefficient (Q) for the assignment of genotypes into groups. The genotypes are named according to the annotated numbers listed in Table 1.

Analysis performed with STRUCTURE software. Lb-1: Library constructed from a sexual accession (H031), Lb-2: Library constructed from a pool of eight apomictic accessions, Lb-3: Library constructed from an apomictic accession (H016) [12], Lb-c: Joint analysis of Lb-1 and Lb-2, Lb-ct: Joint analysis of Lb-1, Lb-2, and Lb-3. Each of the 34 genotypes is represented by a single column divided into colored segments with lengths proportional to each of the allelic pools inferred by K through Evanno method [24]. Each K is represented by a different color and Lb-1 presented K = 18, Lb-2 K = 17, Lb-c K = 17, Lb-3 K = 15, and Lb-ct K = 18. The individuals were grouped into clusters according to the Q proportion of each allelic pool in an individual. Eight clusters were identified for Lb-1, Lb-c, Lb-3, and Lb-ct (I to VIII) and seven clusters for Lb-2 (I to VII). The left scale indicates the association coefficient (Q) for the assignment of genotypes into groups. The genotypes are named according to the annotated numbers listed in Table 1. The STRUCTURE analysis for Lb-3 and Lb-ct showed K = 15 and K = 18 allelic pools, respectively (Figure 1), classified in the same clusters as for Lb-1 and Lb-c.

Discussion

In the present study, we described 72 new SSRs for U. humidicola, 64 of which are polymorphic. Along with the 67 previous developed SSRs [12,13], these markers contribute to the genetic breeding of the species and other species of the genus Urochloa in efforts to obtain new cultivars and better understanding of the species genetic, through genetic mapping, marker-assisted selection, genome sequencing and synteny. The increased occurrence of di-nucleotide motifs for Lb-1 and Lb-2 is in accordance with the enrichment of both libraries with (CT)8 and (GT)8 probes. In addition, Morgante et al. [30] reported a higher occurrence of microsatellites with di-nucleotide motifs in plants, which may have been a contributing factor in our observation. Among the microsatellites analyzed, 88% had a polymorphism among the evaluated genotypes. The most informative loci in this panel of SSRs were those with the highest PIC and DP values (BhUNICAMP075 and BhUNICAMP107). Locus BhUNICAMP094 showed the lowest values for PIC and DP, at 0.3165 and 0.3969, respectively, even though it was amplified in all the Urochloa species evaluated. This also occurred with the BhUNICAMP030 locus [12]. Both loci may be useful markers for studies in Urochloa because it may be the result of a conserved region among the species studied herein. Monomorphic loci may be useful in other studies. The transferability rates of the loci from U. humidicola to four other species were very similar. Although these results were not highly variable, U. dictyoneura presented the highest transferability, corroborating the genetic closeness between U. dictyoneura and U. humidicola, as has been previously described [2,31] and the results obtained in another study [13]. For the population structure analysis, different numbers of allelic pools [K] were observed for all analyses. However, the individual composition presented in each cluster was maintained into Lb-1, Lb-c, Lb-3, and Lb-ct analyses, but for Lb-2 analysis, the Clusters VII and VIII were grouped into Cluster VII. The genotypes of the species U. brizantha, U. decumbens, and U. ruziziensis were grouped into the same cluster in all the analyses. However, the U. dictyoneura genotypes were grouped separately from the other species for all the analyses, except for Lb-2, with the four species grouping into Cluster VII. In all analyses, Cluster VI included accessions 9 and 12, and six hybrids derived from crosses between these two accessions grouped together. However, in a previous study, the progenitors did not group together with the hybrids [13], as only runs from K = 1 to K = 10 were performed. These hybrids are part of an F1 population that is being mapped with the SSRs described in this study and previously published [12,13]. Although some discrepancies were found among the three libraries (Lb-1, Lb-2, and Lb-3), the set of loci belonging to each was able to satisfactorily differentiate the accessions. Comparing the three libraries developed, Lb-1 presented the highest number of allelic pools, which may be correlated to the usage of the accession H031, a highly diverse genotype, as described by [7]. The genotype used for the enriched library construction directly influences the results. The joint analysis of the three libraries (Lb-ct) would be the most recommended way to differentiate among accessions, because it uses loci derived from many different genotypes, conferring a greater reliability of the observed results. These markers are immediately useful for U. humidicola breeding programs, aiding in areas such as the construction of linkage and QTL maps, gene flow and mating system evaluation, and marker-assisted selection.

Availability of supporting data

The datasets supporting the results of this article are included in the article.
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