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ScienceDirect Energy Procedia 47 (2014) 196 – 203

Conference and Exhibition Indonesia Renewable Energy & Energy Conservation [Indonesia EBTKE CONEX 2013]

Genetic Diversity of DxP Population Yield Component in Oil Palm's

Paternal Half-Sib Family Based on Microsatellite Markers Nida Wafiqah Nabila M. Solina,*, Sobira, Nurita Toruan-Mathiusb a Departmen of Agronomy and Horticulture, Bogor Agricultural University 16680, Indonesia Plant Production and Biotechnology Division, PT SMART Tbk. Sinarmas Land Plaza, 2 nd Tower, 10th Floor. Jakarta 10350, Indonesia

b

Abstract Oil palm is a commodity that has potential to be transferred to biodiesel. This study is aimed to elucidate genetic diversity of four population based on yield component, using 27 microsatellites. Analysis of banding pattern resulted average polymorphic loci and PIC are 52.78% and 0.51. One, three, one and two markers specific to the group OB, BN, OY and FFB, respectively. Cluster analysis revealed level of genetic diversity and similarity at 0.56 and 0.78-0.98, which is succesfully separated the four population, as well as confirmed by PCoA, indicated that can be used to elucidate specific markers corresponding to populations used.

©©2014 Elsevier Ltd. Ltd. 2014 The The Authors. Authors. Published by Elsevier Selection and and peer-review peer-review under responsibility Selection responsibility of ofthe theScientific ScientificCommittee CommitteeofofIndonesia IndonesiaEBTKE EBTKEConex Conex2013. 2013 Keywords: Elaeis guineensis Jacq.; half-sib population; population grouping; specific markers; microsatellite

Nomenclature OB BN OY FFB PCoA CPO PCR SSR PIC

Oil to Bunch Bunch Number Oil Yield Fresh Fruit to Bunch Principal Coordinate Analysis Crude Palm Oil Polymerase Chain Reaction Simple Sequence Repeat Polymorphism Information Content

1.

Introduction

Oil palm (Elaeis guineensis Jacq.) is an agricultural commodity that has an important role in Indonesia, especially in the aspect of the domestic economy. Indonesia is currently the largest Crude Palm Oil (CPO) country producer in the world. Indonesia's CPO production reached 23,521,071 tons, with a land area of 9,074,671 [1]. In addition, Indonesia has an advantage as one of the potential countries to invest in the plantation and oil palm downstream industry. This is supported by the increasing ____________________ * Corresponding author. Tel.: +62-83198547546 E-mail address: [email protected]

1876-6102 © 2014 The Authors. Published by Elsevier Ltd.

Selection and peer-review under responsibility of the Scientific Committee of Indonesia EBTKE Conex 2013 doi:10.1016/j.egypro.2014.01.214

Nida Wafiqah Nabila M. Solin et al. / Energy Procedia 47 (2014) 196 – 203

demand for palm oil for food (edible oil), industrial (oleochemical), and alternative energy sources-based biodiesel [2]. The most detrimental properties of these oils are their high viscosity, low volatility, poor atomization and auto-oxidation [3]. Recently considerable attention in developing countries such as Malaysia, Indonesia and Thailand has been drawn to the production of biofuels from domestic, renewable resources [4]. biofuels from domestic, renewable resources [4]. Oil palm development is inseparable from the needs of the plant material, such as seeds that will largely determine the quality of production. The seeds can be obtained through plant breeding programs, both conventional and non-conventional. There are some obstacles in conventional breeding, it requires longer time and the selection of the target gene to be expressed in morphological traits is difficult to determine. The appearance of plant phenotype is not only determined by the genetic composition but also by the environmental factors. In addition, the low frequency of the desired individual in a population, makes it difficult for the selection to get statistically valid results, and the linkage gene between desirable trait and unwanted trait is difficult to separate when crossing [5]. Information related to a variety of morphological and genetic populations is needed to support the efforts on empowering the potential genetic selection program. Genetic information is very useful to provide complete information about the plant and to reflect the potential of each individual [6]. Due to the a perennial nature and long generative cycle of oil palm, conventional breeding can take several years. This greatly hampers rapid and efficient progress in the selection of individuals. Various molecular biology techniques are currently available to detect genetic variability and genetic similarity among individuals and can be used in various applications of breeding programs. Molecular markers is an excellent tool for breeders and geneticists to analyze the genomes of plants. Molecular markers can be used to detect genetic variation and the polymorphic traits are not influenced by the environment [7]. The ability of SSR markers are highly efficient to show the structure of the genetic diversity of the genus Elaeis according to the region of the origin [8]. Allelic diversity is also found in natural populations of E. guineensis in Africa [9]. SSR markers have a high degree of allelic variability, therefore SSR markers are powerful tools for genetic studies of the genus Elaeis, among others, for the identification of germplasm and genetic mapping of intra- or interspecific. Several reasons for the use of SSR molecular analysis are: (1) abundant, (2) with uniformly distributed, (3) highly polymorphic, (4) codominant, (5) rapidly generated by PCR, (6) relatively simple to be interpreted, and (7) easily accessed by other laboratories through the publication of the primary sequence [10]. Even [11] show that of the four molecular markers tested (RFLP, RAPD, AFLP and SSR), SSR markers have the highest information content (the ability to distinguish genotypes) to evaluate soybean germplasm compared with other molecular markers. The aim of this study is to determine the genetic diversity of populations DxP yield component in oil palm's paternal half - sib families based on microsatellite markers 2.

Materials and methods

2.1 Plant material and DNA isolation Plants used were samples of young leaves palm plant consisting 60 parents (Dura) selfing and 160 half-sib progeny plants (Dura x Pisifera) owned by one of the private company. Plants observed were 9 years old. Female parents are siblings (sibs) and both crossed with the same pollen. The results of both female parents selfing are available as samples in field that located in Riau. Total genomic DNA was obtained by grinding the sample using liquid Nitrogen, and then the samples were isolated using the Plant Genomic DNA GenElute Miniprep Kit (Sigma - Aldrich) following the manufacturer's instructions. The DNA quality is known by electrophoresis using 1 % agarose gel, and DNA quantity is estimated using a NanoDrop spectrophotometer HND 1,000 (NanoDrop Technologies Inc.), and the final concentration of DNA was diluted to 20 ng μL-1. 2.2 Selection of the population The populations associated with the production of oil palm plant populations were observed and analyzed to determine the level of population diversity. A total of four populations were observed, they are oil to bunch (OB), bunch number (BN), oil yield (OY), and fresh fruit to bunches (FFB). The observations were conducted during the 5 years. The results of the analysis on the variance and classification based on the lowest and the highest value of yield component become the basis for determining the selection of plants which are used in the SSR marker using Bulk Segregant Analysis (BSA) methods. Genetic material used in the marker selection is DNA group from each of 10 DNA plants from four yield component grouped based on highs and lows. A total of 50 microsatellite markers developed in the oil palm [8, 12], were screened for polymorphism testing.

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2.2.PCR amplification A total of 80 samples of selected progeny and 60 samples of Dura parents were evaluated using the Polymerase Chain Reaction (PCR) with 50 microsatellite markers in accordance with the amplification conditions reported by [8]. Polyacrylamide gel electrophoresis (PAGE) 6% w/v was used for the visualization of the PCR amplification product using staining method suggested by [13]. DNA bands obtained from the SSR loci were scored manually according to the method described by [14]. 2.3. Data analysis The analysis is based on the scoring results of the DNA bands in the acrylamide gel. The bands were manually scored as presence (1) or absence (0) bands. Then the data were exported as demanded by the software used. To determine the number of alleles and Polymorphism Information Content (PIC), the PowerMarker software V3.25 [15] were used. To calculate the effective number of alleles per locus (Ne), information index (I) observed heterozigosity (Ho), expected heterozigosity (He), fixation index, and Principal Coordinate Analysis (PcoA), GenAlex ver. 6,501 [16] were used. To create a phylogeny tree and to calculate the genetic distance between individuals in the group, the NTSyspc2.1 [17] was used. 3. Results and discussion 3.1. Microsatellite analysis and polymorphism The standard method of DNA isolation and PCR parameters evaluation for microsatellite amplification is the first phase of the study which involves the analysis of the four populations used. The marker selection is done by selecting the locus which differentiate the high and low group (Fig. 1). The polymorphic markers in each group of each locus were then tested for each individual in the group. The results from the 50 markers evaluated, there were 28 polymorphic marker used for subsequent analysis. 15 polymorphic marker contained in OB population, 18 marker in BN population, 11 marker in OY population, and 13 marker in FFB population.

(a) OY - the locus mEgCIR0521

(b) BN - the locus mEgCIR3890 Fig. 1. Amplification patterns obtained from the two microsatellite markers from the genetic material of palm oil (a) monomorphic loci, (b) polymorphic loci with 4 alleles. 10 loci at the left is an individual in the group with low yield, and 10 loci at the right is an individual in the group with high yield.

From the four populations observed, the percentage of polymorphic loci is, OB 53.57%, BN 64.29%, OY 39.29%, and FFB 46.43% with an average of 50.89 %. The polymorphism is an amplification description obtained from the DNA fragment differences which were observed and scored as presence or absence dealing with sequence differences indicating variation [18]. There are loci which can amplify only in particular population. These loci are expected to be used as a specific marker for these populations. One loci only amplify the population of OB is mEgCIR3543, three loci only amplify the population of BN are mEgCIR3574, mEgCIR3809, and mEgCIR0779, one loci only amplify the population of OY is mEgCIR3683, whereas 2 loci can amplify the population of FFB are mEgCIR3569 and mEgCIR3389. In addition, three loci found out in the 28 loci tested, which can amplify all the four populations, namely loci mEgCIR2144, mEgCIR2590, and mEgCIR3260 (Table 1). 3.2. Polymorphism Information Content (PIC) From the analysis using 28 marker on the four populations, it was found that the value of PIC obtained were between 0.36 to 0.70 (Table 1) with an average PIC value of 0.41. This value indicates that the SSR markers used quite informative to see the diversity among the four populations tested. However, this value is smaller than that obtained by [19] on oil palm parental population, ie from 0.58 to 0.82, and [20] who obtained the average PIC value 0.60 . PIC values are needed to select markers to distinguish between individuals. PIC quantification is based on the number of alleles generated by a marker and the frequency of each allele in the set of genotypes tested. Polymorphism value is determined by the frequency of allele occurrence [21].

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Nida Wafiqah Nabila M. Solin et al. / Energy Procedia 47 (2014) 196 – 203 Table 1 . The number of alleles and polymorphism information content (PIC) were evaluated in microsatellite. Locus mEgCIR3847 mEgCIR3574 mEgCIR0878 mEgCIR2518 mEgCIR2569 mEgCIR2427 mEgCIR0783 mEgCIR3683 mEgCIR0059 mEgCIR3869 mEgCIR3519 mEgCIR3639 mEgCIR0134 mEgCIR0046 mEgCIR3890 mEgCIR3389 mEgCIR3543 mEgCIR0779 mEgCIR2144 mEgCIR3555 mEgCIR3569 mEgCIR3809 mEgCIR3275 mEgCIR2590 mEgCIR3260 mEgCIR0801 mEgCIR0521 mEgCIR0326

Forward marker (5' - 3')

Reverse Marker (5' - 3')

CGTTAGTGTCGCTTATTATG AGAGACCCTATTTGCTTGAT CAAAGCAACAAAGCTAGTTAGTA GATCCCATGGTAAAGACT TAGCCGCACTCCCACGAAGC GAAGGGGCATTGGATTT GAATGTGGCTGTAAATGCTGAGTG GTAGCTTGAACCTGAAA TGCAGGGGATGCTTTTATT CCAATGCAGGGGACATT CCACTGCTTCAAATTTACTAG ACGTTTTGGCAACTCTC AGTTTGGGGCTTACCTG AGCCTTAGTATTTTGTTGAT GTGCAGATGCAGATTATATG GTCCATGTGCATAAGAGAG GTTCCCTGACCATCTTTGAG AATGCAGACCAAGCTAATCATATAC ACAAGGCTCTTCAAGAGAT CATCAGAGCCTTCAAACTAC AAGGCTTGGAGTTGAGGTAT CCTTGCATTCCACTATT GAAGCCTGAGACCGCATAGA GTAGTTAAGGGACTTGTAGTC AGGGCAAGTCATGTTTC TGGTTGGCAGGTATTATTAG GTGACTTTGGGCTGAAT GCTAACCACAGGCAAAAACA

AAATGAGGAAGCGTAAC GACAAAGAGCTTGTCACAC CAAGCAACCTCCATTTAGAT AAGCCTCAAAAGAAGACC CCAGAATCATCAGACTCGGACAG TACCTATTACAGCGAGAGTG AAGCCGCATGGACAACTCTAGTAA AGA ACC ACC GGA GTT AC CCCTTAATTCCTGCCTTATT GAAGCCAGTGGAAAGATAGT GCGTCCAAAACATAAATCAC ACTCCCCTCTTTGACAT CTTCCACGCACCCTCTC CCTCTGATTTGTCCTTTTGG CCTTTAGAATTGCCGTATC CTCTTGGCATTTCAGATAC GTCGGCGATTGATTAGATTC GTTCAGGTGATGGTGACTCAGATAG CCACTGCCAACACTAGTAC AGCCTGAATTGCCTCTC CACCATTGCATCATTATTCC AGTTCTCAAGCCTCACA TTCGGTGATGAAGATTGAAG AAGTCTCTTGTGCTGATACA TATAAGGGCGAGGTATT TTAGAGGCTGTGATGAGTTG ACAGCATCTCCAACTCTATC AAGCCGCACTAACATACACATC

Number of alleles on amplified population OB BN OY FFB 3 0 0 4 0 4 0 0 2 0 0 3 0 2 3 0 3 0 3 0 0 2 3 0 3 3 0 3 0 0 2 0 2 2 0 0 0 3 0 0 3 2 0 2 0 0 3 0 3 0 0 3 3 3 0 0 3 4 3 0 0 0 0 3 3 0 0 0 0 4 0 0 2 3 3 3 0 0 2 3 0 0 0 3 0 2 0 0 3 4 0 0 2 2 3 2 2 3 2 3 0 3 3 3 3 3 0 3 0 2 0 0

PIC 0.66 0.67 0.51 0.54 0.58 0.50 0.55 0.36 0.37 0.49 0.53 0.44 0.55 0.51 0.67 0.50 0.53 0.70 0.55 0.43 0.56 0.37 0.57 0.40 0.45 0.55 0.52 0.36

The value of the PIC classified into three classes, namely PIC > 0.5 as very informative, 0.25 > PIC > 0.5 as moderate and PIC 0.5, which means that these markers can be selected to study the diversity of oil palm. Table 2. The average number of alleles (Na), effective number of alleles (Ne) , information index (I), observed heterozigosity (Ho), expected heterozygosity (He) and fixation index (F) for each population. Pop

Na

Ne

I

Ho

He

F

Mean

2,67

2,31

0,88

0,82

0,55

-0,49

SE

0,13

0,11

0,05

0,05

0,03

0,06

Mean

2,83

2,37

0,89

0,80

0,55

-0,47

SE

0,19

0,16

0,06

0,05

0,03

0,08

OY

Mean

2,72

2,35

0,88

0,84

0,54

-0,50

SE

0,14

0,17

0,07

0,08

0,04

0,06

FFB

Mean

2,92

2,50

0,95

0,88

0,57

-0,49

SE

0,14

0,17

0,06

0,07

0,03

0,07

OB

BN

Ne is the measurement for effective alleles numbers derived from each populations. This is reciprocal or inverse value of the homozygosity. The higher the value of Ne, the more the individuals are heterozygous. The highest number of alleles per locus, is found in the population of FFB, which is 2.92 and the lowest is found in OB population which is 2.67. While the highest number of effective alleles are found in the population of FFB which is 2.49 and the lowest in OB population which is 2,30 (Table 2). This number is lower than that obtained by [24] (3.67), [25] (3.85), [20] (4.71), [8] (5.3), but higher than that obtained by [26] (1.9) and [14] (1.75). The low number of alleles in this diversity is due to the genetic material used in the study is a population of half-sibs, in which the Dura parents used are siblings (sibs) crossed with pollen from selected Pisifera. The genetic improvement efforts of oil palm narrows the genetic diversity, so the alleles obtained also less than before. [9] found that alleles of wild populations showed a decrease caused by many years selection on genetic material. This is described as the general trend of the genetic diversity loss due to genetic improvement of oil palm [27].

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In general, the fourth population indicates the average value of observed heterozygosity (Ho) is higher than the value of the average expectation of heterozygosity (He). This means that each population has a high heterozygosity . 3.3 Genetic diversity inter and intra population The results of PCoA four populations (Fig. 2) shows the information of the four groups based on their genetic similarity. These populations have a high genetic diversity in the group, but low genetic diversity between populations. OB population form his own group, just as population BN, OY and FFB. The percentage of variability is shown by the first three axes, namely 30.86 %, 29.57 % and 16.71 % . PCoA (Principal Coordinate Analysis) is a scaling or ordination method that starts with a matrix of similarities or dissimilarities between a set of individuals and aims to produce the low-dimensional graphical plots of the data, so that the geometric distance between the individuals in the plot reflects the genetic distance between them with minimal distortion. Aggregation of individuals in the plot as it would reveal a similar set of genetic individuals [28].

Fig. 2. Pricipal Coordinate Analysis ( PCoA ) of the four populations of oil palm.

From the results of PCoA on each population (Fig. 3), it can be seen that almost all individuals number 1-10 are separated from the individuals number 11-20. The individuals in these populations had previously been grouped according to high - low production based on phenotypic data. In general it can be seen that there is a cluster of 3-4 genotype. From the phenotypic data in the field, these individuals have higher production than others. It shows that SSR markers used are able, but not clearly enough to distinguish between the populations of high and low production.

Fig. 3. Principal Coordinate Analysis on each population tested using 28 microsatellite markers .


The dendogram of the result of SSR analysis using 28 polymorphic marker to all individuals in the group for oil production population shows a clustering corresponds to the four populations production namely OB, BN, OY, and FFB with the level of genetic diveristy 0.56 and the level of similarity 0.78-0.98 (Appendix A. 1.). This suggests that the markers used are able to show locus differences between production population being tested. As in the case of PCoA analysis, in general the results of the SSR analysis in each population based on the production population shows that the 28 markers used are able, but not clearly enough to classify individuals in the group according to the population production low and high. The possibility of markers used are not clearly enough to demonstrate the specificity in distinguishing population of high and low production, these results may be caused by the population production is a quantitative trait which is determined by many genes, so a specific locus is difficult to obtain to indicate the trait as the qualitative population have. Conclusion The average percentage of polymorphic loci is 50.89% with an average PIC value of 0.41%. The results of microsatellite analysis shows one marker specific to the group OB, three markers specific to the group BN, one marker specific to the group OY, and two markers specific to the group FFB. Cluster analysis revealed that genetic diversity level at 0.56 and the similarity level at 0.78-0.98, which is succesfully separated the four population based on the group, as well as confirmed by Principal Coordinate Analysis (PCoA). The study results indicated that the population grouping was accurate and can be used to elucidate specific markers corresponding to BN, OB, OY, and FFB populations. The results of PCoA analysis on each population SSR marker used are not clearly enough to separate some individuals based on high - low production. Similar results are obtained by using cluster analysis.

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Nida Wafiqah Nabila M. Solin et al. / Energy Procedia 47 (2014) 196 – 203 Appendix

A. 1. The dendogram of individuals genetic similarity in the group for four populations oil production based on SSR markers.


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