Mol Breeding (2014) 33:415–424 DOI 10.1007/s11032-013-9959-0
Oil palm (Elaeis guineensis Jacq.) linkage map, and quantitative trait locus analysis for sex ratio and related traits Kittipat Ukoskit • Vipavee Chanroj • Ganlayarat Bhusudsawang • Kwanjai Pipatchartlearnwong • Sithichoke Tangphatsornruang • Somvong Tragoonrung
Received: 8 November 2012 / Accepted: 13 September 2013 / Published online: 24 September 2013 Ó Springer Science+Business Media Dordrecht 2013
Abstract Sex ratio and shell-thickness type are among the main components determining yield in oil palm. An integrated linkage map of oil palm was constructed based on 208 offspring derived from a cross between two tenera palms differing in inherited sex ratio. The map consisted of 210 genomic simple sequence repeats (SSRs), 28 expressed sequence tag SSRs, 185 amplified fragment length polymorphism markers, and the Sh locus, which controls shellthickness phenotype, distributed across 16 linkage groups covering 1,931 cM, with an average marker distance of 4.6 cM. Quantitative trait locus (QTL) analysis identified eight QTLs across six linkage groups associated with sex ratio and related traits. These QTLs explained 8.1–13.1 % of the total phenotypic variance. The QTL for sex ratio on linkage group 8 overlapped with a QTL for number of
Electronic supplementary material The online version of this article (doi:10.1007/s11032-013-9959-0) contains supplementary material, which is available to authorized users. K. Ukoskit (&) V. Chanroj G. Bhusudsawang K. Pipatchartlearnwong Department of Biotechnology, Faculty of Science and Technology, Thammasat University, Rangsit Campus, Klong Luang, Pathumtani 12121, Thailand e-mail:
[email protected] S. Tangphatsornruang S. Tragoonrung National Center for Genetic Engineering and Biotechnology, 113 Phaholyothin Rd., Klong 1, Klong Luang, Pathumthani 12120, Thailand
male inflorescences. In most cases a specific QTL allele combination was responsible for genotype class mean differences, suggesting that most QTLs in heterozygous oil palm are likely to be segregating for multiple alleles with different degrees of dominance. In addition, two new SSRs were shown to flank the major Sh locus controlling the fruit variety type in oil palm. Keywords
Oil palm Sex ratio QTL mapping
Introduction Oil palm (Elaeis guineensis Jacq.) is an important oilproducing crop in Southeast Asia, Africa, and South America, with the highest potential oil yield per hectare per year. It has a haploid chromosome number of 16 (Maria et al. 1995) and an estimated genome size of 1,700 Mbp (Rival et al. 1997). It is monoecious and predominantly outcrossing, which leads to a high degree of heterozygosity. Oil palm trees can be classified into three types according to the shellthickness gene, Sh (Beirnaert and Vanderweyen 1941). dura oil palm (homozygous Sh?/Sh?) produces fruit with thick shells, thin mesocarp, and lower oil content, while the fruit of pisifera oil palm (homozygous Sh-/Sh-) have no shell. Further, most pisifera are naturally sterile and have no economic importance for palm oil production. tenera oil palm (heterozygous Sh?/Sh-), a hybrid between the dura and pisifera
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palms, has a thick mesocarp containing 30 % more mesocarp than the dura parent. Oil palm trees produce separate male and female inflorescences in leaf axils on the same palm in an alternating cycle of variable duration depending on genetic factors, age, and environmental conditions. The yield of oil palm is mainly a function of the number of harvested bunches of fruit per month and their weight (Corley and Tinker 2003). This is determined by sex ratio, fraction of aborted inflorescences, bunch failure resulting in absence of fruit set, and the ratio of mesocarp to the total dry mass of the bunch (Corley 1977). Oil palm sex ratio is defined as the ratio of females to total inflorescences (Corley and Tinker 2003). An apparent change in sex ratio may actually be due to a change in abortion rate, together with preferential abortion of female inflorescences. The sex ratios of individual palms are found to vary greatly. It seems probable that genetic factors are of chief importance in determining the differences observed in the sex ratios (Mason and Lewin 1925). Because oil palm is a perennial species, it is impossible to determine sex ratio until it is reproductively mature (4 years after germination). With the assistance of molecular markers, genetic linkage maps can be constructed and used to identify markers cosegregating with important traits. Characterization of sex ratio through the identification of linked markers would accelerate oil palm breeding programs by allowing marker-assisted selection (MAS) at the seed garden stage. Several genetic maps have been constructed for oil palm through the use of restriction fragment length polymorphism (Mayes et al., 1997; Singh et al. 2009), random amplified polymorphic DNA (Moretzsohn et al. 2000), amplified fragment length polymorphism (AFLP) (Singh et al. 2009; Billotte et al. 2005), and simple sequence repeats (SSR) (Billotte et al. 2005; Seng et al. 2011). Several quantitative trait locus (QTL) mapping reports have revealed the existence of major-effect QTLs for a number of traits in oil palm (Singh et al. 2009; Moretzsohn et al. 2000; Billotte et al. 2010; Rance et al. 2001). With the current availability of transferable SSR markers, it is possible to determine the synteny of QTLs. This can assist in designing a targeted search for new allelic variants in a QTL known both within and between oil palm species, increasing the opportunities for introgression of favorable alleles and elimination of
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unfavorable alleles while attempting improvement by hybridization. The current study reports the construction of an integrated genetic linkage map of tenera oil palm using expressed sequence tag simple sequence repeat (ESSR) and genomic SSR (GSSR) markers developed in-house using 454 GS-FLX pyrosequencing technology, published GSSR markers from another oil palm mapping study (Billotte et al. 2005), and AFLP markers. The QTLs associated with sex ratio and related traits were determined using the integrated maps constructed in the present study. The possible linkage phase relationships between markers and QTL for sex ratio were analysed.
Materials and methods Plant material A segregating population of 208 progenies, derived from the crossing of Clone B tenera and Clone D tenera at the Golden Tenera Limited Partnership, Krabi, Thailand, was field-planted in 2007 and used for linkage mapping. Clone B, the female parent, exhibited a high sex ratio. Clone B resulted from the cross between a Deli dura from Banting and a AVROS pisifera. Clone D, the male parent, had a low sex ratio, and resulted from the cross between a Ulu Remis Deli dura with a AVROS Ulu Remis. Although the two parents had close genetic backgrounds (as indicated by pedigree), their progeny showed a wide distribution of the sex ratio trait. The phenotypes for shell thickness consisted of 44 dura (homozygous thick-shell types), 108 tenera (heterozygotes), and 56 pisifera (homozygous shell-less types) fitting to a 1:2:1 segregation ratio for the co-dominant locus (v2 = 1.27; P = 0.53). A subset of ten random individuals and the parent plants were used for preliminary screening of polymorphism before markers were applied to the entire population. DNA was extracted from leaf samples from individual plants using the method of Gawel and Jarret (1991). Marker development and analysis Expressed sequence tag (EST) sequences were obtained in-house (from the National Centre for Genetic Engineering and Biotechnology, Thailand)
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and from the PalmGenes database of the Malaysian Palm Oil Board (MPOB, Bandar Baru Bangi, Malaysia). The in-house EST sequences were created using high-throughput 454 sequencing that yielded 75,948 quality-filtered sequence reads with an average length of 266 bp. The PalmGenes database (http://palmoilis. mpob.gov.my/) included 5,610 EST sequences. The EST sequences were pooled and clustered into 47,256 non-redundant groups using CAP3 (Huang and Madan 1999) and then screened for SSR using WebSat (Martins et al. 2009). Detection criteria for mono-, di-, tri-, tetra-, penta- and hexa-nucleotide motifs were a minimum of ten, five, five, three, three, and three repeats, respectively. Identified ESSRs were subjected to masking of other repeats and low-complexity sequences with the RepeatMasker Program (http:// www.repeatmasker.org). PCR primers amplifying SSR loci from ESTs (ESSRs) were designed using Primer3 (Rozen and Skaletsky 2000). Two hundred and ninety-two genomic SSR primer pairs were developed in-house from a partial oil palm genome sequencing using 454 sequencing technology. Briefly, approximately 5 lg of genomic DNA was sheared into small fragments, and sequenced using a GS-FLX Titanium platform (Roche Applied Science). Newbler v2.5, software for de novo contig assembly, was used to cluster and assemble quality-filtered reads into a set of non-redundant contigs. Unique sequences (contigs and singletons) were subsequently searched for the presence of SSRs using the Microsatellite identification software (http://pgrc.ipk-gatersleben.de/ misa/). The minimum length for each type of SSR is set as follows: mononucleotide repeats C10 nucleotides; dinucleotide repeats C12 nucleotides; trinucleotide repeats C15 nucleotides; tetranucleotide repeats C16 nucleotides; pentanucleotide repeats C20 nucleotides; and hexanucleotide repeats C24 nucleotides. Oligonucleotide primers were designed for selected SSR loci (where the repeats were located at least 50 bp from the 50 and 30 ends of the sequences) using the Primer3. In addition, 256 PCR primer pairs for genomic SSRs (mEgCIRxxxx) obtained from Billotte et al. (2005) were included in the linkage analysis. All SSR primer pairs were tested for polymorphism between the two map parents and ten random individuals from the progeny. Polymorphic SSRs were then analysed on the mapping population. Polymerase chain reaction (PCR) amplification was
417
performed in a MJ Thermal Cycler with 20 ng of DNA in a 20 ll final volume containing 1.5 mM MgCl2, 10 mM Tris HCI pH 8.3, 50 mM KCI, 20 lM of each dNTP, 0.25 lM of each primer, and 0.5 U Taq DNA polymerase. The PCR program was 5 min at 94 °C, 40 cycles of 30 s at 94 °C, 30 s at the appropriate annealing temperature for each template/primer combination, and 1 min at 72 °C, with a final extension of 7 min at 72 °C. PCR products were resolved by 6 % (w/v) denaturing PAGE and visualized by silver staining (Benbouza et al. 2006). AFLP analysis was performed as described by Vos et al. (1995). After selective amplification, 5 ll of the PCR product was separated on 6 % denaturing polyacrylamide gel. The gel was silver-stained as described by Benbouza et al. (2006). Linkage analysis The mapping population was analysed as a double pseudo-testcross (Grattapaglia and Sederoff 1994). Linkage analysis was performed using JoinMap 3.0 (Van Ooijen and Voorrips 2001) with the ‘cp’ option for a cross between two heterozygous parents. Markers showing segregation distortion from expected Mendelian ratios with a probability less than P = 0.001 were excluded from further analyses. Markers with ratios having a probability between P = 0.05 and P = 0.001 were retained in the analysis but were noted as distorted markers. The distorted markers were only included in the map if they did not give rise to a rearrangement of the map obtained without them (Hackett and Broadfoot, 2003). In the first round of analysis, separate linkage maps for each parent were constructed based on the markers being heterozygous in one parent only. For the integrated map, all marker data, including all cross-type configurations, were utilized. For all maps, linkage groups (LGs) were determined using a minimum LOD threshold of 4.0 and a recombination fraction threshold of 0.35. The Kosambi mapping function was applied to convert recombination fractions to genetic distances (in cM [centiMorgans]). For the ordering step, the parameters r \ 0.45, LOD [ 5.00, and jump \ 5 were used to improve the order. The resulting linkage maps were drawn using the MapChart software implemented in JoinMap 3.0. The robustness of the integrated linkage map was assessed by comparison of marker orders with the separate
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parental maps. Conflicting markers that impeded mapping were removed from the grouping. LGs were numbered such that they corresponded to the 16 LGs reported by Billotte et al. (2005) The genome mapped size and the expected proportion of genome coverage were estimated for the integrated map based on the methods given by Hulbert et al. (1988) and Bishop et al. (1983), respectively. QTL analysis The mapping population was examined for sex ratio (SR; per palm per year) and other related traits, including female inflorescence number (FN; per palm per year), male inflorescence number (MN; per palm per year), and fresh fruit bunch yield (FFB; kg per palm per year). The sex ratio was calculated by dividing the number of female inflorescences by the total number of inflorescences. These values were recorded over two successive years from each individual 6-year-old palm. A regular record was taken of the sex of each inflorescence as it emerged at the spathe opening stage. This was achieved by a 2-monthly census of each palm. The observed values were averaged on a yearly basis over two consecutive years. All pisifera progenies were excluded from the QTL analysis as suggested by Rance et al. (2001). The correlation coefficients were calculated to determine the degree of association between traits. Statistical analyses for distribution, correlation, and analysis of variance were performed with SPSS version 16.0 (SPSS, Chicago, IL, USA). QTL mapping analysis was performed by using the Kruskal–Wallis nonparametric rank-sum test (KW) and the multiple QTL analysis model (MQM) with MapQTL version 4.0 (Van Ooijen et al. 2002). The KW method was conducted to test a marker associated with the segregation of a QTL between individual markers and the trait at a significance of P B 0.01. If a significant QTL was detected by KW, it was then tested as a possible cofactor using the automatic cofactor selection option in MapQTL. This option is designed to refine detection of putative QTLs using MQM. To determine the genome-wide (aG) and chromosome-wide (aC) LOD threshold for significance (P \ 0.05), 1,000 permutations were performed to declare the significance level. QTLs were considered significant when the LOD score was above the genome-wide threshold or the significance thresholds
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were met concurrently for the chromosome-wide LOD threshold and the KW test with Bonferroni’s correction (P \ 0.0001). Genotype class means were extracted from MapQTL output for all four combinations at each marker locus, and for inferred genotypes by alleles of the markers nearest the QTL. The detected QTLs were reported based on the closest molecular markers. QTL positions were graphically represented using MapChart (Voorrips 2002).
Results Molecular markers and segregation analysis Mining of ESSRs according to the search criteria resulted in a total of 1,570 ESSRs containing a total SSR motif number of 1,663. This result corresponded to one SSR-containing EST in every 277 non-redundant ESTs. The 1,570 oil palm ESSRs were screened for larger repeat size core units, which resulted in the selection of 374 loci and successful design of the corresponding primer pairs. Among the 374 ESSR primer pairs tested, 31 were polymorphic within the parents and among ten random offspring. Of the total polymorphic markers, the number of markers segregating with a 1X cross-type configuration was three (Table 1). Ten, six, and five markers were observed to segregate with the cross-type configurations 2B, 2D, and 2X, respectively. Three markers segregating with a 3X cross-type configuration were detected. Two hundred and ninety-two GSSRs generated inhouse and 256 genomic SSRs from Billotte et al. (2005) were pooled to yield a total of 548 genomic SSRs. Out of all of the genomic SSRs tested, two and 13 markers were 1B and 1X, respectively (Table 1). The numbers of markers observed with cross-type configurations 2B, 2D, and 2X were 45, 35, and 43, respectively. Five and three genomic SSR markers, respectively, segregated with cross-type configurations 3B and 3D. Finally, 48 and 11 markers were observed with cross-type configurations 3X and 4X, respectively. Six markers, ESSR607, GSSRI078, GSSRI159, GSSRI242, GSSRI466, and GSSR3399, generated more than two bands after PCR optimization, indicating the possibility of duplicated loci for such genomic regions.
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Table 1 Cross-type configurations of polymorphic markers used for mapping offspring generated from outbred parental genotypes Clone B and Clone D Segregating alleles 1 Allele
2 Alleles
3 Alleles
4 Alleles
Cross-type configurationsa
Parent phenotypes
Progeny phenotypes
B
1
D
2
3
4
Segregation ratio
No. of segregating markersb GSSR
ESSR
Total
AFLP
1B
ao
oo
ao
oo
–
–
1:1
2
–
64
66
1D
oo
ao
ao
oo
–
–
1:1
0 (1)
–
55
55 (1)
1X
ao
ao
ao
oo
–
–
3:1
13 (1)
3
106
122 (1)
2B
ab
aa
ab
aa
–
–
1:1
45 (1)
10 (2)
–
55 (3)
2D
aa
ab
ab
aa
–
–
1:1
35
6 (1)
–
41 (1)
2X
ab
ab
aa
ab
bb
–
1:2:1
43 (6)
5 (1)
–
48 (7)
3B
ab
cc
ac
bc
–
–
1:1
5
–
–
5
3D
cc
ab
ac
bc
–
–
1:1
3 (1)
–
–
3 (1)
3X
ab
ac
aa
ab
ac
bc
1:1:1:1
48 (4)
3
–
51 (4)
4X
ab
cd
ab
ac
bc
bd
1:1:1:1
11 (1)
–
–
11 (1)
205 (15)
27 (4)
225
457 (19)
Total a
A number, 1, 2, 3, or 4, represents the number of segregating alleles (excluding a null allele). A letter B or D indicates the parental polymorphism origin. A letter X indicates loci heterozygous in both parents
b
Numbers in parentheses are distorted markers (0.001 \ P \ 0.05)
Of the 230 AFLP primer combinations tested in selective AFLP amplification, 44 were retained because of the large number of polymorphic bands amplified among the two parents and ten random offspring. From the entire progeny, 325 polymorphic loci were scored from 44 AFLP primer pairs, an average of 7.4 loci per primer pair combination. Of the total number of polymorphic AFLP markers, the number of markers segregating for cross-type configurations 1B, 1D, and 1X were 64, 55, and 106 (Table 1), with an average of 1.3, 1.1, and 2.2 per primer combination, respectively. Following analysis of genotype frequencies for each marker, 100 (30.8 %) markers showed segregation distortion (P \ 0.05). In total, 457 marker loci were scored in the present study. Of these, 126, 99, and 232 marker loci were Clone B, Clone D, and intercross markers (X crosstype configurations), respectively. Skewed segregation was detected at 0.001 \ P \ 0.05 for 15 and four of the 220 GSSRs and 31 ESSRs, respectively.
Table 2 Description of the parental and integrated linkage maps
Linkage map
unlinked. For the D map, a total of 209 GSSR, 28 ESSR, and 126 AFLP markers were included. At a LOD threshold of 4.0, 363 markers could be assigned to 19 LGs covering 1,873 cM, with 47 markers remaining unlinked. For the B map, the average LG size was 102.2 cM, ranging from 24.9 to 188.4 cM. For the D map, the average size was 98.6 cM, ranging
In the B map, markers were assigned to 18 LGs at a LOD threshold of 4.0. These markers identified 381 framework loci represented by 209 GSSR, 28 ESSR, and 144 AFLP loci covering a total map length of 1,839 cM (Table 2), with 39 markers remaining
Number of markers
B map
D map
Integrated map
420
410
476
GSSR
219
218
220
ESSR
31
31
31
AFLP
170
161
225
Number of mapped markers
381
363
423
GSSR
209
209
209
ESSR
28
28
28
AFLP
144
126
186
Number of linkage groups
18
19
16
Number of unlinked markers
39
47
53
Number of distorted markers* Map length (cM)
16 1,839
16 1,873
16 1,931
Estimated map length (cM)
1,925
1,971
2,002
Marker density
4.8
5.1
4.6
* 0.05 \ P \ 0.001
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420
from 24.9 to 172.5 cM. The total number of markers per LG was between two and 46 for the B map and between two and 40 for the D map. The average distance between two markers was 4.8 cM in the B map and 5.1 cM in the D map. The parental maps were quite similar except for a few local rearrangements. Integration of the B and D maps was done based on markers segregating for all cross-type configurations (220 genomic SSRs, 31 ESSRs, and 225 AFLPs). The 245 intercross markers (1X, 2X, 3X, and 4X crosstype configurations) were used as bridges between the two parent-specific genetic maps to produce an integrated map of 16 LGs of more than three markers, comprising 209 genomic SSR, 28 ESSR, and 186 AFLP markers spanning 1,931 cM (Table 2 and Supplementary Fig. S1). The novel mapped SSR markers are shown in Supplementary Table S1. On average, the integrated map presented one marker every 4.6 cM. The Sh locus was mapped on the distal arm of LG4 between the fully informative marker, 4XGSSRI261, and the marker segregating for two alleles heterozygous in both parents, 2XGSSRI371, at 1.2 cM and 4.4 cM, respectively. The average estimate of genome length at LOD threshold 4 was 2,002 cM. The expected proportion of genome coverage assuming a random distribution of markers was 93.2 %. Only slight differences in marker order were observed between the integrated map and the parental maps. The large number of bridge markers used to merge the parental genetic maps resulted in map position consistency in the integrated map. QTL analysis SR and other related traits, including FN, MN, and FFB, were examined using the phenotypic data from dura and tenera. The calculations of means, minimum and maximum values, standard deviations, and Shapiro–Wilk test results are summarized in Table 3. All traits were approximately normal, suggestive of quantitative genetic control. Correlations between the assayed traits were taken into account to detect the degree of association between the traits, since it has been noted that the map positions of QTLs for correlated traits are often similar (Paterson et al. 1991). There were significant correlations between SR and other related traits. A strong positive correlation value (0.728; P \ 0.01) between SR and FN was observed, while a highly negative correlation value
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Mol Breeding (2014) 33:415–424 Table 3 Statistical parameters of sex ratio and related traits Trait Sex ratio (SR)
Mean
Min
Max
SD
W
0.64
0.30
1.00
0.14
0.150
Female inflorescence number (FN)
17.66
1.50
26.50
4.39
0.014
Male inflorescence number (MN)
11.07
0.00
21.00
3.89
0.179
121.17 6.40
213.10
30.99
0.314
Fresh fruit bunch yield (FFB)
SD standard deviation, W Shapiro–Wilk normality test
(-0.869; P \ 0.01) was observed between SR and MN. A positive correlation was observed between FFB and FN (0.558; P \ 0.01) and between FFB and SR (0.299; P \ 0.01). FFB was not significantly correlated with MN. KW analysis detected 11, 8, 17, and 16 significant (P \ 0.01) marker-associated effects with the traits SR, MN, FN, and FFB, respectively. After being tested as possible cofactors using the automatic cofactor selection, 3, 3, 4, and 3 markers were chosen as cofactors in MQM analysis for SR, MN, FN, and FFB, respectively (Table 4). Among markers chosen as the cofactors, there were eight genomic regions with highly significant phenotype–genotype associations after Bonferroni correction (P \ 0.0001). For SR, two highly significant marker–trait associations were revealed on LG8 and LG11. Three highly significant marker–trait associations were detected for MN in LG8, LG11, and LG12 and for FFB in LG1, LG5, and LG8. Two highly significant marker–trait associations for FFB were identified on LG7 and LG15. Comparing across traits based on the highly significant marker– trait associations, the single-marker results showed the phenotypic data for SR and MN (1DEtctMcga26 on LG8 and 2DGSSRI422 on LG11) and SR and FN (3XGSSR3399 on LG1) to be associated with the same markers; this is expected as the correlations between these pairs of traits are significant (P \ 0.01). In most cases the same marker allele inherited from each parent contributed to an increase in trait values. With few exceptions, the marker allele inherited from Clone D was associated with the increase in SR, MN, and FFB on LG8, LG11, and LG7, respectively, and one marker allele inherited from Clone B was associated with the increase in MN on LG12. QTL mapping by applying the MQM analysis to the integrated genetic map was performed for SR, MN,
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Table 4 Results of the QTL analysis for sex ratio and related traits based on Kruskal–Wallis analysis Traita SR
MN
FN
FFB
LG
Markerb
Position (cM)
Kc
B9D
Genotype class means
1
3XGSSR3399
45.0
**
ab 9 ac
aa: 0.68
ab: 0.65
8
1DEtctMcga26
87.4
****
oo 9 ao
oo: 0.61
ao: 0.68
11 8
2DGSSRI422 1DEtctMcga26
73.0 87.4
**** ****
aa 9 ab oo 9 ao
aa: 0.67 oo: 11.9
ab: 0.61 ao: 10.2 ab: 12.2
11
2DGSSRI422
12
1BEtagMcgg18
73.0
****
aa 9 ab
aa: 10.3
115.8
****
ao 9 oo
oo: 10.1
ao: 12.0
ac: 0.67
bc: 0.58
bc: 16.1
1
3XGSSR3399
45.0
****
ab 9 ac
aa: 19.9
ab: 17.0
ac: 18.5
5
2XGSSRI277
37.2
****
ab 9 ab
aa: 17.0
ab: 17.1
bb: 19.7
8
1BEtctMcga14
93.5
****
ao 9 oo
oo: 19.0
ao: 16.7
14
1XGSSRI064
63.8
**
ao 9 ao
oo: 19.1
a–: 17.2
7
1DEttaMcga14
61.6
****
oo 9 ao
oo: 114.1
ao: 129.1
10
2DGSSRI420
73.6
***
aa 9 ab
aa: 128.4
ab: 113.8
15
2BmEgCIR2380
17.0
****
ab 9 aa
aa: 130.5
ab: 113.6
LG linkage group ** P \ 0.01 **** P \ 0.0001 a
Trait abbreviations are indicated in Table 3
b
All markers of each trait were chosen as cofactors for a corresponding trait in MQM analysis
c
Kruskal–Wallis analysis
FN, and FFB. Most QTL identified by KW were confirmed after MQM analysis, with the exception of the two QTL for SR and MN on LG11 and LG12, respectively (Table 5). MQM analysis identified one genome-wide significance QTL for SR and six chromosome-wide significance QTLs for related traits, which were distributed across six linkage groups in the oil palm genome. Significant LOD scores ranged from 2.86 to 4.53, and the percentage of phenotypic variation accounted for ranged from 8.1 to 13.1 %. All QTLs for a trait were observed in only one region on a linkage group. The QTL for SR (1DEtctMcga26) on LG8 that was significant at the genome-wide threshold explained 11.3 % of the phenotypic variance. Two QTLs were detected for MN on LG8 and LG11 and explained 8.6 and 9.7 % of phenotypic variance, respectively. The MN QTL on LG8 shared common genomic regions with the SR QTL. Three QTLs affecting FN were detected on LG5, LG8, and LG14, explaining from 6.8 to 11.7 % of the variation. Three QTLs were found for FFB in LG7, LG10, and LG15, with the phenotypic variances ranging between 9 and 13.1 %. In most cases a specific QTL allele combination was responsible for genotype class mean differences
(e.g. genotype classes of all QTLs for FN and FFB and one MN QTL on LG11). More than two classes have different genotype class means. The parents of the cross are therefore not heterozygous for the same two QTL alleles and it may be inferred that there are at least three QTL alleles present in this family. For the SR and MN QTLs on LG8, one QTL allele combination was markedly different. This result implied that both parents were heterozygous for the same two alleles showing dominant gene action.
Discussion Mapping of SSR and AFLP markers using the population generated from crossing a tenera with a dura palm has been previously conducted, and is herein referred to as the T 9 D map (Billotte et al. 2005). In the tenera 9 tenera map constructed in this study, referred to as the T 9 T map, 186 AFLP markers were distributed relatively evenly across the map. One hundred and nine of the GSSR markers were common to both the T 9 D map and the T 9 T map. Out of 109 GSSR common markers, 95 (87 %) maintained the same order, eight (7.3 %) showed
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Table 5 Results of the QTL analysis for sex ratio and related traits Traita
LG
Closest marker
Position (cM)
LODb
%PVEc
LOD aC
d
LOD e
aG
Genotype class means ac
ad
bc
bd
SR
8
1DEtctMcga26
87.4
4.53
11.3
3.4
4.5
0.75
0.64
0.75
0.71
MN
8
1DEtctMcga26
87.4
3.42
8.6
3.3
4.6
10.02
12.75
10.12
10.60
11
2DGSSRI422
73.0
3.76
9.7
3.2
10.02
11.08
10.04
13.02
FN FFB
5
2XGSSRI277
37.2
2.86
6.8
2.8
8
1BEtctMcga14
93.5
3.38
8.1
3.3
4.6 4.4
21.66
20.49
18.65
19.54
21.66
22.12
24.97
23.05 112.16
7
1DEttaMcga14
61.6
3.29
9.0
3.1
110.51
116.1
93.21
10
2DGSSR3213
72.2
3.76
8.7
3.3
110.84
125.66
100.74
119.40
15
2BmEgCIR2380
17.0
3.88
13.1
3.1
110.52
114.82
141.21
120.30
Output from MapQTL program for MQM mapping LG linkage group a
Trait abbreviations are indicated in Table 3
b
Maximum LOD (logarithm of odds ratio) score (QTL peak)
c
Percentage of phenotypic variance explained
d
Chromosome-wide significance threshold—in this case, a QTL is declared only if the corresponding marker was significant based on KW (see Table 4)
e
Genome-wide significance threshold
order inversions, and six (5.5 %) mapped to different LGs. In addition, the placement of the Sh locus confirms the original map position for shell thickness as reported by Billotte et al. (2005). The majority of the common GSSRs and the Sh loci illustrated colinearity between the T 9 D and T 9 T map, indicating the reliability of the two maps. The T 9 T map, developed from 208 individuals in the present study, differed from the reference T 9 D map, generated from 118 individuals, with respect to map length, genome coverage, and marker density. Differences in map length between the two maps may result from variation in the number of recombination events in the two maps, variations in the numbers and locations of mapped loci, and variations in population size. The map inflation could be due partially to a high level of genome homology between the two parents, which were derived from the same gene pool as that used in this experiment. A higher genome homology results in a higher genomewide recombination rate, which expands the genetic map. A very low rate (8.2 %) of ESSR polymorphism, as described above, supported the possibility of high genome homology between the two parents. Although the traditional practice of QTL mapping utilizes parents with divergent genetic potential to create QTL discovery populations, parent plants with
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high genome homology may be heterozygous at key loci in outcross species such as oil palm, and may therefore still give rise to useful QTL discovery populations. As oil palm has a high degree of heterozygosity, any given locus could segregate up to four alleles in a biparental cross population. The analysis of QTL allele combination suggested that most QTLs in heterogeneous oil palm are likely to be multiallelic. Most QTLs identified in the present study indicated dominant effects rather than additive gene interactions, with the alleles within one QTL interacting together with different degrees of dominance. These results were in agreement with other allogamous species such as white clover (Barrett et al. 2005). QTL analysis basically tests the difference between the average trait values of QTL alleles inherited from each parent. No specific intralocus interactions among the segregating alleles, which affect the final phenotype, can be taken into account in the analysis. However, oil palm populations are expected to show a high degree of linkage equilibrium and, as a result, linkage phase relationships between markers and QTLs will differ among individuals. It is essential to test these superior alleles in other genetic backgrounds to verify their mode of gene action and to assess their potential value for oil palm improvement.
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Clone D, which demonstrated inferior SR performance relative to Clone B, was found to contain superior alleles at some SR QTLs. Detection of superior alleles in inferior plants is common in outcrossed species (Barrett et al. 2005). The discovery of inferior germplasm is useful for mining novel and superior alleles from accessions in oil palm germplasm banks, as superior alleles may not be detected using only phenotypic evaluation (Tanksley and McCouch 1997). The SR QTL linked to the dominant marker (1DEtctMcga26) on LG8 was significant at the genome-wide threshold. The null allele of the dominant marker was unable to track the QTL in two heterozygous classes. Although AFLP markers are suitable for linkage mapping, they are unsuitable for locus-specific use because of the inefficiencies in determining linkage phase relationships, in addition to the associated high cost and complexity. Conversion of AFLP markers to PCR-based markers would considerably enhance their usefulness in genetic applications. The discovery of QTL for SR is a beginning point for implementation of MAS schemes and/or for cloning of the sequence conferring the genetic effect. The first requirement in either case is for validation of QTL effects in independent or related populations. In this experiment, characterization of the sex ratio at the individual palm may be biased on productive dura or tenera palms when these are planted at normal field density with female-sterile and highly competitive pisifera palms, due to their subsequent over-vegetative development. Therefore, the phenotypic data of pisifera palms were discarded from QTL analysis. If validation of identified QTLs were to be performed in the future, a design based on populations derived from dura 9 tenera or dura 9 dura crosses that would not give rise to pisifera palms should be included. It would be interesting to determine whether the genes involved in SR regulation are homeotic genes in flower development, as previously described for oil palm (Adam et al. 2006, 2007a, b). Molecular genetic studies have revealed a large family of MADS box genes playing roles in flower-formation regulatory pathways (Coen and Meyerowitz 1991) as transcription factors regulating flower structure in higher plants. MADS-domain proteins were reported to bind to, and modulate, the transcription of target genes involved in hormonal signaling pathways (Kaufmann
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et al. 2009). Candidate gene mapping may be suited for MAS in plant breeding programs for openpollinated crop species such as oil palm. Acknowledgments This study was supported by grants from the National Centre for Genetic Engineering and Biotechnology (BIOTEC), Thailand.
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