Genetic variation among oil palm parent genotypes and their progenies based on microsatellite markers

Knowl­edge on genetic dis­tances and rela­tion­ships among breed­ing mate­ri­als has a sig­nif­i­cant impact on crop improve­ment. Mol­e­c­u­lar mark­ers are being used increas­ingly to deter­mine the genetic dis­tance between indi­vid­u­als. In this study, microsatel­lite mark­ers were used to esti­mate the genetic dis­tances between selected oil palm par­ent lines. Microsatel­lite mark­ers are highly reli­able, inher­ited in codom­i­nant fash­ion whereby het­erozy­gotes and homozy­gotes are dis­tin­guish­able, easy to score and can be rapidly pro­duced using PCR tech­nol­ogy. Nine microsatel­lite mark­ers were used to screen selected par­ent palms (15 duras and 4 pisiferas) and their prog­e­nies (16 DxP crosses). Data were scored and analysed using the Biosys-1 soft­ware to cal­cu­late the genetic dis­tance val­ues. A total of 29 poly­mor­phic bands were gen­er­ated. The genetic dis­tances between prog­e­nies ranged from 0.089 to 0.313. These results indi­cate that microsatel­lite mark­ers are pow­er­ful tools for study­ing genetic rela­tion­ships among DxP prog­e­nies. These mark­ers should be fur­ther explored to assist oil palm breeding

Statistical mapping of quantitative trait loci controlling the time to first callusing in oil palm (elaeis guineensis Jacq.) tissue culture

An additional 400 genetic markers (126 RFLPs, 274 AFLPs) were successfully mapped on the earlier developed linkage maps using 87 F1 progenies derived from Deli dura X Yangambi pisifera cross. This resulted in a denser map with coverage length of 1, 714cM and 1,225cM for pisifera and dura, respectively. Further exploration to searchfor quantitative trait loci (QTL) associated with time to first callusing (TFC) was carried out by Kosambi Interval Mapping using the computer program MapQTL Version 4. O. The tissue culture trait data showed a continuous distribution. In this paper; three likelihood QTLs were detected in pisifera and two QTLs in dura at 99% and 95% significant thresholds. These QTL locations can be designated as statistically significant for contributing to the variation of TFG. Therefore, the information points to a genomic loci affecting tissue culturability in oil palm

Analysing population structure of Elaeis Oleifera germplasm using model-based approach programme STRUCTURE / Wan Nurhayati Wan Hanafi …[et al.]

Elaeis oleifera serves as a source of genetic foundation in oil palm improvement programme, as it possess several interesting agronomic traits such as slow growth, higher oil unsaturation and disease resistance. Malaysian Palm Oil Board (MPOB) has developed a collection of simple sequence repeats (SSRs) from Elaeis oleifera genome (E. oleifera-gSSRs). A total of 21 polymoprhic SSR markers were evaluated in the attempt to assess the population structure of E. oleifera populations. The appropriate common ancestry (K) value was determined to be seven from the likelihood scores. The profile from STRUCTURE analysis indicates considerable sharing of genetic components among E. oleifera population with an exception for Population 01 from Columbia and Population 02 from Costa Rica. The present study provides information on population structure of MPOB E. oleifera collection via model-based method for germplasm conservation and utilisation in breeding programmes

Genetic variability of oil palm parental genotypes and performance of its' progenies as revealed by molecular markers and quantitative traits.

Studies were conducted to assess the genetic relationships between the parental palms (dura and pisifera) and performance of their progenies based on nine microsatellite markers and 29 quantitative traits. Correlation analyses between genetic distances and hybrids performance were estimated. The coefficients of correlation values of genetic distances with hybrid performance were non-significant, except for mean nut weight and leaf number. However, the correlation coefficient of genetic distances with these characters was low to be used as predicted value. These results indicated that genetic distances based on the microsatellite markers may not be useful for predicting hybrid performance. The genetic distance analysis using UPGMA clustering system generated 5 genetic clusters with coefficient of 1.26 based on quantitative traits of progenies. The genotypes, DP16, DP14, DP4, DP13, DP12, DP15, DP8, DP1 and DP2 belonging to distant clusters and greater genetic distances could be selected for further breeding programs

SSR mining in oil palm EST database: application in oil palm germplasm diversity studies.

This study reports on the detection of additional expressed sequence tags (EST) derived simple sequence repeat (SSR) markers for the oil palm. A large collection of 19243 Elaeis guineensis ESTs were assembled to give 10258 unique sequences, of which 629 ESTs were found to contain 722 SSRs with a variety of motifs. Dinucleotide repeats formed the largest group(45.6%) consisting of 66.9% AG/CT, 21.9% AT/AT, 10.9% AC/GT and 0.3% CG/CG motifs. This was followed by trinucleotide repeats, which is the second most abundant repeat types (34.5%) consisting of AAG/CTT (23.3%), AGG/CCT (13.7%), CCG/CGG (11.2%), AAT/ATT (10.8%), AGC/GCT (10.0%), ACT/AGT (8.8%), ACG/CGT (7.6%), ACC/GGT(7.2%), AAC/GTT (3.6%) and AGT/ACT (3.6%) motifs. Primer pairs were designed for 405 unique EST-SSRs and 15 of these were used to genotype 105 E. guineensis and 30 E. oleifera accessions. Fourteen SSRs were polymorphic in at least one germplasm revealing a total of 101 alleles. The high percentage (78.0%) of alleles found to be specific for either E. guineensis or E. oleifera has increased the power for discriminating the two species. The estimates of genetic differentiation detected by EST-SSRs were compared to those reported previously. The transferability across palm taxa to two Cocos nucifera and six exotic palms is also presented. The polymerase chain reaction (PCR) products of three primer-pairs detected in E. guineensis, E. oleifera, C. nucifera and Jessinia bataua were cloned and sequenced. Sequence alignments showed mutations within the SSR site and the flanking regions. Phenetic analysis based on the sequence data revealed that C. nucifera is closer to oil palm compared to J. bataua; consistent with the taxanomic classification

Comparison of quantitative trait loci (QTLs) associated with yield components in two commercial Dura × Pisifera breeding crosses

The high yielding tenera is the commercial oil palm planting material of choice in Southeast Asia. Notwithstanding this, there is continuous effort to further improve the yield and one way to do this is by addressing the yield components (YCs ). Using 4,451 SNP and over 600 SSR markers , this study revealed quantitative trait loci (QTL) associated with YCs in two breeding populations, a Deli dura x Yangambi pisifera (P2) and a Deli dura x AVROS pisifera (KULIM DxP). Thirteen and 29 QTLs were identified in P2 and KULIM DxP, respectively . They were compared to other YC-linked QTLs reported previously for different genetic backgrounds by mapping the QTL-linked markers to the oil palm genome . The comparison revealedfour common chromosomes containing QTLs influencing various YCs . The results reveal the possible presence of closely linked loci or pleiotropic genes influencing YCs in oil palm. Exploiting the genome data has also facilitated the discovery of candidate genes within or near the QTL regions including those related to glycosylation, fatty acid and oil biosynthesis, and development of flower, seed and fruit

Genetic diversity of Elaeis oleifera (HBK) Cortes populations using cross species SSRs: implication’s for germplasm utilization and conservation

Abstract Background The Elaeis oleifera genetic materials were assembled from its center of diversity in South and Central America. These materials are currently being preserved in Malaysia as ex situ living collections. Maintaining such collections is expensive and requires sizable land. Information on the genetic diversity of these collections can help achieve efficient conservation via maintenance of core collection. For this purpose, we have applied fourteen unlinked microsatellite markers to evaluate 532 E. oleifera palms representing 19 populations distributed across Honduras, Costa Rica, Panama and Colombia. Results In general, the genetic diversity decreased from Costa Rica towards the north (Honduras) and south-east (Colombia). Principle coordinate analysis (PCoA) showed a single cluster indicating low divergence among palms. The phylogenetic tree and STRUCTURE analysis revealed clusters based on country of origin, indicating considerable gene flow among populations within countries. Based on the values of the genetic diversity parameters, some genetically diverse populations could be identified. Further, a total of 34 individual palms that collectively captured maximum allelic diversity with reduced redundancy were also identified. High pairwise genetic differentiation (Fst > 0.250) among populations was evident, particularly between the Colombian populations and those from Honduras, Panama and Costa Rica. Crossing selected palms from highly differentiated populations could generate off-springs that retain more genetic diversity. Conclusion The results attained are useful for selecting palms and populations for core collection. The selected materials can also be included into crossing scheme to generate offsprings that capture greater genetic diversity for selection gain in the future

VARIABLE SELECTION FOR ROAD SEGMENTATION IN AERIAL IMAGES

For extraction of road pixels from combined image and elevation data, Wegner et al. (2015) proposed classification of superpixels into road and non-road, after which a refinement of the classification results using minimum cost paths and non-local optimization methods took place. We believed that the variable set used for classification was to a certain extent suboptimal, because many variables were redundant while several features known as useful in Photogrammetry and Remote Sensing are missed. This motivated us to implement a variable selection approach which builds a model for classification using portions of training data and subsets of features, evaluates this model, updates the feature set, and terminates when a stopping criterion is satisfied. The choice of classifier is flexible; however, we tested the approach with Logistic Regression and Random Forests, and taylored the evaluation module to the chosen classifier. To guarantee a fair comparison, we kept the segment-based approach and most of the variables from the related work, but we extended them by additional, mostly higher-level features. Applying these superior features, removing the redundant ones, as well as using more accurately acquired 3D data allowed to keep stable or even to reduce the misclassification error in a challenging dataset