An ecological transcriptome approach to capture the molecular and physiological mechanisms of mass flowering in Shorea curtisii

Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation.

Evaluation of methods and marker Systems in Genomic Selection of oil palm (Elaeis guineensis Jacq.)

Background

Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits.

Results

The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.

Conclusion

Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.

Electronic supplementary material

The online version of this article (10.1186/s12863-017-0576-5) contains supplementary material, which is available to authorized users.

Unravelling proximate cues of mass flowering in the tropical forests of South-East Asia from gene expression analyses

Elucidating the physiological mechanisms of the irregular yet concerted flowering rhythm of mass flowering tree species in the tropics requires long-term monitoring of flowering phenology, exogenous and endogenous environmental factors, as well as identifying interactions and dependencies among these factors. To investigate the proximate factors for floral initiation of mast seeding trees in the tropics, we monitored the expression dynamics of two key flowering genes, meteorological conditions and endogenous resources over two flowering events of Shorea curtisii and Shorea leprosula in the Malay Peninsula. Comparisons of expression dynamics of genes studied indicated functional conservation of FLOWERING LOCUS T (FT) and LEAFY (LFY) in Shorea. The genes were highly expressed at least 1 month before anthesis for both species. A mathematical model considering the synergistic effect of cool temperature and drought on activation of the flowering gene was successful in predicting the observed gene expression patterns. Requirement of both cool temperature and drought for floral transition suggested by the model implies that flowering phenologies of these species are sensitive to climate change. Our molecular phenology approach in the tropics sheds light on the conserved role of flowering genes in plants inhabiting different climate zones and can be widely applied to dissect the flowering processes in other plant species.

Genomic Selection in Commercial Perennial Crops: Applicability and Improvement in Oil Palm (Elaeis guineensis Jacq.)

Genomic selection (GS) uses genome-wide markers to select individuals with the desired overall combination of breeding traits. A total of 1,218 individuals from a commercial population of Ulu Remis x AVROS (UR x AVROS) were genotyped using the OP200K array. The traits of interest included: shell-to-fruit ratio (S/F, %), mesocarp-to-fruit ratio (M/F, %), kernel-to-fruit ratio (K/F, %), fruit per bunch (F/B, %), oil per bunch (O/B, %) and oil per palm (O/P, kg/palm/year). Genomic heritabilities of these traits were estimated to be in the range of 0.40 to 0.80. GS methods assessed were RR-BLUP, Bayes A (BA), Cπ (BC), Lasso (BL) and Ridge Regression (BRR). All methods resulted in almost equal prediction accuracy. The accuracy achieved ranged from 0.40 to 0.70, correlating with the heritability of traits. By selecting the most important markers, RR-BLUP B has the potential to outperform other methods. The marker density for certain traits can be further reduced based on the linkage disequilibrium (LD). Together with in silico breeding, GS is now being used in oil palm breeding programs to hasten parental palm selection.

Validation Study of the Malay version of the Neuropsychiatric Inventory

OBJECTIVES

There is a lack of local instruments to assess behavioural and psychological symptoms of dementia (BPSD). This 2-stage cross-sectional study was aimed at validating a Malay translated version of the Neuropsychiaric Inventory (MvNPI).

MATERIALS AND METHODS

It was conducted on a selected group of 138 elderly outpatients with dementia and their caregivers in Hospital Pulau Pinang. Severity of dementia was assessed using the Malay-translated version of Mini Mental State Examination (MMSE). The original NPI was translated and then back-translated before it was pilot-tested. The MvNPI was administered twice, a week apart on the same caregiver by the same investigator.

RESULTS

The individual items and total scale score of MvNPI had high internal consistency, with Corrected Item-Total Correlation ranging from satisfactory to good (0.41 to 0.77). The Cronbach's alpha for all the NPI domains showed high internal consistency (0.83), and subtotal for severity and distress scores were perfect (0.998 to 1.00). There was no significant difference between test-retest mean scores (p>0.05) and their correlations were perfect (0.996 to 1.00). Content validity indicated mild and inverse relationship between MMSE scores and severity, and distress score (-0.281 and -0.268, respectively, with p<0.001). Discriminant validity calculated using Mann-Whitney U test was found to be significant (p<0.001) in differentiating severity of cognitive impairment. Factor analysis revealed four possible components existed in MvNPI.

CONCLUSIONS

The MvNPI is a valid and reliable tool for assessing BPSD among Malay speaking populations of Malaysia and its neighbouring South East Asian countries.

The molecular basis of quantitative variation in foliar secondary metabolites in Eucalyptus globulus

Eucalyptus is characterized by high foliar concentrations of plant secondary metabolites with marked qualitative and quantitative variation within a single species. Secondary metabolites in eucalypts are important mediators of a diverse community of herbivores. We used a candidate gene approach to investigate genetic associations between 195 single nucleotide polymorphisms (SNPs) from 24 candidate genes and 33 traits related to secondary metabolites in the Tasmanian Blue Gum (Eucalyptus globulus). We discovered 37 significant associations (false discovery rate (FDR) Q < 0.05) across 11 candidate genes and 19 traits. The effects of SNPs on phenotypic variation were within the expected range (0.018 < r(2) < 0.061) for forest trees. Whereas most marker effects were nonadditive, two alleles from two consecutive genes in the methylerythritol phosphate pathway (MEP) showed additive effects. This study successfully links allelic variants to ecologically important phenotypes which can have a large impact on the entire community. It is one of very few studies to identify the genetic variants of a foundation tree that influences ecosystem function.

Comparative SNP diversity among four Eucalyptus species for genes from secondary metabolite biosynthetic pathways

Background

There is little information about the DNA sequence variation within and between closely related plant species. The combination of re-sequencing technologies, large-scale DNA pools and availability of reference gene sequences allowed the extensive characterisation of single nucleotide polymorphisms (SNPs) in genes of four biosynthetic pathways leading to the formation of ecologically relevant secondary metabolites in Eucalyptus. With this approach the occurrence and patterns of SNP variation for a set of genes can be compared across different species from the same genus.

Results

In a single GS-FLX run, we sequenced over 103 Mbp and assembled them to approximately 50 kbp of reference sequences. An average sequencing depth of 315 reads per nucleotide site was achieved for all four eucalypt species, Eucalyptus globulus, E. nitens, E. camaldulensis and E. loxophleba. We sequenced 23 genes from 1,764 individuals and discovered 8,631 SNPs across the species, with about 1.5 times as many SNPs per kbp in the introns compared to exons. The exons of the two closely related species (E. globulus and E. nitens) had similar numbers of SNPs at synonymous and non-synonymous sites. These species also had similar levels of SNP diversity, whereas E. camaldulensis and E. loxophleba had much higher SNP diversity. Neither the pathway nor the position in the pathway influenced gene diversity. The four species share between 20 and 43% of the SNPs in these genes.

Conclusion

By using conservative statistical detection methods, we were confident about the validity of each SNP. With numerous individuals sampled over the geographical range of each species, we discovered one SNP in every 33 bp for E. nitens and one in every 31 bp in E. globulus. In contrast, the more distantly related species contained more SNPs: one in every 16 bp for E. camaldulensis and one in 17 bp for E. loxophleba, which is, to the best of our knowledge, the highest frequency of SNPs described in woody plant species.