METHODS: The correlation of these variants to the plasma BDNF level among Malaysian MDD patients was assessed. A total of 300 cases and 300 matched controls recruited from four public hospitals within the Klang Valley of Selangor State, Malaysia and matched for age, sex and ethnicity were screened for BDNF rs6265, rs1048218 and rs1048220 using high resolution melting (HRM).

FINDINGS: BDNF rs1048218 and BDNF rs1048220 were monomorphic and were excluded from further analysis. The distribution of the alleles and genotypes for BDNF rs6265 was in Hardy-Weinberg equilibrium for the controls (p = 0.13) but was in Hardy Weinberg disequilibrium for the cases (p = 0.011). Findings from this study indicated that having BDNF rs6265 in the Malaysian population increase the odds of developing MDD by 2.05 folds (95% CI = 1.48-3.65). Plasma from 206 cases and 206 controls were randomly selected to measure the BDNF level using enzyme-linked immunosorbent assay (ELISA). A significant decrease in the plasma BDNF level of the cases as compared to controls (p<0.0001) was observed. However, there was no evidence of the effect of the rs6265 genotypes on the BDNF level indicating a possible role of other factors in modulating the BDNF level that warrants further investigation.

RESULTS: Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC3-rich genes (GC3 ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures.

CONCLUSIONS: We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC3-rich and intronless), as well as those associated with important functions, such as FA biosynthesis and disease resistance. The study demonstrated the advantages of having an integrated approach to gene prediction and developed a computational framework for combining multiple genome annotations. These results, available in the oil palm annotation database ( http://palmxplore.mpob.gov.my ), will provide important resources for studies on the genomes of oil palm and related crops.

RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).