Methods: A targeted GWAS was used to investigate whether ten candidate genes with known roles in corneal development were associated with CCT in two Singaporean populations. The single nucleotide polymorphisms (SNPs) within a 500 kb interval encompassing each candidate were analyzed, and in light of the resulting data, members of the Wnt pathway were subsequently screened using similar methodology.
Results: Variants within the 500 kb interval encompassing three candidate genes, DKK1 (rs1896368, p=1.32×10-3), DKK2 (rs17510449, p=7.34×10-4), and FOXO1 (rs7326616, p=1.56×10-4 and rs4943785, p=1.19×10-3), were statistically significantly associated with CCT in the Singapore Indian population. DKK2 was statistically significantly associated with CCT in a separate Singapore Malaysian population (rs10015200, p=2.26×10-3). Analysis of Wnt signaling pathway genes in each population demonstrated that TCF7L2 (rs3814573, p=1.18×10-3), RYK (rs6763231, p=1.12×10-3 and rs4854785, p=1.11×10-3), and FZD8 (rs640827, p=5.17×10-4) were statistically significantly associated with CCT.
Conclusions: The targeted GWAS identified four genes (DKK1, DKK2, RYK, and FZD8) with novel associations with CCT and confirmed known associations with two genes, FOXO1 and TCF7L2. All six participate in the Wnt pathway, supporting a broader role for Wnt signaling in regulating the thickness of the cornea. In parallel, this study demonstrated that a hypothesis-driven candidate gene approach can identify associations in existing GWAS data sets.
METHODOLOGY/PRINCIPAL FINDINGS: To facilitate this, we have performed transcriptome sequencing of ripe yellow pineapple fruit flesh using Illumina technology. About 4.7 millions Illumina paired-end reads were generated and assembled using the Velvet de novo assembler. The assembly produced 28,728 unique transcripts with a mean length of approximately 200 bp. Sequence similarity search against non-redundant NCBI database identified a total of 16,932 unique transcripts (58.93%) with significant hits. Out of these, 15,507 unique transcripts were assigned to gene ontology terms. Functional annotation against Kyoto Encyclopedia of Genes and Genomes pathway database identified 13,598 unique transcripts (47.33%) which were mapped to 126 pathways. The assembly revealed many transcripts that were previously unknown.
CONCLUSIONS: The unique transcripts derived from this work have rapidly increased of the number of the pineapple fruit mRNA transcripts as it is now available in public databases. This information can be further utilized in gene expression, genomics and other functional genomics studies in pineapple.
METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.
PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.
CONCLUSIONS: The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.