METHODOLOGY: In this study, 47 GDM patients and 40 age-matched controls were genotyped for rs10946398 CDKAL1 variant using Tetra primer Amplification Refractory Mutation System Polymerase Chain Reaction (Tetra ARMS-PCR).
RESULTS: Analysis of the results showed the significant association of the C allele of CDKAL1 SNP rs10946398 (χ2 = 0.02 p = 0.001) with the risk of GDM development. Conclusively, the results support the role of SNP i.e., rs10946398 of CDKAL1 gene in GDM development in Pakistani female patients. However, future large-scale studies are needed to functionally authenticate the role of variant genotypes in the disease pathogenesis and progression.
METHODS: We performed an allelic association analysis in patients with SLE, followed by a meta-analysis assessing genome-wide association data across 11 independent cohorts (n = 28,872). In silico bioinformatics analysis and experimental validation in SLE-relevant cell lines were applied to determine the functional consequences of rs34330.
RESULTS: We replicated a genetic association between SLE and rs34330 (meta-analysis P = 5.29 × 10-22 , odds ratio 0.84 [95% confidence interval 0.81-0.87]). Follow-up bioinformatics and expression quantitative trait locus analysis suggested that rs34330 is located in active chromatin and potentially regulates several target genes. Using luciferase and chromatin immunoprecipitation-real-time quantitative polymerase chain reaction, we demonstrated substantial allele-specific promoter and enhancer activity, and allele-specific binding of 3 histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), CCCTC-binding factor, and a critical immune transcription factor (interferon regulatory factor 1 [IRF-1]). Chromosome conformation capture revealed long-range chromatin interactions between rs34330 and the promoters of neighboring genes APOLD1 and DDX47, and effects on CDKN1B and the other target genes were directly validated by clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. Finally, CRISPR/dead CRISPR-associated protein 9-based epigenetic activation/silencing confirmed these results. Gene-edited cell lines also showed higher levels of proliferation and apoptosis.
CONCLUSION: Collectively, these findings suggest a mechanism whereby the rs34330 risk allele (C) influences the presence of histone marks, RNA Pol II, and IRF-1 transcription factor to regulate expression of several target genes linked to proliferation and apoptosis. This process could potentially underlie the association of rs34330 with SLE.
METHODS: Polymerase chain reaction primers were designed and validated to specifically amplify the cytosine that is followed by guanine residues (CpGs) A and B regions. Prior epigenotyping on 110 Kelantanese Malays, the serial pyrosequencing assays for the CpGs A and B regions were validated using five validation controls. The mean values of the DNA methylation profiles of CpGs A and B were calculated.
RESULTS: The mean DNA methylation levels for CpGs A and B were 0.984 ± 0.582 and 2.456 ± 1.406, respectively. The CpGs 8 and 20 showed the highest (5.581 ± 4.497) and the lowest (0.414 ± 2.814) levels of DNA methylation at a single-base resolution.
CONCLUSION: We have successfully developed and validated a pyrosequencing assay that is fast and can yield high-quality pyrograms for DNA methylation analysis and is therefore applicable to high throughput study. Using this newly developed pyrosequencing assay, the MTHFR DNA methylation profiles of 110 Kelantanese Malays were successfully determined. It also validated our computational epigenetic research on MTHFR.
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).
CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.
RESULTS: In line with this, we have generated two small RNAs libraries from samples with contrasting lignin content using Illumina GAII sequencer. About 10 million sequence reads were obtained in secondary xylem of Am48 with high lignin content (41%) and a corresponding 14 million sequence reads were obtained in secondary xylem of Am54 with low lignin content (21%). Our results suggested that A. mangium small RNAs are composed of a set of 12 highly conserved miRNAs families found in plant miRNAs database, 82 novel miRNAs and a large proportion of non-conserved small RNAs with low expression levels. The predicted target genes of those differentially expressed conserved and non-conserved miRNAs include transcription factors associated with regulation of the lignin biosynthetic pathway genes. Some of these small RNAs play an important role in epigenetic silencing. Differential expression of the small RNAs between secondary xylem tissues with contrasting lignin content suggests that a cascade of miRNAs play an interconnected role in regulating the lignin biosynthetic pathway in Acacia species.
CONCLUSIONS: Our study critically demonstrated the roles of small RNAs during secondary wall formation. Comparison of the expression pattern of small RNAs between secondary xylem tissues with contrasting lignin content strongly indicated that small RNAs play a key regulatory role during lignin biosynthesis. Our analyses suggest an evolutionary mechanism for miRNA targets on the basis of the length of their 5' and 3' UTRs and their cellular roles. The results obtained can be used to better understand the roles of small RNAs during lignin biosynthesis and for the development of gene constructs for silencing of specific genes involved in monolignol biosynthesis with minimal effect on plant fitness and viability. For the first time, small RNAs were proven to play an important regulatory role during lignin biosynthesis in A. mangium.