GMQN: A Reference-Based Method for Correcting Batch Effects and Probe Bias in HumanMethylation BeadChip

The Illumina HumanMethylation BeadChip is one of the most cost-effective methods to quantify DNA methylation levels at single-base resolution across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, providing great support for data integration and further analysis. However, the majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here, we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probe bias in the HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.

Identification of the best housekeeping gene for RT-qPCR analysis of human pancreatic organoids

In the last few years, there has been a considerable increase in the use of organoids, which is a new three-dimensional culture technology applied in scientific research. The main reasons for their extensive use are their plasticity and multiple applications, including in regenerative medicine and the screening of new drugs. The aim of this study was to better understand these structures by focusing on the choice of the best housekeeping gene (HKG) to perform accurate molecular analysis on such a heterogeneous system. This feature should not be underestimated because the inappropriate use of a HKG can lead to misleading data and incorrect results, especially when the subject of the study is innovative and not totally explored like organoids. We focused our attention on the newly described human pancreatic organoids (hPOs) and compared 12 well-known HKGs (ACTB, B2M, EF1α, GAPDH, GUSB, HPRT, PPIA, RNA18S, RPL13A TBP, UBC and YWHAZ). Four different statistical algorithms (NormFinder, geNorm, BestKeeper and ΔCt) were applied to estimate the expression stability of each HKG, and RefFinder was used to identify the most suitable genes for RT-qPCR data normalization. Our results showed that the intragroup and intergroup comparisons could influence the best choice of the HKG, making clear that the identification of a stable reference gene for accurate and reproducible RT-qPCR data normalization remains a critical issue. In summary, this is the first report on HKGs in human organoids, and this work provides a strong basis to pave the way for further gene analysis in hPOs.

Stable Reference Gene Selection for qRT-PCR Normalization in Strawberry (Fragaria × ananassa) Leaves under Different Stress and Light-Quality Conditions

Selecting an appropriate reference gene is of crucial importance for improving the accuracy of qRT-PCR analyses. In this study, strawberry (Fragaria ananassa) seedlings were subjected to different environmental conditions including heat, cold, drought, salt, white-light, blue-light, and red-light treatments. The expression levels of seven candidate reference genes, including Fa18S, FaGAPDH, FaPIRUV, FaDBP, FaHISTH4, FaACTIN1, and FaACTIN2, in the strawberry leaves were measured by qRT-PCR. Then, four programs (geNorm, NormFinder, BestKeeper, and RefFinder) were employed as tools to evaluate the expression stability of the candidate reference genes. The results showed that the expression stability of the reference genes varied under different conditions. For the cold stress and white-light treatments, FaACTIN2 was evaluated to be the most stable reference gene. FaGAPDH should be used as the reference gene under salt-stress condition and red-light treatment. For the data normalization under drought-stress treatment, FaDBP is the recommended reference gene with the highest expression stability. FaHISTH4 was observed to be the best reference gene for data normalization under heat stress and blue-light treatment. This work provides information on selecting reference genes for accurate gene expression analyses of target genes in strawberry leaves under various abiotic stress and light-quality conditions.

An Improved Reference Gene for Detection of “Candidatus Liberibacter asiaticus” Associated with Citrus Huanglongbing by qPCR and Digital Droplet PCR Assays

Citrus huanglongbing (HLB) disease associated with the ‘Candidatus Liberibacter asiaticus’ (CLas) bacterium has caused significant financial damage to many citrus industries. Large-scale pathogen surveys are routinely conducted in California to detect CLas early in the disease cycle by lab-based qPCR assays. We have developed an improved reference gene for the sensitive detection of CLas from plants in diagnostic duplex qPCR and analytical digital droplet PCR (ddPCR) assays. The mitochondrial cytochrome oxidase gene (COX), widely used as a reference, is not ideal because its high copy number can inhibit amplification of small quantities of target genes. In ddPCRs, oversaturation of droplets complicates data normalization and quantification. The variable copy numbers of COX gene in metabolically active young tissue, greenhouse plants, and citrus relatives suggest the need for a non-variable, nuclear, low copy, universal reference gene for analysis of HLB hosts. The single-copy nuclear gene, malate dehydrogenase (MDH), developed here as a reference gene, is amenable to data normalization, suitable for duplex qPCR and ddPCR assays. The sequence of MDH fragment selected is conserved in most HLB hosts in the taxonomic group Aurantioideae. This study emphasizes the need to develop standard guidelines for reference genes in DNA-based PCR assays.