Reverse transcription quantitative real-time PCR (RT-qPCR) is a common way to study gene regulation at the transcriptional level due to its sensibility and specificity, but it needs appropriate reference genes to normalize data, with white-green chimeric leaves, is an important pantropical ornamental plant. Up to date, no reference genes have been evaluated in var. . In this work, we used five common statistics tools (geNorm, NormFinder, BestKeeper, ΔCt method, RefFinder) to evaluate 10 candidate reference genes. The results showed that and were the optimal reference genes for different tissues, and zinc finger ran-binding domain-containing protein 2 () for chimeric leaf at different developmental stages, isocitrate dehydrogenase [NADP] () and triacylglycerol lipase SDP1-like () for seedlings under different hormone treatments. The comprehensive results showed , pentatricopeptide repeat-containing protein (), and caffeoyl-CoA O methyltransferase 5-like () are the top-ranked stable genes across all the samples. The stability of glyceraldehyde-3-phosphate dehydrogenase () was the least during all experiments. Furthermore, the reliability of recommended reference gene was validated by the detection of porphobilinogen deaminase () expression levels in chimeric leaves. Overall, this study provides appropriate reference genes under three specific experimental conditions and will be useful for future research on spatial and temporal regulation of gene expression and multiple hormone regulation pathways in var. .
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http://dx.doi.org/10.3389/fgene.2021.716137 | DOI Listing |
Eur J Hum Genet
January 2025
CENTOGENE GmbH, Rostock, Germany.
We aimed to assess the impact of splicing variants reported in our laboratory to gain insight into their clinical relevance. A total of 108 consecutive individuals, for whom 113 splicing variants had been reported, were selected for RNA-sequencing (RNA-seq), considering the gene expression in blood. A protocol was developed to perform RNA extraction and sequencing using the same sample (dried blood spots, DBS) provided for the DNA analysis, including library preparation and bioinformatic pipeline analysis.
View Article and Find Full Text PDFSci Data
January 2025
State Key Laboratory of Rice Biology, Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, 310058, China.
The grassland caterpillars are the most damaging insect pests to the alpine meadow of the Qinghai-Tibetan Plateau in China. In this study, we present a genome assembly of one grassland caterpillar Gynaephora qinghaiensis by using Oxford Nanopore long-read and BGI short-read sequencing. The genome assembly of 861.
View Article and Find Full Text PDFLife Sci Alliance
April 2025
https://ror.org/0220qvk04 Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
A pangenome is the sum of the genetic information of all individuals in a species or a population. Genomics research has been gradually shifted to a paradigm using a pangenome as the reference. However, in disease genomics study, pangenome-based analysis is still in its infancy.
View Article and Find Full Text PDFComp Biochem Physiol C Toxicol Pharmacol
January 2025
College of Fisheries and Life Science, Dalian Ocean University, 116023 Dalian, China; Engineering Research Center of Shellfish Culture and Breeding in Liaoning Province, Dalian Ocean University, 116023 Dalian, China.
Aminotransferase is involved in the regulation of amino acid metabolism, which can affect the balance and distribution of amino acids in the organism, help maintain the homeostasis of amino acids in the organism, and play an important role in the environmental adaptation of aquatic animals. In this study, a total of 28 aminotransferase genes were identified in the genome of R. philippinarum.
View Article and Find Full Text PDFComput Biol Med
January 2025
Turku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520, Turku, Finland; Institute of Biomedicine, University of Turku, FI-20520, Turku, Finland. Electronic address:
With advances in sequencing technologies, the use of high-throughput sequencing to characterize microbial communities is becoming increasingly feasible. However, metagenomic assembly poses computational challenges in reconstructing genes and organisms from complex samples. To address this issue, we introduce a new concept called Adaptive Sequence Alignment (ASA) for analyzing metagenomic DNA sequence data.
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