Correction: Differential roles of coding and non-coding transcripts in obesity: insights from RNA-seq analysis of Macaca fascicularis hepatocytes

Correction: BMC Genomics 26, 1133 (2025)

https://doi.org/10.1186/s12864-025-12380-5

Following publication of the original article, several errors were flagged in the author list, Fig. 3, and in the article body.

Author list

The originally published, incorrect author list is given below. The correct authorship is reflected in the author list of this Correction and in the updated article.

Yu Liu^1†, Ziting Wang^1†, Linna Liu¹ , Ya Tan¹ , Wenling Zheng¹ , Pengfei Zhang³ , Andrew P. Hutchins² , Leonard Lipovich^1,4 and Weizhong Wang^1,4*

1 Shenzhen Huayuan Biotechnology Co., Ltd, Shenzhen 518052, PR China

2 Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518052, PR China

3 Guangdong Key Laboratory of Nanomedicine, CAS-HK Joint Lab of Biomaterials, CAS Key Laboratory of Biomedical Imaging Science and System, Shenzhen Key Laboratory of Metabolic Health, Shenzhen Metabolism and Reproductive Targeted Delivery Proof-of-Concept Center, CAS Key Lab for Health Informatics,, Chinese Academy of Science, ShenZhen 518055, PR China

4 Institute of Biomedicine and Biotechnology, Chinese Academy of Science, Shenzhen 518055, PR China

Figure 3

Panel G in the original Fig. 3 has been removed and Panel H relabeled to Panel G.

The incorrect Fig. 3 and caption was:

Fig. 3.

Principal component and differential expression analysis for coding and non-coding RNAs. (A, B) Scatter plots showing the first 2 principal components (PCs) for coding (panel A) and non-coding (panel B). Dots represent each sample, and the colors represent the same sample group. (C) PC loading plot, the PC loading is indicated on the axis labels. (D, E) Volcano plots, the two volcano plots show the differentially expressed genes. Differential expression compared with HFD group and NC group Macaque liver samples. Each dot represents the log2(fold-change) versus the adjusted p-value for coding mRNAs (panel D) and ncRNAs (panel E). A gene was considered differentially expressed if its absolute fold-change was greater than 1 and the adjusted p-value was less than 0.05. Differential expression was called using DESeq2 [10]. (F) Up and Down-regulated lncRNAs were mapped from the Macaca (macFas5) genome to the human (hg38) genome. (G) Example view of the same lncRNA in Macaca (top plot) and human (bottom plot) genomes. (H) Clustalomega alignment of the human and Macaca gene orthologous lncRNAs from panel G

The correct Fig. 3 and caption is:

Fig. 3.

Principal component and differential expression analysis for coding and non-coding RNAs. A, B Scatter plots showing the first 2 principal components (PCs) for coding (panel A) and non-coding (panel B). Dots represent each sample, and the colors represent the same sample group. C PC loading plot;, the PC loading is indicated on the axis labels. D, E Volcano plots, the two volcano plots show the showing the differentially expressed genes. Differential expression compared with HFD group and NC group Macaque liver samples. Each dot represents the log2(fold-change) versus the adjusted p-value for coding mRNAs (panel D) and ncRNAs (panel E). A gene was considered differentially expressed if its absolute fold-change was greater than 1 and the adjusted p-value was less than 0.05. Differential expression was called using DESeq2 [10]. F Up and Down-regulated lncRNAs were mapped from the Macaca (macFas5) genome to the human (hg38) genome. G Clustal-omega alignment of human (top) and Macaca (bottom) cDNA copies of transcripts of a putatively orthologous lncRNA gene

Article Body

In the article body several spelling and grammatical errors were corrected in the last paragraph of the ‘Introduction’ section, the first sentence of the ‘Quality control’ section, and the second paragraph of the ‘Principal component and differential expression analysis’ section.

The last paragraph of the ‘Introduction’ section was:

Numerous non-coding genes which control organisms’ glycogen levels, or govern metabolic activities are known to have a greater expression in the liver, all of which have an impact on this expression pattern. PPP1R3B, for instance, is a regulatory switch involved in the metabolism of glucose [9]. In liver cells, it controls the synthesis and reorganization of glycogen. It has a significant impact on blood sugar homeostasis and increases the activity of glycogen synthase by joining forces with protein phosphatase 1 (PP1). Similarly, in this study, we found through enrichment analysis that amongst the up-regulated genes in a model of diabetes, many genes related to lipid metabolism and fatty acid transport processes are enriched. We discovered that whereas a small number of related genes were concentrated in the non-coding areas of Macaca fascicularis, a high number of coding genes regulating lipid transport and metabolism were enriched. Suggesting, coding genes are primarily responsible for the obesity phenotype. This report represents the first large-scale transcriptome sequencing and gene analysis of obese Macaca fascicularis and may contribute to its applications in biomedical research and basic biology. This provides evidence for genetic regulation of the obesity phenotype.

The corrected text is:

Numerous non-coding genes which control organisms’ glycogen levels, or govern metabolic activities are known to have a greater expression in the liver, all of which have an impact on this expression pattern. PPP1R3B, for instance, is a regulatory switch involved in the metabolism of glucose [9]. In liver cells, it controls the synthesis and reorganization of glycogen. It has a significant impact on blood sugar homeostasis and increases the activity of glycogen synthase by joining forces with protein phosphatase 1 (PP1). Similarly, in this study, we found through enrichment analysis that amongst the up-regulated genes in a model of diabetes, many genes related to lipid metabolism and fatty acid transport processes are enriched. We discovered that, whereas small numbers of these genes were concentrated in the non-coding areas of the Macaca fascicularis genome, protein-coding genes regulating lipid transport and metabolism were highly enriched. Therefore, protein-coding genes appear to be primarily responsible for the obesity phenotype, although this conclusion is tempered by the severe under-annotation of noncoding-RNA genes in gene ontologies. This report represents the first large-scale transcriptome sequencing and gene analysis of obese Macaca fascicularis and may contribute to its applications in biomedical research and basic biology. This provides evidence for genetic regulation of the obesity phenotype.

The ‘Quality control’ text in the original publication was:

The Macaque fascicularis genome assembly does not reach the same quality as the human genome or other model species, hence we validated the quality of our RNA-seq.

The corrected text is:

The Macaca fascicularis genome assembly is not comparable in its quality to that of the human genome or other model organisms. To identify potential problems in our locus of interest, we aligned our RNA-seq reads to the assembly.

The third paragraph of the ‘Principal component and differential expression analysis’ section in the original publication was:

We compared the conserved differentially regulated lncRNAs in the HFD samples with humans. Mapping from the Macaca genome to the human genome suggested around 30% of differentially regulated lncRNAs are conserved (Fig. 3F). This should be considered a lower bound for conservation, as the Macaca genome and transcriptome annotation is considerably less comprehensive than the human genome. We explored one lncRNA as an example. The differentially regulated lncRNA LOC107126806 is conserved between Macaca and human (Fig. 3G), although the Macaca annotated gene is considerably shorter (374 nucleotides) versus the human gene (3155 nucleotides). However, the Macaca sequence aligned well to a segment of the human gene (Fig. 3H). This suggests the Macaca lncRNA is longer than the current annotation.

The corrected text is:

We compared the conserved differentially regulated lncRNAs in the HFD samples with humans. Mapping from the Macaca genome to the human genome suggested around 30% of differentially regulated lncRNAs are conserved (Fig. 3F). This should be considered a lower bound for conservation, as the Macaca genome and transcriptome annotation is considerably less comprehensive than the human genome. Despite this, and as a representative example of an orthologous transcript-to-transcript alignment shows, the Macaca transcript sequences aligned well to orthologous human transcripts (Fig. 3G), even in cases where apparent human-Macaca gene structure differences were present at orthologous loci.

The original publication has been updated.