A self-inactivating CD-tagging retroviral vector was used to introduce epitope and GFP tags into genes and proteins in NIH 3T3 cells. Several hundred cell clones, each expressing GFP fluorescence in a distinctive pattern, were isolated. Molecular analysis showed that a wide variety of genes and proteins, some known and some newly discovered, had been tagged. The analysis also revealed that, in the great majority of instances, the abundance and cellular location of the tagged protein mirrored that of its untagged counterpart. This approach provides a systematic means for the functional annotation of mammalian genomes and proteomes in living cells.
Human gene annotation is crucial for conducting transcriptomic and genetic studies; however, the impacts of human gene annotations in diverse databases on related studies have been less evaluated. To enable full use of various human annotation resources and better understand the human transcriptome, here we systematically compare the human annotations present in RefSeq, Ensembl (GENCODE), and AceView on diverse transcriptomic and genetic analyses. We found that the human gene annotations in the three databases are far from complete. Although Ensembl and AceView annotated more genes than RefSeq, more than 15,800 genes from Ensembl (or AceView) are within the intergenic and intronic regions of AceView (or Ensembl) annotation. The human transcriptome annotations in RefSeq, Ensembl, and AceView had distinct effects on short-read mapping, gene and isoform expression profiling, and differential expression calling. Furthermore, our findings indicate that the integrated annotation of these databases can obtain a more complete gene set and significantly enhance those transcriptomic analyses. We also observed that many more known SNPs were located within genes annotated in Ensembl and AceView than in RefSeq. In particular, 1033 of 3041 trait/disease-associated SNPs involved in about 200 human traits/diseases that were previously reported to be in RefSeq intergenic regions could be relocated within Ensembl and AceView genes. Our findings illustrate that a more complete transcriptome generated by incorporating human gene annotations in diverse databases can strikingly improve the overall results of transcriptomic and genetic studies.
Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.
Human and mouse orthologs are expected to have similar biological functions; however, many discrepancies have also been reported. We systematically compared human and mouse orthologs in terms of alternative splicing patterns and expression profiles. Human-mouse orthologs are divergent in alternative splicing, as human orthologs could generally encode more isoforms than their mouse orthologs. In early embryos, exon skipping is far more common with human orthologs, whereas constitutive exons are more prevalent with mouse orthologs. This may correlate with divergence in expression of splicing regulators. Orthologous expression similarities are different in distinct embryonic stages, with the highest in morula. Expression differences for orthologous transcription factor genes could play an important role in orthologous expression discordance. We further detected largely orthologous divergence in differential expression between distinct embryonic stages. Collectively, our study uncovers significant orthologous divergence from multiple aspects, which may result in functional differences and dynamics between human-mouse orthologs during embryonic development. ortholog, alternative splicing, RNA-seq, early embryo, gene expression Citation:
The human reference genome is still incomplete and a number of gene sequences are missing from it. The approaches to uncover them, the reasons causing their absence and their functions are less explored. Here, we comprehensively identified and characterized the missing genes of human reference genome with RNA-Seq data from 16 different human tissues. By using a combined approach of genome-guided transcriptome reconstruction coupled with genome-wide comparison, we uncovered 3.78 and 2.37 Mb transcribed regions in the human genome assemblies of Celera and HuRef either missed from their homologous chromosomes of NCBI human reference genome build 37.2 or partially or entirely absent from the reference. We further identified a significant number of novel transcript contigs in each tissue from de novo transcriptome assembly that are unalignable to NCBI build 37.2 but can be aligned to at least one of the genomes from Celera, HuRef, chimpanzee, macaca or mouse. Our analyses indicate that the missing genes could result from genome misassembly, transposition, copy number variation, translocation and other structural variations. Moreover, our results further suggest that a large portion of these missing genes are conserved between human and other mammals, implying their important biological functions. Totally, 1,233 functional protein domains were detected in these missing genes. Collectively, our study not only provides approaches for uncovering the missing genes of a genome, but also proposes the potential reasons causing genes missed from the genome and highlights the importance of uncovering the missing genes of incomplete genomes.
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