Background: Recent genetic studies showed that polygenic risk score (PRS) could be used to identify individuals at high risk of Alzheimer’s disease (AD). Despite this success, early detection and intervention of AD still remain challenging. In this study, we suggest a novel PRS approach that is weighted by predicted tissue-specific gene expression levels.
Method: We used whole-genome sequencing and phenotypic data of 446 European participants (207 late-onset AD cases and 239 cognitively normal controls) from the Alzheimer’s disease Neuroimaging Initiative (ADNI) (Table 1). We performed transcriptome-wide association studies (TWAS) in 13 brain regions by using MetaXcan (weights from GTEx V8) and GWAS summary statistics (IGAP stage 1 excluding ADNI participants) and integrated these 13 TWAS results using MultiXcan. To generate transcriptome-based weighting (TW)-PRS, expression weights in each gene were mapped to SNPs in the gene, and these were applied as additional weights to the SNPs’ beta coefficients in the GWAS summary statistics. Then, PRS was derived based on the weighted GWAS summary statistics using PRSice-2. Finally, we evaluated prediction performance of a set of different models that incorporated demographic information and TW-PRS.
Result: A total of 17,588 gene expression weights were obtained from 13 brain tissues. These gene expression weights covered about 220,000 SNPs. Among them, expression weights were applied to about 140,000 SNPs overlapped with GWAS summary statistics. An AD prediction using conventional PRS yielded a pseudo-R2 of 0.0462 (P=1.30E-04). Compared with the conventional PRS, the TW-PRS improved the performance and statistical power with a pseudo-R2 of 0.0574 (P=1.74E-05). As shown in Table 2, a fully adjusted model achieved an AUC of 0.794 in which TW-PRS were significant even when APOE ε4 status and demographic information were adjusted (P=2.33E-05).
Conclusion: This study proposes a novel TW-PRS approach that combines predicted tissue-specific transcriptomic weights and PRS. Expression weights of brain regions critical to AD progression enhanced the performance of conventional PRS. Our finding suggests that tissue-specific transcriptomic factors may be independent and complementary to conventional PRS and provide additional information for tissue-specific regulatory effects in AD.
Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
Background: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours.
Methods: In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan-Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS.
Results: Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed.
Conclusion: The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets.
De novo gonad transcriptome analysis of elongate loach (Leptobotia elongata) provides novel insights into sex-related genes
- Elongate loach (Leptobotia elongata) is endemic in middle and upper reaches of the Yangtze River in China. Because of many anthropogenic factors such as overfishing and dam construction, the loach has become a highly endangered species. So far, the genomic resources which benefit for species conservation and utilization are still lacking in elongate loach. Therefore, the first gonad transcriptome analysis of the loach was conducted in this study, providing novel insights into sex-related genes.
- A total of 286,800,660 clean reads with a total length of 42.02 Gb were obtained. 18,975 differentially expressed genes (DEGs) were identified, where 12,976 DEGs, especially Sox9a, Sox9b, Igf2 and Fgfr2, were upregulated in the testis, and 5999 DEGs, especially Zp3, Eg2, Plk1, Ccnb1, Cdc20 and Mos, were upregulated in the ovary. Meanwhile, some testis-specific genes (i.e. Cald1, Atp1a, Muc2 and Ca2) and ovary-specific genes (i.e. Ca4, Tuba, Acp5, Ccna, Larp6 and Nop4) were identified and verified.
- According to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs, we found a series of enrichment pathways related to reproduction in elongate loach, such as the MAPK signaling pathway, oxytocin signaling pathway and oocyte meiosis pathway. Twelve DEGs were randomly selected to verify RNA-seq results by qPCR. In conclusion, this study provides a data source to study the molecular characteristics and regulatory mechanisms of sex-related genes in elongate loach, which has a potential to improve the resource protection and aquaculture production of the loach.
Novo? Transcriptome cDNA Kit |
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| M1167-100 | Biovision | each | 1142.4 EUR |
Novo? Transcriptome cDNA Kit |
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| M1167-25 | Biovision | each | 529.2 EUR |
Novo? Reverse Transcriptase |
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| M1174-100 | Biovision | each | 457.2 EUR |
Novo? Reverse Transcriptase |
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| M1174-25 | Biovision | each | 385.2 EUR |
Novo? cDNA Kit |
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| M1165-100 | Biovision | each | 424.8 EUR |
Novo? cDNA Kit |
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| M1165-25 | Biovision | each | 320.4 EUR |
Novo? cDNA Supermix |
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| M1169-100 | Biovision | each | 529.2 EUR |
Novo? cDNA Supermix |
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| M1169-25 | Biovision | each | 346.8 EUR |
Novo? Two Step RT Kit |
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| M1161-100 | Biovision | each | 457.2 EUR |
Novo? Two Step RT Kit |
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| M1161-25 | Biovision | each | 320.4 EUR |
MK TETRATHIONATE NOVO COMPLETE - PK50 |
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| MED1114 | Scientific Laboratory Supplies | PK50 | 66.15 EUR |
Recombinant Novosphingobium aromaticivorans Transcriptional repressor NrdR (nrdR) |
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| MBS1453669-002mgBaculovirus | MyBiosource | 0.02mg(Baculovirus) | 1080 EUR |
Recombinant Novosphingobium aromaticivorans Transcriptional repressor NrdR (nrdR) |
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| MBS1453669-002mgEColi | MyBiosource | 0.02mg(E-Coli) | 670 EUR |
Recombinant Novosphingobium aromaticivorans Transcriptional repressor NrdR (nrdR) |
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| MBS1453669-002mgYeast | MyBiosource | 0.02mg(Yeast) | 835 EUR |
Recombinant Novosphingobium aromaticivorans Transcriptional repressor NrdR (nrdR) |
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| MBS1453669-01mgEColi | MyBiosource | 0.1mg(E-Coli) | 780 EUR |
Recombinant Novosphingobium aromaticivorans Transcriptional repressor NrdR (nrdR) |
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| MBS1453669-01mgYeast | MyBiosource | 0.1mg(Yeast) | 975 EUR |
Recombinant Novosphingobium aromaticivorans Transcription elongation factor GreA (greA) |
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| MBS1456131-002mgBaculovirus | MyBiosource | 0.02mg(Baculovirus) | 1080 EUR |
Recombinant Novosphingobium aromaticivorans Transcription elongation factor GreA (greA) |
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| MBS1456131-002mgEColi | MyBiosource | 0.02mg(E-Coli) | 670 EUR |
Recombinant Novosphingobium aromaticivorans Transcription elongation factor GreA (greA) |
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| MBS1456131-002mgYeast | MyBiosource | 0.02mg(Yeast) | 830 EUR |
Recombinant Novosphingobium aromaticivorans Transcription elongation factor GreA (greA) |
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| MBS1456131-01mgEColi | MyBiosource | 0.1mg(E-Coli) | 780 EUR |
Recombinant Novosphingobium aromaticivorans Transcription elongation factor GreA (greA) |
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| MBS1456131-01mgYeast | MyBiosource | 0.1mg(Yeast) | 975 EUR |
Recombinant Novosphingobium aromaticivorans Probable transcriptional regulatory protein Saro_0419 (Saro_0419) |
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| MBS1284462-002mgBaculovirus | MyBiosource | 0.02mg(Baculovirus) | 1135 EUR |
Recombinant Novosphingobium aromaticivorans Probable transcriptional regulatory protein Saro_0419 (Saro_0419) |
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| MBS1284462-002mgEColi | MyBiosource | 0.02mg(E-Coli) | 770 EUR |
Recombinant Novosphingobium aromaticivorans Probable transcriptional regulatory protein Saro_0419 (Saro_0419) |
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| MBS1284462-002mgYeast | MyBiosource | 0.02mg(Yeast) | 925 EUR |
Recombinant Novosphingobium aromaticivorans Probable transcriptional regulatory protein Saro_0419 (Saro_0419) |
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| MBS1284462-01mgEColi | MyBiosource | 0.1mg(E-Coli) | 920 EUR |
Recombinant Novosphingobium aromaticivorans Probable transcriptional regulatory protein Saro_0419 (Saro_0419) |
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| MBS1284462-01mgYeast | MyBiosource | 0.1mg(Yeast) | 1085 EUR |
Recombinant Novosphingobium aromaticivorans Heat-inducible transcription repressor HrcA (hrcA) |
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| MBS1414688-002mgBaculovirus | MyBiosource | 0.02mg(Baculovirus) | 1230 EUR |
Recombinant Novosphingobium aromaticivorans Heat-inducible transcription repressor HrcA (hrcA) |
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| MBS1414688-002mgEColi | MyBiosource | 0.02mg(E-Coli) | 890 EUR |
Transcriptome and Metabolome Profiling of a Novel Isolate Chlorella sorokiniana G32 (Chlorophyta) Displaying Enhanced Starch Accumulation at High Growth Rate Under Mixotrophic Condition
Chlorella sorokiniana is one of the most productive microalgal species with a high potential for the production of biofuels and other high value-added molecules. Many studies have focused on its capability of mixotrophic growth using reduced organic carbon and growth pattern shift between autotrophic and mixotrophic conditions. In this study, we investigated growth patterns of a novel isolate, C. sorokiniana G32, under mixotrophic growth conditions supplemented with a low level (1.25 g L-1) and a high level (5 g L-1) of glucose.
Physiological, transcriptomic (i.e., RNA-seq), and metabolomic (i.e., LC-MS/MS) methods were used. We showed that peak growth based on OD680nm absorbance is ∼4-fold higher with high glucose vs. low glucose supplementation. Photosynthetic efficiency (Fv/Fm) in G32 mixotrophic cultures with high or low glucose supplementation remains identical to that of G32 phototrophic growth. We also found that the conversion rate between absorbance-based cell density and cell dry weight with high glucose supplementation was lower than with low glucose. This suggests that more cell biomass is produced under high glucose treatment than with low glucose. The result was confirmed via sucrose density gradient centrifugation. It is likely that accumulation of high concentration of starch may account for this effect. Transcriptomic analysis of G32 cultures (i.e., via RNA-seq) in response to reciprocal change of glucose levels reveals that expression of a subset of differentially expressed genes (DEGs) is correlated with the amount of glucose supplementation.
These DEGs are designated as glucose-specific responsive (GSR) genes. GSR genes are enriched for a number of energy metabolic pathways. Together with metabolomics data (i.e., LC-MS/MS), we show that under high-level supplementation, glucose is preferentially oxidized through an oxidative pentose phosphate pathway. Collectively, our results indicate the mechanism of regulation of glucose assimilation and energy metabolism in G32 under mixotrophic conditions with different levels of glucose supplementation revealed by transcriptomic and metabolomic analyses. We propose that C. sorokiniana G32 has the potential for the production of high value-added molecules.