Acetylation of Cytidine in mRNA Promotes Translation Efficiency.

Generation of the "epitranscriptome" through post-transcriptional ribonucleoside modification embeds a layer of regulatory complexity into RNA structure and function. Here, we describe N4-acetylcytidine (ac4C) as an mRNA modification that is catalyzed by the acetyltransferase NAT10. Transcriptome-wide mapping of ac4C revealed discretely acetylated regions that were enriched within coding sequences. Ablation of NAT10 reduced ac4C detection at the mapped mRNA sites and was globally associated with target mRNA downregulation. Analysis of mRNA half-lives revealed a NAT10-dependent increase in stability in the cohort of acetylated mRNAs. mRNA acetylation was further demonstrated to enhance substrate translation in vitro and in vivo. Codon content analysis within ac4C peaks uncovered a biased representation of cytidine within wobble sites that was empirically determined to influence mRNA decoding efficiency. These findings expand the repertoire of mRNA modifications to include an acetylated residue and establish a role for ac4C in the regulation of mRNA translation.

geneHummus: an R package to define gene families and their expression in legumes and beyond.

BACKGROUND: During the last decade, plant biotechnological laboratories have sparked a monumental revolution with the rapid development of next sequencing technologies at affordable prices. Soon, these sequencing technologies and assembling of whole genomes will extend beyond the plant computational biologists and become commonplace within the plant biology disciplines. The current availability of large-scale genomic resources for non-traditional plant model systems (the so-called 'orphan crops') is enabling the construction of high-density integrated physical and genetic linkage maps with potential applications in plant breeding. The newly available fully sequenced plant genomes represent an incredible opportunity for comparative analyses that may reveal new aspects of genome biology and evolution. The analysis of the expansion and evolution of gene families across species is a common approach to infer biological functions. To date, the extent and role of gene families in plants has only been partially addressed and many gene families remain to be investigated. Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family, typically combining numerous BLAST searches and manually cleaning data. Due to the increasing abundance of genome sequences and the agronomical interest in plant gene families, the field needs a clear, automated annotation tool. RESULTS: Here, we present the geneHummus package, an R-based pipeline for the identification and characterization of plant gene families. The impact of this pipeline comes from a reduction in hands-on annotation time combined with high specificity and sensitivity in extracting only proteins from the RefSeq database and providing the conserved domain architectures based on SPARCLE. As a case study we focused on the auxin receptor factors gene (ARF) family in Cicer arietinum (chickpea) and other legumes. CONCLUSION: We anticipate that our pipeline should be suitable for any taxonomic plant family, and likely other gene families, vastly improving the speed and ease of genomic data processing.

Differences in Stability, Activity and Mutation Effects Between Human and Mouse Leucine-Rich Repeat Kinase 2.

Mutations in the Leucine-rich repeat kinase 2 (LRRK2) gene have been implicated in the pathogenesis of Parkinson's disease (PD). Identification of PD-associated LRRK2 mutations has led to the development of novel animal models, primarily in mice. However, the characteristics of human LRRK2 and mouse Lrrk2 protein have not previously been directly compared. Here we show that proteins from different species have different biochemical properties, with the mouse protein being more stable but having significantly lower kinase activity compared to the human orthologue. In examining the effects of PD-associated mutations and risk factors on protein function, we found that conserved substitutions such as G2019S affect human and mouse LRRK2 proteins similarly, but variation around position 2385, which is not fully conserved between humans and mice, induces divergent in vitro behavior. Overall our results indicate that structural differences between human and mouse LRRK2 are likely responsible for the different properties we have observed for these two species of LRRK2 protein. These results have implications for disease modelling of LRRK2 mutations in mice and on the testing of pharmacological therapies in animals.

The G2385R risk factor for Parkinson's disease enhances CHIP-dependent intracellular degradation of LRRK2.

Autosomal dominant mutations in leucine-rich repeat kinase 2 (LRRK2) are associated with Parkinson's disease (PD). Most pathogenic LRRK2 mutations result in amino acid substitutions in the central ROC (Ras of complex proteins)-C-terminus of ROC-kinase triple domain and affect enzymatic functions of the protein. However, there are several variants in LRRK2, including the risk factor G2385R, that affect PD pathogenesis by unknown mechanisms. Previously, we have shown that G2385R LRRK2 has decreased kinase activity in vitro and altered affinity to LRRK2 interactors. Specifically, we found an increased binding to the chaperone Hsp90 (heat shock protein 90 kDa) that is known to stabilize LRRK2, suggesting that G2385R may have structural effects on LRRK2. In the present study, we further explored the effects of G2385R on LRRK2 in cells. We found that G2385R LRRK2 has lower steady-state intracellular protein levels compared with wild-type LRRK2 due to increased protein turnover of the mutant protein. Mechanistically, this is a consequence of a higher affinity of G2385R compared with the wild-type protein for two proteins involved in proteasomal degradation, Hsc70 and carboxyl-terminus of Hsc70-interacting protein (CHIP). Overexpression of CHIP decreased intracellular protein levels of both G2385R mutant and wild-type LRRK2, while short interfering RNA CHIP knockdown had the opposite effect. We suggest that the G2385R substitution tilts the equilibrium between refolding and proteasomal degradation toward intracellular degradation. The observation of lower steady-state protein levels may explain why G2385R is a risk factor rather than a penetrant variant for inherited PD.

ADAR2 affects mRNA coding sequence edits with only modest effects on gene expression or splicing in vivo.

Adenosine deaminases bind double stranded RNA and convert adenosine to inosine. Editing creates multiple isoforms of neurotransmitter receptors, such as with Gria2. Adar2 KO mice die of seizures shortly after birth, but if the Gria2 Q/R editing site is mutated to mimic the edited version then the animals are viable. We performed RNA-Seq on frontal cortices of Adar2(-/-) Gria2(R/R) mice and littermates. We found 56 editing sites with significantly diminished editing levels in Adar2 deficient animals with the majority in coding regions. Only two genes and 3 exons showed statistically significant differences in expression levels. This work illustrates that ADAR2 is important in site-specific changes of protein coding sequences but has relatively modest effects on gene expression and splicing in the adult mouse frontal cortex.

Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies.

Polymorphisms in the target mRNA sequence can greatly affect the binding affinity of microarray probe sequences, leading to false-positive and false-negative expression quantitative trait locus (QTL) signals with any other polymorphisms in linkage disequilibrium. We provide the most complete solution to this problem, by using the latest genome and exome sequence reference data to identify almost all common polymorphisms (frequency >1% in Europeans) in probe sequences for two commonly used microarray panels (the gene-based Illumina Human HT12 array, which uses 50-mer probes, and exon-based Affymetrix Human Exon 1.0 ST array, which uses 25-mer probes). We demonstrate the impact of this problem using cerebellum and frontal cortex tissues from 438 neuropathologically normal individuals. We find that although only a small proportion of the probes contain polymorphisms, they account for a large proportion of apparent expression QTL signals, and therefore result in many false signals being declared as real. We find that the polymorphism-in-probe problem is insufficiently controlled by previous protocols, and illustrate this using some notable false-positive and false-negative examples in MAPT and PRICKLE1 that can be found in many eQTL databases. We recommend that both new and existing eQTL data sets should be carefully checked in order to adequately address this issue.

MAPT expression and splicing is differentially regulated by brain region: relation to genotype and implication for tauopathies.

The MAPT (microtubule-associated protein tau) locus is one of the most remarkable in neurogenetics due not only to its involvement in multiple neurodegenerative disorders, including progressive supranuclear palsy, corticobasal degeneration, Parksinson's disease and possibly Alzheimer's disease, but also due its genetic evolution and complex alternative splicing features which are, to some extent, linked and so all the more intriguing. Therefore, obtaining robust information regarding the expression, splicing and genetic regulation of this gene within the human brain is of immense importance. In this study, we used 2011 brain samples originating from 439 individuals to provide the most reliable and coherent information on the regional expression, splicing and regulation of MAPT available to date. We found significant regional variation in mRNA expression and splicing of MAPT within the human brain. Furthermore, at the gene level, the regional distribution of mRNA expression and total tau protein expression levels were largely in agreement, appearing to be highly correlated. Finally and most importantly, we show that while the reported H1/H2 association with gene level expression is likely to be due to a technical artefact, this polymorphism is associated with the expression of exon 3-containing isoforms in human brain. These findings would suggest that contrary to the prevailing view, genetic risk factors for neurodegenerative diseases at the MAPT locus are likely to operate by changing mRNA splicing in different brain regions, as opposed to the overall expression of the MAPT gene.

Initial assessment of the pathogenic mechanisms of the recently identified Alzheimer risk Loci.

Recent genome wide association studies have identified CLU, CR1, ABCA7 BIN1, PICALM and MS4A6A/MS4A6E in addition to the long established APOE, as loci for Alzheimer's disease. We have systematically examined each of these loci to assess whether common coding variability contributes to the risk of disease. We have also assessed the regional expression of all the genes in the brain and whether there is evidence of an eQTL explaining the risk. In agreement with other studies we find that coding variability may explain the ABCA7 association, but common coding variability does not explain any of the other loci. We were not able to show that any of the loci had eQTLs within the power of this study. Furthermore the regional expression of each of the loci did not match the pattern of brain regional distribution in Alzheimer pathology. Although these results are mainly negative, they allow us to start defining more realistic alternative approaches to determine the role of all the genetic loci involved in Alzheimer's disease.

Genome-wide screen identifies rs646776 near sortilin as a regulator of progranulin levels in human plasma.

Recent studies suggest progranulin (GRN) is a neurotrophic factor. Loss-of-function mutations in the progranulin gene (GRN) cause frontotemporal lobar degeneration (FTLD), a progressive neurodegenerative disease affecting ∼10% of early-onset dementia patients. Using an enzyme-linked immunosorbent assay, we previously showed that GRN is detectable in human plasma and can be used to predict GRN mutation status. This study also showed a wide range in plasma GRN levels in non-GRN mutation carriers, including controls. We have now performed a genome-wide association study of 313,504 single-nucleotide polymorphisms (SNPs) in 533 control samples and identified on chromosome 1p13.3 two SNPs with genome-wide significant association with plasma GRN levels (top SNP rs646776; p = 1.7 × 10⁻³°). The association of rs646776 with plasma GRN levels was replicated in two independent series of 508 controls (p = 1.9 × 10⁻¹9) and 197 FTLD patients (p = 6.4 × 10⁻¹²). Overall, each copy of the minor C allele decreased GRN levels by ∼15%. SNP rs646776 is located near sortilin (SORT1), and the minor C allele of rs646776 was previously associated with increased SORT1 mRNA levels. Supporting these findings, overexpression of SORT1 in cultured HeLa cells dramatically reduced GRN levels in the conditioned media, whereas knockdown of SORT1 increased extracellular GRN levels. In summary, we identified significant association of a locus on chromosome 1p13.3 with plasma GRN levels through an unbiased genome-wide screening approach and implicated SORT1 as an important regulator of GRN levels. This finding opens avenues for future research into GRN biology and the pathophysiology of neurodegenerative diseases.

Kinesin-associated protein 3 (KIFAP3) has no effect on survival in a population-based cohort of ALS patients.

It was recently reported that rs1541160 on chromosome 1q24.2 has a marked effect on survival of amyotrophic lateral sclerosis (ALS) patients by influencing KIFAP3 expression. The cohorts used in that study were collected from ALS specialty clinics. We attempted to replicate these findings in a population-based cohort of 504 Italian ALS patients. None of 140 SNPs genotyped within the KIFAP3 locus (including rs1541160) had an effect on survival (log-rank P value for rs1541160 = 0.47) or on gene expression in that region. These data illustrate the complexities associated with analyzing ALS phenotypes for association.

Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain.

A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We present a set of integrated experiments that investigate the effects of common genetic variability on DNA methylation and mRNA expression in four human brain regions each from 150 individuals (600 samples total). We find an abundance of genetic cis regulation of mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation across the genome. We show peak enrichment for cis expression QTLs to be approximately 68,000 bp away from individual transcription start sites; however, the peak enrichment for cis CpG methylation QTLs is located much closer, only 45 bp from the CpG site in question. We observe that the largest magnitude quantitative trait loci occur across distinct brain tissues. Our analyses reveal that CpG methylation quantitative trait loci are more likely to occur for CpG sites outside of islands. Lastly, we show that while we can observe individual QTLs that appear to affect both the level of a transcript and a physically close CpG methylation site, these are quite rare. We believe these data, which we have made publicly available, will provide a critical step toward understanding the biological effects of genetic variation.

An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond.

Science, technology, engineering, mathematics, and medicine (STEMM) fields change rapidly and are increasingly interdisciplinary. Commonly, STEMM practitioners use short-format training (SFT) such as workshops and short courses for upskilling and reskilling, but unaddressed challenges limit SFT's effectiveness and inclusiveness. Education researchers, students in SFT courses, and organizations have called for research and strategies that can strengthen SFT in terms of effectiveness, inclusiveness, and accessibility across multiple dimensions. This paper describes the project that resulted in a consensus set of 14 actionable recommendations to systematically strengthen SFT. A diverse international group of 30 experts in education, accessibility, and life sciences came together from 10 countries to develop recommendations that can help strengthen SFT globally. Participants, including representation from some of the largest life science training programs globally, assembled findings in the educational sciences and encompassed the experiences of several of the largest life science SFT programs. The 14 recommendations were derived through a Delphi method, where consensus was achieved in real time as the group completed a series of meetings and tasks designed to elicit specific recommendations. Recommendations cover the breadth of SFT contexts and stakeholder groups and include actions for instructors (e.g., make equity and inclusion an ethical obligation), programs (e.g., centralize infrastructure for assessment and evaluation), as well as organizations and funders (e.g., professionalize training SFT instructors; deploy SFT to counter inequity). Recommendations are aligned with a purpose-built framework-"The Bicycle Principles"-that prioritizes evidenced-based teaching, inclusiveness, and equity, as well as the ability to scale, share, and sustain SFT. We also describe how the Bicycle Principles and recommendations are consistent with educational change theories and can overcome systemic barriers to delivering consistently effective, inclusive, and career-spanning SFT.

Cell population-specific expression analysis of human cerebellum.

BACKGROUND: Interpreting gene expression profiles obtained from heterogeneous samples can be difficult because bulk gene expression measures are not resolved to individual cell populations. We have recently devised Population-Specific Expression Analysis (PSEA), a statistical method that identifies individual cell types expressing genes of interest and achieves quantitative estimates of cell type-specific expression levels. This procedure makes use of marker gene expression and circumvents the need for additional experimental information like tissue composition. RESULTS: To systematically assess the performance of statistical deconvolution, we applied PSEA to gene expression profiles from cerebellum tissue samples and compared with parallel, experimental separation methods. Owing to the particular histological organization of the cerebellum, we could obtain cellular expression data from in situ hybridization and laser-capture microdissection experiments and successfully validated computational predictions made with PSEA. Upon statistical deconvolution of whole tissue samples, we identified a set of transcripts showing age-related expression changes in the astrocyte population. CONCLUSIONS: PSEA can predict cell-type specific expression levels from tissues homogenates on a genome-wide scale. It thus represents a computational alternative to experimental separation methods and allowed us to identify age-related expression changes in the astrocytes of the cerebellum. These molecular changes might underlie important physiological modifications previously observed in the aging brain.

Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain.

Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied.

Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children.

The clinical presentation overlap between malaria and COVID-19 poses special challenges for rapid diagnosis in febrile children. In this study, we collected RNA-seq data of children with malaria and COVID-19 infection from the public databases as raw data in fastq format paired end files. A group of six, five and two biological replicates of malaria, COVID-19 and healthy donors respectively were used for the study. We conducted differential gene expression analysis to visualize differences in the expression profiles. Using edgeR, we explored particularly gene expression levels in different phenotype groups and found that 1084 genes and 2495 genes were differentially expressed in the malaria samples and COVID-19 samples respectively when compared to healthy controls. The highly expressed gene in the COVID-19 group we found CD151 gene which is facilitates in T cell proliferation, while in the malaria group, among the highly expressed gene we identified GBP5 gene which involved in inflammatory response and response to bacterium. By comparing both malaria and COVID-19 infections, the overlap of 62 differentially expressed genes patterns were identified. Among them, three genes (ENSG00000234998, H2AC19 and TXNDC5) were highly upregulated in both infections. Strikingly, we observed 13 genes such as HBQ1, HBM, SLC7A5, SERINC2, ATP6V0C, ST6GALNAC4, RAD23A, PNPLA2, GAS2L1, TMEM86B, SLC6A8, UBALD1, RNF187 were downregulated in children with malaria and uniquely upregulated in children with COVID-19, thus may be further validated as potential biomarkers to delineate COVID-19 from malaria-related febrile infection. The hemoglobin complexes and lipid metabolism biological pathways are highly expressed in both infections. Our study provided new insights for further investigation of the biological pattern in hosts with malaria and COVID-19 coinfection.

Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive.

The Sequence Read Archive (SRA) is a large public repository that stores raw next-generation sequencing data from thousands of diverse scientific investigations.  Despite its promise, reuse and re-analysis of SRA data has been challenged by the heterogeneity and poor quality of the metadata that describe its biological samples. Recently, the MetaSRA project standardized these metadata by annotating each sample with terms from biomedical ontologies. In this work, we present a pair of Jupyter notebook-based tools that utilize the MetaSRA for building structured datasets from the SRA in order to facilitate secondary analyses of the SRA's human RNA-seq data. The first tool, called the Case-Control Finder, finds suitable case and control samples for a given disease or condition where the cases and controls are matched by tissue or cell type.  The second tool, called the Series Finder, finds ordered sets of samples for the purpose of addressing biological questions pertaining to changes over a numerical property such as time. These tools were the result of a three-day-long NCBI Codeathon in March 2019 held at the University of North Carolina at Chapel Hill.

Characterization of unique PMEPA1 gene splice variants (isoforms d and e) from RNA Seq profiling provides novel insights into prognostic evaluation of prostate cancer.

Prostate cancer is a disease with heterogeneity of multiple gene transcriptomes and biological signaling pathways involved in tumor development. The prostate transmembrane protein, androgen induced 1 (PMEPA1), a multifunctional protein played critical roles in prostate tumorigenesis. The pleiotropic nature of PMEPA1 in modulating androgen and TGF-ß signaling as well as splice variants mechanisms for functional regulations of cancer-associated genes prompted us to investigate the biological roles of PMEPA1 isoforms in prostate cancer. In addition to 4 reported PMEPA1 isoforms (a, b, c and d), one novel isoform PMEPA1-e was identified with RNA Seq analysis of hormone responsive VCaP, LNCaP cells and human prostate cancer samples from The Cancer Genome Atlas (TCGA) dataset. We analyzed the structures, expressions, biological functions and clinical relevance of PMEPA1-e isoform and less characterized isoforms c and d in the context of prostate cancer and AR/TGF-ß signaling. The expression of PMEPA1-e was induced by androgen and AR. In contrast, PMEPA1-d was responsive to TGF-ß and inhibited TGF-ß signaling. Both PMEPA1-d and PMPEA1-e promoted the growth of androgen independent prostate cancer cells. Although PMEPA1-c was responsive to TGF-ß, it was found to have no impacts on cell growth and androgen/TGF-ß signaling. The TCGA data analysis from 499 patients showed higher expression ratios of PMEAP1-b versus -d or -e strongly associated with enhanced Gleason score. Taken together, our findings first time defined the prostate tumorigenesis mediated by PMEPA1-d and -e isoforms, providing novel insights into the new strategies for prognostic evaluation and therapeutics of prostate tumor.

APOE4 is Associated with Differential Regional Vulnerability to Bioenergetic Deficits in Aged APOE Mice.

The ε4 allele of apolipoprotein E (APOE) is the dominant genetic risk factor for late-onset Alzheimer's disease (AD). However, the reason for the association between APOE4 and AD remains unclear. While much of the research has focused on the ability of the apoE4 protein to increase the aggregation and decrease the clearance of Aß, there is also an abundance of data showing that APOE4 negatively impacts many additional processes in the brain, including bioenergetics. In order to gain a more comprehensive understanding of APOE4's role in AD pathogenesis, we performed a transcriptomics analysis of APOE4 vs. APOE3 expression in the entorhinal cortex (EC) and primary visual cortex (PVC) of aged APOE mice. This study revealed EC-specific upregulation of genes related to oxidative phosphorylation (OxPhos). Follow-up analysis utilizing the Seahorse platform showed decreased mitochondrial respiration with age in the hippocampus and cortex of APOE4 vs. APOE3 mice, but not in the EC of these mice. Additional studies, as well as the original transcriptomics data, suggest that multiple bioenergetic pathways are differentially regulated by APOE4 expression in the EC of aged APOE mice in order to increase the mitochondrial coupling efficiency in this region. Given the importance of the EC as one of the first regions to be affected by AD pathology in humans, the observation that the EC is susceptible to differential bioenergetic regulation in response to a metabolic stressor such as APOE4 may point to a causative factor in the pathogenesis of AD.

TET-Catalyzed 5-Carboxylcytosine Promotes CTCF Binding to Suboptimal Sequences Genome-wide.

The mechanisms supporting dynamic regulation of CTCF-binding sites remain poorly understood. Here we describe the TET-catalyzed 5-methylcytosine derivative, 5-carboxylcytosine (5caC), as a factor driving new CTCF binding within genomic DNA. Through a combination of in vivo and in vitro approaches, we reveal that 5caC generally strengthens CTCF association with DNA and facilitates binding to suboptimal sequences. Dramatically, profiling of CTCF binding in a cellular model that accumulates genomic 5caC identified ~13,000 new CTCF sites. The new sites were enriched for overlapping 5caC and were marked by an overall reduction in CTCF motif strength. As CTCF has multiple roles in gene expression, these findings have wide-reaching implications and point to induced 5caC as a potential mechanism to achieve differential CTCF binding in cells.

Transcriptomic profiling of the human brain reveals that altered synaptic gene expression is associated with chronological aging.

Aging is a biologically universal event, and yet the key events that drive aging are still poorly understood. One approach to generate new hypotheses about aging is to use unbiased methods to look at change across lifespan. Here, we have examined gene expression in the human dorsolateral frontal cortex using RNA- Seq to populate a whole gene co-expression network analysis. We show that modules of co-expressed genes enriched for those encoding synaptic proteins are liable to change with age. We extensively validate these age-dependent changes in gene expression across several datasets including the publically available GTEx resource which demonstrated that gene expression associations with aging vary between brain regions. We also estimated the extent to which changes in cellular composition account for age associations and find that there are independent signals for cellularity and aging. Overall, these results demonstrate that there are robust age-related alterations in gene expression in the human brain and that genes encoding for neuronal synaptic function may be particularly sensitive to the aging process.