A-to-I RNA editing promotes developmental stage–specific gene and lncRNA expression

Context: The detection and replication of genes involved in psychiatric outcome has been notoriously difficult. Phenotypic measurement has been offered as one explanation, although most of this discussion has focused on problems with binary diagnoses. Objective: This article focuses on two additional components of phenotypic measurement that deserve further consideration in evaluating genetic associations: (1) the measure used to reflect the outcome of interest, and (2) the developmental stage of the study population. We focus our discussion of these issues around the construct of impulsivity and externalizing disorders, and the association of these measures with a specific gene, GABRA2. Design, Setting, and Participants: Data were analyzed from the Collaborative Study on the Genetics of Alcoholism Phase IV assessment of adolescents and young adults (ages 12–26; N = 2,128). Main Outcome Measures: Alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder symptoms were measured by psychiatric interview; Achenbach youth/adult self-report externalizing scale; Zuckerman Sensation-Seeking scale; Barratt Impulsivity scale; NEO extraversion and consciousness. Results: GABRA2 was associated with subclinical levels of externalizing behavior as measured by the Achenbach in both the adolescent and young adult samples. Contrary to previous associations in adult samples, it was not associated with clinical-level DSM symptom counts of any externalizing disorders in these younger samples. There was also association with sensation-seeking and extraversion, but only in the adolescent sample. There was no association with the Barratt impulsivity scale or conscientiousness. Conclusions: Our results suggest that the pathway by which GABRA2 initially confers risk for eventual alcohol problems begins with a predisposition to sensation-seeking early in adolescence. The findings support the heterogeneous nature of impulsivity and demonstrate that both the measure used to assess a construct of interest and the age of the participants can have profound implications for the detection of genetic associations.

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The beta globin 3' enhancer element confers regulated expression on the human gamma globin gene in the human embryonic-fetal erythroleukemia cell line K562

Blood ◽

10.1182/blood.v77.4.855.bloodjournal774855 ◽

1991 ◽

Vol 77 (4) ◽

pp. 855-860

Author(s):

M Donovan-Peluso ◽

S Acuto ◽

D O'Neill ◽

A Hom ◽

A Maggio ◽

...

Keyword(s):

Developmental Stage ◽

Globin Gene ◽

K562 Cells ◽

Specific Gene ◽

Fetal Life ◽

Globin Genes ◽

Beta Globin ◽

Specific Expression ◽

Enhancer Element ◽

Gamma Globin

We have constructed fusion genes comprised of gamma and beta globin elements and globin sequences linked to neomycin resistance (neoR) genes to define the cis acting sequences responsible for developmental stage-specific expression and induction of fetal globin genes in embryonic-fetal erythroleukemia K562 cells. The results indicate that the gamma promoter is required for proper initiation of transcription. However, the accumulation of gamma globin transcripts in response to hemin induction requires the additional presence of either gamma intervening sequence 2 or the 3′ enhancer element of the beta globin gene. Thus, the gamma promoter may provide the elements for developmental stage-specific gene expression during fetal life. By contrast, the beta 3′ enhancer is erythroid-specific but not developmental stage- or gene-specific.

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Exploring the Expression Profile of Long Non-Coding RNA (lncRNA) in Different Acute Myeloid Leukemia (AML) Subtypes: t(8;16)(p11;p13)/MYST3-Crebbp AML Harbors a Distinctive Lncrna Signature

Blood ◽

10.1182/blood.v126.23.1397.1397 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1397-1397 ◽

Cited By ~ 2

Author(s):

Marina Diaz-Beya ◽

Alfons Navarro ◽

Anna Cordeiro ◽

Marta Pratcorona ◽

Joan Castellano ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Transcription Factors ◽

Expression Pattern ◽

Expression Profile ◽

Myeloid Leukemia ◽

Genomic Region ◽

Differentially Expressed ◽

Specific Gene ◽

Lncrna Expression ◽

Acute Myeloid

Abstract Introduction: Long non-coding RNAs (lncRNAs) have recently emerged as important actors in the regulation of multiple cellular processes including cancer. Acute myeloid leukemia (AML) is a heterogeneous disease; most of the main cytogenetic AML subgroups harbor a specific gene expression profile. AML with translocation t(8;16)(p11;p13) (t(8;16) AML) is a subtype with specific clinical and biological characteristics including a distinctive gene (Camós et al, Cancer Research 2006) and microRNA (Díaz-Beyá et al, Leukemia 2013) expression profile. In this translocation, MYST3 on chromosome 8p11 fuses with CREBBP on chromosome 16p13.3. The MYST3-CREBBP fusion protein is able to interact with multiple transcription factors (TF) producing a disturbed transcriptional program. However, the lncRNA expression pattern of different cytogenetic AML subtypes, including t(8;16) AML, have not been described yet. Aims: To examine the expression profile of lncRNAs within different AML subtypes, and to characterize the expression pattern of lncRNAs in t(8;16) AML in comparison to other AML subtypes. Patients and Methods: 46 AML patients, 4 normal bone marrow (NBM) and 3 CD34+ NBM samples were included in the study. Samples included different AML subtypes: intermediate-risk cytogenetic AML (IR-AML, n=18), t(15;17) (APL, n=4), t(8;21) AML (n=4), inv(16) AML(n=2), t(6;9) AML (n=7), AML with monosomal karyotype (n=4), t(3;3) AML (n=1), t(9;11) AML (n=1) and t(8;16) AML (n=5). Within IR-AML patients with a different mutational profile: FLT3-ITD (n=7), NPM1 (n=5), CEBPA (n=7) and DNMT3A (n=6) were included. The lncRNA expression was studied using Affymetrix® Human Gene 2.1 ST platform which includes 9698 lncRNAs transcripts. The filtering and normalization of the array data was performed using oligo package from Bioconductor. Statistical analyses were performed with TiGR MultiExperiment Viewer, BRB tools and R. The Transcription factor Affinity Prediction Web Tool was used to determine the putative transcription factors binding to the differentially expressed lncRNAs promoters. Results: The hierarchical cluster analysis showed that all 4 NBM as well as all 3 CD34+ NBM clustered together according to their lncRNA expression. Interestingly, all 5 t(8;16) AML samples clustered together, as well as the 3 APL, the 7 t(6;9) AML and 5 out of 7 cases with CEBPA mutations. The specific lncRNA signature of APL was composed of 79 differentially expressed lncRNA and t(6;9) AML lncRNA signature comprised of 15 differentially expressed lncRNAs. When we focused on t(8;16) AML lncRNA profile, we identified an specific 113-lncRNA signature in the supervised analysis (Figure). Interestingly, when we analyzed which (TF) had motifs overrepresented in the promoters regions of the t(8;16) AML lncRNA signature, we identified GATA2 as the TF with significantly overrepresented motifs for GATA2 (p<0.001). Interestingly, levels of GATA2 were differentially expressed in t(8;16) AML samples in comparison with other AMLs samples (p<0.001). GATA2 has been described to interact with CREBBP, one of the partners involved in t(8;16) AML. Of note, 4 overexpressed lncRNAs of the signature (linc-HOXA11, HOXA11-AS, HOTTIP and NR_038120) were located in the HOXA genomic region, previously found upregulated in t(8:16) AML. Since several studies suggest an active crosstalk between microRNAs and lncRNAs, we also correlated the expression of these lncRNAs with the microRNA t(8;16) AML profile. We found significant correlation between linc-HOXA11 and miR-222* (R2 =0.996, p=0.003), HOXA11-AS and miR-let-7c (R2=0.994, p=0.006), HOTTIP and miR-196b*(R2=0.958, p=0.041), and NR_038120 with miR-486-3p (R2=0.999, p=0.0004) and miR-19a (R2=0.953, p=0.04). Conclusions: LncRNAs expression profile seems specific of several AML subtypes, including t(8;16) AML. Some of the lncRNAs of this distinctive signature in t(8;16) AML are located in the HOXA genomic region, and correlate with several of the characteristic microRNAs previously described in this entity. Interestingly, we have predicted in silico GATA2, which interacts with CREBBP, as the most significant TF that could potentially regulate this lncRNAs signature. Nonetheless, further investigation is warranted to determine the mechanisms leading to this lncRNA signature and to identify the specific targets of these lncRNAs. Río Hortega CM13/00205, FIS PI13/00999 Disclosures No relevant conflicts of interest to declare.

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RNA editing in inflorescences of wild grapevine unveils association to sex and development

10.1101/2020.03.03.974626 ◽

2020 ◽

Author(s):

Miguel J. N. Ramos ◽

David Faísca-Silva ◽

João L. Coito ◽

Jorge Cunha ◽

Helena Gomes Silva ◽

...

Keyword(s):

Molecular Biology ◽

Developmental Stage ◽

Rna Editing ◽

Genetic Information ◽

Perennial Species ◽

Transcription Level ◽

Central Dogma ◽

Wild Grapevine ◽

First Time

SUMMARYRNA editing challenges the central dogma of molecular biology, by modifying the genetic information at the transcription level. Recent reports, suggesting increased levels of RNA editing in plants, raised questions on the nature and dynamics of such events during development. We here report the occurrence of distinct RNA editing patterns in wild Vitis flowers during development, with twelve possible RNA editing modifications observed for the first time in plants. RNA editing events are gender and developmental stage specific, identical in subsequent years of this perennial species and with distinct nucleotide frequencies neighboring editing sites on the 5’ and 3’ flanks. The transcriptome dynamics unveils a new regulatory layer responsible for gender plasticity enhancement or underling dioecy evolution in Vitis.

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Comprehensive transcriptional profiling of the gastrointestinal tract of ruminants from birth to adulthood reveals strong developmental stage specific gene expression

10.1101/364752 ◽

2018 ◽

Cited By ~ 1

Author(s):

S. J. Bush ◽

M. E. B. McCulloch ◽

C. Muriuki ◽

M. Salavati ◽

G. M. Davis ◽

...

Keyword(s):

Gene Expression ◽

Developmental Stage ◽

Transcriptional Profiling ◽

Ovis Aries ◽

Specific Gene ◽

Gi Tract ◽

Sequencing Data ◽

Tissue Samples ◽

Adult Sheep ◽

Network Cluster

AbstractOne of the most significant physiological challenges to neonatal and juvenile ruminants is the development and establishment of the rumen. Using a subset of RNA-Seq data from our high-resolution atlas of gene expression in sheep (Ovis aries) we have provided the first comprehensive characterisation of transcription of the entire the gastrointestinal (GI) tract during the transition from pre-ruminant to ruminant. The dataset comprises 168 tissue samples from sheep at four different time points (birth, one week, 8 weeks and adult). Using network cluster analysis we illustrate how the complexity of the GI tract is reflected in tissue- and developmental stage-specific differences in gene expression. The most significant transcriptional differences between neonatal and adult sheep were observed in the rumen complex. Differences in transcription between neonatal and adult sheep were particularly evident in macrophage specific signatures indicating they might be driving the observed developmental stage-specific differences. Comparative analysis of gene expression in three GI tract tissues from age-matched sheep and goats revealed species-specific differences in genes involved in immunity and metabolism. This study improves our understanding of the transcriptomic mechanisms involved in the transition from pre-ruminant to ruminant. It highlights key genes involved in immunity, microbe recognition, metabolism and cellular differentiation in the GI tract. The results form a basis for future studies linking gene expression with microbial colonisation of the developing GI tract and will contribute towards identifying genes that underlie immunity in early development, which could be utilised to improve ruminant efficiency and productivity.Reference Numbers for Data in the Public RepositoriesThe raw RNA-Sequencing data are deposited in the European Nucleotide Archive (ENA) under study accessions PRJEB19199 (sheep) and PRJEB23196 (goat). Metadata for all samples is deposited in the EBI BioSamples database under group identifiers SAMEG317052 (sheep) and SAMEG330351 (goat).

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