Large intergenic non-coding RNA-RoR modulates reprogramming of human induced pluripotent stem cells

February 17, 2011The conversion of lineage-committed cells to induced pluripotent stem cells (iPSCs) by reprogramming is accompanied by a global remodeling of the epigenome[superscript 1, 2, 3, 4, 5], resulting in altered patterns of gene expression[superscript 2, 6, 7, 8, 9]. Here we characterize the transcriptional reorganization of large intergenic non-coding RNAs (lincRNAs)[superscript 10, 11] that occurs upon derivation of human iPSCs and identify numerous lincRNAs whose expression is linked to pluripotency. Among these, we defined ten lincRNAs whose expression was elevated in iPSCs compared with embryonic stem cells, suggesting that their activation may promote the emergence of iPSCs. Supporting this, our results indicate that these lincRNAs are direct targets of key pluripotency transcription factors. Using loss-of-function and gain-of-function approaches, we found that one such lincRNA (lincRNA-RoR) modulates reprogramming, thus providing a first demonstration for critical functions of lincRNAs in the derivation of pluripotent stem cells

A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients.

Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML

Mood Induction in Depressive Patients: A Comparative Multidimensional Approach

Anhedonia, reduced positive affect and enhanced negative affect are integral characteristics of major depressive disorder (MDD). Emotion dysregulation, e.g. in terms of different emotion processing deficits, has consistently been reported. The aim of the present study was to investigate mood changes in depressive patients using a multidimensional approach for the measurement of emotional reactivity to mood induction procedures. Experimentally, mood states can be altered using various mood induction procedures. The present study aimed at validating two different positive mood induction procedures in patients with MDD and investigating which procedure is more effective and applicable in detecting dysfunctions in MDD. The first procedure relied on the presentation of happy vs. neutral faces, while the second used funny vs. neutral cartoons. Emotional reactivity was assessed in 16 depressed and 16 healthy subjects using self-report measures, measurements of electrodermal activity and standardized analyses of facial responses. Positive mood induction was successful in both procedures according to subjective ratings in patients and controls. In the cartoon condition, however, a discrepancy between reduced facial activity and concurrently enhanced autonomous reactivity was found in patients. Relying on a multidimensional assessment technique, a more comprehensive estimate of dysfunctions in emotional reactivity in MDD was available than by self-report measures alone and this was unsheathed especially by the mood induction procedure relying on cartoons. The divergent facial and autonomic responses in the presence of unaffected subjective reactivity suggest an underlying deficit in the patients' ability to express the felt arousal to funny cartoons. Our results encourage the application of both procedures in functional imaging studies for investigating the neural substrates of emotion dysregulation in MDD patients. Mood induction via cartoons appears to be superior to mood induction via faces and autobiographical material in uncovering specific emotional dysfunctions in MDD

Facial mimcry and emotion consistency : Influences of memory and context.

This study investigates whether mimicry of facial emotions is a stable response or can instead be modulated and influenced by memory of the context in which the emotion was initially observed, and therefore the meaning of the expression. The study manipulated emotion consistency implicitly, where a face expressing smiles or frowns was irrelevant and to be ignored while participants categorised target scenes. Some face identities always expressed emotions consistent with the scene (e.g., smiling with a positive scene), whilst others were always inconsistent (e.g., frowning with a positive scene). During this implicit learning of face identity and emotion consistency there was evidence for encoding of face-scene emotion consistency, with slower RTs, a reduction in trust, and inhibited facial EMG for faces expressing incompatible emotions. However, in a later task where the faces were subsequently viewed expressing emotions with no additional context, there was no evidence for retrieval of prior emotion consistency, as mimicry of emotion was similar for consistent and inconsistent individuals. We conclude that facial mimicry can be influenced by current emotion context, but there is little evidence of learning, as subsequent mimicry of emotionally consistent and inconsistent faces is similar

Human and machine validation of 14 databases of dynamic facial expressions

With a shift in interest toward dynamic expressions, numerous corpora of dynamic facial stimuli have been developed over the past two decades. The present research aimed to test existing sets of dynamic facial expressions (published between 2000 and 2015) in a cross-corpus validation effort. For this, 14 dynamic databases were selected that featured facial expressions of the basic six emotions (anger, disgust, fear, happiness, sadness, surprise) in posed or spontaneous form. In Study 1, a subset of stimuli from each database (N = 162) were presented to human observers and machine analysis, yielding considerable variance in emotion recognition performance across the databases. Classification accuracy further varied with perceived intensity and naturalness of the displays, with posed expressions being judged more accurately and as intense, but less natural compared to spontaneous ones. Study 2 aimed for a full validation of the 14 databases by subjecting the entire stimulus set (N = 3812) to machine analysis. A FACS-based Action Unit (AU) analysis revealed that facial AU configurations were more prototypical in posed than spontaneous expressions. The prototypicality of an expression in turn predicted emotion classification accuracy, with higher performance observed for more prototypical facial behavior. Furthermore, technical features of each database (i.e., duration, face box size, head rotation, and motion) had a significant impact on recognition accuracy. Together, the findings suggest that existing databases vary in their ability to signal specific emotions, thereby facing a trade-off between realism and ecological validity on the one end, and expression uniformity and comparability on the other