List Of Pairs Research Articles

Validating a set of Verbal-Paired-Associates word-pair lists for Repeat, Remote, Automated Testing.

Verbal-Paired Associates (VPA) is a widely used memory task, typically administered by a trained rater, with lists of pairs of words learned over up to three attempts, followed by delayed recall. Automated scoring and administration could enable remote testing to monitor change over time but requires parallel forms of the test with equivalent psychometric properties. Here we describe the validation process and memorability characteristics of a group of 12 parallel forms of automated VPA. We generated 15 candidate VPA word-pair lists based on prior modelling. Piloting and simulation-based power calculations suggested a sample size of 375 would provide power of .8 to detect lists where the mean number of errors at the first attempt was more than one error different from the Grand Mean. We recruited 375 healthy participants aged 50-90 years via the Prolific online platform. We used a mixed counterbalanced design with the aim of evaluating the memorability characteristics of the candidate set of word-pair lists. Participants were tested twice on the VPA task using different word-pair lists, separated by a distractor task. All testing was delivered via the NeuroVocalix platform on participants' own devices at home and was administered and scored automatically using automatic speech recognition. Automated scoring results were reviewed by a human experimenter to ensure accuracy. Memory performance in individual word-lists conformed broadly to our model-based expectations, with significant correlations between predicted and observed performance (p < 0.05). We observed expected significant improvement in recall performance with repeated administration, showing learning of word pairs over the task. In this healthy sample there was only modest forgetting at delayed recall. Although performance was broadly equivalent across the different lists, the final selection of lists excluded three with the highest numeric difference in performance versus the overall grand mean, yielding 12 lists for repeated administration. Qualitative feedback showed good levels of acceptability and engagement with the task by participants. We now have a set of 12 parallel-form word-pair lists for use with the automated NeuroVocalix system, with consistent performance characteristics enabling long-term repeat testing remotely and at scale.

Validating a set of Verbal‐Paired‐Associates word‐pair lists for Repeat, Remote, Automated Testing

AbstractBackgroundVerbal‐Paired Associates (VPA) is a widely used memory task, typically administered by a trained rater, with lists of pairs of words learned over up to three attempts, followed by delayed recall. Automated scoring and administration could enable remote testing to monitor change over time but requires parallel forms of the test with equivalent psychometric properties. Here we describe the validation process and memorability characteristics of a group of 12 parallel forms of automated VPA.MethodWe generated 15 candidate VPA word‐pair lists based on prior modelling. Piloting and simulation‐based power calculations suggested a sample size of 375 would provide power of .8 to detect lists where the mean number of errors at the first attempt was more than one error different from the Grand Mean. We recruited 375 healthy participants aged 50–90 years via the Prolific online platform. We used a mixed counterbalanced design with the aim of evaluating the memorability characteristics of the candidate set of word‐pair lists. Participants were tested twice on the VPA task using different word‐pair lists, separated by a distractor task. All testing was delivered via the NeuroVocalix platform on participants’ own devices at home and was administered and scored automatically using automatic speech recognition. Automated scoring results were reviewed by a human experimenter to ensure accuracy.ResultMemory performance in individual word‐lists conformed broadly to our model‐based expectations, with significant correlations between predicted and observed performance (p &lt; 0.05). We observed expected significant improvement in recall performance with repeated administration, showing learning of word pairs over the task. In this healthy sample there was only modest forgetting at delayed recall. Although performance was broadly equivalent across the different lists, the final selection of lists excluded three with the highest numeric difference in performance versus the overall grand mean, yielding 12 lists for repeated administration. Qualitative feedback showed good levels of acceptability and engagement with the task by participants.ConclusionWe now have a set of 12 parallel‐form word‐pair lists for use with the automated NeuroVocalix system, with consistent performance characteristics enabling long‐term repeat testing remotely and at scale.

Measuring drug name similarity to prioritise the application of tall-man lettering in a computerised pharmacy dispensing system

Abstract Introduction Medicine name similarity is a contributory factor to medication errors.1 Published lists exists highlighting medicine pairs that are easily confused; locally a Look-Alike-Sound-Alike (LASA) list has expanded over time with no formal system of triage. A multipronged approach is required to address LASA risks. Tall-Man Lettering (TML) is one intervention that uses uppercase lettering for the dissimilarities in look-alike drug names to alert staff to the risk of error.1 For greatest impact, it should be reserved for pairs with the highest risk for patient safety. Aim This study aimed to use Levenshtein Distance (LD), Bigram (Bi) and Trigram (Tri) methods to prioritise medicine pairs for TML in the Pharmacy dispensing system. Objectives were to: Produce a comprehensive list of medicines pairs; Establish normalised thresholds from LD, Bi and Tri to prioritise medicine pairs for TML; and, measure drug name similarity using validated software2 applying LD, Bi and Tri to medication pairs as a method of triage for orthographic assessment. Methods Approval was obtained by the Trust Pharmacy Research Committee. The need for ethical submission was waived. A LASA list was developed combining medicine name pairs from National Pharmacy Association list3, historical local list and internal incidents where medicine name confusion was cited. Duplicated, branded and non-stock pairs were excluded. A literature search was undertaken to identify published thresholds for accuracy and sensitivity of the methods in the measure of medicine name similarity. LD measures the minimum number of edit operations needed to transform one string into another; Bi and Tri measures the frequency in which two/three similar sequential strings appear within a medicine name respectively. Two assessors independently entered medicine pairs through a validated computer program2 applying LD, Bi and Tri to measure orthographic similarity. Normalised computed similarity scores (between 0-1 where higher values represent increased drug similarity) were collated on Microsoft excel for comparison against thresholds. Results Two-hundred and twelve medicine pairs were identified for review. The literature defined Bi and Tri thresholds at ≥0.3 and ≥0.1 respectively; in absence of this for LD, in-house thresholds were assessed then defined at ≥0.6. LD identified 84 medicine pairs; Bi identified 144; and Tri identified 158; none were uniquely found by LD, four by Bi and 18 by Tri. A final look-alike list with 82 medicine pairs meeting all three thresholds was identified for TML. Discussion/Conclusion Screening using all three methods led to a 61% reduction in medicines pairs allowing prioritisation of TML as an effective intervention based on look-alike pairs with the highest risk of error. This study focused on identifying orthographic similarity in ‘look-alike’ medicine pairs only. With no single intervention available to prevent LASA errors, future work can explore other interventions. In the absence of literature around normalised LD, the definition of an in-house threshold posed to be another limitation and an area where further exploratory work should be considered. As new LASA incidents arise or the Trust catalogue increases, these methods should be applied to triage their look-alike potential, confirming if TML is an appropriate intervention.

KUALA: a machine learning-driven framework for kinase inhibitors repositioning

The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, Kinase binding sites high similarity has a double role. On the one hand it is a critical issue for selectivity, on the other hand, according to poly-pharmacology, a synergistic controlled effect on more than one target could be of great pharmacological interest. Another important aspect of binding similarity is the possibility of exploit it for repositioning of drugs on targets of the same family. In this study, we propose our approach called Kinase drUgs mAchine Learning frAmework (KUALA) to automatically identify kinase active ligands by using specific sets of molecular descriptors and provide a multi-target priority score and a repurposing threshold to suggest the best repurposable and non-repurposable molecules. The comprehensive list of all kinase-ligand pairs and their scores can be found at https://github.com/molinfrimed/multi-kinases.

ALMOST THEOREMS OF HYPERARITHMETIC ANALYSIS

AbstractTheorems of hyperarithmetic analysis (THAs) occupy an unusual neighborhood in the realms of reverse mathematics and recursion theoretic complexity. They lie above all the fixed (recursive) iterations of the Turing Jump but below ATR $_{0}$ (and so $\Pi _{1}^{1}$ -CA $_{0}$ or the hyperjump). There is a long history of proof theoretic principles which are THAs. Until Barnes, Goh, and Shore [ta] revealed an array of theorems in graph theory living in this neighborhood, there was only one mathematical denizen. In this paper we introduce a new neighborhood of theorems which are almost theorems of hyperarithmetic analysis (ATHAs). When combined with ACA $_{0}$ they are THAs but on their own they are very weak. We generalize several conservativity classes ( $\Pi _{1}^{1}$ , r- $\Pi _{2}^{1}$ , and Tanaka) and show that all our examples (and many others) are conservative over RCA $_{0}$ in all these senses and weak in other recursion theoretic ways as well. We provide denizens, both mathematical and logical. These results answer a question raised by Hirschfeldt and reported in Montalbán [2011] by providing a long list of pairs of principles one of which is very weak over RCA $_{0}$ but over ACA $_{0}$ is equivalent to the other which may be strong (THA) or very strong going up a standard hierarchy and at the end being stronger than full second order arithmetic.

Numerical Characterization of the Flow Dynamics and COP Estimation of a Binary Fluid Ejector Ground Source Heat Pump Cooling System

Ejector-based refrigeration systems can make direct use of many forms of thermal energy, such as solar thermal, waste heat, biogas, or natural gas. The present paper describes the estimation of the thermal coefficient of performance (COP) of a binary fluid ejector ground source heat pump (BFE GSHP) cooling system. A method for fluid selection was defined based on the favorable thermo-physical properties of the working fluids. A short list of fluid pairs were selected based on their favorable properties for the BFE GSHP cooling system. Computational Fluid Dynamics (CFD) investigation was conducted for the selected fluid pairs and a suitable ejector geometry is proposed for the high compression ratios encountered in the GSHP applications. The mixing between primary and secondary fluids was investigated using physical analysis of the CFD results. The effect of the fluids’ thermo-physical properties on the system performance was also discussed.

Adipocyte differentiation between obese and lean conditions depends on changes in miRNA expression

Adipogenesis is the process by which precursor cells, preadipocytes (preACs), differentiate into adipocytes (ACs). Here, we investigated differentially expressed miRNAs (DEMs) between the two conditions to understand the regulatory role of miRNAs in altering adipogenesis-related mRNAs. A total of 812 and 748 DEMs were obtained in lean and obese conditions, respectively. The up- and downregulated DEMs were highly concordant with each other in both lean and obese conditions; however, DEMs related to adipogenesis in obese conditions were more strongly downregulated than DEMs related to adipogenesis in lean conditions. There were more obese-specific downregulated DEMs than lean-specific downregulated DEMs; in contrast, there were more lean-specific upregulated DEMs than obese-specific upregulated DEMs. Approximately 45% of DEMs were mapped to the list of miRNA-target mRNA pairs when DEMs were matched to the experimentally validated list of miRNA-target mRNA information of miRTarBase. Many of the target mRNAs were differentially expressed genes (DEGs) with functions in processes such as inflammatory responses and fat metabolism. In particular, a total of 25 miRNAs that target three upregulated adipogenesis-associated inflammatory genes (IL-6, TNF-α, and IL-1β) were commonly altered during adipogenesis. Taken together, our study reveals the types of adipogenesis-related miRNAs that are altered and the degree to which they influence healthy or pathogenic adipogenesis.

Proposing a Set of Far-Field Records for Time History Analysis in Tehran City and Comparison with FEMA-P695 Set Records

The aim of this paper is to prepare a list of appropriate far-field records for the purpose of time history analysis and structural design assessment in Tehran. Accordingly, the study focused on considering all parameters affecting the choice of accelerogram pair for Tehran. For this purpose, a total of 1000 accelerogram pairs of the earthquakes that occurred in Iran during 1978–2010 were studied in terms of the parameters affecting the choice of appropriate accelerogram pair for Tehran, including distance to the epicenter, magnitude, frequency content, earthquake mechanism, soil properties, and configuration of ground layers. An important objective followed by preparing such a list was to appropriately match it to susceptibility and performance levels set in local design standards. For this purpose, seismic, statistical, and analytic studies were performed, finally ending up with a list of appropriate accelerogram pairs for time history analysis and design assessment in Tehran. In this research, to provide a proper understanding of the proposed list’s applied demands on the region’s structures, numerical and statistical studies and comparisons with the FEMA-P695 list have been done.

ExpertRNA: A New Framework for RNA Secondary Structure Prediction

Ribonucleic acid (RNA) is a fundamental biological molecule that is essential to all living organisms, performing a versatile array of cellular tasks. The function of many RNA molecules is strongly related to the structure it adopts. As a result, great effort is being dedicated to the design of efficient algorithms that solve the “folding problem”—given a sequence of nucleotides, return a probable list of base pairs, referred to as the secondary structure prediction. Early algorithms largely rely on finding the structure with minimum free energy. However, the predictions rely on effective simplified free energy models that may not correctly identify the correct structure as the one with the lowest free energy. In light of this, new, data-driven approaches that not only consider free energy, but also use machine learning techniques to learn motifs are also investigated and recently been shown to outperform free energy–based algorithms on several experimental data sets. In this work, we introduce the new ExpertRNA algorithm that provides a modular framework that can easily incorporate an arbitrary number of rewards (free energy or nonparametric/data driven) and secondary structure prediction algorithms. We argue that this capability of ExpertRNA has the potential to balance out different strengths and weaknesses of state-of-the-art folding tools. We test ExpertRNA on several RNA sequence-structure data sets, and we compare the performance of ExpertRNA against a state-of-the-art folding algorithm. We find that ExpertRNA produces, on average, more accurate predictions of nonpseudoknotted secondary structures than the structure prediction algorithm used, thus validating the promise of the approach. Summary of Contribution: ExpertRNA is a new algorithm inspired by a biological problem. It is applied to solve the problem of secondary structure prediction for RNA molecules given an input sequence. The computational contribution is given by the design of a multibranch, multiexpert rollout algorithm that enables the use of several state-of-the-art approaches as base heuristics and allowing several experts to evaluate partial candidate solutions generated, thus avoiding assuming the reward being optimized by an RNA molecule when folding. Our implementation allows for the effective use of parallel computational resources as well as to control the size of the rollout tree as the algorithm progresses. The problem of RNA secondary structure prediction is of primary importance within the biology field because the molecule structure is strongly related to its functionality. Whereas the contribution of the paper is in the algorithm, the importance of the application makes ExpertRNA a showcase of the relevance of computationally efficient algorithms in supporting scientific discovery.

A New Strategy for Multitarget Drug Discovery/Repositioning Through the Identification of Similar 3D Amino Acid Patterns Among Proteins Structures: The Case of Tafluprost and its Effects on Cardiac Ion Channels.

The identification of similar three-dimensional (3D) amino acid patterns among different proteins might be helpful to explain the polypharmacological profile of many currently used drugs. Also, it would be a reasonable first step for the design of novel multitarget compounds. Most of the current computational tools employed for this aim are limited to the comparisons among known binding sites, and do not consider several additional important 3D patterns such as allosteric sites or other conserved motifs. In the present work, we introduce Geomfinder2.0, which is a new and improved version of our previously described algorithm for the deep exploration and discovery of similar and druggable 3D patterns. As compared with the original version, substantial improvements that have been incorporated to our software allow: (i) to compare quaternary structures, (ii) to deal with a list of pairs of structures, (iii) to know how druggable is the zone where similar 3D patterns are detected and (iv) to significantly reduce the execution time. Thus, the new algorithm achieves up to 353x speedup as compared to the previous sequential version, allowing the exploration of a significant number of quaternary structures in a reasonable time. In order to illustrate the potential of the updated Geomfinder version, we show a case of use in which similar 3D patterns were detected in the cardiac ions channels NaV1.5 and TASK-1. These channels are quite different in terms of structure, sequence and function and both have been regarded as important targets for drugs aimed at treating atrial fibrillation. Finally, we describe the in vitro effects of tafluprost (a drug currently used to treat glaucoma, which was identified as a novel putative ligand of NaV1.5 and TASK-1) upon both ion channels’ activity and discuss its possible repositioning as a novel antiarrhythmic drug.

THEOREMS OF HYPERARITHMETIC ANALYSIS AND ALMOST THEOREMS OF HYPERARITHMETIC ANALYSIS

AbstractTheorems of hyperarithmetic analysis (THAs) occupy an unusual neighborhood in the realms of reverse mathematics and recursion-theoretic complexity. They lie above all the fixed (recursive) iterations of the Turing jump but below ATR $_{0}$ (and so $\Pi _{1}^{1}$ -CA $_{0}$ or the hyperjump). There is a long history of proof-theoretic principles which are THAs. Until the papers reported on in this communication, there was only one mathematical example. Barnes, Goh, and Shore [1] analyze an array of ubiquity theorems in graph theory descended from Halin’s [9] work on rays in graphs. They seem to be typical applications of ACA $_{0}$ but are actually THAs. These results answer Question 30 of Montalbán’s Open Questions in Reverse Mathematics [19] and supply several other natural principles of different and unusual levels of complexity.This work led in [25] to a new neighborhood of the reverse mathematical zoo: almost theorems of hyperarithmetic analysis (ATHAs). When combined with ACA $_{0}$ they are THAs but on their own are very weak. Denizens both mathematical and logical are provided. Generalizations of several conservativity classes ( $\Pi _{1}^{1}$ , r- $\Pi _{1}^{1}$ , and Tanaka) are defined and these ATHAs as well as many other principles are shown to be conservative over RCA $_{0}$ in all these senses and weak in other recursion-theoretic ways as well. These results answer a question raised by Hirschfeldt and reported in [19] by providing a long list of pairs of principles one of which is very weak over RCA $_{0}$ but over ACA $_{0}$ is equivalent to the other which may be strong (THA) or very strong going up a standard hierarchy and at the end being stronger than full second-order arithmetic.

On the existence of primitive normal elements of rational form over finite fields of even characteristic

Let [Formula: see text] be an even prime power and [Formula: see text] an integer. By [Formula: see text], we denote the finite field of order [Formula: see text] and by [Formula: see text] its extension of degree [Formula: see text]. In this paper, we investigate the existence of a primitive normal pair [Formula: see text], with [Formula: see text] where the rank of the matrix [Formula: see text] is 2. Namely, we establish sufficient conditions to show that nearly all fields of even characteristic possess such elements, except for [Formula: see text] if [Formula: see text] and [Formula: see text] is odd, and then we provide an explicit small list of possible and genuine exceptional pairs [Formula: see text].

A systematic study of motif pairs that may facilitate enhancer-promoter interactions.

Pairs of interacting transcription factors (TFs) have previously been shown to bind to enhancers and promoters and contribute to their physical interactions. However, to date, we have limited knowledge about such TF pairs. To fill this void, we systematically studied the co-occurrence of TF-binding motifs in interacting enhancer–promoter (EP) pairs in seven human cell lines. We discovered 423 motif pairs that significantly co-occur in enhancers and promoters of interacting EP pairs. We demonstrated that these motif pairs are biologically meaningful and significantly enriched with motif pairs of known interacting TF pairs. We also showed that the identified motif pairs facilitated the discovery of the interacting EP pairs. The developed pipeline, EPmotifPair, together with the predicted motifs and motif pairs, is available at https://doi.org/10.6084/m9.figshare.14192000. Our study provides a comprehensive list of motif pairs that may contribute to EP physical interactions, which facilitate generating meaningful hypotheses for experimental validation.

Calculating Complete Lists of Belyi Pairs

Belyi pairs constitute an important element of the program developed by Alexander Grothendieck in 1972–1984. This program related seemingly distant domains of mathematics; in the case of Belyi pairs, such domains are two-dimensional combinatorial topology and one-dimensional arithmetic geometry. The paper contains an account of some computer-assisted calculations of Belyi pairs with fixed discrete invariants. We present three complete lists of polynomial-like Belyi pairs: (1) of genus 2 and (minimal possible) degree 5; (2) clean ones of genus 1 and degree 8; and (3) clean ones of genus 2 and degree 8. The explanation of some phenomena we encounter in these calculations will hopefully stimulate further development of the dessins d’enfants theory.

Фуга как искусство: между формой и метаморфозами

The article explores the informative value of the most common oppositions “typical vs. individual”, “traditional vs. unique”, “stable vs. dynamic” for the study of evolutionary processes in music. The dichotomous method helps to reveal the dialectic of the general and the individual. On top of that, it is instrumental in discovering new approaches and meanings behind them. At the same time, the concepts of “typical”, “traditional”, and “stable” are understood as a generally accepted, recognizable (at the level of a compositional solution), essential and basic property of the form, while the concept of “metamorphosis” is understood as something special, changeable and non-conventional. The study focuses on the fugue as the key polyphonic form commonly perceived as the embodiment of strict traditions of academicism and, to a certain degree, of conservatism. At the same time, the fugue effectively demonstrates the interaction of technical and aesthetic aspects of the archetype and its numerous stylistic modifications. This is extremely important as regards studies into the evolution of the fugue and the discovery of its internally open and creative nature. Examples of fugues in various composing practices—from the heyday of the Baroque to the present day—show metamorphoses as an organic process that naturally permeates the entire history of the form. Diverse and sometimes paradoxical compositional solutions of the fugue provide a ground to supplement the above list of antonymic pairs with one more opposition: “morph vs. metamorphosis” (“morph” is a Greek word for “form”). This opposition makes it possible to identify the relations between different compositional and structural units of the invariant form and their variants in a modified form.

Sequence, structural and functional conservation among the human and fission yeast ELL and EAF transcription elongation factors.

Transcription elongation is a dynamic and tightly regulated step of gene expression in eukaryotic cells. Eleven nineteen Lysine rich Leukemia (ELL) and ELL Associated Factors (EAF) family of conserved proteins are required for efficient RNA polymerase II-mediated transcription elongation. Orthologs of these proteins have been identified in different organisms, including fission yeast and humans. In the present study, we have examined the sequence, structural and functional conservation between the fission yeast and human ELL and EAF orthologs. Our computational analysis revealed that these proteins share some sequence characteristics, and were predominantly disordered in both organisms. Our functional complementation assays revealed that both human ELL and EAF proteins could complement the lack of ell1+ or eaf1+ in Schizosaccharomyces pombe respectively. Furthermore, our domain mapping experiments demonstrated that both the amino and carboxyl terminal domains of human EAF proteins could functionally complement the S. pombe eaf1 deletion phenotypes. However, only the carboxyl-terminus domain of human ELL was able to partially rescue the phenotypes associated with lack of ell1+ in S. pombe. Collectively, our work adds ELL-EAF to the increasing list of human-yeast complementation gene pairs, wherein the simpler fission yeast can be used to further enhance our understanding of the role of these proteins in transcription elongation and human disease.

Full farsighted rationality

An abstract game consists of a set of states, preferences over states, and an effectivity correspondence specifying what coalitions are allowed to replace one state by another one. Agents are called farsighted if, when deciding whether to support a coalition's move, they compare the status quo to the long term outcome following their deviation. Yet, this definition of farsightedness ignores a coalition's option to remain at the status quo allowing another coalition to move: agents are not fully farsighted. Therefore, we introduce extended expectation functions, which assign to each state a list of pairs consisting of a state and a coalition that is expected to move from the former to the latter. They endow agents with an expectation about what any deviation vis-a-vis maintaining the status quo entails. We impose three rationality axioms and provide a characterization of extended expectation functions that satisfy our axioms in terms of coalition behavior.

NNfold: RNA Secondary Structure Prediction by Deep Learning with an Architecture Imposing Contextual Constraining

Ribonucleic acid (RNA) secondary structures are the determining factor for the many roles RNA plays in life. They can be obtained experimentally by techniques such as X-ray diffraction and NMR imaging. However, given that experimental methods are laborious and expensive, they are not fit for high throughput analysis. Computational prediction algorithms are complementary in predicting the RNA secondary structures for the multitude of known RNA sequences lacking structural information. Here, we introduce NNfold, a novel sequence-based deep neural network method to predict RNA secondary structures. The predictions are made by combining a local and a global model: first, we construct a matrix with the pairing likelihood of each nucleotide by predicting all potential interactions using a convolutional deep learning model. Next, we modify the list of base pairs obtained from the matrix using a second model whose output is used to ensure the contextual validity of the predicted secondary structure. Within the RNA Strand database, NNfold performed much better than thermodynamics-based methods on a diverse set of RNA sequences, improving the average F1 score by 0.20. It is capable of predicting pseudoknots which is a challenging task for other approaches. We also extracted the learned thermodynamic features within the model, which can help advance the construction of new biological models to predict RNA secondary structures. Our developed method is available as a service online at http://www.cbrc.kaust.edu.sa/NNfold/, or as an installable package at https://github.com/ramzan1990/NNfold.

A case of convergent-gene interference in the budding yeast knockout library causing chromosome instability.

To maintain genome stability, organisms depend on faithful chromosome segregation, a process affected by diverse genetic pathways, some of which are not directly linked to mitosis. In this study, we set out to explore one such pathway represented by an undercharacterized gene, SNO1, identified previously in screens of the yeast knockout (YKO) library for mitotic fidelity genes. We found that the causative factor increasing mitotic error rate in the sno1Δ mutant is not loss of the Sno1 protein, but rather perturbation to the mRNA of the neighboring convergent gene, CTF13, encoding an essential component for forming the yeast kinetochore. This is caused by a combination of the Kanamycin resistance gene and the transcriptional terminator used in the YKO library affecting the CTF13 mRNA level and quality . We further provide a list of gene pairs potentially subjected to this artifact, which may be useful for accurate phenotypic interpretation of YKO mutants.

Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease

Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.