Dosage Sensitivity Research Articles

Neurodevelopmental Disorder Caused by Deletion of CHASERR, a lncRNA Gene

SummaryCHASERR encodes a human long noncoding RNA (lncRNA) adjacent to CHD2, a coding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here, we report our findings in three unrelated children with a syndromic, early-onset neurodevelopmental disorder, each of whom had a de novo deletion in the CHASERR locus. The children had severe encephalopathy, shared facial dysmorphisms, cortical atrophy, and cerebral hypomyelination — a phenotype that is distinct from the phenotypes of patients with CHD2 haploinsufficiency. We found that the CHASERR deletion results in increased CHD2 protein abundance in patient-derived cell lines and increased expression of the CHD2 transcript in cis. These findings indicate that CHD2 has bidirectional dosage sensitivity in human disease, and we recommend that other lncRNA-encoding genes be evaluated, particularly those upstream of genes associated with mendelian disorders. (Funded by the National Human Genome Research Institute and others.)

The Clinical Genome Resource (ClinGen): Advancing genomic knowledge through global curation.

The Clinical Genome Resource (ClinGen) is a National Institutes of Health-funded program founded 10 years ago that defines the clinical relevance of genes and variants for medical and research use. ClinGen working groups develop standards for data sharing and curating genomic knowledge. Expert panels, with >2500 active members from 67 countries, curate the validity of monogenic disease relationships, pathogenicity of genetic variation, dosage sensitivity of genes, and actionability of gene-disease interventions using ClinGen standards, infrastructure, and curation interfaces. Results are available on clinicalgenome.org and classified variants are also submitted to ClinVar, a publicly available database hosted by the National Institutes of Health. As of January 2024, over 2700 genes have been curated (2420 gene-disease relationships for validity, 1557 genes for dosage sensitivity, and 447 gene-condition pairs for actionability), and 5161 unique variants have been classified for pathogenicity. New efforts are underway in somatic cancer, complex disease and pharmacogenomics, and a systematic approach to addressing justice, equity, diversity, and inclusion. ClinGen's knowledge can be used to build evidence-based genetic testing panels, interpret copy-number variation, resolve discrepancies in variant classification, guide disclosure of genomic findings to patients, and assess new predictive algorithms. To get involved in ClinGen activities go to https://www.clinicalgenome.org/start.

Site-Blocking Antisense Oligonucleotides as a Mechanism to Fine-Tune MECP2 Expression.

Rett syndrome (RTT) is a neurodevelopmental disorder caused by loss-of-function mutations in the methyl CpG binding protein 2 (MECP2) gene. Despite its severe phenotype, studies in mouse models suggest that restoring MeCP2 levels can reverse RTT symptomology. Nevertheless, traditional gene therapy approaches are hindered by MECP2's narrow therapeutic window, complicating the safe delivery of viral constructs without overshooting the threshold for toxicity. The 3' untranslated region (3'UTR) plays a key role in gene regulation, where factors like miRNAs bind to pre-mRNA and fine-tune expression. Given that each miRNA's contribution is modest, blocking miRNA binding may represent a potential therapeutic strategy for diseases with high dosage sensitivity, like RTT. Here, we present a series of site-blocking antisense oligonucleotides (sbASOs) designed to outcompete repressive miRNA binding at the MECP2 3'UTR. This strategy aims to increase MECP2 levels in patients with missense or late-truncating mutations, where the hypomorphic nature of the protein can be offset by increased abundance. Our results demonstrate that sbASOs can elevate MECP2 levels in a dose-dependent manner in SH-SY5Y and patient fibroblast cell lines, plateauing at levels projected to be safe. Confirming in vivo functionality, sbASO administration in wild-type mice led to significant MeCP2 upregulation and the emergence of phenotypes associated with MeCP2 overexpression. In a T158M neural stem cell model of RTT, sbASO treatment significantly increased MECP2 expression and levels of the downstream effector protein, brain-derived neurotrophic factor (BDNF). These findings highlight the potential of sbASO-based therapies for MECP2-related disorders and advocate for their continued development.

8530 Characterizing the Genomic Effects of Low-Dose Estrogen in Breast Cancer Cells

Abstract Disclosure: H. Kim: None. T.S. Nandu: None. W.L. Kraus: None. Estrogens are steroid hormones that play a key role in a wide range of physiological and pathological processes. The predominant nuclear receptor for estrogens, estrogen receptor-alpha (ERɑ), functions primarily as a nuclear transcription factor (TF) through ligand-dependent activation by 17β-estradiol (E2), the major naturally-occurring estrogen. The physiological levels of E2 are regulated by production, sequestration, and degradation, which can limit the amount of bioavailable E2. However, many studies examining the genomic effects of E2-regulated signaling in cell-based assays used supraphysiological levels of hormone. While this has allowed us to understand the extremes of E2 signaling, it limits our ability to examine cellular functions which operate at lower hormone concentrations. The genomic actions of ligand-bound ERɑ are mediated through transcriptional enhancer formation and function. Alterations in protein and DNA components dictate different enhancer molecular subtypes that specify distinct regulatory mechanisms and downstream cellular phenotypes. How the amount of available hormone affects these genomic processes is unknown. In order to understand the genomic effects of physiological low-dose levels of E2, we have treated MCF-7 ERɑ-positive human breast cancer cells with a range of E2 concentrations and examined the global regulation of gene expression using a multi-omics approach (RNA-seq, ERɑ ChIP-seq, H3K27ac ChIP-seq, PRO-seq, ATAC-seq). Interestingly, we identified gene sets that are preferentially expressed maximally at picomolar or nanomolar concentrations. We are using these genes sets to explore the mechanisms of estrogen-regulated gene expression at physiologically relevant of E2 concentrations. Analysis of nascent RNA transcription using PRO-seq indicates regulation at the transcriptional level. Preliminary ERɑ chromatin binding assays show that while many loci require high levels of E2 for maximum ERɑ binding, others show maximum ERɑ binding at lower doses of E2. Further analyses show distinct enhancer features, such as chromatin accessibility and H3K27ac enrichment, may play a role in determining the response to E2 dosage. We are now determining the molecular mechanisms of dosage sensitivity using a multipronged approach integrating genomics, molecular biology, and cell-based assays. With these studies, we hope to understand a long overlooked physiological aspect of E2 with a comprehensive and global analysis of signal-dependent genomic responses. Presentation: 6/3/2024

9273 Characterizing the Genomic Effects of Low-Dose Estrogen in Breast Cancer Cells

Abstract Disclosure: H. Kim: None. T.S. Nandu: None. W.L. Kraus: None. Estrogens are steroid hormones that play a key role in a wide range of physiological and pathological processes. The predominant nuclear receptor for estrogens, estrogen receptor-alpha (ERɑ), functions primarily as a nuclear transcription factor (TF) through ligand-dependent activation by 17β-estradiol (E2), the major naturally-occurring estrogen. The physiological levels of E2 are regulated by production, sequestration, and degradation, which can limit the amount of bioavailable E2. However, many studies examining the genomic effects of E2-regulated signaling in cell-based assays used supraphysiological levels of hormone. While this has allowed us to understand the extremes of E2 signaling, it limits our ability to examine cellular functions which operate at lower hormone concentrations. The genomic actions of ligand-bound ERɑ are mediated through transcriptional enhancer formation and function. Alterations in protein and DNA components dictate different enhancer molecular subtypes that specify distinct regulatory mechanisms and downstream cellular phenotypes. How the amount of available hormone affects these genomic processes is unknown. In order to understand the genomic effects of physiological low-dose levels of E2, we have treated MCF-7 ERɑ-positive human breast cancer cells with a range of E2 concentrations and examined the global regulation of gene expression using a multi-omics approach (RNA-seq, ERɑ ChIP-seq, H3K27ac ChIP-seq, PRO-seq, ATAC-seq). Interestingly, we identified gene sets that are preferentially expressed maximally at picomolar or nanomolar concentrations. We are using these genes sets to explore the mechanisms of estrogen-regulated gene expression at physiologically relevant of E2 concentrations. Analysis of nascent RNA transcription using PRO-seq indicates regulation at the transcriptional level. Preliminary ERɑ chromatin binding assays show that while many loci require high levels of E2 for maximum ERɑ binding, others show maximum ERɑ binding at lower doses of E2. Further analyses show distinct enhancer features, such as chromatin accessibility and H3K27ac enrichment, may play a role in determining the response to E2 dosage. We are now determining the molecular mechanisms of dosage sensitivity using a multipronged approach integrating genomics, molecular biology, and cell-based assays. With these studies, we hope to understand a long overlooked physiological aspect of E2 with a comprehensive and global analysis of signal-dependent genomic responses. Presentation: 6/3/2024

Dosage sensitivity shapes balanced expression and gene longevity of homoeologs after whole-genome duplications in angiosperms.

Following whole-genome duplication (WGD), duplicate gene pairs (homoeologs) can evolve varying degrees of expression divergence. However, the determinants influencing these relative expression level differences (RFPKM) between homoeologs remain elusive. In this study, we analyzed the RFPKM between homoeologs in 3 angiosperms, Nymphaea colorata, Nelumbo nucifera, and Acorus tatarinowii, all having undergone a single WGD since the origin of angiosperms. Our results show significant positive correlations in RFPKM of homoeologs among tissues within the same species, and among orthologs across these 3 species, indicating convergent expression balance/bias between homoeologous gene copies following independent WGDs. We linked RFPKM between homoeologs to gene attributes associated with dosage-balance constraints, such as protein-protein interactions, lethal-phenotype scores in Arabidopsis (Arabidopsis thaliana) orthologs, domain numbers, and expression breadth. Notably, homoeologs with lower RFPKM often had more interactions and higher lethal-phenotype scores, indicating selective pressures favoring balanced expression. Also, homoeologs with lower RFPKM were more likely to be retained after WGDs in angiosperms. Within Nelumbo, greater RFPKM between homoeologs correlated with increased cis- and trans-regulatory differentiation between species, highlighting the ongoing escalation of gene expression divergence. We further found that expression degeneration in 1 copy of homoeologs is inclined toward nonfunctionalization. Our research highlights the importance of balanced expression, shaped by dosage-balance constraints, in the evolutionary retention of homoeologs in plants.

Copy Number Variants in 30 Saudi Pediatric Patients with Neurodevelopmental Disorders: From Unknown Significance to Diagnosis

Abstract Background: Structural variants (SVs), such as copy number variants (CNVs), insertions, deletions, inversions, and translocations, contribute significantly to genetic diversity and disease etiology. CNVs, which involve the duplication or deletion of DNA segments, are particularly impactful on genes crucial for biological functions and disease processes. Objective: To reassess unclassified SVs that may be underlying unresolved neurodevelopmental disorders among Saudi patients. Methodology: In this retrospective study conducted at King Saud Medical City, Riyadh, Saudi Arabia, 30 probands with neurodevelopmental disorders and congenital malformations were examined using next-generation sequencing methods—exome sequencing, gene panels, or SNP arrays (the Illumina platform). Reclassification was aided by online tools such as VarSome and ClinVar, with pathogenicity assessments using the ClinGen CNV Pathogenicity Calculator based on American College of Medical Genetics and Genomics criteria for CNV loss and gain, and dosage sensitivity. Results: A total of 31 CNVs were analyzed, of which 2 were reclassified: one as benign and the other as pathogenic. The pathogenic CNV, [3p13p12.3 (70411134_75249376) x1], included a deletion of the FOXP1 gene and was associated with an intellectual developmental disorder, language impairment, possible autistic features, psychomotor impairment, developmental regression, and epilepsy. Conclusion: This study underscores the importance of continuously documenting and revisiting unclassified CNVs in accessible databases to enhance the diagnosis and understanding of complex genotype–phenotype relationships. Reclassifying these CNVs not only accelerates diagnostic processes but also enriches our insight into their significant roles in health and disease.

CNVoyant a machine learning framework for accurate and explainable copy number variant classification

The precise classification of copy number variants (CNVs) presents a significant challenge in genomic medicine, primarily due to the complex nature of CNVs and their diverse impact on rare genetic diseases (RGDs). This complexity is compounded by the limitations of existing methods in accurately distinguishing between benign, uncertain, and pathogenic CNVs. Addressing this gap, we introduce CNVoyant, a machine learning-based multi-class framework designed to enhance the clinical significance classification of CNVs. Trained on a comprehensive dataset of 52,176 ClinVar entries across pathogenic, uncertain, and benign classifications, CNVoyant incorporates a broad spectrum of genomic features, including genome position, disease-gene annotations, dosage sensitivity, and conservation scores. Models to predict the clinical significance of copy number gains and losses were trained independently. Final models were selected after testing 29 machine learning architectures and 10,000 hyperparameter combinations each for deletions and duplications via fivefold cross-validation. We validate the performance of CNVoyant by leveraging a comprehensive set of 21,574 CNVs from the DECIPHER database, a highly regarded resource known for its extensive catalog of chromosomal imbalances linked to clinical outcomes. Compared to alternative approaches, CNVoyant shows marked improvements in precision-recall and ROC AUC metrics for binary pathogenic classifications while going one step further, offering multi-classification of clinical significance and corresponding SHAP explainability plots. Additionally, when provided germline CNV calls from real-world RGD cases with diagnostic CNV(s), CNVoyant correctly classified all diagnostic CNVs as having pathogenic significance with high confidence. This large-scale validation demonstrates CNVoyant’s superior accuracy and underscores its potential to aid genomic researchers and clinical geneticists in interpreting the clinical implications of real CNVs.

Interpretation of molecular autopsy findings in 45 sudden unexplained death cases: from coding region to untranslated region.

Sudden unexplained death (SUD) can affect apparently healthy adolescents and young adults with no prior clinical symptoms and no clear diagnostic findings at autopsy. Although primary cardiac arrhythmias have been shown to be the direct cause of death in the majority of SUD cases, the genetic predisposition contributing to SUD remains incompletely understood. Currently, molecular autopsy is considered to be an effective diagnostic tool in the multidisciplinary management of SUD, but the analysis focuses mainly on the coding region and the significance of many identified variants remains unclear. Recent studies have demonstrated the strong association between human disease and genetic variants in untranslated regions (UTRs), highlighting the potential role of UTR variants in the genetic predisposition to SUD. In this study, we searched for UTR variants with likely functional effects in the exome data of 45 SUD cases. Among 244 genes associated with cardiac diseases, three candidate variants with high confidence of pathogenicity were identified in the UTRs of SCO2, CALM2 and TBX3 based on a rigorous filtering strategy. A functional assay further validated the effect of these candidate variants on gene transcriptional activity. In addition, the constraint metrics, intolerance indexes, and dosage sensitivity scores of genes affected by the candidate variants were considered when estimating the consequence of aberrant gene expression. In conclusion, our study presents a practical strategy for UTR variant prioritization and functional annotation, which could improve the interpretation of molecular autopsy findings in SUD cohorts.

Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance

Structural variations (SV) are large (> 50 bp) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) has been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2913 duplications, 8710 insertions, and 13 inversions. 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the under-represented Indian population provides valuable insights that extends beyond Euro-centric human genetic studies.

Phase separation as a possible mechanism for dosage sensitivity

BackgroundDeletion of haploinsufficient genes or duplication of triplosensitive ones results in phenotypic effects in a concentration-dependent manner, and the mechanisms underlying these dosage-sensitive effects remain elusive. Phase separation drives functional compartmentalization of biomolecules in a concentration-dependent manner as well, which suggests a potential link between these two processes, and warrants further systematic investigation.ResultsHere we provide bioinformatic and experimental evidence to show a close link between phase separation and dosage sensitivity. We first demonstrate that haploinsufficient or triplosensitive gene products exhibit a higher tendency to undergo phase separation. Assessing the well-established dosage-sensitive genes HNRNPK, PAX6, and PQBP1 with experiments, we show that these proteins undergo phase separation. Critically, pathogenic variations in dosage-sensitive genes disturb the phase separation process either through reduced protein levels, or loss of phase-separation-prone regions. Analysis of multi-omics data further demonstrates that loss-of-function genetic perturbations on phase-separating genes cause similar dysfunction phenotypes as dosage-sensitive gene perturbations. In addition, dosage-sensitive scores derived from population genetics data predict phase-separating proteins with much better performance than available sequence-based predictors, further illustrating close ties between these two parameters.ConclusionsTogether, our study shows that phase separation is functionally linked to dosage sensitivity and provides novel insights for phase-separating protein prediction from the perspective of population genetics data.

A roadmap to cure CHD2-related disorders.

Coalition to Cure CHD2 (CCC) is a patient advocacy group dedicated to improving the lives of those affected by CHD2-related disorders (CHD2-RD) by increasing education, building community, and accelerating research to uncover a cure. CHD2 is a chromatin remodeler that was identified in 2013 as being a genetic cause for developmental and epileptic encephalopathies. Pathogenic changes in CHD2 can cause treatment-resistant epilepsy, intellectual and developmental delays, and autism, and some individuals experience neurodevelopmental regression. There are currently no targeted therapies available for CHD2-related disorders. Haploinsufficiency of CHD2 is a causative mechanism of disease for individuals with pathogenic variants (primarily truncating) in CHD2. Recently, identification of individuals with deletion of nearby gene CHASERR, a regulator of CHD2 gene expression, has established dosage sensitivity in CHD2 and solidified the CHASERR gene as a potential therapeutic target for CHD2 levels. Through collaboration with our community and our scientific advisory board, CCC has created a Roadmap to Cure CHD2 as our guide toward a targeted cure that can benefit our community, with steps including (1) identifying and defining patients, (2) developing models of CHD2, (3) studying models of CHD2, (4) testing therapies, (5) involving patients, and (6) reaching a cure. Despite some of the challenges inherent in CHD2 research including establishing animal and cellular models that recapitulate the CHD2 clinical phenotype, identifying measurable outcomes and reliable biomarkers, or testing emerging therapeutic approaches, CCC continues to engage with our community to support ongoing research that aligns with our priorities. CCC sees new and exciting opportunities for additional research that can move our community toward our common goal of a cure that will improve the lives of individuals and their families now and in the future.

Improvement of red banana (Musa acuminata) through gamma ray: Determination of gamma ray dosage sensitivity and genetic exploration of dwarf traits through molecular marker

Improvement of red banana (Musa acuminata) through gamma ray: Determination of gamma ray dosage sensitivity and genetic exploration of dwarf traits through molecular marker

Drosophila CASK regulates brain size and neuronal morphogenesis, providing a genetic model of postnatal microcephaly suitable for drug discovery

BackgroundCASK-related neurodevelopmental disorders are untreatable. Affected children show variable severity, with microcephaly, intellectual disability (ID), and short stature as common features. X-linked human CASK shows dosage sensitivity with haploinsufficiency in females. CASK protein has multiple domains, binding partners, and proposed functions at synapses and in the nucleus. Human and Drosophila CASK show high amino-acid-sequence similarity in all functional domains. Flies homozygous for a hypomorphic CASK mutation (∆18) have motor and cognitive deficits. A Drosophila genetic model of CASK-related disorders could have great scientific and translational value.MethodsWe assessed the effects of CASK loss of function on morphological phenotypes in Drosophila using established genetic, histological, and primary neuronal culture approaches. NeuronMetrics software was used to quantify neurite-arbor morphology. Standard nonparametric statistics methods were supplemented by linear mixed effects modeling in some cases. Microfluidic devices of varied dimensions were fabricated and numerous fluid-flow parameters were used to induce oscillatory stress fields on CNS tissue. Dissociation into viable neurons and neurite outgrowth in vitro were assessed.ResultsWe demonstrated that ∆18 homozygous flies have small brains, small heads, and short bodies. When neurons from developing CASK-mutant CNS were cultured in vitro, they grew small neurite arbors with a distinctive, quantifiable “bushy” morphology that was significantly rescued by transgenic CASK+. As in humans, the bushy phenotype showed dosage-sensitive severity. To overcome the limitations of manual tissue trituration for neuronal culture, we optimized the design and operation of a microfluidic system for standardized, automated dissociation of CNS tissue into individual viable neurons. Neurons from CASK-mutant CNS dissociated in the microfluidic system recapitulate the bushy morphology. Moreover, for any given genotype, device-dissociated neurons grew larger arbors than did manually dissociated neurons. This automated dissociation method is also effective for rodent CNS.ConclusionsThese biological and engineering advances set the stage for drug discovery using the Drosophila model of CASK-related disorders. The bushy phenotype provides a cell-based assay for compound screening. Nearly a dozen genes encoding CASK-binding proteins or transcriptional targets also have brain-development mutant phenotypes, including ID. Hence, drugs that improve CASK phenotypes might also benefit children with disorders due to mutant CASK partners.

An RNA-informed dosage sensitivity map reflects the intrinsic functional nature of genes

Understanding dosage sensitivity or why Mendelian diseases have dominant vs. recessive modes of inheritance is crucial for uncovering the etiology of human disease. Previous knowledge of dosage sensitivity is mainly based on observations of rare loss-of-function mutations or copy number changes, which are underpowered due to ultra rareness of such variants. Thus, the functional underpinnings of dosage constraint remain elusive. In this study, we aim to systematically quantify dosage perturbations from cis-regulatory variants in the general population to yield a tissue-specific dosage constraint map of genes and further explore their underlying functional logic. We reveal an inherent divergence of dosage constraints in genes by functional categories with signaling genes (transcription factors, protein kinases, ion channels, and cellular machinery) being dosage sensitive, while effector genes (transporters, metabolic enzymes, cytokines, and receptors) are generally dosage resilient. Instead of being a metric of functional dispensability, we show that dosage constraint reflects underlying homeostatic constraints arising from negative feedback. Finally, we employ machine learning to integrate DNA and RNA metrics to generate a comprehensive, tissue-specific map of dosage sensitivity (MoDs) for autosomal genes.

A Study Review of the Appropriateness of Oral Antibiotic Discharge Prescriptions in the Emergency Department at a Rural Hospital in Mississippi, USA.

Antimicrobial therapy in emergency departments (EDs) is usually empiric in nature. Due to workload and a goal to reduce patient wait times, providers often make rapid decisions regarding antibiotic prescriptions for discharge. A review of current empiric prescribing practices would determine the appropriateness of oral antibiotic discharge prescriptions from EDs. A single-center retrospective electronic health record review of all adult patients with an ED visit from 1 June 2019, to 30 June 2021 who received at least one oral antibiotic prescription at discharge from Baptist Memorial Hospital-Golden Triangle was conducted. The primary outcome was the assessment of appropriate antibiotic discharge prescriptions. The parameters for appropriateness included empiric drug selection, dosage, frequency, duration, and subsequent cultures and sensitivities. Of the 18,289 identified records, 421 patients were randomly sampled with 400 patients included in the final analysis. Of these, 190 (47.8%) discharge oral antibiotic prescriptions were assessed as appropriate and 209 (52.3%) discharge oral antibiotic prescriptions were assessed as inappropriate based on the guideline recommendations. With approximately half of the patients receiving discharge antibiotics that did not fully follow the guideline recommendations, there is a need for provider education, pharmacist intervention, and antimicrobial stewardship programs focusing on this practice.

Ancient roots: A Cambrian explosion of autism susceptibility genes.

Functional gene groups often share unique evolutionary patterns. The present study addresses whether autism susceptibility genes, which frequently share functional overlap, display unusual gene age and conservation patterns compared to other gene groups. Using phylostratigraphically-derived and other genetic data, the investigator explores average gene age, Ohnolog status, evolutionary rate, variation intolerance, and numbers of protein-protein (PPI) interactions across autism susceptibility, nervous system, developmental regulatory, immune, housekeeping, and luxury gene groups. Autism susceptibility genes are unusually old compared to controls, many genes having radiated in the Cambrian period in early vertebrates from whole genome duplication events. They are also tightly conserved across the animal kingdom, are highly variation intolerant, and have more PPI than other genes-all features suggesting extreme dosage sensitivity. The results of the current study indicate that autism susceptibility genes display unique radiation and conservation patterns, which may be a reflection of the major transitions in nervous system evolution that were occurring in early animals and which are still foundational in brain development today.

RILEM TC 277-LHS report: additives and admixtures for modern lime-based mortars

The scope of this collective paper produced in the frame of RILEM TC 277-LHS is to provide sound knowledge on the use of additives/admixtures in lime-based mortars, based on literature and practice. The most widely known additives/admixtures are systematically presented. Their main effects and testing of their performance have been properly tabulated. It is well known that a plethora of additives/admixtures are produced every year by chemical industries. However, when using them in lime-based mortars, compatibility and durability aspects are of primary importance. The introduction of additives/admixtures in lime mortars was imposed by the need to improve important properties of these composites in the fresh and hardened state, namely, workability, durability, early-age and long-term strength and to reduce defects, such as shrinkage and long setting time. In this review paper, the terminology proposed by EN 16572 is followed, designating additive as a constituent added in small quantity to the binder, and admixture as a substance in quantities at least 1% w/w added to the mix. The additives/admixtures are classified according to their action and their validation with specific testing methodologies highlights the dosage sensitivity and the need to develop further standardization. The combination of different additives proposed in several studies resulted as the most promising strategy to enhance the performance of lime mortars. However, recently developed additives and admixtures need to be further evaluated with reference to their compatibility with other mortar constituents, and their effects on the overall mortar and render durability need to be studied. Finally, adopting similar terminology for additives/admixtures in lime and cement-based mortars will facilitate better comparison and assessment issues.

Empirical evidence that complexity limits horizontal gene transfer.

Horizontal gene transfer (HGT) is a major contributor to bacterial genome evolution, generating phenotypic diversity, driving the expansion of protein families, and facilitating the evolution of new phenotypes, new metabolic pathways, and new species. Comparative studies of gene gain in bacteria suggest that the frequency with which individual genes successfully undergo HGT varies considerably and may be associated with the number of protein-protein interactions in which the gene participates, i.e., its connectivity. Two non-exclusive hypotheses have emerged to explain why transferability should decrease with connectivity: the Complexity Hypothesis (Jain, Rivera, & Lake, 1999) and the Balance Hypothesis (Papp, Pál, & Hurst, 2003). These hypotheses predict that the functional costs of HGT arise from a failure of divergent homologues to make normal protein-protein interactions or from gene mis-expression, respectively. Here we describe genome-wide assessments of these hypotheses in which we used 74 existing prokaryotic whole genome shotgun libraries to estimate rates of horizontal transfer of genes from taxonomically diverse prokaryotic donors into E. coli. We show that 1) transferability declines as connectivity increases, 2) transferability declines as the divergence between donor and recipient orthologs increases, and that 3) the magnitude of this negative effect of divergence on transferability increases with connectivity. These effects are particularly robust among the translational proteins, which span the widest range of connectivities. Whereas the Complexity Hypotheses explains all three of these observations, the Balance Hypothesis explains only the first one.

Reanalysis of Chromosomal Microarray Data Using a Smaller Copy Number Variant Call Threshold Identifies Four Cases with Heterozygous Multiexon Deletions of ARID1B, EHMT1, and FOXP1 Genes

Introduction: Chromosomal microarray (CMA) is a highly accurate and established method for detecting copy number variations (CNVs) in clinical genetic testing. CNVs are important etiological factors for disorders such as intellectual disability, developmental delay, and multiple congenital anomalies. Recently developed analytical methods have facilitated the identification of smaller CNVs. Therefore, reanalyzing CMA data using a smaller CNV calling threshold may yield useful information. However, this method was left to the discretion of each institution. Methods: We reanalyzed the CMA data of 131 patients using a smaller CNV call threshold: 50 kb 50 probes for gain and 25 kb 25 probes for loss. We interpreted the reanalyzed CNVs based on the most recently available information. In the reanalysis, we filtered the data using the Clinical Genome Resource dosage sensitivity gene list as an index to quickly and efficiently check morbid genes. Results: The number of copy number loss was approximately 20 times greater, and copy number gain was approximately three times greater compared to those in the previous analysis. We detected new likely pathogenic CNVs in four participants: a 236.5 kb loss within ARID1B, a 50.6 kb loss including EHMT1, a 46.5 kb loss including EHMT1, and an 89.1 kb loss within the FOXP1 gene. Conclusion: The method employed in this study is simple and effective for CMA data reanalysis using a smaller CNV call threshold. Thus, this method is efficient for both ongoing and repeated analyses. This study may stimulate further discussion of reanalysis methodology in clinical laboratories.