Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Forensic Microbiology: When, Where and How

Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.

Bacterial community profiles within the water samples of leptospirosis outbreak areas

Background

Leptospirosis is a water-related zoonotic disease. The disease is primarily transmitted from animals to humans through pathogenic Leptospira bacteria in contaminated water and soil. Rivers have a critical role in Leptospira transmissions, while co-infection potentials with other waterborne bacteria might increase the severity and death risk of the disease.

Methods

The water samples evaluated in this study were collected from four recreational forest rivers, Sungai Congkak, Sungai Lopo, Hulu Perdik, and Gunung Nuang. The samples were subjected to next-generation sequencing (NGS) for the 16S rRNA and in-depth metagenomic analysis of the bacterial communities.

Results

The water samples recorded various bacterial diversity. The samples from the Hulu Perdik and Sungai Lopo downstream sampling sites had a more significant diversity, followed by Sungai Congkak. Conversely, the upstream samples from Gunung Nuang exhibited the lowest bacterial diversity. Proteobacteria, Firmicutes, and Acidobacteria were the dominant phyla detected in downstream areas. Potential pathogenic bacteria belonging to the genera Burkholderiales and Serratia were also identified, raising concerns about co-infection possibilities. Nevertheless, Leptospira pathogenic bacteria were absent from all sites, which is attributable to its limited persistence. The bacteria might also be washed to other locations, contributing to the reduced environmental bacterial load.

Conclusion

The present study established the presence of pathogenic bacteria in the river ecosystems assessed. The findings offer valuable insights for designing strategies for preventing pathogenic bacteria environmental contamination and managing leptospirosis co-infections with other human diseases. Furthermore, closely monitoring water sample compositions with diverse approaches, including sentinel programs, wastewater-based epidemiology, and clinical surveillance, enables disease transmission and outbreak early detections. The data also provides valuable information for suitable treatments and long-term strategies for combating infectious diseases.

Research Gaps in Pediatric Heart Failure: Defining the Gaps and Then Closing Them Over the Next Decade

Given the numerous opportunities and the wide knowledge gaps in pediatric heart failure, an international group of pediatric heart failure experts with diverse backgrounds were invited and tasked with identifying research gaps in each pediatric heart failure domain that scientists and funding agencies need to focus on over the next decade.

A Comprehensive Review of Genetic Variations in Collagen-Encoding Genes and Their Implications in Intervertebral Disc Degeneration

This comprehensive review examines the intricate relationship between genetic variations in collagen-encoding genes and their implications in intervertebral disc degeneration (IVDD). Intervertebral disc degeneration is a prevalent spinal condition characterized by structural and functional changes in intervertebral discs (IVDs), and understanding its genetic underpinnings is crucial for advancing diagnostic and therapeutic strategies. The review begins by exploring the background and importance of collagen in IVDs, emphasizing its role in providing structural integrity. It then delves into the significance of genetic variations within collagen-encoding genes, categorizing and discussing their potential impact on disc health. The methods employed in studying these variations, such as genome-wide association studies (GWASs) and next-generation sequencing (NGS), are also reviewed. The subsequent sections analyze existing literature to establish associations between genetic variations and IVDD, unraveling molecular mechanisms linking genetic factors to disc degeneration. The review concludes with a summary of key findings, implications for future research and clinical practice, and a reflection on the importance of understanding genetic variations in collagen-encoding genes to diagnose and treat IVDD. The insights gleaned from this review contribute to our understanding of IVDD and hold promise for the development of personalized interventions based on individual genetic profiles.

Next-Generation Sequencing to Study the DNA Interaction

Next-generation sequencing (NGS) has transformed genomics by allowing researchers to sequence DNA and RNA at highest speed, accuracy, and cost-effectiveness. Researchers investigate DNA interactions with the help next-generation sequencing with a great deal of information. Over the last decade, NGS technologies have advanced significantly, with the development of several platforms, including Illumina, PacBio, and Oxford Nanopore, each offering distinct advantages and uses. The use of next-generation sequencing (NGS) has aided in the discovery of genetic variations, gene expression patterns, and epigenetic modifications connected with a variety of diseases, including cancer, neurological disorders, and infectious diseases. By identifying these regions, we can control the expression of genes, cellular signaling pathways, and other key biological processes. NGS is an effective method for researching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting in new discoveries and applications in medicine, environmental sciences, and other fields.

The Role of Personalized Medicine in Companion Animal Cardiology

Cardiomyopathies remain one of the most common inherited cardiac diseases in both human and veterinary patients. To date, well over 100 mutated genes are known to cause cardiomyopathies in humans with only a handful known in cats and dogs. This review highlights the need and use of personalized one-health approaches to cardiovascular case management and advancement in pharmacogenetic-based therapy in veterinary medicine. Personalized medicine holds promise in understanding the molecular basis of disease and ultimately will unlock the next generation of targeted novel pharmaceuticals and aid in the reversal of detrimental effects at a molecular level.

Comprehensive clinical assays for molecular diagnostics of gliomas: the current state and future prospects

Glioma is one of the most intractable types of cancer, due to delayed diagnosis at advanced stages. The clinical symptoms of glioma are unclear and due to a variety of glioma subtypes, available low-invasive testing is not effective enough to be introduced into routine medical laboratory practice. Therefore, recent advances in the clinical diagnosis of glioma have focused on liquid biopsy approaches that utilize a wide range of techniques such as next-generation sequencing (NGS), droplet-digital polymerase chain reaction (ddPCR), and quantitative PCR (qPCR). Among all techniques, NGS is the most advantageous diagnostic method. Despite the rapid cheapening of NGS experiments, the cost of such diagnostics remains high. Moreover, high-throughput diagnostics are not appropriate for molecular profiling of gliomas since patients with gliomas exhibit only a few diagnostic markers. In this review, we highlighted all available assays for glioma diagnosing for main pathogenic glioma DNA sequence alterations. In the present study, we reviewed the possibility of integrating routine molecular methods into the diagnosis of gliomas. We state that the development of an affordable assay covering all glioma genetic aberrations could enable early detection and improve patient outcomes. Moreover, the development of such molecular diagnostic kits could potentially be a good alternative to expensive NGS-based approaches.

Identification of Markers Associated with Wheat Dwarf Virus (WDV) Tolerance/Resistance in Barley (Hordeum vulgare ssp. vulgare) Using Genome-Wide Association Studies

Wheat dwarf virus (WDV) causes an important vector transmitted virus disease, which leads to significant yield losses in barley production. Due to the fact that, at the moment, no plant protection products are approved to combat the vector Psammotettix alienus, and this disease cannot be controlled by chemical means, the use of WDV-resistant or -tolerant genotypes is the most efficient method to control and reduce the negative effects of WDV on barley growth and production. In this study, a set of 480 barley genotypes were screened to identify genotypic differences in response to WDV, and five traits were assessed under infected and noninfected conditions. In total, 32 genotypes showed resistance or tolerance to WDV. Subsequently, phenotypic data of 191 out of 480 genotypes combined with 34,408 single-nucleotide polymorphisms (SNPs) were used for a genome-wide association study to identify quantitative trait loci (QTLs) and markers linked to resistance/tolerance to WDV. Genomic regions significantly associated with WDV resistance/tolerance in barley were identified on chromosomes 3H, 4H, 5H, and 7H for traits such as relative virus titer, relative performance of total grain weight, plant height, number of ears per plant, and thousand grain weight.

Learning from mistakes: challenges in finding holobiont factors from environmental samples and the importance of methodological consistency

The cause of harmful algal blooms has been a mystery, but research to elucidate its mechanism has progressed over the years thanks to genetic technologies. We have monitored toxic algae and its associated bacteria as a community, the so-called 'holobiont' in Chilean coastal waters for years from the perspective of bacteria as an algal bloom driver. This review describes the challenges of holobiont monitoring, specifically with respect to standardizing and compliance with the monitoring protocols to collect reliable and sustainable data. Further, we suggest adopting the high-throughput sequencing (HTS) standard operating procedure (SOP) by the International Human Microbiome to improve the quality and consistency of holobiont monitoring in the harmful algal world.

A classification of genes involved in normal and delayed male puberty

Puberty is a pivotal biological process that completes sexual maturation to achieve full reproductive capability. It is a major transformational period of life, whose timing is strongly affected by genetic makeup of the individual, along with various internal and external factors. Although the exact mechanism for initiation of the cascade of molecular events that culminate in puberty is not yet known, the process of pubertal onset involves interaction of numerous complex signaling pathways of hypothalamo-pituitary-testicular (HPT) axis. We developed a classification of the mechanisms involved in male puberty that allowed placing many genes into physiological context. These include (i) hypothalamic development during embryogenesis, (ii) synaptogenesis where gonadotropin releasing hormone (GnRH) neurons form neuronal connections with suprahypothalamic neurons, (iii) maintenance of neuron homeostasis, (iv) regulation of synthesis and secretion of GnRH, (v) appropriate receptors/proteins on neurons governing GnRH production and release, (vi) signaling molecules activated by the receptors, (vii) the synthesis and release of GnRH, (viii) the production and release of gonadotropins, (ix) testicular development, (x) synthesis and release of steroid hormones from testes, and (xi)the action of steroid hormones in downstream effector tissues. Defects in components of this system during embryonic development, childhood/adolescence, or adulthood may disrupt/nullify puberty, leading to long-term male infertility and/or hypogonadism. This review provides a list of 598 genes involved in the development of HPT axis and classified according to this schema. Furthermore, this review identifies a subset of 75 genes for which genetic mutations are reported to delay or disrupt male puberty.

Evaluation of in silico pathogenicity prediction tools for the classification of small in-frame indels

BACKGROUND

The use of in silico pathogenicity predictions as evidence when interpreting genetic variants is widely accepted as part of standard variant classification guidelines. Although numerous algorithms have been developed and evaluated for classifying missense variants, in-frame insertions/deletions (indels) have been much less well studied.

METHODS

We created a dataset of 3964 small (< 100 bp) indels predicted to result in in-frame amino acid insertions or deletions using data from gnomAD v3.1 (minor allele frequency of 1-5%), ClinVar and the Deciphering Developmental Disorders (DDD) study. We used this dataset to evaluate the performance of nine pathogenicity predictor tools: CADD, CAPICE, FATHMM-indel, MutPred-Indel, MutationTaster2021, PROVEAN, SIFT-indel, VEST-indel and VVP.

RESULTS

Our dataset consisted of 2224 benign/likely benign and 1740 pathogenic/likely pathogenic variants from gnomAD (n = 809), ClinVar (n = 2882) and, DDD (n = 273). We were able to generate scores across all tools for 91% of the variants, with areas under the ROC curve (AUC) of 0.81-0.96 based on the published recommended thresholds. To avoid biases caused by inclusion of our dataset in the tools' training data, we also evaluated just DDD variants not present in either gnomAD or ClinVar (70 pathogenic and 81 benign). Using this subset, the AUC of all tools decreased substantially to 0.64-0.87. Several of the tools performed similarly however, VEST-indel had the highest AUCs of 0.93 (full dataset) and 0.87 (DDD subset).

CONCLUSIONS

Algorithms designed for predicting the pathogenicity of in-frame indels perform well enough to aid clinical variant classification in a similar manner to missense prediction tools.

Economic evaluation of next-generation sequencing techniques in diagnosis of genetic disorders: A systematic review

In recent years, massively parallel sequencing or next generation sequencing (NGS) has considerably changed both the research and diagnostic fields, and rapid developments have led to the combination of NGS techniques in clinical practice, ease of analysis, and detection of genetic mutations. This article aimed at reviewing the economic evaluation studies of the NGS techniques in the diagnosis of genetic diseases. In this systematic review, scientific databases (PubMed, EMBASE, Web of Science, Cochrane, Scopus, and CEA registry) were searched from 2005 to 2022 to identify the related literature on the economic evaluation of NGS techniques in the diagnosis of genetic diseases. Full-text reviews and data extraction were all performed by two independent researchers. The quality of all the articles included in this study was evaluated using the Checklist of Quality of Health Economic Studies (QHES). Out of 20 521 screened abstracts, 36 studies met the inclusion criteria. The mean score of the QHES checklist for the studies was 0.78 (high quality). Seventeen studies were conducted based on modeling. Cost-effectiveness analysis, cost-utility analysis, and cost-minimization analysis were done in 26 studies, 13 studies, and 1 study, respectively. Based on the available evidence and findings, exome sequencing, which is one of the NGS techniques, could have the potential to be used as a cost-effective genomic test to diagnose children with suspected genetic diseases. The results of the present study support the cost-effectiveness of exome sequencing in diagnosing suspected genetic disorders. However, the use of exome sequencing as a first- or second-line diagnostic test is still controversial. Most studies have been conducted in high-income countries, and research on the cost-effectiveness of NGS methods is recommended in low- and middle-income countries.

Liquid biopsy in pediatric brain tumors

Malignant primary brain tumors are the most common cancer in children aged 0-14 years, and are the most common cause of death among pediatric cancer patients. Compared to other cancers, pediatric brain tumors have been difficult to diagnose and study given the high risk of intracranial biopsy penetrating through vital midline structures, where the majority of pediatric brain tumors originate (Ostrom et al., 2015). Furthermore, the vast majority of these tumors recur. With limitations in the ability to monitor using clinical and radiographic methods alone, minimally invasive methods such as liquid biopsy will be crucial to our understanding and treatment. Liquid biopsy of blood, urine, and cerebrospinal fluid (CSF) can be used to sample cfDNA, ctDNA, RNA, extracellular vesicles, and tumor-associated proteins. In the past year, four seminal papers have made significant advances in the use of liquid biopsy in pediatric brain tumor patients (Liu et al., 2021; Cantor et al., 2022; Miller et al., 2022; Pagès et al., 2022). In this review, we integrate the results of these studies and others to discuss how the newest technologies in liquid biopsy are being developed for molecular diagnosis and treatment response in pediatric brain tumors.

Integrating Cutting-Edge Methods to Oral Cancer Screening, Analysis, and Prognosis

Oral cancer (OC) has become a significant barrier to health worldwide due to its high morbidity and mortality rates. OC is among the most prevalent types of cancer that affect the head and neck region, and the overall survival rate at 5 years is still around 50%. Moreover, it is a multifactorial malignancy instigated by genetic and epigenetic variabilities, and molecular heterogeneity makes it a complex malignancy. Oral potentially malignant disorders (OPMDs) are often the first warning signs of OC, although it is challenging to predict which cases will develop into malignancies. Visual oral examination and histological examination are still the standard initial steps in diagnosing oral lesions; however, these approaches have limitations that might lead to late diagnosis of OC or missed diagnosis of OPMDs in high-risk individuals. The objective of this review is to present a comprehensive overview of the currently used novel techniques viz., liquid biopsy, next-generation sequencing (NGS), microarray, nanotechnology, lab-on-a-chip (LOC) or microfluidics, and artificial intelligence (AI) for the clinical diagnostics and management of this malignancy. The potential of these novel techniques in expanding OC diagnostics and clinical management is also reviewed.

Electrochemical DNA Biosensor Based on Immobilization of a Non-Modified ssDNA Using Phosphoramidate-Bonding Strategy and Pencil Graphite Electrode Modified with AuNPs/CB and Self-Assembled Cysteamine Monolayer

The present paper describes an alternative approach to the traditionally used covalent immobilization methods that require cost-intensive and complicated chemistry modification of a single-stranded DNA (ssDNA) capture probe. The low-cost pencil graphite electrode (PGE) modified with carbon black (CB) and gold nanoparticles (AuNPs) was used as an electrochemical platform and the non-modified ssDNA was immobilized on a self-assembled cysteamine modified AuNPs/CB-PGE through a phosphoramidate bond between the 5'-terminal phosphate group of ssDNA and the primary amine group of cysteamine. The microRNA-21 was used as a target model in the fabrication of this electrochemical DNA biosensor and the hybridization process with the complementary probe was monitored by differential pulse voltammetry using methylene blue (MB) as an electrochemical hybridization indicator. The decreased reduction peak current of MB shows a good linear correlation with the increased concentration of microRNA-21 target sequences because the MB signal is determined by the amount of exposed guanine bases. The linear range of the fabricated DNA biosensor was from 1.0 × 10^-8 to 5.0 × 10^-7 M with a detection limit of 1.0 × 10^-9 M. These results show that the covalent immobilization of a non-modified ssDNA capture probe through a phosphoramidate-bonding strategy could serve as a cost-effective and versatile approach for the fabrication of DNA biosensors related to a wide range of applications that cover the fields of medical diagnostic and environmental monitoring. The fabricated electrochemical DNA biosensor was used to analyze microRNA-21 in a (spiked) human serum sample and it showed satisfactory and encouraging results as an electrochemical DNA biosensor platform.

Molecular Breeding and Drought Tolerance in Chickpea

Cicer arietinum L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to the Leguminosae family. Drought is the utmost common abiotic factor on plants, distressing their water status and limiting their growth and development. Chickpea genotypes have the natural ability to fight drought stress using certain strategies viz., escape, avoidance and tolerance. Assorted breeding methods, including hybridization, mutation, and marker-aided breeding, genome sequencing along with omics approaches, could be used to improve the chickpea germplasm lines(s) against drought stress. Root features, for instance depth and root biomass, have been recognized as the greatest beneficial morphological factors for managing terminal drought tolerance in the chickpea. Marker-aided selection, for example, is a genomics-assisted breeding (GAB) strategy that can considerably increase crop breeding accuracy and competence. These breeding technologies, notably marker-assisted breeding, omics, and plant physiology knowledge, underlined the importance of chickpea breeding and can be used in future crop improvement programmes to generate drought-tolerant cultivars(s).

CTLA-4 Insufficiency due to a Novel CTLA-4 Deletion, Identified through Copy Number Variation Analysis

BACKGROUND

The diagnostic yield of next-generation sequencing (NGS) technologies in the diagnosis of monogenic inborn errors of immunity (IEI) remains limited, rarely exceeding 30%. Monoallelic pathogenic germline variants in cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) result in variable immunodeficiency and immune dysregulation. The genetic diagnosis of CTLA-4 insufficiency can affect follow-up procedures and may lead to consideration of treatment with CTLA-4-Ig.

OBJECTIVES

The aim of the study was to identify the genetic cause of familial immunodeficiency and immune dysregulation in cases where single nucleotide variant analysis of short-read NGS data yielded no diagnostic result.

METHODS

Analysis of copy number variants (CNVs) was applied on short-read NGS data.

RESULTS

We identified a novel monoallelic deletion-insertion variant in CTLA-4 (c.445_568-544delinsTTTGCGATTG) resulting in familial autoimmunity. This is the second larger scale variant in CTLA-4, which despite consistently reduced expression of CTLA-4 displayed variable expressivity, ranging from typical juvenile idiopathic arthritis to common variable immunodeficiency-like immunodeficiency.

CONCLUSIONS

Our report suggests the significance of integration of CNV analysis in routine evaluation of NGS, which may increase its diagnostic yield in IEI.

Genetic screening of Chinese patients with hydatidiform mole by whole-exome sequencing and comprehensive analysis

PURPOSE

We aim to explore if there are any other candidate genetic variants in patients with a history of at least one hydatidiform mole (HM) besides the well-known variants in NLRP7 and KHDC3L.

METHODS

The diagnosis of HM type was based on histopathology, and available HM tissues were collected for short tandem repeat (STR) genotyping to verify the diagnosis. DNA extracted from blood samples or decidual tissues of the 78 patients was subjected to whole-exome sequencing (WES).

RESULTS

We identified five novel variants in NLRP7, two novel variants in KHDC3L, and a chromosome abnormality covering the KHDC3L locus among patients with HM. We found that patients with HM who carried heterozygous variants in KHDC3L had a chance of normal pregnancy. We also detected four novel genetic variants in candidate genes that may be associated with HM.

CONCLUSION

Our study enriched the spectrum of variants in NLRP7 and KHDC3L in Chinese HM patients and provided a new outlook on the effects of heterozygous variants in KHDC3L. The novel candidate genetic variants associated with HMs reported in this study will also contribute to further research on HMs.

Computational approaches for predicting variant impact: An overview from resources, principles to applications

One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.

Listeria monocytogenes in foods-From culture identification to whole-genome characteristics

Listeria monocytogenes is an important foodborne pathogen, which is able to persist in the food production environments. The presence of these bacteria in different niches makes them a potential threat for public health. In the present review, the current information on the classical and alternative methods used for isolation and identification of L. monocytogenes in food have been described. Although these techniques are usually simple, standardized, inexpensive, and are routinely used in many food testing laboratories, several alternative molecular-based approaches for the bacteria detection in food and food production environments have been developed. They are characterized by the high sample throughput, a short time of analysis, and cost-effectiveness. However, these methods are important for the routine testing toward the presence and number of L. monocytogenes, but are not suitable for characteristics and typing of the bacterial isolates, which are crucial in the study of listeriosis infections. For these purposes, novel approaches, with a high discriminatory power to genetically distinguish the strains during epidemiological studies, have been developed, e.g., whole-genome sequence-based techniques such as NGS which provide an opportunity to perform comparison between strains of the same species. In the present review, we have shown a short description of the principles of microbiological, alternative, and modern methods of detection of L. monocytogenes in foods and characterization of the isolates for epidemiological purposes. According to our knowledge, similar comprehensive papers on such subject have not been recently published, and we hope that the current review may be interesting for research communities.

Haplotype phasing of a bipolar disorder pedigree revealed rare multiple mutations of SPOCD1 gene in the 1p36-35 susceptibility locus

BACKGROUND

The etiology of bipolar disorder (BD) is poorly understood. Considering the complexity of BD, pedigree-based sequencing studies focusing on haplotypes at specific loci may be practical to discover high-impact risk variants. This study comprehensively examined the haplotype sequence at 1p36-35 BD and recurrent depressive disorder (RDD) susceptibility loci.

METHODS

We surveyed BD families in Okinawa, Japan. We performed linkage analysis and determined the phased sequence of the affected haplotype using whole genome sequencing. We filtered rare missense variants on the haplotype. For validation, we conducted a case-control genetic association study on approximately 3000 Japanese subjects.

RESULTS

We identified a three-generation multiplex pedigree with BD and RDD. Strikingly, we identified a significant linkage with mood disorders (logarithm of odds [LOD] = 3.61) at 1p36-35, supported in other ancestry studies. Finally, we determined the entire sequence of the 6.4-Mb haplotype shared by all affected subjects. Moreover, we found a rare triplet of missense variants in the SPOCD1 gene on the haplotype. Notably, despite the rare frequency, one heterozygote with multiple SPOCD1 variants was identified in an independent set of 88 BD type I genotyping samples.

LIMITATIONS

The 1p36-35 sequence was obtained from only a single pedigree. The replicate sample was small. Short-read sequencing might miss structural variants. A polygenic risk score was not analyzed.

CONCLUSION

The 1p36-35 haplotype sequence may be valuable for future BD variant studies. In particular, SPOCD1 is a promising candidate gene and should be validated.

Incomplete lineage sorting and reticulate evolution mask species relationships in Brunelliaceae, an Andean family with rapid, recent diversification

PREMISE

To date, phylogenetic relationships within the monogeneric Brunelliaceae have been based on morphological evidence, which does not provide sufficient phylogenetic resolution. Here we use target-enriched nuclear data to improve our understanding of phylogenetic relationships in the family.

METHODS

We used the Angiosperms353 toolkit for targeted recovery of exonic regions and supercontigs (exons + introns) from low copy nuclear genes from 53 of 70 species in Brunellia, and several outgroup taxa. We removed loci that indicated biased inference of relationships and applied concatenated and coalescent methods to infer Brunellia phylogeny. We identified conflicts among gene trees that may reflect hybridization or incomplete lineage sorting events and assessed their impact on phylogenetic inference. Finally, we performed ancestral-state reconstructions of morphological traits and assessed the homology of character states used to define sections and subsections in Brunellia.

RESULTS

Brunellia comprises two major clades and several subclades. Most of these clades/subclades do not correspond to previous infrageneric taxa. There is high topological incongruence among the subclades across analyses.

CONCLUSIONS

Phylogenetic reconstructions point to rapid species diversification in Brunelliaceae, reflected in very short branches between successive species splits. The removal of putatively biased loci slightly improves phylogenetic support for individual clades. Reticulate evolution due to hybridization and/or incomplete lineage sorting likely both contribute to gene-tree discordance. Morphological characters used to define taxa in current classification schemes are homoplastic in the ancestral character-state reconstructions. While target enrichment data allows us to broaden our understanding of diversification in Brunellia, the relationships among subclades remain incompletely understood.

wde, calpA, if, dap160, and poe genes knock down Drosophila models exhibit neurofunctional deficit

Intellectual disability (ID) is a heterogeneous disorder with high prevalence and remarkable social and cost burdens. Novel genetic variants of ATF7IP, CAPN9, ITGAV, ITSN1, and UBR4 genes are reported to be associated with the ID among Iranian families. However, in vivo validation is required to confirm the functional role of these variants in ID development. Drosophila melanogaster is a convenient model for such functional investigations as its genome bears ortholog of more than 75% of the disease-causing genes in human and represents numerous approaches to study defects in neuronal function. In this connection, RNAi gene silencing was applied to wde, calpA, if, dap160, and poe genes, the Drosophila ortholog of the selected human genes, and then consequent structural and functional changes in neurons were studied by means of immunohistochemistry and confocal microscopy of mushroom bodies (MBs) and validated behavioural assays including larvae and adult conditioning learning and memories, and ethanol sensitivity. Down-regulation of these genes led to neuronal loss which was evident by decline in total fluorescent signal intensity in micrographs of MBs structure. The gene silencing caused neuronal dysfunction and induction of ID-like symptoms manifested by deficits in larval preference learning, and short-term olfactory memory and courtship suppression learning in adults. Moreover, the RNAi flies showed higher sensitivity to ethanol vapour. Interestingly, the poe knock-down flies exhibited the most severe phenotypes among other genes. Altogether, we believe this study is first-of-its-kind and findings are highly applicable to confirm pathogenecity of the selected ID gene variants in Iranian population.

Genetics Matters: Voyaging from the Past into the Future of Humanity and Sustainability

The understanding of how genetic information may be inherited through generations was established by Gregor Mendel in the 1860s when he developed the fundamental principles of inheritance. The science of genetics, however, began to flourish only during the mid-1940s when DNA was identified as the carrier of genetic information. The world has since then witnessed rapid development of genetic technologies, with the latest being genome-editing tools, which have revolutionized fields from medicine to agriculture. This review walks through the historical timeline of genetics research and deliberates how this discipline might furnish a sustainable future for humanity.

OUP accepted manuscript

The mutations in modifier genes may contribute to some inherited diseases including Wilson disease (WD). This study was designed to identify potential modifier genes that contribute to WD. A total of 10 WD patients with single or no heterozygous ATP7B mutations were recruited for whole-exome sequencing (WES). Five hundred and thirteen candidate genes, of which the genetic variants present in at least two patients, were identified. In order to clarify which proteins might be involved in copper transfer or metabolism processes, the isobaric tags for relative and absolute quantitation (iTRAQ) was performed to identify the differentially expressed proteins between normal and CuSO₄-treated cell lines. Thirteen genes/proteins were identified by both WES and iTRAQ, indicating that disease-causing variants of these genes may actually contribute to the aberrant copper ion accumulation. Additionally, the c.86C > T (p.S29L) mutation in the SLC31A2 gene (coding CTR2) has a relative higher frequency in our cohort of WD patients (6/191) than reported (0.0024 in gnomAD database) in our healthy donors (0/109), and CTR2^S29L leads to increased intracellular Cu concentration and Cu-induced apoptosis in cultured cell lines. In conclusion, the WES and iTRAQ approaches successfully identified several disease-causing variants in potential modifier genes that may be involved in the WD phenotype.

Focused Strategies for Defining the Genetic Architecture of Congenital Heart Defects

Congenital heart defects (CHD) are malformations present at birth that occur during heart development. Increasing evidence supports a genetic origin of CHD, but in the process important challenges have been identified. This review begins with information about CHD and the importance of detailed phenotyping of study subjects. To facilitate appropriate genetic study design, we review DNA structure, genetic variation in the human genome and tools to identify the genetic variation of interest. Analytic approaches powered for both common and rare variants are assessed. While the ideal outcome of genetic studies is to identify variants that have a causal role, a more realistic goal for genetic analytics is to identify variants in specific genes that influence the occurrence of a phenotype and which provide keys to open biologic doors that inform how the genetic variants modulate heart development. It has never been truer that good genetic studies start with good planning. Continued progress in unraveling the genetic underpinnings of CHD will require multidisciplinary collaboration between geneticists, quantitative scientists, clinicians, and developmental biologists.

A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers

MOTIVATION

A feature selection algorithm may select the subset of features with the best associations with the class labels. The recursive feature elimination (RFE) is a heuristic feature screening framework and has been widely used to select the biological OMIC biomarkers. This study proposed a dynamic recursive feature elimination (dRFE) framework with more flexible feature elimination operations. The proposed dRFE was comprehensively compared with 11 existing feature selection algorithms and five classifiers on the eight difficult transcriptome datasets from a previous study, the ten newly collected transcriptome datasets and the five methylome datasets.

RESULTS

The experimental data suggested that the regular RFE framework did not perform well, and dRFE outperformed the existing feature selection algorithms in most cases. The dRFE-detected features achieved Acc=1.0000 for the two methylome datasets GSE53045 and GSE66695. The best prediction accuracies of the dRFE-detected features were 0.9259, 0.9424, and 0.8601 for the other three methylome datasets GSE74845, GSE103186, and GSE80970, respectively. Four transcriptome datasets received Acc=1.0000 using the dRFE-detected features, and the prediction accuracies for the other six newly collected transcriptome datasets were between 0.6301 and 0.9917.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.