Targeted Next Generation Sequencing Revealed a Novel Homozygous Loss-of-Function Mutation in ILDR1 Gene Causes Autosomal Recessive Nonsyndromic Sensorineural Hearing Loss in a Chinese Family

Systematic Review of Genetic Substrate Reduction Therapy in Lysosomal Storage Diseases: Opportunities, Challenges and Delivery Systems

BACKGROUND

Genetic substrate reduction therapy (gSRT), which involves the use of nucleic acids to downregulate the genes involved in the biosynthesis of storage substances, has been investigated in the treatment of lysosomal storage diseases (LSDs).

OBJECTIVE

To analyze the application of gSRT to the treatment of LSDs, identifying the silencing tools and delivery systems used, and the main challenges for its development and clinical translation, highlighting the contribution of nanotechnology to overcome them.

METHODS

A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines was performed. PubMed, Scopus, and Web of Science databases were used for searching terms related to LSDs and gene-silencing strategies and tools.

RESULTS

Fabry, Gaucher, and Pompe diseases and mucopolysaccharidoses I and III are the only LSDs for which gSRT has been studied, siRNA and lipid nanoparticles being the silencing strategy and the delivery system most frequently employed, respectively. Only in one recently published study was CRISPR/Cas9 applied to treat Fabry disease. Specific tissue targeting, availability of relevant cell and animal LSD models, and the rare disease condition are the main challenges with gSRT for the treatment of these diseases. Out of the 11 studies identified, only two gSRT studies were evaluated in animal models.

CONCLUSIONS

Nucleic acid therapies are expanding the clinical tools and therapies currently available for LSDs. Recent advances in CRISPR/Cas9 technology and the growing impact of nanotechnology are expected to boost the clinical translation of gSRT in the near future, and not only for LSDs.

Selection for stress tolerance and longevity in Drosophila melanogaster have strong impacts on microbiome profiles

There is experimental evidence that microbiomes have a strong influence on a range of host traits. Understanding the basis and importance of symbiosis between host and associated microorganisms is a rapidly developing research field, and we still lack a mechanistic understanding of ecological and genetic pressures affecting host-microbiome associations. Here Drosophila melanogaster lines from a large-scale artificial selection experiment were used to investigate whether the microbiota differ in lines selected for different stress resistance traits and longevity. Following multiple generations of artificial selection all selection regimes and corresponding controls had their microbiomes assessed. The microbiome was interrogated based on 16S rRNA sequencing. We found that the microbiome of flies from the different selection regimes differed markedly from that of the unselected control regime, and microbial diversity was consistently higher in selected relative to control regimes. Several common Drosophila bacterial species showed differentially abundance in the different selection regimes despite flies being exposed to similar environmental conditions for two generations prior to assessment. Our findings provide strong evidence for symbiosis between host and microbiomes but we cannot reveal whether the interactions are adaptive, nor whether they are caused by genetic or ecological factors.

Analysis of UGT1A1 genotype-phenotype correlation in Chinese patients with gilbert and crigler-Najjar II syndrome

The spectrum of UDP-glucuronosyltransferase (UGT1A1) variants, which are associated with Gilbert syndrome (GS) and Crigler-Najjar syndrome (CNS-II), has been reported in Chinese and western countries. However, the genotype-phenotype correlation of the individual UGT1A1 variants in GS and CNS-II remains to be clarified. To explore the UGT1A1 variant pattern and genotype-phenotype correlations, we enrolled 310 Chinese patients, including 232 patients with GS and 78 with CNS-II. Peripheral blood samples were collected for screening variants in the gene UGT1A1 by a polymerase chain reaction and Sanger sequencing. The correlation between different UGT1A1 variants and clinical phenotypes was analyzed. A total of 21 UGT1A1 variants were identified, including nine novel variants, and constituted 42 UGT1A1 genotypes in the GS and CNS-II patients. The most common UGT1A1 variants were A (TA)7TAA, p.G71R, p.Y486D, p.P364L, and p.P229Q, which were different from western countries. The p.Y486D variant had higher minor allele frequency in CNS-II than in GS whereas the A (TA)7TAA variant had higher minor allele frequency in GS than in CNS-II. The serum total bilirubin and triglyceride had significant differences among 14 recurrent genotypes of UGT1A1, in which the serum total bilirubin in patients with compound p.Y486D (homozygous)/p.G71R variant was significantly higher compared with homozygous A (TA)7TAA, homozygous p.G71R, compound heterozygous A (TA)7TAA/p.G71R and A (TA)7TAA/p.P364L, and combined heterozygous A (TA)7TAA/p.G71R/p.P229Q, while the serum triglyceride in patients with combined A (TA)7TAA (homozygous)/p.P229Q variant was significantly higher compared with compound heterozygous A (TA)7TAA/p.G71R, single heterozygous A (TA)7TAA, single heterozygous p.G71R, and homozygous A (TA)7TAA. The spectrum of UGT1A1 genotypes in Chinese patients was distinct from western countries. There were differential levels of serum total bilirubin and triglyceride in patients with recurrent genotypes of UGT1A1.

Variant ranking pipeline for complex familial disorders

Identifying genetic susceptibility factors for complex disorders remains a challenging task. To analyze collections of small and large pedigrees where genetic heterogeneity is likely, but biological commonalities are plausible, we have developed a weights-based pipeline to prioritize variants and genes. The Weights-based vAriant Ranking in Pedigrees (WARP) pipeline prioritizes variants using 5 weights: disease incidence rate, number of cases in a family, genome fraction shared amongst cases in a family, allele frequency and variant deleteriousness. Weights, except for the population allele frequency weight, are normalized between 0 and 1. Weights are combined multiplicatively to produce family-specific-variant weights that are then averaged across all families in which the variant is observed to generate a multifamily weight. Sorting multifamily weights in descending order creates a ranked list of variants and genes for further investigation. WARP was validated using familial melanoma sequence data from the European Genome-phenome Archive. The pipeline identified variation in known germline melanoma genes POT1, MITF and BAP1 in 4 out of 13 families (31%). Analysis of the other 9 families identified several interesting genes, some of which might have a role in melanoma. WARP provides an approach to identify disease predisposing genes in studies with small and large pedigrees.

The association between single-nucleotide polymorphisms within type 1 interferon pathway genes and human immunodeficiency virus type 1 viral load in antiretroviral-naïve participants

BACKGROUND

Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL).

METHODS

Two cohorts of antiretroviral (ART) naïve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025).

RESULTS

The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460-45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4+ T-cell count, CD4+/CD8+ T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants.

CONCLUSION

Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-naïve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.

Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in Nellore cattle

Genomic selection (GS) offers a promising opportunity for selecting more efficient animals to use consumed energy for maintenance and growth functions, impacting profitability and environmental sustainability. Here, we compared the prediction accuracy of multi-layer neural network (MLNN) and support vector regression (SVR) against single-trait (STGBLUP), multi-trait genomic best linear unbiased prediction (MTGBLUP), and Bayesian regression (BayesA, BayesB, BayesC, BRR, and BLasso) for feed efficiency (FE) traits. FE-related traits were measured in 1156 Nellore cattle from an experimental breeding program genotyped for ~ 300 K markers after quality control. Prediction accuracy (Acc) was evaluated using a forward validation splitting the dataset based on birth year, considering the phenotypes adjusted for the fixed effects and covariates as pseudo-phenotypes. The MLNN and SVR approaches were trained by randomly splitting the training population into fivefold to select the best hyperparameters. The results show that the machine learning methods (MLNN and SVR) and MTGBLUP outperformed STGBLUP and the Bayesian regression approaches, increasing the Acc by approximately 8.9%, 14.6%, and 13.7% using MLNN, SVR, and MTGBLUP, respectively. Acc for SVR and MTGBLUP were slightly different, ranging from 0.62 to 0.69 and 0.62 to 0.68, respectively, with empirically unbiased for both models (0.97 and 1.09). Our results indicated that SVR and MTGBLUBP approaches were more accurate in predicting FE-related traits than Bayesian regression and STGBLUP and seemed competitive for GS of complex phenotypes with various degrees of inheritance.

A first characterization of the microbiota-resilience link in swine

BACKGROUND

The gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.

RESULTS

This study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.

CONCLUSION

Our comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations. Video Abstract.

Emerging roles of the Protein Phosphatase 1 (PP1) in the context of viral infections

Protein Phosphatase 1 (PP1) is a major serine/threonine phosphatase in eukaryotes, participating in several cellular processes and metabolic pathways. Due to their low substrate specificity, PP1's catalytic subunits do not exist as free entities but instead bind to Regulatory Interactors of Protein Phosphatase One (RIPPO), which regulate PP1's substrate specificity and subcellular localization. Most RIPPOs bind to PP1 through combinations of short linear motifs (4-12 residues), forming highly specific PP1 holoenzymes. These PP1-binding motifs may, hence, represent attractive targets for the development of specific drugs that interfere with a subset of PP1 holoenzymes. Several viruses exploit the host cell protein (de)phosphorylation machinery to ensure efficient virus particle formation and propagation. While the role of many host cell kinases in viral life cycles has been extensively studied, the targeting of phosphatases by viral proteins has been studied in less detail. Here, we compile and review what is known concerning the role of PP1 in the context of viral infections and discuss how it may constitute a putative host-based target for the development of novel antiviral strategies.

Lactosylated lipid calcium phosphate-based nanoparticles: A promising approach for efficient DNA delivery to hepatocytes

Objectives

For safe and effective gene therapy, the ability to deliver the therapeutic nucleic acid to the target sites is crucial. In this study, lactosylated lipid phosphate calcium nanoparticles (lac-LCP) were developed for targeted delivery of pDNA to the hepatocyte cells. The lac-LCP formulation contained lactose-modified cholesterol (CHL), a ligand that binds to the asialoglycoprotein receptor (ASGR) expressed on hepatocytes, and polyethyleneimine (PEI) in the core.

Materials and Methods

Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR) were used to monitor the chemical modification, and the physicochemical properties of NPs were studied using dynamic light scattering (DLS) and transmission electron microscopy (TEM). To evaluate transfection efficiency, cellular uptake and GFP expression were assessed using fluorescence microscopy and flow cytometry.

Results

The results revealed that lactose-targeted particles (lac-LCP) had a significant increase in cellular uptake by hepatocytes. The inclusion of a low molecular weight PEI (1.8 KDa) with a low PEI/pDNA ratio of 1 in the core of LCP, elicited high degrees of GFP protein expression (by 5 and 6-fold), which exhibited significantly higher efficiency than PEI 1.8 KDa and Lipofectamine.

Conclusion

The successful functionalization and nuclear delivery of LCP NPs described here indicate its promise as an efficient delivery vector to hepatocyte nuclei.

Speciation in Coastal Basins Driven by Staggered Headwater Captures: Dispersal of a Species Complex, Leporinus bahiensis, as Revealed by Genome-wide SNP Data

Past sea level changes and geological instability along watershed boundaries have largely influenced fish distribution across coastal basins, either by dispersal via palaeodrainages now submerged or by headwater captures, respectively. Accordingly, the South American Atlantic coast encompasses several small and isolated drainages that share a similar species composition, representing a suitable model to infer historical processes. Leporinus bahiensis is a freshwater fish species widespread along adjacent coastal basins over narrow continental shelf with no evidence of palaeodrainage connections at low sea level periods. Therefore, this study aimed to reconstruct its evolutionary history to infer the role of headwater captures in the dispersal process. To accomplish this, we employed molecular-level phylogenetic and population structure analyses based on Sanger sequences (5 genes) and genome-wide SNP data. Phylogenetic trees based on Sanger data were inconclusive, but SNPs data did support the monophyletic status of L. bahiensis. Both COI and SNP data revealed structured populations according to each hydrographic basin. Species delimitation analyses revealed from 3 (COI) to 5 (multilocus approach) MOTUs, corresponding to the sampled basins. An intricate biogeographic scenario was inferred and supported by Approximate Bayesian Computation (ABC) analysis. Specifically, a staggered pattern was revealed and characterized by sequential headwater captures from basins adjacent to upland drainages into small coastal basins at different periods. These headwater captures resulted in dispersal throughout contiguous coastal basins, followed by deep genetic divergence among lineages. To decipher such recent divergences, as herein represented by L. bahiensis populations, we used genome-wide SNPs data. Indeed, the combined use of genome-wide SNPs data and ABC method allowed us to reconstruct the evolutionary history and speciation of L. bahiensis. This framework might be useful in disentangling the diversification process in other neotropical fishes subject to a reticulate geological history.

Human-specific evolutionary markers linked to foetal neurodevelopment modulate brain surface area in schizophrenia

Schizophrenia may represent a trade-off in the evolution of human-specific ontogenetic mechanisms that guide neurodevelopment. Human Accelerated Regions (HARs) are evolutionary markers functioning as neurodevelopmental transcription enhancers that have been associated with brain configuration, neural information processing, and schizophrenia risk. Here, we have investigated the influence of HARs' polygenic load on neuroanatomical measures through a case-control approach (128 patients with schizophrenia and 115 controls). To this end, we have calculated the global schizophrenia Polygenic Risk Score (Global PRSSZ) and that specific to HARs (HARs PRSSZ). We have also estimated the polygenic burden restricted to the HARs linked to transcriptional regulatory elements active in the foetal brain (FB-HARs PRSSZ) and the adult brain (AB-HARs PRSSZ). We have explored the main effects of the PRSs and the PRSs x diagnosis interactions on brain regional cortical thickness (CT) and surface area (SA). The results indicate that a higher FB-HARs PRSSZ is associated with patients' lower SA in the lateral orbitofrontal cortex, the superior temporal cortex, the pars triangularis and the paracentral lobule. While noHARs-derived PRSs show an effect on the risk, our neuroanatomical findings suggest that the human-specific transcriptional regulation during the prenatal period underlies SA variability, highlighting the role of these evolutionary markers in the schizophrenia genomic architecture.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Genomic studies of the additive and dominant genetic control on production traits of Euterpe edulis fruits

In forest genetic improvement programs for non-domesticated species, limited knowledge of kinship can compromise or make the estimation of variance components and genetic parameters of traits of interest unfeasible. We used mixed models and genomics (in the latter, considering additive and non-additive effects) to evaluate the genetic architecture of 12 traits in juçaizeiro for fruit production. A population of 275 genotypes without genetic relationship knowledge was phenotyped over three years and genotyped by whole genome SNP markers. We have verified superiority in the quality of the fits, the prediction accuracy for unbalanced data, and the possibility of unfolding the genetic effects into their additive and non-additive terms in the genomic models. Estimates of the variance components and genetic parameters obtained by the additive models may be overestimated since, when considering the dominance effect in the model, there are substantial reductions in them. The number of bunches, fresh fruit mass of bunch, rachis length, fresh mass of 25 fruits, and amount of pulp were strongly influenced by the dominance effect, showing that genomic models with such effect should be considered for these traits, which may result in selective improvements by being able to return more accurate genomic breeding values. The present study reveals the additive and non-additive genetic control of the evaluated traits and highlights the importance of genomic information-based approaches for populations without knowledge of kinship and experimental design. Our findings underscore the critical role of genomic data in elucidating the genetic control architecture of quantitative traits, thereby providing crucial insights for driving species' genetic improvement.

MiSurv: an Integrative Web Cloud Platform for User-Friendly Microbiome Data Analysis with Survival Responses

Investigators have studied the treatment effects on human health or disease, the treatment effects on human microbiome, and the roles of the microbiome on human health or disease. Especially, in a clinical trial, investigators commonly trace disease status over a lengthy period to survey the sequential disease progression for different treatment groups (e.g., treatment versus placebo, new treatment versus old treatment). Hence, disease responses are often available in the form of survival (i.e., time-to-event) responses stratified by treatment groups. While the recent web cloud platforms have enabled user-friendly microbiome data processing and analytics, there is currently no web cloud platform to analyze microbiome data with survival responses. Therefore, we introduce here an integrative web cloud platform, called MiSurv, for comprehensive microbiome data analysis with survival responses. IMPORTANCE MiSurv consists of a data processing module and its following four data analytic modules: (i) Module 1: Comparative survival analysis between treatment groups, (ii) Module 2: Comparative analysis in microbial composition between treatment groups, (iii) Module 3: Association testing between microbial composition and survival responses, (iv) Module 4: Prediction modeling using microbial taxa on survival responses. We demonstrate its use through an example trial on the effects of antibiotic use on the survival rate against type 1 diabetes (T1D) onset and gut microbiome composition, respectively, and the effects of the gut microbiome on the survival rate against T1D onset. MiSurv is freely available on our web server (http://misurv.micloud.kr) or can alternatively run on the user's local computer (https://github.com/wg99526/MiSurvGit).

Bioinformatics and its role in the study of the evolution and probiotic potential of lactic acid bacteria

Due to their numerous well-established applications in the food industry, there have been many studies regarding the adaptation and evolution of lactic acid bacteria (LAB) in a wide variety of hosts and environments. Progress in sequencing technology and continual decreases in its costs have led to the availability of LAB genome sequence data. Bioinformatics has been central to the extraction of valuable information from these raw genome sequence data. This paper presents the roles of bioinformatics tools and databases in understanding the adaptation and evolution of LAB, as well as the bioinformatics methods used in the initial screening of LAB for probiotic potential. Moreover, the advantages, challenges, and limitations of employing bioinformatics for these purposes are discussed.

Organ-on-a-chip technologies for biomedical research and drug development: A focus on the vasculature

Current biomedical models fail to replicate the complexity of human biology. Consequently, almost 90% of drug candidates fail during clinical trials after decades of research and billions of investments in drug development. Despite their physiological similarities, animal models often misrepresent human responses, and instead, trigger ethical and societal debates regarding their use. The overall aim across regulatory entities worldwide is to replace, reduce, and refine the use of animal experimentation, a concept known as the Three Rs principle. In response, researchers develop experimental alternatives to improve the biological relevance of in vitro models through interdisciplinary approaches. This article highlights the emerging organ-on-a-chip technologies, also known as microphysiological systems, with a focus on models of the vasculature. The cardiovascular system transports all necessary substances, including drugs, throughout the body while in charge of thermal regulation and communication between other organ systems. In addition, we discuss the benefits, limitations, and challenges in the widespread use of new biomedical models. Coupled with patient-derived induced pluripotent stem cells, organ-on-a-chip technologies are the future of drug discovery, development, and personalized medicine.

Class I Myosins, molecular motors involved in cell migration and cancer

Class I Myosins are a subfamily of motor proteins with ATPase activity and a characteristic structure conserved in all myosins: A N-Terminal Motor Domain, a central Neck and a C terminal Tail domain. Humans have eight genes for these myosins. Class I Myosins have different functions: regulate membrane tension, participate in endocytosis, exocytosis, intracellular trafficking and cell migration. Cell migration is influenced by many cellular components including motor proteins, like myosins. Recently has been reported that changes in myosin expression have an impact on the migration of cancer cells, the formation of infiltrates and metastasis. We propose that class I myosins might be potential markers for future diagnostic, prognostic or even as therapeutic targets in leukemia and other cancers.Abbreviations: Myo1g: Myosin 1g; ALL: Acute Lymphoblastic Leukemia, TH1: Tail Homology 1; TH2: Tail Homology 2; TH3: Tail Homology 3.

Estimating genetics of body dimensions and activity levels in pigs using automated pose estimation

Pig breeding is changing rapidly due to technological progress and socio-ecological factors. New precision livestock farming technologies such as computer vision systems are crucial for automated phenotyping on a large scale for novel traits, as pigs’ robustness and behavior are gaining importance in breeding goals. However, individual identification, data processing and the availability of adequate (open source) software currently pose the main hurdles. The overall goal of this study was to expand pig weighing with automated measurements of body dimensions and activity levels using an automated video-analytic system: DeepLabCut. Furthermore, these data were coupled with pedigree information to estimate genetic parameters for breeding programs. We analyzed 7428 recordings over the fattening period of 1556 finishing pigs (Piétrain sire x crossbred dam) with two-week intervals between recordings on the same pig. We were able to accurately estimate relevant body parts with an average tracking error of 3.3 cm. Body metrics extracted from video images were highly heritable (61–74%) and significantly genetically correlated with average daily gain (r_g = 0.81–0.92). Activity traits were low to moderately heritable (22–35%) and showed low genetic correlations with production traits and physical abnormalities. We demonstrated a simple and cost-efficient method to extract body dimension parameters and activity traits. These traits were estimated to be heritable, and hence, can be selected on. These findings are valuable for (pig) breeding organizations, as they offer a method to automatically phenotype new production and behavioral traits on an individual level.

Analyses of the expression and prognosis of ILDR1 in human gastric cancer

The worldwide mortality rate of gastric cancer worldwide remains high. Immunoglobulin-like domain containing receptor 1 (ILDR1) belongs to an evolutionarily conserved protein family, and little is known about this gene in gastric cancer. In this paper, we analyzed the expression of ILDR1 and its relationship with clinical outcomes in gastric cancer using publicly available databases. ONCOMINE, GEPIA2, UALCAN, Kaplan–Meier Plotter, cBioPortal, GeneMANIA and LinkedOmics databases were used to analyze the expression, prognostic values, mutations and functional networks of ILDR1 in gastric cancer. We observed that ILDR1 was overexpressed in gastric cancer than in normal tissues. ILDR1 expression was significantly higher in patients with gastric cancer than in normal controls during subgroup analysis based on cancer stage, patient’s race, sex, age, tumor grade, H. pylori infection, histological subtype, and nodal metastasis status. Survival analysis showed that upregulation of ILDR1 expression was significantly associated with poor prognosis. Genomic alterations in ILDR1 were analyzed using cBioPortal, protein–protein interaction (PPI) networks were constructed using GeneMANIA and the co-expressed genes, gene ontology, and pathways of ILDR1 were determined using the LinkedOmics web tool. ILDR1 showed significant differences in expression between gastric cancer and normal tissues and, thus, may be a promising prognostic biomarker for gastric cancer.

Deep polygenic neural network for predicting and identifying yield-associated genes in Indonesian rice accessions

As the fourth most populous country in the world, Indonesia must increase the annual rice production rate to achieve national food security by 2050. One possible solution comes from the nanoscopic level: a genetic variant called Single Nucleotide Polymorphism (SNP), which can express significant yield-associated genes. The prior benchmark of this study utilized a statistical genetics model where no SNP position information and attention mechanism were involved. Hence, we developed a novel deep polygenic neural network, named the NucleoNet model, to address these obstacles. The NucleoNets were constructed with the combination of prominent components that include positional SNP encoding, the context vector, wide models, Elastic Net, and Shannon’s entropy loss. This polygenic modeling obtained up to 2.779 of Mean Squared Error (MSE) with 47.156% of Symmetric Mean Absolute Percentage Error (SMAPE), while revealing 15 new important SNPs. Furthermore, the NucleoNets reduced the MSE score up to 32.28% compared to the Ordinary Least Squares (OLS) model. Through the ablation study, we learned that the combination of Xavier distribution for weights initialization and Normal distribution for biases initialization sparked more various important SNPs throughout 12 chromosomes. Our findings confirmed that the NucleoNet model was successfully outperformed the OLS model and identified important SNPs to Indonesian rice yields.

Parental competition for the regulators of chromatin dynamics in mouse zygotes

The underlying mechanism for parental asymmetric chromatin dynamics is still unclear. To reveal this, we investigate chromatin dynamics in parthenogenetic, androgenic, and several types of male germ cells-fertilized zygotes. Here we illustrate that parental conflicting role mediates the regulation of chromatin dynamics. Sperm reduces chromatin dynamics in both parental pronuclei (PNs). During spermiogenesis, male germ cells acquire this reducing ability and its resistance. On the other hand, oocytes can increase chromatin dynamics. Notably, the oocytes-derived chromatin dynamics enhancing ability is dominant for the sperm-derived opposing one. This maternal enhancing ability is competed between parental pronuclei. Delayed fertilization timing is critical for this competition and compromises parental asymmetric chromatin dynamics and zygotic transcription. Together, parental competition for the maternal factor enhancing chromatin dynamics is a determinant to establish parental asymmetry, and paternal repressive effects have supporting roles to enhance asymmetry.

Whole exome sequencing identified a homozygous novel mutation in SUOX gene causes extremely rare autosomal recessive isolated sulfite oxidase deficiency

BACKGROUND

Isolated sulfite oxidase deficiency (ISOD) is a rare type of life-threatening neurometabolic disorders characterized by neonatal intractable seizures and severe developmental delay with an autosomal recessive mode of inheritance. Germline mutation in SUOX gene causes ISOD. Till date, only 32 mutations of SUOX gene have been identified and reported to be associated with ISOD.

METHODS

Here, we investigated a 5-days old Chinese female child, presented with intermittent tremor or seizures of limbs, neonatal encephalopathy, subarachnoid cyst and haemorrhage, dysplasia of corpus callosum, neonatal convulsion, hyperlactatemia, severe metabolic acidosis, hyperglycemia, and hyperkalemia.

RESULTS

Whole exome sequencing identified a novel homozygous transition (c.1227G > A) in exon 6 of the SUOX gene in the proband. This novel homozygous variant leads to the formation of a truncated sulfite oxidase (p.Trp409*) of 408 amino acids. This variant causes partial loss of the dimerization domain of sulfite oxidase. Hence, it is a loss-of-function variant. Proband's father and mother is carrying this novel variant in a heterozygous state. This variant was not found in 200 ethnically matched normal healthy control individuals.

CONCLUSIONS

Our study not only expanded the mutational spectrum of SUOX gene associated with ISOD, but also strongly suggested the significance of whole exome sequencing for identifying candidate genes and novel disease-causing variants.

Prospect of Stem Cells as Promising Therapy for Brachial Plexus Injury: A Systematic Review

Background

Brachial plexus injury is an advanced and devastating neurological injury, for which both nerve surgery and tendon transfers sometimes remain insufficient in restoring normal movement. Stem cell therapy may be applicable to rescue the injured motor neurons from degeneration which potentially improves muscle strength.

Study Design

Systematic Review; Level of evidence V.

Data Sources

A systematic literature search was conducted on PubMed (MEDLINE), EMBASE, the Cochrane Library, and Scopus using the terms ("stem cell") AND ("brachial plexus") as search keywords.

Methods

The process of study selection was summarized by PRISMA flow diagram. The study included in vivo and in vitro studies with English language, humans or animals with some brachial plexus injuries, interventions, some applications of stem cells to the groups of study, with functional, biomechanical, or safety outcomes.

Results

In total, there were 199 studies identified from the literature sources where 75 articles were qualified for forward evaluation following selecting the titles and abstracts. Ten studies were finally included in this systematic review after full-text assessment. Stem cells can produce neurotrophic factors in vitro and in vivo in rats, and their level was increased after injury. Electrophysiological measurement showed that the intervention group had distinctly higher CMAP amplitude and evidently shorter CMAP latency than the model group. Application of bone marrow stem cells (BMSCs) showed an elevation in the numbers of axons and density of myelinated fibers, the density of nerve fibers, the diameter of regenerating axons, and a decrease in axonal degeneration. A study in humans indicated an improvement of the movements in a patient with traumatic total BPI after injection of Ad-MSC. It is associated with increased muscle mass and sensory recovery and also suggested that mononuclear cell injection enhances muscle regeneration and reinnervation in the partly denervated muscle of brachial plexus injury. Various muscle groups had obtained strength together with restoration, the muscle strength attained after the previous transplantation were preserved. The results of this review support stem cell treatment in brachial plexus injury.

Conclusion

This review provides evidence of the positive effects of stem cell treatment in brachial plexus injury.

HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods—ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Here the authors present “HarmonizR”, a tool for missing data tolerant experimental variance reduction in large, integrated but independently generated datasets without data imputation, adjustable for individual dataset modalities, correction algorithm, and user preferences.

Mechanisms of structural chromosomal rearrangement formation

Structural chromosomal rearrangements result from different mechanisms of formation, usually related to certain genomic architectural features that may lead to genetic instability. Most of these rearrangements arise from recombination, repair, or replication mechanisms that occur after a double-strand break or the stalling/breakage of a replication fork. Here, we review the mechanisms of formation of structural rearrangements, highlighting their main features and differences. The most important mechanisms of constitutional chromosomal alterations are discussed, including Non-Allelic Homologous Recombination (NAHR), Non-Homologous End-Joining (NHEJ), Fork Stalling and Template Switching (FoSTeS), and Microhomology-Mediated Break-Induced Replication (MMBIR). Their involvement in chromoanagenesis and in the formation of complex chromosomal rearrangements, inverted duplications associated with terminal deletions, and ring chromosomes is also outlined. We reinforce the importance of high-resolution analysis to determine the DNA sequence at, and near, their breakpoints in order to infer the mechanisms of formation of structural rearrangements and to reveal how cells respond to DNA damage and repair broken ends.

Acute thermal stress elicits interactions between gene expression and alternative splicing in a fish of conservation concern

Transcriptomic research provides a mechanistic understanding of an organism's response to environmental challenges such as increasing temperatures, which can provide key insights into the threats posed by thermal challenges associated with urbanization and climate change. Differential gene expression and alternative splicing are two elements of the transcriptomic stress response that may work in tandem, but relatively few studies have investigated these interactions in fishes of conservation concern. We studied the imperilled redside dace (Clinostomus elongatus) as thermal stress is hypothesised to be an important cause of population declines. We tested the hypothesis that gene expression-splicing interactions contribute to the thermal stress response. Wild fish exposed to acute thermal stress were compared with both handling controls and fish sampled directly from a river. Liver tissue was sampled to study the transcriptomic stress response. With a gene set enrichment analysis, we found that thermally stressed fish showed a transcriptional response related to transcription regulation and responses to unfolded proteins, and alternatively spliced genes related to gene expression regulation and metabolism. One splicing factor, prpf38b, was upregulated in the thermally stressed group compared to the other treatments. This splicing factor may have a role in the Jun/AP-1 cellular stress response, a pathway with wide-ranging and context-dependent effects. Given large gene interaction networks and the context-dependent nature of transcriptional responses, our results highlight the importance of understanding interactions between gene expression and splicing for understanding transcriptomic responses to thermal stress. Our results also reveal transcriptional pathways that can inform conservation breeding, translocation, and reintroduction programs for redside dace and other imperilled species by identifying appropriate source populations.

Double Isochromosome X, a Rare Cytogenetic Variant of Turner Syndrome: A Case Report and a Review of the Literature

Turner Syndrome (TS) is a genetic disorder caused by total or partial loss of an X chromosome. The isochromosome X (i(X)) is a known variant of TS, however, double i(X) is a very rare variant, reported very few times in the literature. We report on a rare case of TS with double i(X). This is an 11-year-old female patient , addressed to the medical genetics consultation for short stature and facial features suggestive of TS. We performed a constitutional postnatal karyotype from a peripheral blood sample, with lymphocyte culture, and an R band analysis, performed on 70 metaphases. Metaphases analysis in our patient identified the presence of three cell populations: 45,X[22]/46,X,i(X)(q10)[30]/47,X,i(X)(q10),i(X)(q10) [18]. The first has total chromosome X monosomy, the second with a normal X chromosome and one isochromosome of the long arm of the other X chromosome and the third with a normal X chromosome and two isochromosomes of the long arm of the X chromosome. A control cell culture was performed from a second blood sample of the patient and confirmed the abnormality. This paper will discuss this case in comparison with other rare cases described, as well as the formation of the double isochromosome, based on the literature.

Understanding how variable thermal environments affect the molecular mechanisms underlying temperature-sensitive phenotypes: lessons from sex determination

The thermal environment that organisms experience can affect many aspects of their phenotype. As global temperatures become more unpredictable, it is imperative that we understand the molecular mechanisms by which organisms respond to variable, and often transient, thermal environments. Beyond deciphering the mechanisms through which organisms respond to temperature, we must also appreciate the underlying variation in temperature-dependent processes, as this variation is essential for understanding the potential to adapt to changing climates. In this Commentary, we use temperature-dependent sex determination as an example to explore the mechanistic processes underlying the development of temperature-sensitive phenotypes. We synthesize the current literature on how variable thermal conditions affect these processes and address factors that may limit or allow organisms to respond to variable environments. From these examples, we posit a framework for how the field might move forward in a more systematic way to address three key questions: (1) which genes directly respond to temperature-sensitive changes in protein function and which genes are downstream, indirect responders?; (2) how long does it take different proteins and genes to respond to temperature?; and (3) are the experimental temperature manipulations relevant to the climate the organism experiences or to predicted climate change scenarios? This approach combines mechanistic questions (questions 1 and 2) with ecologically relevant conditions (question 3), allowing us to explore how organisms respond to transient thermal environments and, thus, cope with climate change.

Genetic associations in chronic hepatitis B infection: toward developing polygenic risk scores

Chronic hepatitis B (CHB) infection results in multiple clinical phenotypes of varying severity. One of the critical gaps in CHB management is the lack of a genetic-based tool to aid existing hepatocellular carcinoma and cirrhosis risk stratification models for patients with active CHB. Such individual predictive models for CHB are plagued by an inherent limitation of discriminatory power that clearly indicates the need for their improvement. In this article, we highlight genetic association studies in CHB that identified HLA and cytokine genetic susceptibility loci to CHB. We advance the position that translating CHB genetic susceptibility loci into polygenic risk scores will be a welcome addendum to the current arsenal of CHB outcome predictive models. We conclude with comments on hurdles that future research efforts should address within the research enclave of CHB and advocate for increased genetic data representation from sub-Saharan Africa.

Accuracy comparison of ARIMA and XGBoost forecasting models in predicting the incidence of COVID-19 in Bangladesh

Accurate predictive time series modelling is important in public health planning and response during the emergence of a novel pandemic. Therefore, the aims of the study are three-fold: (a) to model the overall trend of COVID-19 confirmed cases and deaths in Bangladesh; (b) to generate a short-term forecast of 8 weeks of COVID-19 cases and deaths; (c) to compare the predictive accuracy of the Autoregressive Integrated Moving Average (ARIMA) and eXtreme Gradient Boosting (XGBoost) for precise modelling of non-linear features and seasonal trends of the time series. The data were collected from the onset of the epidemic in Bangladesh from the Directorate General of Health Service (DGHS) and Institute of Epidemiology, Disease Control and Research (IEDCR). The daily confirmed cases and deaths of COVID-19 of 633 days in Bangladesh were divided into several training and test sets. The ARIMA and XGBoost models were established using those training data, and the test sets were used to evaluate each model's ability to forecast and finally averaged all the predictive performances to choose the best model. The predictive accuracy of the models was assessed using the mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The findings reveal the existence of a nonlinear trend and weekly seasonality in the dataset. The average error measures of the ARIMA model for both COVID-19 confirmed cases and deaths were lower than XGBoost model. Hence, in our study, the ARIMA model performed better than the XGBoost model in predicting COVID-19 confirmed cases and deaths in Bangladesh. The suggested prediction model might play a critical role in estimating the spread of a novel pandemic in Bangladesh and similar countries.

THREE-DIMENSIONAL COMPUTATIONAL MODEL OF EARLY UPPER LIMB DEVELOPMENT

Limb development begins during embryogenesis when a series of biochemical interactions are triggered between a particular region of the mesoderm and the ectoderm. These processes affect the morphogenesis and growth of bones, joints, and all the other constituent elements of limbs; nevertheless, how the biochemical regulation affects mesenchymal condensation is not entirely clear. In this study, a three-dimensional computational model is designed to predict the appearance and location of the mesenchymal condensation in the stylopod and zeugopod; the biochemical events were described with reaction–diffusion equations that were solved using the finite elements method. The result of the gene expression in our model was consistent with the one reported in literature; the obtained patterns of Fgf8, Fgf10, and Wnt3a can predict the shape of the mesenchymal condensation of early upper limb development; the simple diffusive patterns of molecules were suitable to explain the areas where sox9 is expressed. Furthermore, our results suggest that the expression of Tgf-[Formula: see text] in the upper limb could be due to the inhibition of retinoic acid. These results suggest the importance of building computational scenarios where pathologies may be comprehensively examined.

Genetics Landscape of Nonsyndromic Hearing Loss in Indian Populations

Congenital nonsyndromic hearing loss (NSHL) has been considered as one of the most prevalent chronic disorder in children. It affects the physical and mental conditions of a large children population worldwide. Because of the genetic heterogeneity, the identification of target gene is very challenging. However, gap junction β-2 ( GJB2 ) is taken as the key gene for hearing loss, as its involvement has been reported frequently in NSHL cases. This study aimed to identify the association of GJB2 mutants in different Indian populations based on published studies in Indian population. This will provide clear genetic fundamental of NSHL in Indian biogeography, which would be helpful in the diagnosis process.

Analysis of CcGASA family members in Citrus clementina (Hort. ex Tan.) by a genome-wide approach

The Gibberellic Acid Stimulated Arabidopsis (GASA) proteins were investigated in the study to help understand their possible roles in fruit trees, particularly in Citrus. A total of 18 CcGASA proteins were identified and characterized in Citrus clementina via a genome-wide approach. It was shown that the CcGASA proteins structurally shared a conserved GASA domain but varied considerably in primary sequences and motif compositions. Thus, they could be classified into three major phylogenetic groups, G1~G3, and two groups, G1 and G3 could be further classified into subgroups. The cis- elements on all CcGASA promoters were identified and categorized, and the associated transcription factors were predicted. In addition, the possible interactions between the CcGASA proteins and other proteins were predicted. All the clues suggested that these genes should be involved in defense against biotic and abiotic stresses and in growth and development. The notion was further supported by gene expression analysis that showed these genes were more or less responsive to the treatments of plant hormones (GA₃, SA, ABA and IAA), and infections of citrus canker pathogen Xanthomonas citri. It was noted that both the segmental and the tandem duplications had played a role in the expansion of the CcGASA gene family in Citrus. Our results showed that the members of the CcGASA gene family should have structurally and functionally diverged to different degrees, and hence, the representative group members should be individually investigated to dissect their specific roles.

Genetic diversity of Norway spruce ecotypes assessed by GBS-derived SNPs

We investigated the genetic structure of three phenotypically distinct ecotypic groups of Norway spruce (Picea abies) belonging to three elevational classes; namely, low- (acuminata), medium- (europaea), and high-elevation (obovata) form, each represented by 150 trees. After rigorous filtering, we used 1916 Genotyping-by-Sequencing generated SNPs for analysis. Outputs from three multivariate analysis methods (Bayesian clustering algorithm implemented in STRUCTURE, Principal Component Analysis, and the Discriminant Analysis of Principal Components) indicated the presence of a distinct genetic cluster representing the high-elevation ecotypic group. Our findings bring a vital message to forestry practice affirming that artificial transfer of forest reproductive material, especially for stands under harsh climate conditions, should be considered with caution.

Comprehensive functional network analysis and screening of deleterious pathogenic variants in non-syndromic hearing loss causative genes

Hearing loss (HL) is a significant public health problem and causes the most frequent congenital disability in developed societies. The genetic analysis of non-syndromic hearing loss (NSHL) may be considered as a complement to the existent plethora of diagnostic modalities available. The present study focuses on exploring more target genes with respective non-synonymous single nucleotide polymorphisms (nsSNPs) involved in the development of NSHL. The functional network analysis and variant study have successfully been carried out from the gene pool retrieved from reported research articles of the last decade. The analyses have been done through STRING. According to predicted biological processes, various variant analysis tools have successfully classified the NSHL causative genes and identified the deleterious nsSNPs, respectively. Among the predicted pathogenic nsSNPs with rsIDs rs80356586 (I515T), rs80356596 (L1011P), rs80356606 (P1987R) in OTOF have been reported in NSHL earlier. The rs121909642 (P722S), rs267606805 (P722H) in FGFR1, rs121918506 (E565A) and rs121918509 (A628T, A629T) in FGFR2 have not been reported in NSHL yet, which should be clinically experimented in NSHL. This also indicates this variant's novelty as its association in NSHL. The findings and the analyzed data have delivered some vibrant genetic pathogenesis of NSHL. These data might be used in the diagnostic and prognostic purposes in non-syndromic congenitally deaf children.

Genetic polymorphisms in the miR-372 (rs12983273) and LncRNA HULC (rs7763881) genes and susceptibility to Hepatitis B virus (HBV) infection

BACKGROUND

MicroRNAs (miRNAs) and Long non-coding RNAs (lncRNAs) are two major types of non-coding RNAs (ncRNAs) with regulatory roles. The initiation and progression of numerous diseases have been linked to genetic variation in miRNAs and lncRNAs. Many diseases, including hepatitis infection, are thought to be regulated by miRNA-LncRNA interactions. In this study, Single nucleotide polymorphisms (SNPs) in miR-372 (rs28461391 C/T) and HULC (rs7763881 A/C) were believed to play a role in HBV infection risk.

METHODS AND RESULTS

Using the Polymerase chain reaction sequence-specific primer technique (PCR-SSP), 100 HBV patients and 100 healthy controls were genotyped for SNPs rs28461391 in miR-372 and rs7763881 in HULC. There was no significant difference in miR-372 rs12983273 genotype distribution between controls and HBV patients, according to our findings. On the other hand, there was a significant increase in HULC rs7763881 CC genotype (P < 0.05) coincides with a significant decrease in AC genotype distribution (P < 0.05) in HBV patients as compared to controls. Our results showed that the AA genotype is protective for HBV infection (OR 0.3; CI 0.13-9.07) while the CC genotype is associated with an increased risk of HBV infection (OR 3.43; CI 1.3-9.07).

CONCLUSIONS

Our results suggest that HULC rs7763881 A/C might be a biomarker for HBV susceptibility. Larger sample studies are needed to confirm our preliminary data. To the best of our knowledge, the present study was the first to investigate the relevance of miR-372 (rs28461391 C/T) and HULC (rs7763881 A/C) gene polymorphisms to the risk of HBV infection in the Egyptian population.

A high-density linkage map and sex-linked markers for the Amazon Tambaqui Colossoma macropomum

Background

Tambaqui (Colossoma macropomum, Cuvier, 1818) is the most economically important native freshwater fish species in Brazil. It can reach a total length of over 1 m and a weight of over 40 kg. The species displays a clear sex dimorphism in growth performance, with females reaching larger sizes at harvest. In aquaculture, the production of monosex populations in selective breeding programmes has been therefore identified as a key priority.

Results

In the present study, a genetic linkage map was generated by double digest restriction-site associated DNA (ddRAD) sequencing from 248 individuals sampled from two F1 families. The map was constructed using 14,805 informative SNPs and spanned 27 linkage groups. From this, the tambaqui draft genome was improved, by ordering the scaffolds into chromosomes, and sex-linked markers were identified. A total of 235 markers on linkage group 26 showed a significant association with the phenotypic sex, supporting an XX/XY sex determination system in the species. The four most informative sex-linked markers were validated on another 206 sexed individuals, demonstrating an accuracy in predicting sex ranging from 90.0 to 96.7%.

Conclusions

The genetic mapping and novel sex-linked DNA markers identified and validated offer new tools for rapid progeny sexing, thus supporting the development of monosex female production in the industry while also supporting breeding programmes of the species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08037-8.

Omics in the detection and identification of biosynthetic pathways related to mycotoxin synthesis

Mycotoxins are secondary metabolites that are known to be toxic to humans and animals. On the other hand, some mycotoxins and their analogues possess antioxidant as well as antitumor properties, which could be relevant in the fields of pharmaceutical analysis and food research. Omics techniques are a group of analytical tools applied in the biological sciences in order to study genes (genomics), mRNA (transcriptomics), proteins (proteomics), and metabolites (metabolomics). Omics have become a vital tool in the field of mycotoxins, especially contributing to the identification of biomarkers with potential use for the detection of mycotoxigenic species and the gathering of information about the biosynthetic pathways of mycotoxins in different environments. This approach has provided tools for the development of prevention strategies and control measures for different mycotoxins. Additionally, research has revealed important information about the impact of global warming and climate change on the prevalence of mycotoxin issues in society. In the context of foodomics, the aim is to apply omics techniques in order to ensure food safety. The objective of the present review is to determine the state of the art regarding the development of analytical techniques based on omics in the identification of biosynthetic pathways related to mycotoxin synthesis.

Homology-directed gene-editing approaches for hematopoietic stem and progenitor cell gene therapy

The advent of next-generation genome engineering tools like CRISPR-Cas9 has transformed the field of gene therapy, rendering targeted treatment for several incurable diseases. Hematopoietic stem and progenitor cells (HSPCs) continue to be the ideal target cells for gene manipulation due to their long-term repopulation potential. Among the gene manipulation strategies such as lentiviral gene augmentation, non-homologous end joining (NHEJ)-mediated gene editing, base editing and prime editing, only the homology-directed repair (HDR)-mediated gene editing provides the option of inserting a large transgene under its endogenous promoter or any desired locus. In addition, HDR-mediated gene editing can be applied for the gene knock-out, correction of point mutations and introduction of beneficial mutations. HSPC gene therapy studies involving lentiviral vectors and NHEJ-based gene-editing studies have exhibited substantial clinical progress. However, studies involving HDR-mediated HSPC gene editing have not yet progressed to the clinical testing. This suggests the existence of unique challenges in exploiting HDR pathway for HSPC gene therapy. Our review summarizes the mechanism, recent progresses, challenges, and the scope of HDR-based gene editing for the HSPC gene therapy.

Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is still attracting public attention because of its outbreak in various cities in China. Predicting future outbreaks or epidemics disease based on past incidence data can help health departments take targeted measures to prevent diseases in advance. In this study, we propose a multistep prediction strategy based on extreme gradient boosting (XGBoost) for HFRS as an extension of the one-step prediction model. Moreover, the fitting and prediction accuracy of the XGBoost model will be compared with the autoregressive integrated moving average (ARIMA) model by different evaluation indicators.

METHODS

We collected HFRS incidence data from 2004 to 2018 of mainland China. The data from 2004 to 2017 were divided into training sets to establish the seasonal ARIMA model and XGBoost model, while the 2018 data were used to test the prediction performance. In the multistep XGBoost forecasting model, one-hot encoding was used to handle seasonal features. Furthermore, a series of evaluation indices were performed to evaluate the accuracy of the multistep forecast XGBoost model.

RESULTS

There were 200,237 HFRS cases in China from 2004 to 2018. A long-term downward trend and bimodal seasonality were identified in the original time series. According to the minimum corrected akaike information criterion (CAIC) value, the optimal ARIMA (3, 1, 0) × (1, 1, 0)12 model is selected. The index ME, RMSE, MAE, MPE, MAPE, and MASE indices of the XGBoost model were higher than those of the ARIMA model in the fitting part, whereas the RMSE of the XGBoost model was lower. The prediction performance evaluation indicators (MAE, MPE, MAPE, RMSE and MASE) of the one-step prediction and multistep prediction XGBoost model were all notably lower than those of the ARIMA model.

CONCLUSIONS

The multistep XGBoost prediction model showed a much better prediction accuracy and model stability than the multistep ARIMA prediction model. The XGBoost model performed better in predicting complicated and nonlinear data like HFRS. Additionally, Multistep prediction models are more practical than one-step prediction models in forecasting infectious diseases.

Genome-level diversification of eight ancient tea populations in the Guizhou and Yunnan regions identifies candidate genes for core agronomic traits

The ancient tea plant, as a precious natural resource and source of tea plant genetic diversity, is of great value for studying the evolutionary mechanism, diversification, and domestication of plants. The overall genetic diversity among ancient tea plants and the genetic changes that occurred during natural selection remain poorly understood. Here, we report the genome resequencing of eight different groups consisting of 120 ancient tea plants: six groups from Guizhou Province and two groups from Yunnan Province. Based on the 8,082,370 identified high-quality SNPs, we constructed phylogenetic relationships, assessed population structure, and performed genome-wide association studies (GWAS). Our phylogenetic analysis showed that the 120 ancient tea plants were mainly clustered into three groups and five single branches, which is consistent with the results of principal component analysis (PCA). Ancient tea plants were further divided into seven subpopulations based on genetic structure analysis. Moreover, it was found that the variation in ancient tea plants was not reduced by pressure from the external natural environment or artificial breeding (nonsynonymous/synonymous = 1.05). By integrating GWAS, selection signals, and gene function prediction, four candidate genes were significantly associated with three leaf traits, and two candidate genes were significantly associated with plant type. These candidate genes can be used for further functional characterization and genetic improvement of tea plants.

Spatial tissue profiling by imaging-free molecular tomography

Several techniques are currently being developed for spatially resolved omics profiling, but each new method requires the setup of specific detection strategies or specialized instrumentation. Here we describe an imaging-free framework to localize high-throughput readouts within a tissue by cutting the sample into thin strips in a way that allows subsequent image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (called STRP-seq) and validated it by profiling the spatial transcriptome of the mouse brain. We applied the technique to the brain of the Australian bearded dragon, Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. We expect that STRP-seq can be used to derive spatially resolved data from a range of other omics techniques.

Application of high-throughput sequencing for hereditary thrombocytopenia in southwestern China

Background

The aim of this study was to design and analyze the applicability of a 21‐gene high‐throughput sequencing (HTS) panel in the molecular diagnosis of patients with hereditary thrombocytopenia (HT).

Methods

A custom target enrichment library was designed to capture 21 genes known to be associated with HTs. Twenty‐four patients with an HT phenotype were studied using this technology.

Results

One pathogenic variant on the MYH9 gene and one likely pathogenic variant on the ABCG8 gene previously known to cause HTs were identified. Additionally, 3 previously reported variants affecting WAS, ADAMTS13, and GP1BA were detected, and 9 novel variants affecting FLNA, ITGB3, NBEAL2, MYH9, VWF, and ANKRD26 genes were identified. The 12 variants were classified to be of uncertain significance.

Conclusion

Our results demonstrate that HTS is an accurate and reliable method of pre‐screening patients for variants in known HT‐causing genes. With the advantage of distinguishing HT from immune thrombocytopenia, HTS could play a key role in improving the clinical management of patients.

Distinct whole-blood transcriptome profile of children with metabolic healthy overweight/obesity compared to metabolic unhealthy overweight/obesity

BACKGROUND

Youth populations with overweight/obesity (OW/OB) exhibit heterogeneity in cardiometabolic health phenotypes. The underlying mechanisms for those differences are still unclear. This study aimed to analyze the whole-blood transcriptome profile (RNA-seq) of children with metabolic healthy overweight/obesity (MHO) and metabolic unhealthy overweight/obesity (MUO) phenotypes.

METHODS

Twenty-seven children with OW/OB (10.1 ± 1.3 years, 59% boys) from the ActiveBrains project were included. MHO was defined as having none of the following criteria for metabolic syndrome: elevated fasting glucose, high serum triglycerides, low high-density lipoprotein-cholesterol, and high systolic or diastolic blood pressure, while MUO was defined as presenting one or more of these criteria. Inflammatory markers were additionally determined. Total blood RNA was analyzed by 5'-end RNA-sequencing.

RESULTS

Whole-blood transcriptome analysis revealed a distinct pattern of gene expression in children with MHO compared to MUO children. Thirty-two genes differentially expressed were linked to metabolism, mitochondrial, and immune functions.

CONCLUSIONS

The identified gene expression patterns related to metabolism, mitochondrial, and immune functions contribute to a better understanding of why a subset of the population remains metabolically healthy despite having overweight/obesity.

IMPACT

A distinct pattern of whole-blood transcriptome profile (RNA-seq) was identified in children with metabolic healthy overweight/obesity (MHO) compared to metabolic unhealthy overweight/obesity (MUO) phenotype. The most relevant genes in understanding the molecular basis underlying the MHO/MUO phenotypes in children could be: RREB1, FAM83E, SLC44A1, NRG1, TMC5, CYP3A5, TRIM11, and ADAMTSL2. The identified whole-blood transcriptome profile related to metabolism, mitochondrial, and immune functions contribute to a better understanding of why a subset of the population remains metabolically healthy despite having overweight/obesity.

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.

A novel mutation in NF1 gene of patient with Neurofibromatosis type 1: A case report and functional study

BACKGROUND

Neurofibromatosis type 1 is an autosomal dominant inherited disease and caused by NF1 gene mutation. Its clinical manifestations include multiple cafe´-au lait (CAL) spots, skinfold freckling, neurofibroma, bone dysplasia, learning disabilities, and an increased risk of malignancy.

METHODS AND RESULTS

Here, we reported a Chinese patient bearing with a novel NF1 mutation (c.2064delGGATGCAGCGG/p.Gly672AsnfsTer24) and complaining mainly about bone phenotype. Functional studies found that this novel mutation caused the damage of NF1 mRNA and protein levels, and lost the inhibition on Ras/Erk signaling.

CONCLUSION

A novel mutation in NF1 gene was identified and in vitro functional studies were performed, which provided a potential molecular mechanism to explain the bone maldevelopment of patients with neurofibromatosis type 1.

Wafer-scale transfer route for top-down III-nitride nanowire LED arrays based on the femtosecond laser lift-off technique

The integration of gallium nitride (GaN) nanowire light-emitting diodes (nanoLEDs) on flexible substrates offers opportunities for applications beyond rigid solid-state lighting (e.g., for wearable optoelectronics and bendable inorganic displays). Here, we report on a fast physical transfer route based on femtosecond laser lift-off (fs-LLO) to realize wafer-scale top-down GaN nanoLED arrays on unconventional platforms. Combined with photolithography and hybrid etching processes, we successfully transferred GaN blue nanoLEDs from a full two-inch sapphire substrate onto a flexible copper (Cu) foil with a high nanowire density (~107 wires/cm2), transfer yield (~99.5%), and reproducibility. Various nanoanalytical measurements were conducted to evaluate the performance and limitations of the fs-LLO technique as well as to gain insights into physical material properties such as strain relaxation and assess the maturity of the transfer process. This work could enable the easy recycling of native growth substrates and inspire the development of large-scale hybrid GaN nanowire optoelectronic devices by solely employing standard epitaxial LED wafers (i.e., customized LED wafers with additional embedded sacrificial materials and a complicated growth process are not required).

Polycystic Ovary Syndrome: the Epigenetics Behind the Disease

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders, affecting approximately 5-20% of women of reproductive age. PCOS is a multifactorial, complex, and heterogeneous disease, characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries, which may lead to impaired fertility. Besides the reproductive outcomes, multiple comorbidities, such as metabolic disturbances, insulin resistance, obesity, diabetes, and cardiovascular disease, are associated with PCOS. In addition to the clear genetic basis, epigenetic alterations may also play a central role in PCOS outcomes, as environmental and hormonal alterations directly affect clinical manifestations and PCOS development. Here, we highlighted the epigenetic modifications in the multiplicity of clinical manifestations, as well as environmental epigenetic disruptors, as intrauterine hormonal and metabolic alterations affecting embryo development and the adulthood lifestyle, which may contribute to PCOS development. Additionally, we also discussed the new approaches for future studies and potential epigenetic biomarkers for the treatment of associated comorbidities and improvement in quality of life of women with PCOS.

Expanding the drug discovery space with predicted metabolite-target interactions

Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potential metabolite-target interactions using the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2). Using a consensus of multiple machine learning methods, we ranked metabolites based on importance to IBD, followed by virtual ligand-based screening to identify possible human targets and adding evidence from compound assay, differential gene expression, pathway enrichment, and genome-wide association studies. We confirmed known metabolite-target pairs such as nicotinic acid-GPR109a or linoleoyl ethanolamide-GPR119 and inferred interactions of interest including oleanolic acid-GABRG2 and alpha-CEHC-THRB. Eleven metabolites were tested for bioactivity in vitro using human primary cell-types. By expanding the universe of possible microbial metabolite-host protein interactions, we provide multiple drug targets for potential immune-therapies.

Disorders of sex development in Wolf-Hirschhorn syndrome: a genotype-phenotype correlation and MSX1 as candidate gene

BACKGROUND

Wolf-Hirschhorn (WHS) is a set of congenital physical anomalies and mental retardation associated with a partial deletion of the short arm of chromosome 4. To establish a genotype-phenotype correlation; we carried out a molecular cytogenetic analysis on two Tunisian WHS patients. Patient 1 was a boy of 1-year-old, presented a typical WHS phenotype while patient 2, is a boy of 2 days presented an hypospadias, a micropenis and a cryptorchidie in addition to the typical WHS phenotype. Both the array comparative genomic hybridization and fluorescence in situ hybridization techniques were used.

RESULTS

Results of the analysis showed that patient 2 had a greater deletion size (4.8 Mb) of chromosome 4 than patient 1 (3.4 Mb). Here, we notice that the larger the deletion, the more genes are likely to be involved, and the more severe the phenotype is likely to be. If we analyze the uncommon deleted region between patient1 and patient 2 we found that the Muscle Segment Homeobox (MSX1) gene is included in this region. MSX1 is a critical transcriptional repressor factor, expressed in the ventral side of the developing anterior pituitary and implicated in gonadotrope differentiation. Msx1 acts as a negative regulatory pituitary development by repressing the gonadotropin releasing hormone (GnRH) genes during embryogenesis. We hypothesized that the deletion of MSX1 in our patient may deregulate the androgen synthesis.

CONCLUSION

Based on the MSX1 gene function, its absence might be indirectly responsible for the hypospadias phenotype by contributing to the spatiotemporal regulation of GnRH transcription during development.