Showing papers in "Frontiers in Genetics in 2023"

A novel cuproptosis-related lncRNA signature predicts prognosis and therapeutic response in bladder cancer

Abstract: Bladder cancer (BC) ranks the tenth in the incidence of global tumor epidemiology. LncRNAs and cuproptosis were discovered to regulate the cell death. Herein, we downloaded transcriptome profiling, mutational data, and clinical data on patients from The Cancer Genome Atlas (TCGA). High- and low-risk BC patients were categorized. Three CRLs (AL590428.1, AL138756.1 and GUSBP11) were taken into prognostic signature through least absolute shrinkage and selection operator (LASSO) Cox regression. Worse OS and PFS were shown in high-risk group (p < 0.05). ROC, independent prognostic analyses, nomogram and C-index were predicted via CRLs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated IncRNAs play a biological role in BC progression. Immune-related functions showed the high-risk group received more benefit from immunotherapy and had stronger immune responses, and the overall survival was better (p < 0.05). Finally, a more effective outcome (p < 0.05) was found from clinical immunotherapy via the TIDE algorithm and many potential anti-tumor drugs were identified. In our study, the cuproptosis-related signature provided a novel tool to predict the prognosis in BC patients accurately and provided a novel strategy for clinical immunotherapy and clinical applications.

Genome-wide identification, characterization, and validation of the bHLH transcription factors in grass pea

Abstract: Background: The basic helix-loop-helix (bHLH) transcription factor is a vital component in plant biology, with a significant impact on various aspects of plant growth, cell development, and physiological processes. Grass pea is a vital agricultural crop that plays a crucial role in food security. However, the lack of genomic information presents a major challenge to its improvement and development. This highlights the urgency for deeper investigation into the function of bHLH genes in grass pea to improve our understanding of this important crop. Results: The identification of bHLH genes in grass pea was performed on a genome-wide scale using genomic and transcriptomic screening. A total of 122 genes were identified as having conserved bHLH domains and were functionally and fully annotated. The LsbHLH proteins could be classified into 18 subfamilies. There were variations in intron-exon distribution, with some genes lacking introns. The cis-element and gene enrichment analyses showed that the LsbHLHs were involved in various plant functions, including response to phytohormones, flower and fruit development, and anthocyanin synthesis. A total of 28 LsbHLHs were found to have cis-elements associated with light response and endosperm expression biosynthesis. Ten conserved motifs were identified across the LsbHLH proteins. The protein-protein interaction analysis showed that all LsbHLH proteins interacted with each other, and nine of them displayed high levels of interaction. RNA-seq analysis of four Sequence Read Archive (SRA) experiments showed high expression levels of LsbHLHs across a range of environmental conditions. Seven highly expressed genes were selected for qPCR validation, and their expression patterns in response to salt stress showed that LsbHLHD4, LsbHLHD5, LsbHLHR6, LsbHLHD8, LsbHLHR14, LsbHLHR68, and LsbHLHR86 were all expressed in response to salt stress. Conclusion: The study provides an overview of the bHLH family in the grass pea genome and sheds light on the molecular mechanisms underlying the growth and evolution of this crop. The report covers the diversity in gene structure, expression patterns, and potential roles in regulating plant growth and response to environmental stress factors in grass pea. The identified candidate LsbHLHs could be utilized as a tool to enhance the resilience and adaptation of grass pea to environmental stress.

Regulatory mechanisms of microRNAs in endocrine disorders and their therapeutic potential

Abstract: MicroRNAs (miRNAs) are small endogenous non-coding RNA molecules capable of regulating gene expression at the post-transcriptional level either by translational inhibition or mRNA degradation and have recently been importantly related to the diagnosis and prognosis of the most relevant endocrine disorders. The endocrine system comprises various highly vascularized ductless organs regulating metabolism, growth and development, and sexual function. Endocrine disorders constitute the fifth principal cause of death worldwide, and they are considered a significant public health problem due to their long-term effects and negative impact on the patient’s quality of life. Over the last few years, miRNAs have been discovered to regulate various biological processes associated with endocrine disorders, which could be advantageous in developing new diagnostic and therapeutic tools. The present review aims to provide an overview of the most recent and significant information regarding the regulatory mechanism of miRNAs during the development of the most relevant endocrine disorders, including diabetes mellitus, thyroid diseases, osteoporosis, pituitary tumors, Cushing’s syndrome, adrenal insufficiency and multiple endocrine neoplasia, and their potential implications as disease biomarkers.

RNA Pol III promoters—key players in precisely targeted plant genome editing

Abstract: The clustered regularly interspaced short palindrome repeat (CRISPR)/CRISPR-associated protein Cas) system is a powerful and highly precise gene-editing tool in basic and applied research for crop improvement programs. CRISPR/Cas tool is being extensively used in plants to improve crop yield, quality, and nutritional value and make them tolerant to environmental stresses. CRISPR/Cas system consists of a Cas protein with DNA endonuclease activity and one CRISPR RNA transcript that is processed to form one or several short guide RNAs that direct Cas9 to the target DNA sequence. The expression levels of Cas proteins and gRNAs significantly influence the editing efficiency of CRISPR/Cas-mediated genome editing. This review focuses on insights into RNA Pol III promoters and their types that govern the expression levels of sgRNA in the CRISPR/Cas system. We discussed Pol III promoters structural and functional characteristics and their comparison with Pol II promoters. Further, the use of synthetic promoters to increase the targeting efficiency and overcome the structural, functional, and expressional limitations of RNA Pol III promoters has been discussed. Our review reports various studies that illustrate the use of endogenous U6/U3 promoters for improving editing efficiency in plants and the applicative approach of species-specific RNA pol III promoters for genome editing in model crops like Arabidopsis and tobacco, cereals, legumes, oilseed, and horticultural crops. We further highlight the significance of optimizing these species-specific promoters’ systematic identification and validation for crop improvement and biotic and abiotic stress tolerance through CRISPR/Cas mediated genome editing.

Ancestry: How researchers use it and what they mean by it

Abstract: Background: Ancestry is often viewed as a more objective and less objectionable population descriptor than race or ethnicity. Perhaps reflecting this, usage of the term “ancestry” is rapidly growing in genetics research, with ancestry groups referenced in many situations. The appropriate usage of population descriptors in genetics research is an ongoing source of debate. Sound normative guidance should rest on an empirical understanding of current usage; in the case of ancestry, questions about how researchers use the concept, and what they mean by it, remain unanswered. Methods: Systematic literature analysis of 205 articles at least tangentially related to human health from diverse disciplines that use the concept of ancestry, and semi-structured interviews with 44 lead authors of some of those articles. Results: Ancestry is relied on to structure research questions and key methodological approaches. Yet researchers struggle to define it, and/or offer diverse definitions. For some ancestry is a genetic concept, but for many—including geneticists—ancestry is only tangentially related to genetics. For some interviewees, ancestry is explicitly equated to ethnicity; for others it is explicitly distanced from it. Ancestry is operationalized using multiple data types (including genetic variation and self-reported identities), though for a large fraction of articles (26%) it is impossible to tell which data types were used. Across the literature and interviews there is no consistent understanding of how ancestry relates to genetic concepts (including genetic ancestry and population structure), nor how these genetic concepts relate to each other. Beyond this conceptual confusion, practices related to summarizing patterns of genetic variation often rest on uninterrogated conventions. Continental labels are by far the most common type of label applied to ancestry groups. We observed many instances of slippage between reference to ancestry groups and racial groups. Conclusion: Ancestry is in practice a highly ambiguous concept, and far from an objective counterpart to race or ethnicity. It is not uniquely a “biological” construct, and it does not represent a “safe haven” for researchers seeking to avoid evoking race or ethnicity in their work. Distinguishing genetic ancestry from ancestry more broadly will be a necessary part of providing conceptual clarity.

Prospects of microgreens as budding living functional food: Breeding and biofortification through OMICS and other approaches for nutritional security

Abstract: Nutrient deficiency has resulted in impaired growth and development of the population globally. Microgreens are considered immature greens (required light for photosynthesis and growing medium) and developed from the seeds of vegetables, legumes, herbs, and cereals. These are considered “living superfood/functional food” due to the presence of chlorophyll, beta carotene, lutein, and minerals like magnesium (Mg), Potassium (K), Phosphorus (P), and Calcium (Ca). Microgreens are rich at the nutritional level and contain several phytoactive compounds (carotenoids, phenols, glucosinolates, polysterols) that are helpful for human health on Earth and in space due to their anti-microbial, anti-inflammatory, antioxidant, and anti-carcinogenic properties. Microgreens can be used as plant-based nutritive vegetarian foods that will be fruitful as a nourishing constituent in the food industryfor garnish purposes, complement flavor, texture, and color to salads, soups, flat-breads, pizzas, and sandwiches (substitute to lettuce in tacos, sandwich, burger). Good handling practices may enhance microgreens’stability, storage, and shelf-life under appropriate conditions, including light, temperature, nutrients, humidity, and substrate. Moreover, the substrate may be a nutritive liquid solution (hydroponic system) or solid medium (coco peat, coconut fiber, coir dust and husks, sand, vermicompost, sugarcane filter cake, etc.) based on a variety of microgreens. However integrated multiomics approaches alongwith nutriomics and foodomics may be explored and utilized to identify and breed most potential microgreen genotypes, biofortify including increasing the nutritional content (macro-elements:K, Ca and Mg; oligo-elements: Fe and Zn and antioxidant activity) and microgreens related other traits viz., fast growth, good nutritional values, high germination percentage, and appropriate shelf-life through the implementation of integrated approaches includes genomics, transcriptomics, sequencing-based approaches, molecular breeding, machine learning, nanoparticles, and seed priming strategiesetc.

Identification of the diagnostic genes and immune cell infiltration characteristics of gastric cancer using bioinformatics analysis and machine learning

Abstract: Background: Finding reliable diagnostic markers for gastric cancer (GC) is important. This work uses machine learning (ML) to identify GC diagnostic genes and investigate their connection with immune cell infiltration. Methods: We downloaded eight GC-related datasets from GEO, TCGA, and GTEx. GSE13911, GSE15459, GSE19826, GSE54129, and GSE79973 were used as the training set, GSE66229 as the validation set A, and TCGA & GTEx as the validation set B. First, the training set screened differentially expressed genes (DEGs), and gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG), disease Ontology (DO), and gene set enrichment analysis (GSEA) analyses were performed. Then, the candidate diagnostic genes were screened by LASSO and SVM-RFE algorithms, and receiver operating characteristic (ROC) curves evaluated the diagnostic efficacy. Then, the infiltration characteristics of immune cells in GC samples were analyzed by CIBERSORT, and correlation analysis was performed. Finally, mutation and survival analyses were performed for diagnostic genes. Results: We found 207 up-regulated genes and 349 down-regulated genes among 556 DEGs. gene ontology analysis significantly enriched 413 functional annotations, including 310 biological processes, 23 cellular components, and 80 molecular functions. Six of these biological processes are closely related to immunity. KEGG analysis significantly enriched 11 signaling pathways. 244 diseases were closely related to Ontology analysis. Multiple entries of the gene set enrichment analysis analysis were closely related to immunity. Machine learning screened eight candidate diagnostic genes and further validated them to identify ABCA8, COL4A1, FAP, LY6E, MAMDC2, and TMEM100 as diagnostic genes. Six diagnostic genes were mutated to some extent in GC. ABCA8, COL4A1, LY6E, MAMDC2, TMEM100 had prognostic value. Conclusion: We screened six diagnostic genes for gastric cancer through bioinformatic analysis and machine learning, which are intimately related to immune cell infiltration and have a definite prognostic value.

Editorial: Genetic validation and its role in crop improvement

Abstract: Department of Genetics, Faculty of Agriculture, Assiut University, Assiut, Egypt, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany, Biological Science Program, Department of Biological and Environmental Sciences, College of Art and Science, Qatar University, Doha, Qatar, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, United States, Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan

Omics approaches to understanding the efficacy and safety of disease-modifying treatments in multiple sclerosis

Abstract: From the perspective of precision medicine, the challenge for the future is to improve the accuracy of diagnosis, prognosis, and prediction of therapeutic responses through the identification of biomarkers. In this framework, the omics sciences (genomics, transcriptomics, proteomics, and metabolomics) and their combined use represent innovative approaches for the exploration of the complexity and heterogeneity of multiple sclerosis (MS). This review examines the evidence currently available on the application of omics sciences to MS, analyses the methods, their limitations, the samples used, and their characteristics, with a particular focus on biomarkers associated with the disease state, exposure to disease-modifying treatments (DMTs), and drug efficacies and safety profiles.

Revitalization of small millets for nutritional and food security by advanced genetics and genomics approaches

Abstract: Small millets, also known as nutri-cereals, are smart foods that are expected to dominate food industries and diets to achieve nutritional security. Nutri-cereals are climate resilient and nutritious. Small millet-based foods are becoming popular in markets and are preferred for patients with celiac and diabetes. These crops once ruled as food and fodder but were pushed out of mainstream cultivation with shifts in dietary habits to staple crops during the green revolution. Nevertheless, small millets are rich in micronutrients and essential amino acids for regulatory activities. Hence, international and national organizations have recently aimed to restore these lost crops for their desirable traits. The major goal in reviving these crops is to boost the immune system of the upcoming generations to tackle emerging pandemics and disease infestations in crops. Earlier periods of civilization consumed these crops, which had a greater significance in ethnobotanical values. Along with nutrition, these crops also possess therapeutic traits and have shown vast medicinal use in tribal communities for the treatment of diseases like cancer, cardiovascular disease, and gastrointestinal issues. This review highlights the significance of small millets, their values in cultural heritage, and their prospects. Furthermore, this review dissects the nutritional and therapeutic traits of small millets for developing sustainable diets in near future.

Genes and models for estimating genetic parameters for heat tolerance in dairy cattle

Abstract: Dairy cattle are highly susceptible to heat stress. Heat stress causes a decline in milk yield, reduced dry matter intake, reduced fertility rates, and alteration of physiological traits (e.g., respiration rate, rectal temperature, heart rates, pulse rates, panting score, sweating rates, and drooling score) and other biomarkers (oxidative heat stress biomarkers and stress response genes). Considering the significant effect of global warming on dairy cattle farming, coupled with the aim to reduce income losses of dairy cattle farmers and improve production under hot environment, there is a need to develop heat tolerant dairy cattle that can grow, reproduce and produce milk reasonably under the changing global climate and increasing temperature. The identification of heat tolerant dairy cattle is an alternative strategy for breeding thermotolerant dairy cattle for changing climatic conditions. This review synthesizes information pertaining to quantitative genetic models that have been applied to estimate genetic parameters for heat tolerance and relationship between measures of heat tolerance and production and reproductive performance traits in dairy cattle. Moreover, the review identified the genes that have been shown to influence heat tolerance in dairy cattle and evaluated the possibility of using them in genomic selection programmes. Combining genomics information with environmental, physiological, and production parameters information is a crucial strategy to understand the mechanisms of heat tolerance while breeding heat tolerant dairy cattle adapted to future climatic conditions. Thus, selection for thermotolerant dairy cattle is feasible.

Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer

Abstract: Identifying pathogenic missense variants in hereditary cancer is critical to the efforts of patient surveillance and risk-reduction strategies. For this purpose, many different gene panels consisting of different number and/or set of genes are available and we are particularly interested in a panel of 26 genes with a varying degree of hereditary cancer risk consisting of ABRAXAS1, ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MEN1, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, and XRCC2. In this study, we have compiled a collection of the missense variations reported in any of these 26 genes. More than a thousand missense variants were collected from ClinVar and the targeted screen of a breast cancer cohort of 355 patients which contributed to this set with 160 novel missense variations. We analyzed the impact of the missense variations on protein stability by five different predictors including both sequence- (SAAF2EC and MUpro) and structure-based (Maestro, mCSM, CUPSAT) predictors. For the structure-based tools, we have utilized the AlphaFold (AF2) protein structures which comprise the first structural analysis of this hereditary cancer proteins. Our results agreed with the recent benchmarks that computed the power of stability predictors in discriminating the pathogenic variants. Overall, we reported a low-to-medium-level performance for the stability predictors in discriminating pathogenic variants, except MUpro which had an AUROC of 0.534 (95% CI [0.499–0.570]). The AUROC values ranged between 0.614–0.719 for the total set and 0.596–0.682 for the set with high AF2 confidence regions. Furthermore, our findings revealed that the confidence score for a given variant in the AF2 structure could alone predict pathogenicity more robustly than any of the tested stability predictors with an AUROC of 0.852. Altogether, this study represents the first structural analysis of the 26 hereditary cancer genes underscoring 1) the thermodynamic stability predicted from AF2 structures as a moderate and 2) the confidence score of AF2 as a strong descriptor for variant pathogenicity.

Assessing the causal relationships between human blood metabolites and the risk of NAFLD: A comprehensive mendelian randomization study

Abstract: Background: Non-alcoholic fatty liver disease (NAFLD) is a liver disease associated with obesity, insulin resistance, type 2 diabetes mellitus (T2DM), and metabolic syndrome. The risk factors for NAFLD have not been identified. Metabolic dysfunction has been found to be an important factor in the pathogenesis and progression of NAFLD. However, the causal impact of blood metabolites on NAFLD is unclear. Methods: We performed a two-sample Mendelian randomization (MR) study. A genome-wide association study (GWAS) with 7824 participants provided data on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS meta-analysis of NAFLD, which contained 8,434 cases and 770,180 controls of Europeans. The inverse variance weighted (IVW) model was chosen as the primary two-sample MR analysis approach, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis. In addition, we performed replication, meta-analysis, and metabolic pathway analysis. We further conducted colocalization analysis to deeply reflect the causality. Results: After rigorous genetic variant selection, IVW, sensitivity analysis, replication, and meta-analysis, two known metabolites were identified as being associated with the development of NAFLD [biliverdin: OR = 1.45; 95% CI 1.20-1.75; p = 0.0001; myristoleate: OR = 0.57; 95% CI 0.39-0.83; p = 0.0030]. Conclusion: By combining genomics with metabolomics, our findings provide a new perspective on the underlying mechanisms of NAFLD and have important implications for the screening and prevention of NAFLD.

Urinary extracellular vesicles miRNA—A new era of prostate cancer biomarkers

Abstract: Prostate cancer is the second most common male cancer worldwide showing the highest rates of incidence in Western Europe. Although the measurement of serum prostate-specific antigen levels is the current gold standard in PCa diagnosis, PSA-based screening is not considered a reliable diagnosis and prognosis tool due to its lower sensitivity and poor predictive score which lead to a 22%–43% overdiagnosis, unnecessary biopsies, and over-treatment. These major limitations along with the heterogeneous nature of the disease have made PCa a very unappreciative subject for diagnostics, resulting in poor patient management; thus, it urges to identify and validate new reliable PCa biomarkers that can provide accurate information in regard to disease diagnosis and prognosis. Researchers have explored the analysis of microRNAs (miRNAs), messenger RNAs (mRNAs), small proteins, genomic rearrangements, and gene expression in body fluids and non-solid tissues in search of lesser invasive yet efficient PCa biomarkers. Although the presence of miRNAs in body fluids like blood, urine, and saliva initially sparked great interest among the scientific community; their potential use as liquid biopsy biomarkers in PCa is still at a very nascent stage with respect to other well-established diagnostics and prognosis tools. Up to date, numerous studies have been conducted in search of PCa miRNA-based biomarkers in whole blood or blood serum; however, only a few studies have investigated their presence in urine samples of which less than two tens involve the detection of miRNAs in extracellular vesicles isolated from urine. In addition, there exists some discrepancy around the identification of miRNAs in PCa urine samples due to the diversity of the urine fractions that can be targeted for analysis such as urine circulating cells, cell-free fractions, and exosomes. In this review, we aim to discuss research output from the most recent studies involving the analysis of urinary EVs for the identification of miRNA-based PCa-specific biomarkers.

Governing biotechnology to provide safety and security and address ethical, legal, and social implications

Abstract: The field of biotechnology has produced a wide variety of materials and products which are rapidly entering the commercial marketplace. While many developments promise revolutionary benefits, some of them pose uncertain or largely untested risks and may spur debate, consternation, and outrage from individuals and groups who may be affected by their development and use. In this paper we show that the success of any advanced genetic development and usage requires that the creators establish technical soundness, ensure safety and security, and transparently represent the product’s ethical, legal, and social implications (ELSI). We further identify how failures to address ELSI can manifest as significant roadblocks to product acceptance and adoption and advocate for use of the “safety-by-design” governance philosophy. This approach requires addressing risk and ELSI needs early and often in the technology development process to support innovation while providing security and safety for workers, the public, and the broader environment. This paper identifies and evaluates major ELSI challenges and perspectives to suggest a methodology for implementing safety-by-design in a manner consistent with local institutions and politics. We anticipate the need for safety-by-design approach to grow and permeate biotechnology governance structures as the field expands in scientific and technological complexity, increases in public attention and prominence, and further impacts human health and the environment.

Gene therapy for lysosomal storage diseases: Current clinical trial prospects

Abstract: Lysosomal storage diseases (LSDs) are a group of metabolic inborn errors caused by defective enzymes in the lysosome, resulting in the accumulation of undegraded substrates. LSDs are progressive diseases that exhibit variable rates of progression depending on the disease and the patient. The availability of effective treatment options, including substrate reduction therapy, pharmacological chaperone therapy, enzyme replacement therapy, and bone marrow transplantation, has increased survival time and improved the quality of life in many patients with LSDs. However, these therapies are not sufficiently effective, especially against central nerve system abnormalities and corresponding neurological and psychiatric symptoms because of the blood-brain barrier that prevents the entry of drugs into the brain or limiting features of specific treatments. Gene therapy is a promising tool for the treatment of neurological pathologies associated with LSDs. Here, we review the current state of gene therapy for several LSDs for which clinical trials have been conducted or are planned. Several clinical trials using gene therapy for LSDs are underway as phase 1/2 studies; no adverse events have not been reported in most of these studies. The administration of viral vectors has achieved good therapeutic outcomes in animal models of LSDs, and subsequent human clinical trials are expected to promote the practical application of gene therapy for LSDs.

Triple negative breast cancer: Immunogenicity, tumor microenvironment, and immunotherapy

Abstract: Triple negative breast cancer (TNBC) is a biologically diverse subtype of breast cancer characterized by genomic and transcriptional heterogeneity and exhibiting aggressive clinical behaviour and poor prognosis. In recent years, emphasis has been placed on the identification of mechanisms underlying the complex genomic and biological profile of TNBC, aiming to tailor treatment strategies. High immunogenicity, specific immune activation signatures, higher expression of immunosuppressive genes and higher levels of stromal Tumor Infiltrating Lymphocytes, constitute some of the key elements of the immune driven landscape associated with TNBC. The unprecedented response of TNBC to immunotherapy has undoubtedly changed the standard of care in this disease both in the early and the metastatic setting. However, the extent of interplay between immune infiltration and mutational signatures in TNBC is yet to be fully unravelled. In the present review, we present clinical evidence on the immunogenicity and tumour microenvironment influence on TNBC progression and the current treatment paradigms in TNBC based on immunotherapy.

Genome-wide identification, evolution and transcriptome analysis of GRAS gene family in Chinese chestnut (Castanea mollissima)

Abstract: GRAS transcription factors play an important role in regulating various biological processes in plant growth and development. However, their characterization and potential function are still vague in Chinese chestnut (Castanea mollissima), an important nut with rich nutrition and high economic value. In this study, 48 CmGRAS genes were identified in Chinese chestnut genome and phylogenetic analysis divided CmGRAS genes into nine subfamilies, and each of them has distinct conserved structure domain and features. Genomic organization revealed that CmGRAS tend to have a representative GRAS domain and fewer introns. Tandem duplication had the greatest contribution for the CmGRAS expansion based on the comparative genome analysis, and CmGRAS genes experienced strong purifying selection pressure based on the Ka/Ks. Gene expression analysis revealed some CmGRAS members with potential functions in bud development and ovule fertility. CmGRAS genes with more homologous relationships with reference species had more cis-acting elements and higher expression levels. Notably, the lack of DELLA domain in members of the DELLA subfamily may cause de functionalization, and the differences between the three-dimensional structures of them were exhibited. This comprehensive study provides theoretical and practical basis for future research on the evolution and function of GRAS gene family.

Single-cell omics: A new direction for functional genetic research in human diseases and animal models

Abstract: Over the past decade, with the development of high-throughput single-cell sequencing technology, single-cell omics has been emerged as a powerful tool to understand the molecular basis of cellular mechanisms and refine our knowledge of diverse cell states. They can reveal the heterogeneity at different genetic layers and elucidate their associations by multiple omics analysis, providing a more comprehensive genetic map of biological regulatory networks. In the post-GWAS era, the molecular biological mechanisms influencing human diseases will be further elucidated by single-cell omics. This review mainly summarizes the development and trend of single-cell omics. This involves single-cell omics technologies, single-cell multi-omics technologies, multiple omics data integration methods, applications in various human organs and diseases, classic laboratory cell lines, and animal disease models. The review will reveal some perspectives for elucidating human diseases and constructing animal models.

Positive regulation of innate immune response by miRNA-let-7a-5p

Abstract: Background: We have hypothesized that different factors are involved in the severity of ACD and AD because some but not all patients with atopic dermatitis (AD) present with allergic conjunctival disease (ACD) including severe types such as atopic keratoconjunctivitis (AKC) with/without giant papillae. We previously reported that plasma miR-628-3p was up-regulated in AD with severe ACD, but not in severe AD without severe ACD or in our healthy controls. In this study, to investigate the pathogenesis of AD with and without severe ACD, we performed comprehensive plasma miRNA analysis and studied the function of some miRNAs which were significantly up-regulated in ACD. Methods: Transcriptomics analysis of miRNA was performed using the microarray platform from the plasma of nine individuals (AD, severe ACD, controls: n = 3 each). To confirm up-regulation of the 12 miRNAs of the eight miRNA groups we focused on, we performed quantitative miRNA polymerase chain reaction (PCR) assays using 80 plasma samples (AD: 23, severe ACD: 17, controls: 40). To study the function of the eight miRNAs which were significantly up-regulated in ACD, we transfected their mimic to THP-1 cells, a monocyte cell line, and performed comprehensive gene expression analysis of them. The up-regulation of gene expression of interest in transfected THP-1 cells with the hsa-let-7a-5p miRNA mimic was confirmed by quantitative RT-qPCR assay. Results: Quantitative miRNA PCR assays showed that hsa-let-7a-5p, hsa-let-7days-3p, hsa-let-7e-5p, and hsa-miR-151a-5p were significantly up-regulated in both AD-ACD + and AD-ACD - as were hsa-miR-130a-3p, hsa-miR-151a-3p, has-miR-27b-3p, and hsa-miR-146a-5p in AD-ACD + but not in AD-ACD - . The functions of each miRNA were investigated by comprehensive gene expression analysis of THP-1 cells transfected with each miRNA mimic. Of the eight miRNAs, hsa-let-7a-5p, hsa-let-7e-5p, has-miR-27b-3p, and hsa-miR-146a-5p mimic-transfected THP-1 cells showed the up-regulation of CXCL10 (IP-10; interferon gamma-induced protein 10), which might be one of the innate immune-related genes. Quantitative RT-qPCR assays of transfected THP-1 cells with the hsa-let-7a-5p miRNA mimic showed that the 17 genes up-regulated more than 10-fold in the comprehensive gene expression analysis, and TLR3, RIG-I, and MDA5, important innate immune-related genes, were significantly up-regulated. TNFSF13B, AIM2, USP41, STAP1, GBP4, CCL8, and IFI27, reportedly down-regulated by the hsa-miR-628-3p mimic, were also significantly up-regulated in the transfected cells. Conclusion: Hsa-let-7a-5p, which was significantly up-regulated in AD-ACD + and AD-ACD - , could positively regulate the important innate immune-related genes such as TLR3, RIG-I, and MDA5. It is possible that in an allergic disease such as atopic keratoconjunctivitis and/or dermatitis, innate immune responses might be positively regulated by hsa-let-7a-5p in the plasma.

In-depth analysis of large-scale screening of WRKY members based on genome-wide identification

Abstract: With the rapid advancement of high-throughput sequencing technology, it is now possible to identify individual gene families from genomes on a large scale in order to study their functions. WRKY transcription factors are a key class of regulators that regulate plant growth and abiotic stresses. Here, a total of 74 WRKY genes were identified from Dendrobium officinale Kimura et Migo genome. Based on the genome-wide analysis, an in-depth analysis of gene structure and conserved motif was performed. The phylogenetic analysis indicated that DoWRKYs could be classified into three main groups: I, II, and III, with group II divided into five subgroups: II-a, II-b, II-c, II-d, and II-e. The sequence alignment indicated that these WRKY transcriptional factors contained a highly conserved WRKYGQK heptapeptide. The localization analysis of chromosomes showed that WRKY genes were irregularly distributed across several chromosomes of D. officinale. These genes comprised diverse patterns in both number and species, and there were certain distinguishing motifs among subfamilies. Moreover, the phylogenetic tree and chromosomal location results indicated that DoWRKYs may have undergone a widespread genome duplication event. Based on an evaluation of expression profiles, we proposed that DoWRKY5, 54, 57, 21, etc. may be involved in the transcriptional regulation of the JA signaling pathway. These results provide a scientific reference for the study of DoWRKY family genes.

Genomic epidemiology of Mycobacterium avium subsp. paratuberculosis isolates from Canadian dairy herds provides evidence for multiple infection events

Abstract: Mycobacterium avium subsp. paratuberculosis (MAP) is the pathogen responsible for paratuberculosis or Johne’s Disease (JD) in ruminants, which is responsible for substantial economic losses worldwide. MAP transmission primarily occurs through the fecal-oral route, and the introduction of an MAP infected animal into a herd is an important transmission route. In the current study, we characterized MAP isolates from 67 cows identified in 20 herds from the provinces of Quebec and Ontario, Canada. Whole genome sequencing (WGS) was performed and an average genome coverage (relative to K-10) of ∼14.9 fold was achieved. The total number of SNPs present in each isolate varied from 51 to 132 and differed significantly between herds. Isolates with the highest genetic variability were generally present in herds from Quebec. The isolates were broadly separated into two main clades and this distinction was not influenced by the province from which they originated. Analysis of 8 MIRU-VNTR loci and 11 SSR loci was performed on the 67 isolates from the 20 dairy herds and publicly available references, notably major genetic lineages and six isolates from the province of Newfoundland and Labrador. All 67 field isolates were phylogenetically classified as Type II (C-type) and according to MIRU-VNTR, the predominant type was INMV 2 (76.1%) among four distinct patterns. Multilocus SSR typing identified 49 distinct INMV SSR patterns. The discriminatory index of the multilocus SSR typing was 0.9846, which was much higher than MIRU-VNTR typing (0.3740). Although multilocus SSR analysis provides good discriminatory power, the resolution was not informative enough to determine inter-herd transmission. In select cases, SNP-based analysis was the only approach able to document disease transmission between herds, further validated by animal movement data. The presence of SNPs in several virulence genes, notably for PE, PPE, mce and mmpL, is expected to explain differential antigenic or pathogenetic host responses. SNP-based studies will provide insight into how MAP genetic variation may impact host-pathogen interactions. Our study highlights the informative power of WGS which is now recommended for epidemiological studies and to document mixed genotypes infections.

Transcriptomic data analysis coupled with copy number aberrations reveals a blood-based 17-gene signature for diagnosis and prognosis of patients with colorectal cancer

Abstract: Background: Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-associated deaths worldwide. Diagnosing CRC patients reliably at an early and curable stage is of utmost importance to reduce the risk of mortality. Methods: We identified global differentially expressed genes with copy number alterations in patients with CRC. We then identified genes that are also expressed in blood, which resulted in a blood-based gene signature. We validated the gene signature’s diagnostic and prognostic potential using independent datasets of gene expression profiling from over 800 CRC patients with detailed clinical data. Functional enrichment, gene interaction networks and pathway analyses were also performed. Results: The analysis revealed a 17-gene signature that is expressed in blood and demonstrated that it has diagnostic potential. The 17-gene SVM classifier displayed 99 percent accuracy in predicting the patients with CRC. Moreover, we developed a prognostic model and defined a risk-score using 17-gene and validated that high risk score is strongly associated with poor disease outcome. The 17-gene signature predicted disease outcome independent of other clinical factors in the multivariate analysis (HR = 2.7, 95% CI = 1.3–5.3, p = 0.005). In addition, our gene network and pathway analyses revealed alterations in oxidative stress, STAT3, ERK/MAPK, interleukin and cytokine signaling pathways as well as potentially important hub genes, including BCL2, MS4A1, SLC7A11, AURKA, IL6R, TP53, NUPR1, DICER1, DUSP5, SMAD3, and CCND1. Conclusion: Our results revealed alterations in various genes and cancer-related pathways that may be essential for CRC transformation. Moreover, our study highlights diagnostic and prognostic value of our gene signature as well as its potential use as a blood biomarker as a non-invasive diagnostic method. Integrated analysis transcriptomic data coupled with copy number aberrations may provide a reliable method to identify key biological programs associated with CRC and lead to improved diagnosis and therapeutic options.

A statistical boosting framework for polygenic risk scores based on large-scale genotype data

Abstract: Polygenic risk scores (PRS) evaluate the individual genetic liability to a certain trait and are expected to play an increasingly important role in clinical risk stratification. Most often, PRS are estimated based on summary statistics of univariate effects derived from genome-wide association studies. To improve the predictive performance of PRS, it is desirable to fit multivariable models directly on the genetic data. Due to the large and high-dimensional data, a direct application of existing methods is often not feasible and new efficient algorithms are required to overcome the computational burden regarding efficiency and memory demands. We develop an adapted component-wise L 2 -boosting algorithm to fit genotype data from large cohort studies to continuous outcomes using linear base-learners for the genetic variants. Similar to the snpnet approach implementing lasso regression, the proposed snpboost approach iteratively works on smaller batches of variants. By restricting the set of possible base-learners in each boosting step to variants most correlated with the residuals from previous iterations, the computational efficiency can be substantially increased without losing prediction accuracy. Furthermore, for large-scale data based on various traits from the UK Biobank we show that our method yields competitive prediction accuracy and computational efficiency compared to the snpnet approach and further commonly used methods. Due to the modular structure of boosting, our framework can be further extended to construct PRS for different outcome data and effect types—we illustrate this for the prediction of binary traits.

Maternal high fat diets: impacts on offspring obesity and epigenetic hypothalamic programming

Abstract: Maternal high-fat diet (HFD) during pregnancy is associated with rapid weight gain and fetal fat mass increase at an early stage. Also, HFD during pregnancy can cause the activation of proinflammatory cytokines. Maternal insulin resistance and inflammation lead to increased adipose tissue lipolysis, and also increased free fatty acid (FFA) intake during pregnancy (˃35% of energy from fat) cause a significant increase in FFA levels in the fetus. However, both maternal insulin resistance and HFD have detrimental effects on adiposity in early life. As a result of these metabolic alterations, excess fetal lipid exposure may affect fetal growth and development. On the other hand, increase in blood lipids and inflammation can adversely affect the development of the liver, adipose tissue, brain, skeletal muscle, and pancreas in the fetus, increasing the risk for metabolic disorders. In addition, maternal HFD is associated with changes in the hypothalamic regulation of body weight and energy homeostasis by altering the expression of the leptin receptor, POMC, and neuropeptide Y in the offspring, as well as altering methylation and gene expression of dopamine and opioid-related genes which cause changes in eating behavior. All these maternal metabolic and epigenetic changes may contribute to the childhood obesity epidemic through fetal metabolic programming. Dietary interventions, such as limiting dietary fat intake <35% with appropriate fatty acid intake during the gestation period are the most effective type of intervention to improve the maternal metabolic environment during pregnancy. Appropriate nutritional intake during pregnancy should be the principal goal in reducing the risks of obesity and metabolic disorders.

Cuproptosis-related gene FDX1 as a prognostic biomarker for kidney renal clear cell carcinoma correlates with immune checkpoints and immune cell infiltration

Abstract: Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the “TIDE” algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4+ T cells, CD8+ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Abstract: Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

Transcriptome analysis reveals the regulation of cyclic nucleotide-gated ion channels in response to exogenous abscisic acid and calcium treatment under drought stress in tomato

Abstract: Background: Drought stress can limit the growth and development of tomato seedlings and cause considerable loss of tomato yield. Exogenous abscisic acid (ABA) and calcium (Ca2+) can effectively alleviate the damage of drought stress to plants in part because Ca2+ acts as a second messenger in the drought resistance pathway. Although cyclic nucleotide-gated ion channels (CNGCs) are common non-specific Ca2+ osmotic channels in cell membranes, a thorough understanding of the transcriptome characteristics of tomato treated with exogenous ABA and Ca2+ under drought stress is necessary to characterize the molecular mechanism of CNGC involved in tomato drought resistance. Results: There were 12,896 differentially expressed genes in tomato under drought stress, as well as 11,406 and 12,502 differentially expressed genes after exogenous ABA and Ca2+ application, respectively. According to functional annotations and reports, the 19 SlCNGC genes related to Ca2+ transport were initially screened, with 11 SlCNGC genes that were upregulated under drought stress and downregulated after exogenous ABA application. After exogenous Ca2+ application, the data showed that two of these genes were upregulated, while nine genes were downregulated. Based on these expression patterns, we predicted the role of SlCNGC genes in the drought resistance pathway and their regulation by exogenous ABA and Ca2+ in tomato. Conclusion: The results of this study provide foundational data for further study of the function of SlCNGC genes and a more comprehensive understanding of drought resistance mechanisms in tomato.

RNA-seq data science: From raw data to effective interpretation

Abstract: RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.

Promoting patient engagement in cancer genomics research programs: An environmental scan

Abstract: Background: A national priority in the United States is to promote patient engagement in cancer genomics research, especially among diverse and understudied populations. Several cancer genomics research programs have emerged to accomplish this priority, yet questions remain about the meaning and methods of patient engagement. This study explored how cancer genomics research programs define engagement and what strategies they use to engage patients across stages in the conduct of research. Methods: An environmental scan was conducted of cancer genomics research programs focused on patient engagement. Research programs were identified and characterized using materials identified from publicly available sources (e.g., websites), a targeted literature review, and interviews with key informants. Descriptive information about the programs and their definitions of engagement, were synthesized using thematic analysis. The engagement strategies were synthesized and mapped to different stages in the conduct of research, including recruitment, consent, data collection, sharing results, and retention. Results: Ten research programs were identified, examples of which include the Cancer Moonshot Biobank, the MyPART Network, NCI-CONNECT, and the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. All programs aimed to include understudied or underrepresented populations. Based on publicly available information, four programs explicitly defined engagement. These definitions similarly characterized engagement as being interpersonal, reciprocal, and continuous. Five general strategies of engagement were identified across the programs: 1) digital (such as websites) and 2) non-digital communications (such as radio broadcasts, or printed brochures); 3) partnering with community organizations; 4) providing incentives; and 5) affiliating with non-academic medical centers. Digital communications were the only strategy used across all stages of the conduct of research. Programs tailored these strategies to their study goals, including overcoming barriers to research participation among diverse populations. Conclusion: Programs studying cancer genomics are deeply committed to increasing research participation among diverse populations through patient engagement. Yet, the field needs to reach a consensus on the meaning of patient engagement, develop a taxonomy of patient engagement measures in cancer genomics research, and identify optimal strategies to engage patients in cancer genomics. Addressing these needs could enable patient engagement to fulfill its potential and accelerate the pace of cancer genomic discoveries.