Ryan V. Crawford, Jamie L. Crawford, Julie L. Hansen
et al.
Abstract This study evaluated near‐infrared spectroscopy (NIRS) for nondestructive crude protein (CP) prediction in hemp (Cannabis sativa L.) grain and validated the biological basis of spectral predictions. Note that 149 whole grain samples from 38 cultivars were collected from New York trials (2017–2021) and validated for CP by combustion. Seven preprocessing methods were tested using 100 training/testing splits, with standard normal variate transformation following Savitzky–Golay filtering selected as optimal. Comparing algorithms showed that partial least squares regression (PLSR) significantly outperformed support vector machines and random forest. The best preprocessing method and algorithm was applied to 1000 additional splits. Optimal models contained 12 components with mean performance of root mean square error [RMSE] = 9.94, r2 = 0.84, relative predicted deviation [RPD] = 2.5, and ratio of performance to interquartile distance [RPIQ] = 3.94. More than 99% of the models had, at minimum, the ability to distinguish between high and low values, with 93.2% capable of quantitative prediction. To validate biological relevance, a protein‐focused model was developed using three known protein absorption bands (1200–1250, 1500–1550, and 2040–2090 nm). These models had substantially reduced performance with 86% of models capable of distinguishing between high and low values but only 14% of models capable of quantitative prediction. However, this targeted approach offers evidence that NIRS predictions are biologically grounded in protein‐specific spectral features rather than spurious correlations. This research demonstrates the promise and biological validity of NIRS for hemp grain CP assessment, supporting applications in breeding programs, although applications demanding more accurate prediction will require better models.
Moez Dawood, Ben Heavner, Marsha M. Wheeler
et al.
Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://gregorconsortium.org/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.
Imaging genetics is a growing field that employs structural or functional neuroimaging techniques to study individuals with genetic risk variants potentially linked to specific illnesses. This area presents considerable challenges to statisticians due to the heterogeneous information and different data forms it involves. In addition, both imaging and genetic data are typically high-dimensional, creating a "big data squared" problem. Moreover, brain imaging data contains extensive spatial information. Simply vectorizing tensor images and treating voxels as independent features can lead to computational issues and disregard spatial structure. This paper presents a novel statistical method for imaging genetics modeling while addressing all these challenges. We explore a Canonical Correlation Analysis based linear model for the joint modeling of brain imaging, genetic information, and clinical phenotype, enabling the simultaneous detection of significant brain regions and selection of important genetic variants associated with the phenotype outcome. Scalable algorithms are developed to tackle the "big data squared" issue. We apply the proposed method to explore the reaction speed, an indicator of cognitive functions, and its associations with brain MRI and genetic factors using the UK Biobank database. Our study reveals a notable connection between the caudate nucleus region of brain and specific significant SNPs, along with their respective regulated genes, and the reaction speed.
Andrea Iglesias-Ramas, Samuele Pio Lipani, Rosalind J. Allen
Population genetics lies at the heart of evolutionary theory. This topic forms part of many biological science curricula but is rarely taught to physics students. Since physicists are becoming increasingly interested in biological evolution, we aim to provide a brief introduction to population genetics, written for physicists. We start with two background chapters: chapter 1 provides a brief historical introduction to the topic, while chapter 2 provides some essential biological background. We begin our main content with chapter 3 which discusses the key concepts behind Darwinian natural selection and Mendelian inheritance. Chapter 4 covers the basics of how variation is maintained in populations, while chapter 5 discusses mutation and selection. In chapter 6 we discuss stochastic effects in population genetics using the Wright-Fisher model as our example, and finally we offer concluding thoughts and references to excellent textbooks in chapter 7.
Majed Alluqmani, Abdulfatah M. Alayoubi, Jamil A. Hashmi
et al.
BackgroundVariants in a gene encoding sodium voltage-gated channel alpha subunit 1 (SCN1A) are known to cause a broad clinical spectrum of epilepsy and associated features, including Dravet syndrome (MIM 607208), non-Dravet developmental and epileptic encephalopathy (MIM 619317), familial febrile seizures (MIM 604403), familial hemiplegic migraine (MIM 609634), and generalized epilepsy with febrile seizures (MIM 604403).MethodsIn this study, we examined a patient with Parkinson’s disease (PD) without any clinical manifestations of epilepsy and associated features. Genomic nucleic acid was extracted, and a complete coding sequence of the human genome (whole-exome sequencing) was sequenced. Moreover, Sanger sequencing of variants of interest was performed to validate the exome-discovered variants.ResultsWe identified a heterozygous pathogenic missense mutation (c.1498C>T; p.Arg500Trp) in the SCN1A gene in the patient using the whole-exome sequencing approach. The onset of PD features in our patient occurred at the age of 30 years. Biochemical investigations were carried out to rule out any secondary cause of the disease, including Wilson's disease or another metabolic disorder. MRI of the brain and spinal images were unremarkable. Moreover, a dramatic response to carbidopa–levodopa treatment was also observed in the patient.ConclusionOur results suggest that the pathogenic variant in SCN1A may lead to PD features without epilepsy.
The experiment was conducted during summer seasons of 2021–22 and 2022–2023 at ICAR-Research Complex for Eastern Region, Farming System Research Centre for Hill and Plateau Region, Plandu, Ranchi, Jharkhand focused on assessing the genetic diversity for fruit yield and quality parameters among 46 unique pointed gourd (Trichosanthes dioica Roxb.) genotypes. The data collected underwent thorough statistical analyses, encompassing genetic variability, analysis of variance (ANOVA), correlation coefficients, path analysis, exploration of genetic divergence and biochemical characterization. The ANOVA results revealed significant variations across the selected genotypes in terms of fruit yield and quality traits. Key attributes, such as the number of fruits/plant, harvest frequency, pulp seed ratio and total phenol content, displayed significant positive correlations with total fruit yield. The noteworthy was the positive direct effect of pulp weight on total fruit yield indicated by a coefficient of 0.99. Further, this study identified total fruit yield as the primary contributor to the observed genetic diversity. Cluster analysis results in to the grouping of 46 genotypes into 12 distinct clusters based on D2 values. The study highlighted significant variability among pointed gourd genotypes, suggesting ample opportunities for selection-based improvement. Selection based on characteristics such as the number of fruits per plant, pulp weight and pulp seed ratio is expected to enhance yield potential. Identified genotypes, such as Swarna Alaukik, HAP-79, HAP-70 (for yield-related attributes) and HAP-106 (for quality traits), emerged as promising which hold potential for future breeding initiatives and are recommended for cultivation in the eastern plateau and hill region for augmenting yield potential. Cluster III and cluster XII offer diverse genetics for breeding. Crossing these clusters can create new high-yield cultivars. This strategic cultivation aims to enhance the nutritional well-being of the local population in that area.
Thi Thanh Nga Le, Minh Thiet Vu, Hoang Dang Khoa Do
Abstract Dicliptera tinctoria is a member of Acanthaceae, which has a wide distribution and contains potentially medicinal species, and exhibited pharmaceutical potentials. This study sequenced and characterized the complete chloroplast genome of Dicliptera tinctoria. The newly sequenced cpDNA of D. tinctoria was 150,733 bp in length and had a typical quadripartite structure consisting of a large single copy (LSC, 82,895 bp), a small single copy (SSC, 17,249 bp), and two inverted repeat (IRs, 25,295 bp each) regions. This genome also contained 80 protein-coding genes, 30 transfer RNAs, and four ribosomal RNAs, which is identical to other chloroplast genomes in Acanthaceae family. Nucleotides diversity analysis among chloroplast genomes of Acanthaceae species revealed eight hypervariable regions, including trnK_UUU-matK, trnC_GCA-petN, accD, rps12-clpP, rps3-rps19, ycf1-ndhF, ccsA-ndhD, and ycf1. Phylogenetic analysis revealed the paraphyly of Dicliptera species and monophyly in four Acanthaceae subfamilies. These results provide an overview of genomic variations in Acanthaceae chloroplast genome, which is helpful for further genomic studies.
Background: Fibrosis is a heavy burden on the global healthcare system. Recently, an increasing number of studies have demonstrated that Extracellular vesicles play an important role in intercellular communication under both physiological and pathological conditions. This study aimed to explore the role of extracellular vesicles’ in fibrosis using bibliometric methods. Methods: Original articles and reviews related to extracellular vesicles and fibrosis were obtained from the Web of Science Core Collection database on November 9, 2022. VOSviewer was used to obtain general information, including co-institution, co-authorship, and co-occurrence visualization maps. The CiteSpace software was used to analyze citation bursts of keywords and references, a timeline view of the top clusters of keywords and cited articles, and the dual map. R package ''bibliometrix'' was used to analyze annual production, citation per year, collaboration network between countries/regions, thematic evolution map, and historiography network. Results: In total, 3376 articles related to extracellular vesicles and fibrosis published from 2013 to 2022 were included in this study, with China and the United States being the top contributors. Shanghai Jiao Tong University has the highest number of publications. The main collaborators were Giovanni Camussi, Stefania Bruno, Marta Tepparo, and Cristina Grange. Journals related to molecular, biology, genetics, health, immunology, and medicine tended to publish literature on extracellular vesicles and fibrosis. “Recovery,” “heterogeneity,” “degradation,” “inflammation,” and “mesenchymal stem cells” are the keywords in this research field. Literature on extracellular vesicles and fibrosis associated with several diseases, including “kidney disease,” “rheumatoid arthritis,” and “skin regeneration” may be the latest hot research field. Conclusions: This study provides a comprehensive perspective on extracellular vesicles and fibrosis through a bibliometric analysis of articles published between 2013 and 2022. We identified the most influential countries, institutions, authors, and journals. We provide information on recent research frontiers and trends for scholars interested in the field of extracellular vesicles and fibrosis. Their role in biological processes has great potential to initiate a new upsurge in future research.
Monica H. Wojcik, Chloe M. Reuter, Shruti Marwaha
et al.
Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order and emerging technologies, such as optical genome mapping and long-read DNA or RNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to a consortium such as GREGoR, which is focused on elucidating the underlying cause of rare unsolved genetic disorders.
David J. Cutler, Kiana Jodeiry, Andrew J. Bass
et al.
In this the first of an anticipated four paper series, fundamental results of quantitative genetics are presented from a first principles approach. While none of these results are in any sense new, they are presented in extended detail to precisely distinguish between definition and assumption, with a further emphasis on distinguishing quantities from their usual approximations. Terminology frequently encountered in the field of human genetic disease studies will be defined in terms of their quantitive genetics form. Methods for estimation of both quantitative genetics and the related human genetics quantities will be demonstrated. While practitioners in the field of human quantitative disease studies may find this work pedantic in detail, the principle target audience for this work is trainees reasonably familiar with population genetics theory, but with less experience in its application to human disease studies. We introduce much of this formalism because in later papers in this series, we demonstrate that common areas of confusion in human disease studies can be resolved be appealing directly to these formal definitions. The second paper in this series will discuss polygenic risk scores. The third paper will concern the question of "missing" heritability and the role interactions may play. The fourth paper will discuss sexually dimorphic disease and the potential role of the X chromosome.
Scott Mastromatteo, Angela Chen, Jiafen Gong
et al.
Summary: Phasing of heterozygous alleles is critical for interpretation of cis-effects of disease-relevant variation. We sequenced 477 individuals with cystic fibrosis (CF) using linked-read sequencing, which display an average phase block N50 of 4.39 Mb. We use these samples to construct a graph representation of CFTR haplotypes, demonstrating its utility for understanding complex CF alleles. These are visualized in a Web app, CFTbaRcodes, that enables interactive exploration of CFTR haplotypes present in this cohort. We perform fine-mapping and phasing of the chr7q35 trypsinogen locus associated with CF meconium ileus, an intestinal obstruction at birth associated with more severe CF outcomes and pancreatic disease. A 20-kb deletion polymorphism and a PRSS2 missense variant p.Thr8Ile (rs62473563) are shown to independently contribute to meconium ileus risk (p = 0.0028, p = 0.011, respectively) and are PRSS2 pancreas eQTLs (p = 9.5 × 10−7 and p = 1.4 × 10−4, respectively), suggesting the mechanism by which these polymorphisms contribute to CF. The phase information from linked reads provides a putative causal explanation for variation at a CF-relevant locus, which also has implications for the genetic basis of non-CF pancreatitis, to which this locus has been reported to contribute.
A common sample descriptor in human genomics studies is that of 'genetic ancestry group', with terms such as 'European genetic ancestry' or 'East Asian genetic ancestry' frequently used in publications to describe the genetics of groups of individuals based on the analysis of their genotypes. In this Perspective, I argue that these terms are imprecise and potentially misleading and that, for most applications, simple statements of genetic similarity represent a more accurate description.
PurposeFungal keratitis is a sight-threatening corneal infection caused by fungal pathogens, and the pathogenic mechanisms have not been fully elucidated. The aim of this study was to determine whether NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated pyroptosis contributes to Candida albicans (C. albicans) keratitis and explore the underlying mechanism.MethodsAn in vivo mouse model of C. albicans keratitis and an in vitro culture model of human corneal epithelial cells (HCECs) challenged with heat-killed C. albicans (HKCA) were established in this study. The degree of corneal infection was evaluated by clinical scoring. Gene expression was assessed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot analysis or immunofluorescence staining was performed to evaluate protein expression. TdT-mediated dUTP nick end labeling (TUNEL) staining was performed to examine the pyroptotic cell death. A lactate dehydrogenase (LDH) release assay was performed to assess cytotoxicity.ResultsCompared with the mock-infected group, we observed that the mRNA levels of NLRP3, caspase-1 (CASP1), interleukin (IL)−1β and gasdermin-D (GSDMD) in C. albicans-infected mice cornea was significantly increased. Our data also demonstrated that the protein expression of NLRP3 and the pyroptosis-related markers apoptosis-associated speck-like protein containing a CARD (ASC), cleaved CASP1, N-GSDMD, cleaved IL-1β and cleaved IL-18 as well as pyroptotic cell death were dramatically elevated in the mouse model of C. albicans keratitis. More importantly, NLRP3 knockdown markedly alleviated pyroptosis and consequently reduced corneal inflammatory reaction in C. albicans keratitis. In vitro, the presence of activated NLRP3 inflammasome and pyroptotic cell death were validated in HCECs exposed to HKCA. Furthermore, the potassium (K+) channel inhibitor glyburide decreased LDH release and suppressed NLRP3 inflammasome activation and pyroptosis in HCECs exposed to HKCA.ConclusionIn conclusion, the current study revealed for the first time that NLRP3 inflammasome activation and pyroptosis occur in C. albicans-infected mouse corneas and HCECs. Moreover, NLRP3 inflammasome-mediated pyroptosis signaling is involved in the disease severity of C. albicans keratitis. Therefore, This NLRP3 inflammasome-dependent pathway may be an attractive target for the treatment of fungal keratitis.
Feed efficiency (FE) is critical to the economic and environmental benefits of aquaculture. Both the intestines and intestinal microbiota play a key role in energy acquisition and influence FE. In the current research, intestinal microbiota, metabolome, and key digestive enzyme activities were compared between abalones with high [Residual feed intake (RFI) = −0.029] and low FE (RFI = 0.022). The FE of group A were significantly higher than these of group B. There were significant differences in intestinal microbiota structures between high- and low-FE groups, while higher microbiota diversity was observed in the high-FE group. Differences in FE were also strongly correlated to variations in intestinal digestive enzyme activity that may be caused by Pseudoalteromonas and Cobetia. In addition, Saprospira, Rhodanobacteraceae, Llumatobacteraceae, and Gaiellales may potentially be utilized as biomarkers to distinguish high- from low-FE abalones. Significantly different microorganisms (uncultured beta proteobacterium, BD1_7_clade, and Lautropia) were found to be highly correlated to significantly different metabolites [DL-methionine sulfoxide Arg-Gln, L-pyroglutamic acid, dopamine, tyramine, phosphatidyl cholines (PC) (16:0/16:0), and indoleacetic acid] in the high- and low-FE groups, and intestinal trypsin activity also significantly differed between the two groups. We propose that interactions occur among intestinal microbiota, intestinal metabolites, and enzyme activity, which improve abalone FE by enhancing amino acid metabolism, immune response, and signal transduction pathways. The present study not only elucidates mechanisms of variations in abalone FE, but it also provides important basic knowledge for improving abalone FE by modulating intestinal microbiota.
The language commonly used in human genetics can inadvertently pose problems for multiple reasons. Terms like "ancestry", "ethnicity", and other ways of grouping people can have complex, often poorly understood, or multiple meanings within the various fields of genetics, between different domains of biological sciences and medicine, and between scientists and the general public. Furthermore, some categories in frequently used datasets carry scientifically misleading, outmoded or even racist perspectives derived from the history of science. Here, we discuss examples of problematic lexicon in genetics, and how commonly used statistical practices to control for the non-genetic environment may exacerbate difficulties in our terminology, and therefore understanding. Our intention is to stimulate a much-needed discussion about the language of genetics, to begin a process to clarify existing terminology, and in some cases adopt a new lexicon that both serves scientific insight, and cuts us loose from various aspects of a pernicious past.
Compared to the normal tissues, cancer cells tend to have higher proliferation rate and often lost their ability to undergo apoptosis. In addition, cancer cells can separate themselves from their original tissue thus causing metastasis in other part of body. While undergoing program cell death, disordered cellular programming can happen. The main causes of this cellular programming anomaly are epigenetic and genetic alterations, which have been known as two separate mechanisms in carcinogenetic. A recent outcome of whole exome sequencing of thousands of human cancers has been the unexpected discovery of many inactivating mutations in genes that control the epigenome. These mutations have the potential to disturb the DNA methylation patterns, histone modifications, and nucleosome positioning, hence, the causing gene expression alternation. Genetic alteration of the epigenome therefore contributes to cancer just as epigenetic process can cause point mutations and disable DNA repair functions. Epigenetic mechanisms changes could cause genetic mutations, and genetic mutations in epigenetic regulators could cause epigenome changes. Knowing that epigenome play a major role in the hierarchy of gene control mechanisms suggests that mutations might have impact on multiple pathways related to cancer phenotype. This pinpoint the fact that recently, the way the genes are organized and controlled are suggested to be a relevant factor for human carcinogenesis.
Keywords: cancer genetic, cancer epigenetic, oncogens, tumor suppressor genes, driver mutation, passenger mutation
John P Zepecki, David Karambizi, J Eduardo Fajardo
et al.
Within the glioblastoma cellular niche, glioma stem cells (GSCs) can give rise to differentiated glioma cells (DGCs) and, when necessary, DGCs can reciprocally give rise to GSCs to maintain the cellular equilibrium necessary for optimal tumor growth. Here, using ribosome profiling, transcriptome and m6A RNA sequencing, we show that GSCs from patients with different subtypes of glioblastoma share a set of transcripts, which exhibit a pattern of m6A loss and increased protein translation during differentiation. The target sequences of a group of miRNAs overlap the canonical RRACH m6A motifs of these transcripts, many of which confer a survival advantage in glioblastoma. Ectopic expression of the RRACH-binding miR-145 induces loss of m6A, formation of FTO/AGO1/ILF3/miR-145 complexes on a clinically relevant tumor suppressor gene (CLIP3) and significant increase in its nascent translation. Inhibition of miR-145 maintains RRACH m6A levels of CLIP3 and inhibits its nascent translation. This study highlights a critical role of miRNAs in assembling complexes for m6A demethylation and induction of protein translation during GSC state transition.
Crispus M. Mbaluto, Crispus M. Mbaluto, Esraa M. Ahmad
et al.
Plants mediate interactions between different herbivores that attack simultaneously or sequentially aboveground (AG) and belowground (BG) organs. The local and systemic activation of hormonal signaling pathways and the concomitant accumulation of defense metabolites underlie such AG-BG interactions. The main plant-mediated mechanisms regulating these reciprocal interactions via local and systemic induced responses remain poorly understood. We investigated the impact of root infection by the root-knot nematode (RKN) Meloidogyne incognita at different stages of its infection cycle, on tomato leaf defense responses triggered by the potato aphid Macrosiphum euphorbiae. In addition, we analyzed the reverse impact of aphid leaf feeding on the root responses triggered by the RKN. We focused specifically on the signaling pathways regulated by the phytohormones jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), and indole-3-acetic acid (IAA) as well as steroidal glycoalkaloids as induced defense compounds. We found that aphid feeding did not induce AG hormonal signaling, but it repressed steroidal glycoalkaloids related responses in leaves, specifically when feeding on plants in the vegetative stage. Root infection by the RKN impeded the aphid-triggered repression of the steroidal glycoalkaloids-related response AG. In roots, the RKN triggered the SA pathway during the entire infection cycle and the ABA pathway specifically during its reproduction stage. RKN infection also elicited the steroidal glycoalkaloids related gene expression, specifically when it was in the galling stage. Aphid feeding did not systemically alter the RKN-induced defense responses in roots. Our results point to an asymmetrical interaction between M. incognita and Ma. euphorbiae when co-occurring in tomato plants. Moreover, the RKN seems to determine the root defense response regardless of a later occurring attack by the potato aphid AG.