Journal of Applied Genetics最新文献

Chromatinopathies (CPs), a group of rare inborn defects characterized by chromatin state imbalance, have evolved from initially resembling Cornelia de Lange syndrome to encompass a wide array of genetic diseases with diverse clinical presentations. The CPs classification now includes human developmental disorders caused by germline mutations in epigenes, genes that regulate the epigenome. Recent advances in next-generation sequencing have enabled the association of 154 epigenes with CPs, revealing distinctive DNA methylation patterns known as episignatures.It has been shown that episignatures are unique for a particular CP or share similarities among specific CP subgroup. Consequently, these episignatures have emerged as promising biomarkers for diagnosing and treating CPs, differentiating subtypes, evaluating variants of unknown significance, and facilitating targeted therapies tailored to the underlying epigenetic dysregulation.The following review was conducted to collect, summarize, and analyze data regarding CPs in such aspects as clinical evaluation encompassing long-term patient care, underlying epigenetic changes, and innovative molecular and bioinformatic methodologies that have been devised for the assessment of CPs. We have also shed light on promising novel treatment options that have surfaced in recent research and presented a synthesis of ongoing clinical trials, contributing to the current understanding of the dynamic and evolving nature of CPs investigation.

Deteriorating climatic conditions and increasing human population necessitate the development of robust plant varieties resistant to harsh environments. Manipulation of regulatory proteins such as transcription factors (TFs) and RNA-binding proteins (RBPs) would be a beneficial strategy in this regard. Further, understanding the complex interconnections between different classes of regulatory molecules would be essential for the identification of candidate genes/proteins for trait improvement. Most studies to date have analysed the roles of TFs or RBPs individually, in conferring stress resilience. However, it would be important to identify dominant/upstream TFs and RBPs inducing widespread transcriptomic alterations through other regulators (i.e., other TFs/RBPs targeted by the upstream regulators). To this end, the present study employed a transcriptome meta-analysis and computational approaches to obtain a comprehensive overview of regulatory interactions. This work identified dominant TFs and RBPs potentially influencing stress-mediated differential expression of other regulators, which could in turn influence gene expression, and consequently, physiological responses. Twenty transcriptomic studies [related to (i) UV radiation, (ii) wounding, (iii) salinity, (iv) cold, and (v) drought stresses in Arabidopsis thaliana] were analysed for differential gene expression, followed by the identification of differentially expressed TFs and RBPs. Subsequently, other TFs and RBPs which could be influencing these regulators were identified, and their interaction networks and hub nodes were analysed. As a result, an interacting module of Basic Leucine Zipper (bZIP) family TFs as well as Heterogeneous nuclear ribonucleoproteins (hnRNP) and Glycine-rich protein (GRP) family RBPs (among other TFs and RBPs) were shown to potentially influence the stress-induced differential expression of other TFs and RBPs under all the considered stress conditions. Some of the identified hub TFs and RBPs are known to be of major importance in orchestrating stress-induced transcriptomic changes influencing a variety of physiological processes from seed germination to senescence. This study highlighted the gene/protein candidates that could be considered for multiplexed genetic manipulation - a promising approach to develop robust, multi-stress-resilient plant varieties.

Noonan syndrome (NS; OMIM 163950) is an autosomal dominant RASopathy with variable clinical expression and genetic heterogeneity. Clinical manifestations include characteristic facial features, short stature, and cardiac anomalies. Variants in protein-tyrosine phosphatase, non-receptor-type 11 (PTPN11), encoding SHP-2, account for about half of NS patients, SOS1 in approximately 13%, RAF1 in 10%, and RIT1 each in 9%. Other genes have been reported to cause NS in less than 5% of cases including SHOC2, RASA2, LZTR1, SPRED2, SOS2, CBL, KRAS, NRAS, MRAS, PRAS, BRAF, PPP1CB, A2ML1, MAP2K1, and CDC42. Several additional genes associated with a Noonan syndrome-like phenotype have been identified. Clinical presentation and variants in patients with Noonan syndrome are this study's objectives. We performed Sanger sequencing of PTPN11 hotspot (exons 3, 8, and 13). We report molecular analysis of 61 patients with NS phenotype belonging to 58 families. We screened for hotspot variants (exons 3, 8, and 13) in PTPN11 gene by Sanger sequencing. Twenty-seven patients were carrying heterozygous pathogenic variants of PTPN11 gene with a similar frequency (41.4%) compared to the literature. Our findings expand the variant spectrum of Moroccan patients with NS phenotype in whom the analysis of hotspot variants showed a high frequency of exons 3 and 8. This screening test allowed us to establish a molecular diagnosis in almost half of the patients with a good benefit-cost ratio, with appropriate management and genetic counseling.

Best linear unbiased prediction (BLUP) is widely used in plant research to address experimental variation. For phenotypic values, BLUP accuracy is largely dependent on properly controlled experimental repetition and how variable components are outlined in the model. Thus, determining BLUP robustness implies the need to evaluate contributions from each repetition. Here, we assessed the robustness of BLUP values for simulated or empirical phenotypic datasets, where the BLUP value and each experimental repetition served as dependent and independent (feature) variables, respectively. Our technique incorporated machine learning and partial dependence. First, we compared the feature importance estimated with the neural networks. Second, we compared estimated average marginal effects of individual repetitions, calculated with a partial dependence analysis. We showed that contributions of experimental repetitions are unequal in a phenotypic dataset, suggesting that the calculated BLUP value is likely to be influenced by some repetitions more than others (such as failing to detect simulated true positive associations). To resolve disproportionate sources, variable components in the BLUP model must be further outlined.

Since its initial identification, the Forkhead Box P2 gene (FOXP2) has maintained its singular status as the archetypal monogenic determinant implicated in Mendelian forms of human speech and language impairments. Despite the passage of two decades subsequent to its discovery, extant literature remains disproportionately sparse with regard to case-specific instances and loci of mutational perturbations. The objective of the current investigation centers on furnishing an enriched delineation of both its clinical manifestations and its mutational heterogeneity. Clinical phenotypes and peripheral blood samples were assiduously amassed from familial subjects. Whole-exome sequencing and Sanger sequencing methodologies were deployed for the unambiguous identification of potential genetic variants and for corroborating their co-segregation within the family pedigree. An exhaustive review of published literature focusing on patients manifesting speech and language disorders consequent to FOXP2 genetic anomalies was also undertaken. The investigation yielded the identification of a novel heterozygous variant, c.661del (p.L221Ffs*41), localized within the FOXP2 gene in the proband, an inheritance from his symptomatic mother. The proband presented with an array of symptoms, encompassing dysarthric speech, deficits in instruction comprehension, and communicative impediments. In comparison, the mother exhibited attenuated symptoms, including rudimentary verbalization capabilities punctuated by pronounced stuttering and dysarthria. A comprehensive analysis of articles archived in the Human Gene Mutation Database (HGMD) classified under "DM" disclosed the existence of 74 patients inclusive of the subjects under current examination, sub-divided into 19 patients with null variants, 5 patients with missense variants, and 50 patients with gross deletions or complex genomic rearrangements. A conspicuous predominance of delayed speech, impoverished current verbal abilities, verbal comprehension deficits, and learning difficulties were observed in patients harboring null or missense FOXP2 variants, as compared to their counterparts with gross deletions or complex rearrangements. Developmental delays, hypotonia, and craniofacial aberrations were exclusive to the latter cohort. The elucidated findings augment the existing corpus of knowledge on the genetic architecture influencing both the proband and his mother within this specified familial context. Of critical importance, these discoveries furnish a robust molecular framework conducive to the prenatal diagnostic evaluations of prospective progeny within this familial lineage.

The CRISPR/Cas9 technique applied to modify the cattle genome has value in increasing animal health and welfare. Here, we established a simple, fast, and efficient cloning-free CRISPR/Cas9 protocol for large deletions of genomic loci in the frequently used model bovine MDBK cell line. The main advantages of our protocol are as follows: (i) pre-screening of the sgRNA efficiency with a fast and simple cleavage assay, (ii) reliable detection of genomic edits primarily by PCR and confirmed by DNA sequencing, and (iii) single cell sorting with FACS providing specific genetic information from modified cells of interest. Therefore, our method could be successfully applied in different studies, including functional validation of any genetic or regulatory elements.

Sophisticated and modern crop improvement techniques can bridge the gap for feeding the ever-increasing population. Artificial intelligence (AI) refers to the simulation of human intelligence in machines, which refers to the application of computational algorithms, machine learning (ML) and deep learning (DL) techniques. This is aimed to generalise patterns and relationships from historical data, employing various mathematical optimisation techniques thus making prediction models for facilitating selection of superior genotypes. These techniques are less resource intensive and can solve the problem based on the analysis of large-scale phenotypic datasets. ML for genomic selection (GS) uses high-throughput genotyping technologies to gather genetic information on a large number of markers across the genome. The prediction of GS models is based on the mathematical relation between genotypic and phenotypic data from the training population. ML techniques have emerged as powerful tools for genome editing through analysing large-scale genomic data and facilitating the development of accurate prediction models. Precise phenotyping is a prerequisite to advance crop breeding for solving agricultural production-related issues. ML algorithms can solve this problem through generating predictive models, based on the analysis of large-scale phenotypic datasets. DL models also have the potential reliability of precise phenotyping. This review provides a comprehensive overview on various ML and DL models, their applications, potential to enhance the efficiency, specificity and safety towards advanced crop improvement protocols such as genomic selection, genome editing, along with phenotypic prediction to promote accelerated breeding.

tsRNAs (tRNA-derived small non-coding RNAs), including tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been implicated in some viral infections, such as respiratory viral infections. However, their involvement in SARS-CoV infection is completely unknown. A comprehensive analysis was performed to determine tsRNA populations in a mouse model of SARS-CoV-infected samples containing the wild-type and attenuated viruses. Data from the Gene Expression Omnibus (GEO) dataset at NCBI (accession ID GSE90624 ) was used for this study. A count matrix was generated for the tRNAs. Differentially expressed tRNAs, followed by tsRNAs derived from each significant tRNAs at different conditions and time points between the two groups WT(SARS-CoV-MA15-WT) vs Mock and ΔE (SARS-CoV-MA15-ΔE) vs Mock were identified. Notably, significantly differentially expressed tRNAs at 2dpi but not at 4dpi. The tsRNAs originating from differentially expressed tRNAs across all the samples belonging to each condition (WT, ΔE, and Mock) were identified. Intriguingly, tRFs (tRNA-derived RNA fragments) exhibited higher levels compared to tiRNAs (tRNA-derived stress-induced RNAs) across all samples associated with WT SARS-CoV strain compared to ΔE and mock-infected samples. This discrepancy suggests a non-random formation of tsRNAs, hinting at a possible involvement of tsRNAs in SARS-CoV viral infection.

Atherosclerosis is a chronic inflammatory disease that affects arterial walls and is a leading cause of cardiovascular disease. Gene co-expression modules can provide insight into the molecular mechanisms underlying atherosclerosis progression. In this study, gene co-expression network analysis (WGCNA) was done to identify gene co-expression modules associated with atherosclerosis progression. Before conducting WGCNA, preprocessing and soft power selection were performed on the GSE28829, GSE100927, GSE43292, GSE10334, and GSE16134 datasets ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi ). Co-expression modules were identified using dynamic tree cuts, and their correlations and trait associations were visualized. Enrichment analysis was performed on the blue and magenta modules to identify biological processes (BP) and pathways related to atherosclerosis. The CIBERSORT algorithm was used to predict immune cell infiltration in early and advanced atherosclerotic plaques. We identified 12 co-expression modules, in which blue and magenta were most highly correlated with atherosclerosis progression. The blue module was enriched for inflammation- and immune-related BP and pathways, including phagosome, lysosome, osteoclast differentiation, chemokine signaling pathway, platelet activation, NF-kappa B signaling pathway, Fc gamma R-mediated phagocytosis, lipid and atherosclerosis, autophagy, and apoptosis. The magenta module was significantly enriched for vascular permeability regulation, positive and negative regulation of epithelial to mesenchymal transition, and lamellipodium. Additionally, the CIBERSORT algorithm predicted less abundance of T regulatory cells and monocytes in advanced compared to early atherosclerotic plaques. The enrichment analysis of BP, cellular components, molecular functions, and atherosclerosis-related pathways in the blue and magenta modules showed that inflammation and immune response played a key role in the progression of atherosclerosis. Our study provides insights into the molecular mechanisms underlying atherosclerosis progression and identifies potential therapeutic targets for the treatment of atherosclerosis. The identification of immune cell subtypes associated with atherosclerosis could lead to the development of immunomodulatory therapies to prevent or treat atherosclerosis.

Pigmentation in rice grains is an important quality parameter. Purple-coloured rice (Oryza sativa L.) indicates the presence of high anthocyanin with benefits of antioxidant properties. However, the genetic mechanism of grain colour is not fully understood. Therefore, the study focused on understanding pigmentation in grain pericarp and vegetative parts, and its relationship with blast resistance and enhanced grain yield. Three local cultivars from the northeastern region (NER) of India - Chakhao Poireiton (purple), Mang Meikri (light brown), and Kala Joha (white) - along with high-yielding varieties (HYVs) Shasharang (light brown) and Sahbhagi dhan (white) were used to develop biparental populations. The findings suggested that pigmentation in vegetative tissue was governed by the inter-allelic interaction of several genes. Haplotype analysis revealed that Kala3 complemented Kala4 in enhancing purple pigmentation and that Kala4 is not the only gene responsible for purple colour as evident by the presence of a desired allele for markers RID3 and RID4 (Kala4 locus) in Chakhao Poireiton and Kala Joha irrespective of their pericarp colour, implying the involvement of some other additional, unidentified genes/loci. RID3 and RID4 together with RM15191 (Kala3 locus) could be employed as a reliable marker set for marker-assisted selection (MAS). Pericarp colour was strongly correlated with colour in different vegetative parts, but showed a negative correlation with grain yield. Pb1, reported to be associated with panicle blast resistance, contributed to leaf blast resistance. Transgressive segregants for improved pigmentation and high yield were identified. The selection of lines exhibiting coloured pericarp, high anthocyanin content, aroma, blast resistance, and increased yield compared to their respective HYV parents will be valuable resources in the rice breeding programme.