Identification Of Molecular Markers Research Articles

Key gene modules and hub genes associated with pyrethroid and organophosphate resistance in Anopheles mosquitoes: a systems biology approach

Indoor residual spraying (IRS) and insecticide-treated nets (ITNs) are the main methods used to control mosquito populations for malaria prevention. The efficacy of these strategies is threatened by the spread of insecticide resistance (IR), limiting the success of malaria control. Studies of the genetic evolution leading to insecticide resistance could enable the identification of molecular markers that can be used for IR surveillance and an improved understanding of the molecular mechanisms associated with IR. This study used a weighted gene co-expression network analysis (WGCNA) algorithm, a systems biology approach, to identify genes with similar co-expression patterns (modules) and hub genes that are potential molecular markers for insecticide resistance surveillance in Kenya and Benin. A total of 20 and 26 gene co-expression modules were identified via average linkage hierarchical clustering from Anopheles arabiensis and An. gambiae, respectively, and hub genes (highly connected genes) were identified within each module. Three specific genes stood out: serine protease, E3 ubiquitin-protein ligase, and cuticular proteins, which were top hub genes in both species and could serve as potential markers and targets for monitoring IR in these malaria vectors. In addition to the identified markers, we explored molecular mechanisms using enrichment maps that revealed a complex process involving multiple steps, from odorant binding and neuronal signaling to cellular responses, immune modulation, cellular metabolism, and gene regulation. Incorporation of these dynamics into the development of new insecticides and the tracking of insecticide resistance could improve the sustainable and cost-effective deployment of interventions.

Identification of molecular effect markers of food relevant toxic compounds

Identification of molecular effect markers of food relevant toxic compounds

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Dickkopf-1 (DKK1) drives growth and metastases in castration-resistant prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) is associated with a poor prognosis and remains an incurable fatal disease. Therefore, the identification of molecular markers involved in cancer progression is urgently needed to develop more-effective therapies. The present study investigated the role of the Wnt signaling modulator Dickkopf-1 (DKK1) in the growth and metastatic progression of mCRPC. DKK1 silencing through siRNA and deletion via CRISPR/Cas9 editing were performed in two different metastatic castration-resistant prostate cancer cell lines (PC3 and DU145). A xenograft tumor model was used to assess tumor growth and metastases. In in vitro experiments, both DKK1 silencing and deletion reduced cell growth and migration of both cell lines. DKK1 knockout clones (DKK1-KO) exhibited cell cycle arrest, tubulin reorganization, and modulation of tumor metastasis-associated genes. Furthermore, in DKK1-KO cells, E-cadherin re-expression and its membrane co-localization with β-catenin were observed, contributing to reduced migration; Cadherin-11, known to increase during epithelial-mesenchymal transition, was down-regulated in DKK1-KO cells. In the xenograft mouse model, DKK1 deletion not only reduced tumor growth but also inhibited the formation of lung metastases. In conclusion, our findings support the key role of DKK1 in the growth and metastatic dissemination of mCRPC, both in vitro and in vivo.

The Evolving Classification of Meningiomas: Integration of Molecular Discoveries to Inform Patient Care.

Meningioma classification and treatment have evolved over the past eight decades. Since Bailey, Cushing, and Eisenhart's description of meningiomas in the 1920s and 1930s, there have been continual advances in clinical stratification by histopathology, radiography and, most recently, molecular profiling, to improve prognostication and predict response to therapy. Precise and accurate classification is essential to optimizing management for patients with meningioma, which involves surveillance imaging, surgery, primary or adjuvant radiotherapy, and consideration for clinical trials. Currently, the World Health Organization (WHO) grade, extent of resection (EOR), and patient characteristics are used to guide management. While these have demonstrated reliability, a substantial number of seemingly benign lesions recur, suggesting opportunities for improvement of risk stratification. Furthermore, the role of adjuvant radiotherapy for grade 1 and 2 meningioma remains controversial. Over the last decade, numerous studies investigating the molecular drivers of clinical aggressiveness have been reported, with the identification of molecular markers that carry clinical implications as well as biomarkers of radiotherapy response. Here, we review the historical context of current practices, highlight recent molecular discoveries, and discuss the challenges of translating these findings into clinical practice.

A Lateral Flow-Recombinase Polymerase Amplification Method for Colletotrichum gloeosporioides Detection.

The greater yam (Dioscorea alata), a widely cultivated and nutritious food crop, suffers from widespread yield reduction due to anthracnose caused by Colletotrichum gloeosporioides. Latent infection often occurs before anthracnose phenotypes can be detected, making early prevention difficult and causing significant harm to agricultural production. Through comparative genomic analysis of 60 genomes of 38 species from the Colletotrichum genus, this study identified 17 orthologous gene groups (orthogroups) that were shared by all investigated C. gloeosporioides strains but absent from all other Colletotrichum species. Four of the 17 C. gloeosporioides-specific orthogroups were used as molecular markers for PCR primer designation and C. gloeosporioides detection. All of them can specifically detect C. gloeosporioides out of microbes within and beyond the Colletotrichum genus with different sensitivities. To establish a rapid, portable, and operable anthracnose diagnostic method suitable for field use, specific recombinase polymerase amplification (RPA) primer probe combinations were designed, and a lateral flow (LF)-RPA detection kit for C. gloeosporioides was developed, with the sensitivity reaching the picogram (pg) level. In conclusion, this study identified C. gloeosporioides-specific molecular markers and developed an efficient method for C. gloeosporioides detection, which can be applied to the prevention and control of yam anthracnose as well as anthracnose caused by C. gloeosporioides in other crops. The strategy adopted by this study also serves as a reference for the identification of molecular markers and diagnosis of other plant pathogens.

Genetic analysis and identification of molecular markers associated with lobed leaf shape in watermelons using next generation sequencing

Genetic analysis and identification of molecular markers associated with lobed leaf shape in watermelons using next generation sequencing

Characterization of potential spermatogonia biomarker genes in the European eel (Anguilla anguilla).

Identification of specific molecular markers for spermatogonial stem cells in teleost is crucial for enhancing the efficacy of reproductive biotechnologies in aquaculture, such as transplantation and surrogate production in fishes. Since it is not yet possible to distinguish spermatogonial stem cells of European eel (Anguilla anguilla) using specific molecular markers, we isolated spermatogonial cells from immature European eels to find these potential markers. We attempted this by studying three candidate genes: vasa, nanos2, and dnd1. Two vasa (vasa1 and vasa2) genes, nanos2, and dnd1 were identified, characterized, and studied in the muscle, testis, and isolated spermatogonia. Our results showed that vasa1 and vasa2 had the highest levels of expression when measured by qPCR. In situ hybridization and immunochemistry assays showed that the four genes were localized explicitly in type A spermatogonia. However, vasa1 and vasa2 exhibited stronger signals in the immature testicular tissue than the other two potential markers. According to this, vasa1 and vasa2 were found to be the most effective markers for spermatogonial cells in the European eel.

Radiogenomics in breast cancer: a review

INTRODUCTION: Early detection of breast cancer is essential in the diagnosis and treatment of this disease. The results of core biopsy, immunohistochemical methods or removed surgical specimens contributed to the identification of molecular markers. Currently, the attention of researchers is attracted by the anatomical and functional features of tumor tissue obtained using imaging methods. The correlation of specific phenotypes based on images (radiomics) with large-scale genomic analysis (genomics) is a new field of research called “radiogenomics” or, more precisely, “image genomics”. This new field examines the relationship between diagnostic methods and gene data, as well as with other clinically relevant information.OBJECTIVE: To analyze current trends in the development of radiogenomics in the study of breast cancer based on the literature data.MATERIALS AND METHODS: The medical literature was searched using information and analytical databases Cochrane, Medline, and Elibrary using the text search queries “radiogenomics of breast cancer”, “mammography and radiogenomics”, “magnetic resonance imaging and radiogenomics”, “ultrasonic radiogenomics”.RESULTS: We found strong evidence that there is a moderate relationship between imaging characteristics and genomic characteristics of breast cancer. However, the results obtained have a number of limiting factors that distort the overall picture.CONCLUSION: Precision medicine can be optimized based on the genotypic and phenotypic characteristics of the tumor. However, the development of this direction requires new research and the development of databases using a multicenter approach.

Abstract 5207: Hypermethylation of SOX17 is an important epigenetic mark in Afro-Brazilian breast cancers

Abstract Afro-Brazilian women suffer from higher excess breast cancer mortality after adjusting for age, level of education and stage at diagnosis. Limited studies have researched disease characteristics in this population, which can benefit from the identification of molecular markers that can provide an insight into who is at greater risk of mortality. Epigenetic biomarkers represent the combined effect of environmental and genetic factors. Particularly DNA methylation biomarkers can be valuable as biomarkers of breast cancer risk and prognosis. While studies in other populations have identified DNA methylation biomarkers associated with breast cancer and its clinicopathological outcomes, research on Brazilian cohorts has been limited in scope and focused on women of European descent. The goal of this work was to determine the epigenetic makeup of breast cancer in Brazilian women of African descent. To identify epigenetic biomarkers in Brazilian women who self-identified as Black or Brown, we conducted a case-series analysis investigating DNA methylation patterns in tumor (T) and adjacent non-tumor (NT) tissue. For this, we used the Illumina EPIC (850k) arrays to carry out DNA methylation profiling in 48 frozen tissue paired T and NT samples of breast cancer patients treated at the National Cancer Institute Breast Cancer Hospital in Rio de Janeiro, Brazil. We identified a total of 7,749 probes with Benjamini-Hochberg adjusted p-value < 0.0001 and differences between T and NT tissue above |0.3|. Of these, 5,976 or 77.12% had lower DNA methylation in T when compared to NT tissue; while 1,773 (22.88%) had higher DNA methylation. These were used to identify 21 differentially methylated regions (DMRs) that contained a minimum of seven cg sites, a mean difference larger than |0.2| and a maximum difference above |0.4|. DMRs were mostly (12) hypermethylated in T, and included PCDHGA, NKAPL, ZKSCAN4, SPAG6, CA3, DPP6, RGS22, NXPH1, ANK3, OTX2, SOX17, and CDO1. We used pyrosequencing to validate the levels of SOX17 in eighty-eight tumor and non-adjacent tumor tissue DNAs. We found SOX17 to be hypermethylated in T (44.5±19.1% vs 10.2±10.6, p<0.0001). Differences in DNA methylation in T and NT tissue we still observed by race/ethnicity categories, 43.9±18.6% vs 11.0.±13.2% (p<0.0001) for Brown, and 45.1±20.7% vs 8.8±3.0% for Black women (p<0.0001), respectively. Similarly to previously reported, SOX17 hypermethylation was found to be associated with Luminal A and B molecular subtypes (p<0.0001). To our knowledge, this is the first study to use a discovery approach to identify epigenetic biomarkers in Black and Brown Brazilian women. Our findings confirming previously reported data on SOX17 hypermethylation in breast cancer are encouraging. We expect to validate other epigenetic markers unique to this population that can ultimately aid in the molecular characterization of Brazilian breast cancers. Citation Format: Lissette Delgado-Cruzata, Diego J. Gomes de Paula, Jennifer G. Vieira, André L. Christianes, Tatiana Simao, Leonor B. Gusmao, Luis Felipe Ribeiro Pinto, Sheila Coelho Soares Lima. Hypermethylation of SOX17 is an important epigenetic mark in Afro-Brazilian breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5207.

From Code to Crop: How Bioinformatics is Transforming Crop Genomics in Modern Agriculture and Bettering Environment

Advancements in bioinformatics have ushered in a new era in modern agriculture by seamlessly integrating computational methodologies with crop genomics. This paper explores the transformative impact of bioinformatics on crop genomics and its consequential benefits for both agriculture and the environment. Bioinformatics tools and techniques are instrumental in decoding the intricate genetic information of crops, leading to the development of tailored solutions for improved crop yield, resistance to diseases, and environmental sustainability. The first aspect of this transformation involves the utilization of high-throughput sequencing technologies, which generate vast amounts of genomic data. Bioinformatics algorithms play a crucial role in processing and analysing these data sets, enabling researchers to unravel the complex genetic codes of crops efficiently. This genomic information serves as a foundation for precision breeding programs, allowing scientists to identify desirable traits and accelerate the development of crops with enhanced resilience and productivity. Furthermore, bioinformatics facilitates the identification of molecular markers associated with key agronomic traits. This information enables the implementation of marker-assisted breeding, a technique that expedites the selection of desired traits in crops, reducing the time and resources required for traditional breeding methods. The result is the development of crop varieties that are not only more productive but also more resistant to pests and diseases, contributing to global food security. Beyond enhancing crop performance, bioinformatics-driven crop genomics also addresses environmental concerns. By deciphering the genetic basis of stress tolerance and resource- use efficiency, researchers can develop crops that require fewer inputs such as water, fertilizers, and pesticides. This not only benefits farmers economically but also reduces the ecological footprint of agriculture, promoting sustainable practices and minimizing environmental impact.

Integrated diagnosis of grade 3-4 gliomas using targeted next-generation sequencing and traditional diagnostic data, and its overall implications on patient management

Adult gliomas vary significantly in terms of their genetics, epigenetics, phenotypes as well as clinical outcomes [1]. Optimal tumor classification that leads to more precise diagnoses, and which influences therapy selection is hence critically important. Targeted next-generation sequencing (NGS) is a highly reliable and efficient novel tool for the identification of biomarkers for the diagnosis of CNS tumors [2]. In this study, we aimed to determine the implications of integrating NGS findings with the traditional diagnostic data on clinical diagnostics and patient management. All patients who were diagnosed with glioma at our institution between 2019 and 2020 and whose tumor biopsy materials were analyzed by both traditional histomorphological and immunohistochemical diagnostic techniques as well as NGS were included in our study. Patients’ information was retrieved from the electronic medical record. Data analyzed included the histopathologic diagnosis, tumor grade, ki67, and the mutation status of TP53 and /or IDH, as well as other genes such as BRAF and HER2 for some patients. The overall concordance between NGS and the traditional diagnostic tools for IDH and TP53 mutations was also evaluated. Further, we derived the overall survival of patients using the Kaplan–Meier estimate. We identified 9 patients with grade 3-4 gliomas whose biopsy materials were analyzed by NGS as well as traditional diagnostic tools. Our patients were 33.3 % females and had a median age of 43 years old at diagnosis. In terms of the identification of gene mutations by NGS in comparison to immunohistochemistry (IHC), it was found that the concordance for mutant identification was 77.8 % (7/9) for IDH mutations and 55.6 % (5/9) for TP53 mutations. NGS further led to a change in patient management in which evidence-based targeted therapy (dabrafenib plus trametinib) was used for one patient (11.1 %) with BRAF V600E mutated astroblastoma. Integrating NGS with traditional diagnostic tools for the diagnosis of gliomas can have significant implications on patients. Such integrated diagnosis can lead to more precise diagnosis, enhanced identification of molecular markers, and offers the potential of using targeted therapies for patients.

Assembly and characterization of the complete mitochondrial genome of Descurainia sophia: a medical plant producing glucosinolate

As a commonly used traditional Chinese medicine, Descurainia sophia has various reported pharmacological activities such as prevention of chronic diseases, cardiovascular protection, neuroprotection, anticancer, antioxidant, and has high nutritional values, but its mitochondrial genome (mitogenome) has not been reported. In this study, the D. sophia mitogenome was sequenced, assembled and annotated using next generation sequencing technologies on the Illumina HiSeq and PacBio Sequel platform. The results showed that the D. sophia mitogenome was a circular DNA molecule with the length of 265,457 bp and the GC content of 44.78%, encoding unique 56 genes, including 35 protein coding genes, 18 tRNA genes and 3 rRNA genes. We analyzed codon preference, repeated sequences, DNA sequence transformation, phylogenetic relationship, RNA editing and synteny in the D. sophia mitogenome. Based on the DNA sequences of mitogenomes, the phylogenetic and synteny analysis indicated that D. sophia was more closely related to Boechera stricta, and the mitogenome of D. sophia underwent frequent genome recombination. In this study, we obtained the complete mitogenome of D. sophia, which can provide valuable data support for future studies on genetic characteristics, phylogenetic relationships, species identification and development of new molecular markers in D. sophia.

Identification of molecular markers and candidate regions associated with grain number per spike in Pubing3228 using SLAF-BSA.

Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.

Identification of potential molecular markers for disease resistance in giant gourami through major histocompatibility complex (MHC) II gene analysis

Identification of potential molecular markers for disease resistance in giant gourami through major histocompatibility complex (MHC) II gene analysis

Regulation and tumor-suppressive function of the miR-379/miR-656 (C14MC) cluster in cervical cancer.

Cervical cancer (CC) is a key contributor to cancer-related mortality in several countries. The identification of molecular markers and the underlying mechanism may help improve CC management. We studied the regulation and biological function of the chromosome 14 microRNA cluster (C14MC; miR-379/miR-656) in CC. Most C14MC members exhibited considerably lower expression in CC tissues and cell lines in The Cancer Genome Atlas (TCGA) cervical squamous cell carcinoma and endocervical adenocarcinoma patient cohorts. Bisulfite Sanger sequencing revealed hypermethylation of the C14MC promoter in CC tissues and cell lines. 5-aza-2 deoxy cytidine treatment reactivated expression of the C14MC members. We demonstrated that C14MC is a methylation-regulated miRNA cluster via artificial methylation and luciferase reporter assays. C14MC downregulation correlated with poor overall survival and may promote metastasis. C14MC activation via the lentiviral-based CRISPRa approach inhibited growth, proliferation, migration, and invasion; enhanced G2/M arrest; and induced senescence. Post-transcriptional regulatory network analysis of C14MC transcriptomic data revealed enrichment of key cancer-related pathways, such as metabolism, the cell cycle, and phosphatidylinositol 3-kinase (PI3K)-AKT signaling. Reduced cell proliferation, growth, migration, invasion, and senescence correlated with the downregulation of active AKT, MYC, and cyclin E1 (CCNE1) and the overexpression of p16, p21, and p27. We showed that C14MC miRNA activation increases reactive oxygen species (ROS) levels, intracellular Ca2+ levels, and lipid peroxidation rates, and inhibits epithelial-mesenchymal transition (EMT). C14MC targets pyruvate dehydrogenase kinase-3 (PDK3) according to the luciferase reporter assay. PDK3 is overexpressed in CC and is inversely correlated with C14MC. Both miR-494-mimic transfection and C14MC activation inhibited PDK3 expression. Reduced glucose uptake and lactate production, and upregulation of PDK3 upon C14MC activation suggest the potential role of these proteins in metabolic reprogramming. Finally, we showed that C14MC activation may inhibit EMT signaling. Thus, C14MC is a tumor-suppressive and methylation-regulated miRNA cluster in CC. Reactivation of C14MC can be useful in the management of CC.

Unravelling the novel genetic diversity and marker-trait associations of corn leaf aphid resistance in wheat using microsatellite markers.

The study was conducted to identify novel simple sequence repeat (SSR) markers associated with resistance to corn aphid (CLA), Rhopalosiphum maidis L. in 48 selected bread wheat (Triticum aestivum L.) and wild wheat (Aegilops spp. & T. dicoccoides) genotypes during two consecutive cropping seasons (2018-19 and 2019-20). A total of 51 polymorphic markers containing 143 alleles were used for the analysis. The frequency of the major allele ranged from 0.552 (Xgwm113) to 0.938 (Xcfd45, Xgwm194 and Xgwm526), with a mean of 0.731. Gene diversity ranged from 0.116 (Xgwm526) to 0.489 (Xgwm113), with a mean of 0.354. The polymorphic information content (PIC) value for the SSR markers ranged from 0.107 (Xgwm526) to 0.370 (Xgwm113) with a mean of 0.282. The results of the STRUCTURE analysis revealed the presence of four main subgroups in the populations. Analysis of molecular variance (AMOVA) showed that the between-group difference was around 37 per cent of the total variation contributed to the diversity by the whole germplasm, while 63 per cent of the variation was attributed between individuals within the group. A general linear model (GLM) was used to identify marker-trait associations, which detected a total of 23 and 27 significant new marker-trait associations (MTAs) at the p < 0.01 significance level during the 2018-19 and 2019-20 crop seasons, respectively. The findings of this study have important implications for the identification of molecular markers associated with CLA resistance. These markers can increase the accuracy and efficiency of aphid-resistant germplasm selection, ultimately facilitating the transfer of resistance traits to desirable wheat genotypes.

Genome-wide search for associations method for identification of molecular markers and candidate genes of breed affiliation of sheep of the North Caucasian meat and wool breed

To determine the loci associated with pedigree traits, a genome-wide search was conducted for associations of 275 heads of Russian sheep breeds genotyped using 600 thousand single nucleotide polymorphisms (SNPs). The studies were conducted according to the “case-control” type, where the “case” group is represented by animals of the North Caucasian meat and wool breed, the “control” included animals of other breeds (Karachay, Romanovskaya, Dzhalginsky merino and Russian meat merino). In this study, over 100 SNPs were identified with highly reliable differences in the frequency of occurrence in sheep of the North Caucasian meat and wool breed. For the subsequent analysis, 18 single nucleotides with the highest confidence indices localized on chromosomes were selected 1, 10, 11, 15, 17. As a result of a genome-wide study, significant SNP markers characteristic of the sheep breed under study, located directly in the genes or close to them, were determined. The conducted studies provide a set of new SNP markers and candidate genes associated with the breed characteristics of North Caucasian meat-wool sheep.

Transcription Factor Regulation of Gene Expression Network by ZNF385D and HAND2 in Carotid Atherosclerosis.

Carotid intima-media thickness (CIMT) is a surrogate indicator for atherosclerosis and has been shown to predict cardiovascular risk in multiple large studies. Identification of molecular markers for carotid atheroma plaque formation can be critical for early intervention and prevention of atherosclerosis. This study performed transcription factor (TF) network analysis of global gene expression data focusing on two TF genes, ZNF385D and HAND2, whose polymorphisms have been recently reported to show association with CIMT. Genome-wide gene expression data were measured from pieces of carotid endarterectomy collected from 34 hypertensive patients (atheroma plaque of stages IV and above according to the Stary classification) each paired with one sample of distant macroscopically intact tissue (stages I and II). Transcriptional regulation networks or the regulons were reconstructed for ZNF385D (5644 target genes) and HAND2 (781 target genes) using network inference. Their association with the progression of carotid atheroma was examined using gene-set enrichment analysis with extremely high statistical significance for regulons of both ZNF385D and HAND2 (p < 6.95 × 10-7) suggesting the involvement of expression quantitative loci (eQTL). Functional annotation of the regulon genes found heavy involvement in the immune system's response to inflammation and infection in the development of atherosclerosis. Detailed examination of the regulation and correlation patterns suggests that activities of the two TF genes could have high clinical and interventional impacts on impairing carotid atheroma plaque formation and preventing carotid atherosclerosis.

Identification of molecular markers for predicting the severity of heart failure after AMI: An Olink precision proteomic study

BackgroundAcute myocardial infarction (AMI) still has a high incidence of varying degrees of heart failure (HF). The aim of this study is to identify new molecular markers for predicting the severity of HF after AMI. MethodsWe analyzed demographic indicators, past medical history, clinical indicators, major adverse cardiac events (MACEs) and molecular markers in patients with different Killip classifications after AMI. Olink proteomics was used to explore new molecular markers for predicting different severity of HF after AMI. ResultsNeutrophil count was the independent risk factors for in-hospital MACEs. Nineteen differentially expressed proteins (DEPs) increased significantly with increasing Killip classification. Five DEPs were also found to have an AUC (95 % CI) value greater than 0.8: GDF-15, NT-pro BNP, TNF-R2, TNF-R1 and TFF3. ConclusionsNeutrophil count, GDF-15, TNF-R2, TNF-R1 and TFF3 were closely related to the Killip classification of HF after AMI, which suggests that the inflammatory response plays an important role in the severity of HF after AMI and that regulating inflammation might become a new target for controlling HF.