Marker Database Research Articles

A natural language processing system for the efficient extraction of cell markers

Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal tool for exploring cellular landscapes across diverse species and tissues. Precise annotation of cell types is essential for understanding these landscapes, relying heavily on empirical knowledge and curated cell marker databases. In this study, we introduce MarkerGeneBERT, a natural language processing (NLP) system designed to extract critical information from the literature regarding species, tissues, cell types, and cell marker genes in the context of single-cell sequencing studies. Leveraging MarkerGeneBERT, we systematically parsed full-text articles from 3702 single-cell sequencing-related studies, yielding a comprehensive collection of 7901 cell markers representing 1606 cell types across 425 human tissues/subtissues, and 8223 cell markers representing 1674 cell types across 482 mouse tissues/subtissues. Comparative analysis against manually curated databases demonstrated that our approach achieved 76% completeness and 75% accuracy, while also unveiling 89 cell types and 183 marker genes absent from existing databases. Furthermore, we successfully applied the compiled brain tissue marker gene list from MarkerGeneBERT to annotate scRNA-seq data, yielding results consistent with original studies. Conclusions: Our findings underscore the efficacy of NLP-based methods in expediting and augmenting the annotation and interpretation of scRNA-seq data, providing a systematic demonstration of the transformative potential of this approach. The 27323 manual reviewed sentences for training MarkerGeneBERT and the source code are hosted at https://github.com/chengpeng1116/MarkerGeneBERT.

Isolation and characterization of normal mandibular periosteal stem cells from human and macaca mulatta and cross-species single-cell analysis

Objective: To investigate the presence of a distinct stem cell populations different from mesenchymal stem cells in the mandibular periosteum of both human and non-human primates (macaca mulatta), to explore its properties during intramembranous osteogenesis and to establish standard protocols for the isolation, culturing and expanding of mandibular periosteal stem cells (PSC) distinguished from other PSCs in other anatomical regions. Methods: Periosteum was harvested from the bone surface during flap bone removal in patients aged 18-24 years undergoing third molar extraction and from the buccal side of the mandibular premolar region of 6-year-old macaca mulatta respectively, and then subjected to single-cell sequencing using the Illumina platform Novaseq 6000 sequencer. Cross-species single-cell transcriptome sequencing results were compared using homologous gene matching. PSC were isolated from primary tissues using two digestion methods with body temperature and low temperature, and their surface markers (CD200, CD31, CD45 and CD90) were identified by cell flow cytometry. The ability of cell proliferation and three-lineage differentiation of PSC expanded to the third generation in vitro in different species were evaluated. Finally, the similarities and differences in osteogenic properties of PSC and bone marrow mesenchymal stem cells (BMSC) were compared. Results: The single-cell sequencing results indicated that 18 clusters of cell populations were identified after homologous gene matching for dimensionality reduction, and manual cellular annotation was conducted for each cluster based on cell marker databases. The comparison of different digestion protocols proved that the low-temperature overnight digestion protocol can stably isolate PSC from the human and m. mulatta mandibular periosteum and the cells exhibited a fibroblast-like morphology. This research confirmed that PSC of human and m. mulatta had similar proliferation capabilities through the cell counting kit-8 assay. Flow cytometry analysis was then used to identify the cells isolated from the periosteum expressed CD200(+), CD31(-), CD45(-), CD90(-). Then, human and m. mulatta PSC were induced into osteogenesis, adipogenesis, and chondrogenesis to demonstrate their corresponding multi-lineage differentiation capabilities. Finally, comparison with BMSC further clarified the oesteogenesis characteristics of PSC. The above experiments proved that the cells isolated from the periosteum were peiosteal cells with characteristics of stem cells evidenced by their cell morphology, proliferation ability, surface markers, and differentiation ability, and that this group of PSC possessed characteristics different from traditional mesenchymal stem cells. Conclusions: In this study, normal mandibular PSC from humans and m. mulatta were stably isolated and identified for the first time, providing a cellular foundation for investigating the mechanism of mandibular intramembranous osteogenesis, exploring ideal non-human primate models and establishing innovative strategies for clinically mandibular injury repair.

Evaluation of genetic markers for the metabarcoding of Australian marsupials from predator scats

Context DNA recovered from predator faeces (scats) can be used to determine the presence of fauna and shed light on their life histories and inter-species interactions. DNA metabarcoding, which involves concurrent amplification and sequencing of DNA from multiple taxa, represents an important advance by enabling the simultaneous detection of multiple species from such samples. Although an attractive proposition, metabarcoding requires ‘universally’ applicable genetic markers that can discriminate among a broad range of taxa, while also targeting sequences that are sufficiently short to be amplified from degraded DNA. Aims To identify, evaluate, and test metabarcoding DNA markers suitable for the detection of marsupials and other Australian fauna from terrestrial predator scats found in nature. Methods We apply a bioinformatic approach using publicly available DNA databases and a locally derived and marker-specific reference-DNA database to evaluate the diagnostic ability and likelihood of amplification of candidate metabarcoding markers for marsupials and other taxa that may be consumed by predators. Key results We identify two markers (12SV5 and 16SMam) that are suitable for use and successfully identify marsupial sequences at a high level of resolution. These markers work best in combination because they bring complementary levels of primer specificity and diagnostic ability in detecting multiple prey species as well as the predator. We also show that these samples work well in predator scats sampled from the wild in Tasmania. Conclusions These markers provide a useful tool for surveying mammalian predators and their prey and could also be applied to eDNA analyses from other sample types. Improvements to the reference database and further development of markers targeting different taxonomic groups will improve the resolution and usefulness of this approach. Implications Metabarcoding of predator scats provides a potent approach to non-invasive wildlife survey that offers the opportunity for the detection of multiple species across all vertebrates.

PMBC: a manually curated database for prognostic markers of breast cancer.

Breast cancer is notorious for its high mortality and heterogeneity, resulting in different therapeutic responses. Classical biomarkers have been identified and successfully commercially applied to predict the outcome of breast cancer patients. Accumulating biomarkers, including non-coding RNAs, have been reported as prognostic markers for breast cancer with the development of sequencing techniques. However, there are currently no databases dedicated to the curation and characterization of prognostic markers for breast cancer. Therefore, we constructed a curated database for prognostic markers of breast cancer (PMBC). PMBC consists of 1070 markers covering mRNAs, lncRNAs, miRNAs and circRNAs. These markers are enriched in various cancer- and epithelial-related functions including mitogen-activated protein kinases signaling. We mapped the prognostic markers into the ceRNA network from starBase. The lncRNA NEAT1 competes with 11 RNAs, including lncRNAs and mRNAs. The majority of the ceRNAs in ABAT belong to pseudogenes. The topology analysis of the ceRNA network reveals that known prognostic RNAs have higher closeness than random. Among all the biomarkers, prognostic lncRNAs have a higher degree, while prognostic mRNAs have significantly higher closeness than random RNAs. These results indicate that the lncRNAs play important roles in maintaining the interactions between lncRNAs and their ceRNAs, which might be used as a characteristic to prioritize prognostic lncRNAs based on the ceRNA network. PMBC renders a user-friendly interface and provides detailed information about individual prognostic markers, which will facilitate the precision treatment of breast cancer. PMBC is available at the following URL: http://www.pmbreastcancer.com/.

HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers.

Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.

The Musa Marker Database: A Comprehensive Genomic Resource for the Improvement of the Musaceae Family

The Musa Marker Database: A Comprehensive Genomic Resource for the Improvement of the Musaceae Family

Genetic determinants of resistance to antimicrobial therapeutics are rare in publicly available Clostridioides difficile genome sequences.

To determine the frequencies and clonal distributions of putative genetic determinants of resistance to antimicrobials applied for treatment of Clostridioides difficile infection (CDI), as documented in the genomic record. We scanned 26 557 C. difficile genome sequences publicly available from the EnteroBase platform for plasmids, point mutations and gene truncations previously reported to reduce susceptibility to vancomycin, fidaxomicin or metronidazole, respectively. We measured the antimicrobial susceptibility of 143 selected C. difficile isolates. The frequency of mutations causing reduced susceptibility to vancomycin and metronidazole, respectively, increased strongly after 2000, peaking at up to 52% of all sequenced C. difficile genomes. However, both mutations declined sharply more recently, reflecting major changes in CDI epidemiology. We detected mutations associated with fidaxomicin resistance in several major genotypes, but found no evidence of international spread of resistant clones. The pCD-METRO plasmid, conferring metronidazole resistance, was detected in a single previously unreported C. difficile isolate, recovered from a hospital patient in Germany in 2008. The pX18-498 plasmid, putatively associated with decreased vancomycin susceptibility, was confined to related, recent isolates from the USA. Phenotype measurements confirmed that most of those genetic features were useful predictors of antibiotic susceptibility, even though ranges of MICs typically overlapped among isolates with and without specific mutations. Genomic data suggested that resistance to therapeutic antimicrobial drugs is rare in C. difficile. Public antimicrobial resistance marker databases were not equipped to detect most of the genetic determinants relevant to antibiotic therapy of CDI.

One Step Forwards in Knowledge of Blossom Blight Brown Rot Disease: Monilinia spp. SSR Marker Database.

A freely available Monilinia spp. marker database was created, containing microsatellite (SSR) data of the three most essential European fungal pathogens: M. fructigena, M. laxa, and M. fructicola. These pathogens cause brown rot blossom blight. Microsatellites were identified using the bioinformatics tool Genome-wide Microsatellite Analyzing Toward Application (GMATA). The database provides information about SSR markers: forward and reverse sequences of the primers, fragment sizes, SSR motifs (and repeats), and the exact locations with the coordinates in the reference genome. This database currently contains information about 39,216 SSR motifs and 26,366 markers. In total, eight primers generated in silico were validated experimentally and they are marked in the database. All scientists can join this collaboration by adding their experimental data. This database is the initial start of organizing Monilinia spp. molecular data worldwide and, in the future, it could be extended by adding more molecular and genomic information.

Systematic Pharmacology and Experimental Validation to Reveal the Alleviation of Astragalus membranaceus Regulating Ferroptosis in Osteoarthritis.

Astragalus membranaceus (AM) shows promise as a therapeutic agent for osteoarthritis (OA), a debilitating condition with high disability rates. OA exacerbation is linked to chondrocyte ferroptosis, yet the precise pharmacological mechanisms of AM remain unclear. We validated AM's protective efficacy in an anterior cruciate ligament transection (ACLT) mouse model of OA. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database was utilized to identify AM's active components and their targets. FerrDb (a database for regulators and markers of ferroptosis and ferroptosis-disease associations) pinpointed ferroptosis-related targets, while GeneCards, Online Mendelian Inheritance in Man (OMIM), Pharmacogenomics Knowledgebase (PharmGKB), Therapeutic Target Database (TTD), and DrugBank sourced OA-related genes. Molecular docking analysis further validated these targets. Ultimately, the validation of the results was accomplished through in vitro experiments. AM exhibited anabolic effects and suppressed catabolism in OA chondrocytes. Network pharmacology identified 19 common genes, and molecular docking suggested quercetin, an AM constituent, interacts with key proteins like HO-1 and NRF2 to inhibit chondrocyte ferroptosis. In vitro experiments confirmed AM's ability to modulate the NRF2/HO-1 pathway via quercetin, mitigating chondrocyte ferroptosis. This study elucidates how AM regulates chondrocyte ferroptosis, impacting OA progression, providing a theoretical basis and experimental support for AM's scientific application.

Genome-wide development of intra- and inter-specific transferable SSR markers and construction of a dynamic web resource for yam molecular breeding: Y2MD.

Microsatellite markers are widely used in population genetics and breeding. Despite the economic significance of yams in developing countries, there is a paucity of microsatellite markers, and as of now, no comprehensive microsatellite marker database exists. In this study, we conducted genome-wide microsatellite marker development across four yam species, identified cross-species transferable markers, and designed an easy-to-use web portal for the yam researchers. The screening of Dioscorea alata, Dioscorea rotundata, Dioscorea dumetorum, and Dioscorea zingiberensis genomes resulted in 318,713, 322,501, 307,040, and 253,856 microsatellites, respectively. Mono-, di-, and tri-nucleotides were the most important types of repeats in the different species, and a total of 864,128 primer pairs were designed. Furthermore, we identified 1170 cross-species transferable microsatellite markers. Among them, 17 out of 18 randomly selected were experimentally validated with good discriminatory power, regardless of the species and ploidy levels. Ultimately, we created and deployed a dynamic Yam Microsatellite Markers Database (Y2MD) available at https://y2md.ucad.sn/. Y2MD is embedded with various useful tools such as JBrowse, Blast, insilicoPCR, and SSR Finder to facilitate the exploitation of microsatellite markers in yams. This study represents the first comprehensive microsatellite marker mining across several yam species and will contribute to advancing yam genetic research and marker-assisted breeding. The released user-friendly database constitutes a valuable platform for yam researchers.

Multi-genome comprehensive identification of SSR/SV and development of molecular markers database to serve Sorghum bicolor (L.) breeding

BackgroundAs an important food and cash crop, identification of DNA molecular markers is of great significance for molecular marker-assisted breeding of Sorghum (Sorghum bicolor (L.) moench). Although some sorghum-related mutation databases have been published, the special SSR and SV databases still need to be constructed and updated.ResultsIn this study, the quality of 18 different sorghum genomes was evaluated, and two genomes were assembled at chromosome level. Through the identification and comparative analysis of SSR loci in these genomes, the distribution characteristics of SSR in the above sorghum genomes were initially revealed. At the same time, five representative reference genomes were selected to identify the structural variation of sorghum. Finally, a convenient SSR/SV database of sorghum was constructed by integrating the above results (http://www.sorghum.top:8079/;http://43.154.129.150:8079/;http://47.106.184.91:8079/). Users can query the information of related sites and primer pairs.ConclusionsAnyway, our research provides convenience for sorghum researchers and will play an active role in sorghum molecular marker-assisted breeding.

A forensic population database of autosomal STR and X-STR markers in the Qiang ethnic minority of China

The Qiang ethnic group is one of the oldest ethnic groups in China and is the most active ethnic group among all the populations along the Tibetan-Yi corridor. They have had a profound impact nationally and internationally. The paternal and maternal genetic feature of the Qiang ethnic group has been revealed, leaving the question of the genetic characteristics from autosomes and X chromosome not answered. The aim of this study was to explore the potential of 36 A-STR (Microreader™ 36A ID System) and 19 X-STR (Microreader™ 19X System) for application in the Qiang population and to elucidate their genetic diversity in southwest China. The cumulative probability of exclusion (CPE) for autosomal STRs is 1–1.3814 × 10−15 and the mean paternity exclusion chance (MEC) for X-STRs is 1–1.7323 × 10−6. Forensic parameters suggest that the STRs analyzed here are well-suited for forensic applications. The results of phylogenetic, interpopulation differentiation, and principal coordinates analysis (PCoA) indicate that the Qiang people have extensive connections with ethnic minorities in China, supporting the view that the Qiang people are the oldest group in the entire Sino-Tibetan language family. The Qiang appeared genetically more associated with most ethnic groups in China, especially the Han. The calculation of random matching probability (RMP) was improved by Fst correction of allele frequencies to make RMP more accurate and reasonable. This study can fill in the gaps in the Qiang STR reference database, providing valuable frequency data for forensic applications and evidence for the Qiang's genetic pattern as an important ancestral position in the Sino-Tibetan populations.

Seroprevalence of viral transfusion transmissible infections (HBsAg, anti-HCV, anti-HIV, Syphilis) and coinfection among healthy volunteer blood donors during 5-years in Luanda, Angola

BackgroundThe transmission of diseases by blood products continues to be a worldwide health problem, especially in Africa. Seroprevalence rates of the Hepatitis B virus (HBV), Hepatitis C virus (HCV), Human Immunodeficiency Virus (HIV), Syphilis, and Coinfection in Angola are poorly documented. This study aims to identify the seroprevalence of markers with positive results for Hepatitis B, C, HIV, Syphilis, and Coinfection in blood donors. Material and methodsA retrospective study was conducted using a database of positive serological markers for these infections and coinfection in 2734 blood donors traced from 2011 to 2016 in Luanda, Angola. The Chi-Square test (χ2) or Fisher's exact test was used to evaluate serological positivity and donors’ characteristics. A p-value < 0.05 was considered statistically significant. Results2734 blood donors aged 18 to 64 (median age 32 ± 9) were screened from 2011 to 2016. 73.9 % of the donors were positive for one Transfusion-Transmitted Infection (TTI), and 5.9 % showed evidence of multiple infections. The overall seroprevalence rate was 50.2 % (1373) for HBV, 20 % (436) for Syphilis, 7 % (191) for HIV, 5.1 % (140) for HCV, and 5.8 % for coinfected donors. 2467 (90 %) were men, and 267 (10 %) were women. We identified 118 (5.8 %) coinfected donors. Of those, 40 (33.9 %) simultaneously presented Hepatitis B virus surface antigen (HBsAg)/Syphilis, 24 (20.3 %) HBsAg/HIV, 22 (18.6 %) HBsAg/HCV, 20 (16.9 %) HIV/Syphilis, 8 (6.8 %) HCV/Syphilis, and 4 (3.4 %) HIV/HCV. ConclusionA high transfusion-transmissible infection prevalence was found compared to some countries in Sub-Saharan Africa. Therefore, intensifying the screening for these transfusion-transmitted infections in blood donors is critical to ensure blood safety.

MetaboliteCOVID: A manually curated database of metabolite markers for COVID-19

In the realm of unraveling COVID-19's intricacies, numerous metabolomic investigations have been conducted to discern the unique metabolic traits exhibited within infected patients. These endeavors have yielded a substantial reservoir of potential data pertaining to metabolic biomarkers linked to the virus. Despite these strides, a comprehensive and meticulously structured database housing these crucial biomarkers remains absent. In this study, we developed MetaboliteCOVID, a manually curated database of COVID-19-related metabolite markers. The database currently comprises 665 manually selected entries of significantly altered metabolites associated with early diagnosis, disease severity, prognosis, and drug response in COVID-19, encompassing 337 metabolites. Additionally, the database offers a user-friendly interface, containing abundant information for querying, browsing, and analyzing COVID-19-related abnormal metabolites in different body fluids. In summary, we believe that this database will effectively facilitate research on the functions and mechanisms of COVID-19-related metabolic biomarkers, thereby advancing both basic and clinical research on COVID-19. MetaboliteCOVID is free available at: https://cellknowledge.com.cn/MetaboliteCOVID.

Single-cell Mayo Map (scMayoMap): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis

BackgroundSingle-cell RNA-sequencing (scRNA-seq) has become a widely used tool for both basic and translational biomedical research. In scRNA-seq data analysis, cell type annotation is an essential but challenging step. In the past few years, several annotation tools have been developed. These methods require either labeled training/reference datasets, which are not always available, or a list of predefined cell subset markers, which are subject to biases. Thus, a user-friendly and precise annotation tool is still critically needed.ResultsWe curated a comprehensive cell marker database named scMayoMapDatabase and developed a companion R package scMayoMap, an easy-to-use single-cell annotation tool, to provide fast and accurate cell type annotation. The effectiveness of scMayoMap was demonstrated in 48 independent scRNA-seq datasets across different platforms and tissues. Additionally, the scMayoMapDatabase can be integrated with other tools and further improve their performance.ConclusionsscMayoMap and scMayoMapDatabase will help investigators to define the cell types in their scRNA-seq data in a streamlined and user-friendly way.

OrthoMaM v12: a database of curated single-copy ortholog alignments and trees to study mammalian evolutionary genomics.

To date, the databases built to gather information on gene orthology do not provide end-users with descriptors of the molecular evolution information and phylogenetic pattern of these orthologues. In this context, we developed OrthoMaM, a database of ORTHOlogous MAmmalian Markers describing the evolutionary dynamics of coding sequences in mammalian genomes. OrthoMaM version 12 includes 15,868 alignments of orthologous coding sequences (CDS) from the 190 complete mammalian genomes currently available. All annotations and 1-to-1 orthology assignments are based on NCBI. Orthologous CDS can be mined for potential informative markers at the different taxonomic levels of the mammalian tree. To this end, several evolutionary descriptors of DNA sequences are provided for querying purposes (e.g. base composition and relative substitution rate). The graphical web interface allows the user to easily browse and sort the results of combined queries. The corresponding multiple sequence alignments and ML trees, inferred using state-of-the art approaches, are available for download both at the nucleotide and amino acid levels. OrthoMaM v12 can be used by researchers interested either in reconstructing the phylogenetic relationships of mammalian taxa or in understanding the evolutionary dynamics of coding sequences in their genomes. OrthoMaM is available for browsing, querying and complete or filtered download at https://orthomam.mbb.cnrs.fr/.

Isoform switching leads to downregulation of cytokine producing genes in estrogen receptor positive breast cancer.

Objective: Estrogen receptor breast cancer (BC) is characterized by the expression of estrogen receptors. It is the most common cancer among women, with an incidence rate of 2.26 million cases worldwide. The aim of this study was to identify differentially expressed genes and isoform switching between estrogen receptor positive and triple negative BC samples. Methods: The data were collected from ArrayExpress, followed by preprocessing and subsequent mapping from HISAT2. Read quantification was performed by StringTie, and then R package ballgown was used to perform differential expression analysis. Functional enrichment analysis was conducted using Enrichr, and then immune genes were shortlisted based on the ScType marker database. Isoform switch analysis was also performed using the IsoformSwitchAnalyzeR package. Results: A total of 9,771 differentially expressed genes were identified, of which 86 were upregulated and 117 were downregulated. Six genes were identified as mainly associated with estrogen receptor positive BC, while a novel set of ten genes were found which have not previously been reported in estrogen receptor positive BC. Furthermore, alternative splicing and subsequent isoform usage in the immune system related genes were determined. Conclusion: This study identified the differential usage of isoforms in the immune system related genes in cancer cells that suggest immunosuppression due to the dysregulation of CXCR chemokine receptor binding, iron ion binding, and cytokine activity.

Identification of Breast Cancer Metastasis Markers from Gene Expression Profiles Using Machine Learning Approaches.

Cancer metastasis accounts for approximately 90% of cancer deaths, and elucidating markers in metastasis is the first step in its prevention. To characterize metastasis marker genes (MGs) of breast cancer, XGBoost models that classify metastasis status were trained with gene expression profiles from TCGA. Then, a metastasis score (MS) was assigned to each gene by calculating the inner product between the feature importance and the AUC performance of the models. As a result, 54, 202, and 357 genes with the highest MS were characterized as MGs by empirical p-value cutoffs of 0.001, 0.005, and 0.01, respectively. The three sets of MGs were compared with those from existing metastasis marker databases, which provided significant results in most comparisons (p-value < 0.05). They were also significantly enriched in biological processes associated with breast cancer metastasis. The three MGs, SPPL2C, KRT23, and RGS7, showed highly significant results (p-value < 0.01) in the survival analysis. The MGs that could not be identified by statistical analysis (e.g., GOLM1, ELAVL1, UBP1, and AZGP1), as well as the MGs with the highest MS (e.g., ZNF676, FAM163B, LDOC2, IRF1, and STK40), were verified via the literature. Additionally, we checked how close the MGs were to each other in the protein-protein interaction networks. We expect that the characterized markers will help understand and prevent breast cancer metastasis.

Genome-Wide Single-Nucleotide Polymorphism-Based Genomic Diversity and Runs of Homozygosity for Selection Signatures in Equine Breeds.

The horse, one of the most domesticated animals, has been used for several purposes, like transportation, hunting, in sport, or for agriculture-related works. Kathiawari, Marwari, Manipuri, Zanskari, Bhutia, Spiti, and Thoroughbred are the main breeds of horses, particularly due to their agroclimatic adaptation and role in any kind of strong physical activity, and these characteristics are majorly governed by genetic factors. The genetic diversity and phylogenetic relationship of these Indian equine breeds using microsatellite markers have been reported, but further studies exploring the SNP diversity and runs of homozygosity revealing the selection signature of breeds are still warranted. In our study, the identification of genes that play a vital role in muscle development is performed through SNP detection via the whole-genome sequencing approach. A total of 96 samples, categorized under seven breeds, and 620,721 SNPs were considered to ascertain the ROH patterns amongst all the seven breeds. Over 5444 ROH islands were mined, and the maximum number of ROHs was found to be present in Zanskari, while Thoroughbred was confined to the lowest number of ROHs. Gene enrichment of these ROH islands produced 6757 functional genes, with AGPAT1, CLEC4, and CFAP20 as important gene families. However, QTL annotation revealed that the maximum QTLs were associated with Wither's height trait ontology that falls under the growth trait in all seven breeds. An Equine SNP marker database (EqSNPDb) was developed to catalogue ROHs for all these equine breeds for the flexible and easy chromosome-wise retrieval of ROH along with the genotype details of all the SNPs. Such a study can reveal breed divergence in different climatic and ecological conditions.

Aplikasi Pembelajaran Pedosfer Berbasis Augmented Reality

The pedosphere is a combination of 2 words, namely the word pedo which means soil and sphera which means layer. The pedosphere is commonly referred to as the soil layer that is studied in high school. In this case, the researcher conducted research at SMA Negeri 5 Palu, which usually only used 2-dimensional images and theories in books to study the soil layers because of the lack of teaching aids. The purpose of this study is to help educators or students in the teaching and learning process recognize the soil layers by making an Augmented Reality (AR) technology application that can be used in all Android-based Smartphones. This application requires a marker to display a 3-dimensional object regarding the soil layer. The research method used by the researcher is the multimedia development method developed by Luther which is divided into 6 stages, namely concept, design, material collection, manufacture, testing and distribution. In the process of making the application, the researcher uses the Vuforia software as a marker database, Blender to create 3-dimensional objects and Unity as the application maker. The results of application testing on 47 respondents, namely 52% stated strongly agree, 36.2% agree, 10.5% quite agree, 1.1% disagree and 0.1% disagree.