Genome Database Research Articles

SNP Markers: Analysis of Genetic Diversity and Identification of Genomic Regions in Pantaneiro Sheep and Texel Sheep Under Natural Selection.

Sheep farming is growing substantially in Brazil, driven by the increasing demand for sheep meat. This rising demand has heightened the focus on sheep, making them the subject of numerous studies, including those centered on genetic analysis. A notable research area involves Pantaneiro sheep, which are indigenous to the Pantanal region of Mato Grosso do Sul and other locations. These sheep are of particular interest due to their adaptation to the unique environmental conditions of the Pantanal, a floodplain characterized by its distinctive climatic and ecological features. This study primarily aimed to conduct a comprehensive genomic analysis of Pantanal sheep subjected to natural selection within the Pantanal region and compare different sample herds using methodological approaches. Genomic analysis was performed to examine genetic diversity and structure via GGP50K single nucleotide polymorphism (SNP) analysis. A sample of 192 adult sheep over 4 years old was categorized into seven populations based on location: Six populations comprised Pantaneiro sheep with one Texel sheep population. Outlier SNPs were assessed to pinpoint regions under natural selection, with comparisons between the Pantaneiro and the commercial Texel breeds. All data analyses were conducted using the R programming language, employing specialized genetic analysis packages. These outlier SNPs were detected using three methodologies, PCAdapt, OutFLANK, and FDIST2/fsthet, with false discovery rate (FDR) corrections applied to ensure result accuracy. Each method was evaluated, and the genes associated with the identified SNPs were cross-referenced with the most recent sheep genome database, focusing specifically on genes with known phenotypic traits. Analysis of a sample comprising 192 adult individuals revealed greater genetic variability within the Pantaneiro breed than the Texel breed, highlighting the adaptation of the Pantaneiro breed to the unique Pantanal environment. Conversely, the Texel breed exhibited significantly higher levels of inbreeding, attributed to its controlled breeding practices. Outlier SNPs were detected with notable variation across different methodologies, underscoring the importance of FDR correction in ensuring the reliability and concentration of identified outliers. These outlier SNPs facilitated the identification of genes associated with key phenotypic traits, including hair growth, tissue regeneration, pigmentation regulation, and muscle capacity. The integrated analysis of methodologies demonstrated significant efficiency in elucidating the genomic landscape of Pantanal sheep, highlighting the genetic richness inherent in sheep from the Pantanal region of Mato Grosso do Sul. The techniques employed effectively identified outlier SNPs associated with phenotypically relevant genes. These findings, which reveal greater genetic variability and adaptability, underscore the potential of these animals for future research and their significance within Brazilian sheep farming. The Texel breed served as a valuable comparative group, illustrating the limited genetic variability in highly controlled breeding environments.

Prevalence Estimation of the PALB2 Germline Variant in East Asians and Koreans through Population Database Analysis.

PALB2 is a tumor suppressor gene. Heterozygous germline pathogenic variants of PALB2 significantly increase the lifetime risk of breast cancer and moderately increase the risk of ovarian and pancreatic cancers. This study analyzed the estimated prevalence of PALB2 variants globally, focusing on East Asian and Korean populations, where limited data were previously available. We examined 125,748 exomes from the Genome Aggregation Database (gnomAD), including 9197 East Asians, and additional data from 5305 individuals in the Korean Variant Archive and 1722 in the Korean Reference Genome Database. All PALB2 variants were interpreted according to guidelines from the American College of Medical Genetics and Genomics and the Clinical Genome Resource. The global prevalence of PALB2 variants was 0.18%, with the highest prevalence in Finnish populations (0.41%) and the lowest in Ashkenazi Jewish populations (0.04%). East Asians had a prevalence of 0.09%. By combining data from Korean genome databases and gnomAD totaling 8936 individuals, the overall prevalence of PALB2 variants in the Korean population was determined to be 0.13%. This study is the first comprehensive investigation of PALB2 variant prevalence in East Asians and Koreans using gnomAD and Korean genome databases. These findings provide essential reference data for future research and highlight the importance of region-specific genetic studies that will inform genetic counseling and hereditary cancer risk management.

ANAgdb: a multi-omics and taxonomy database for ANA-grade

BackgroundThe ANA-grade, encompassing early-diverging angiosperm lineages, Amborellales, Nymphaeales, and Austrobaileyales, represents a fundamental phase in the evolutionary history of flowering plants. Since the completion of key assembly of the Amborella genome, the continuous influx of omics data from the lineage underscores the need for a specialized database.ResultsHere, we introduce the ANA-grade Genome Database (ANAgdb, https://anagenome.cn/), which integrates multi-omics data including 11 genomes, 167 transcriptomes, and 10 miRNAomes, as well as extensive taxonomic details specific to the ANA-grade. Designed with an array of user-friendly tools, ANAgdb not only facilitates the effective storage, querying, and analysis of data but also enables the integration and dissemination of crucial genomic and taxonomic information.ConclusionBy integrating the comprehensive resources and tools, ANAgdb aims to significantly advance research in phylogenomics and taxonomic studies, providing a robust platform for researchers to explore the genetic and morphological diversities of these ancient plant lineages.

Genetic Predisposition to Prediabetes in the Kazakh Population.

The aim of this study was to conduct a comparative analysis of the population frequencies of the minor allele of polymorphic variants in the genes TCF7L2 (rs7903146) and PPARG (rs1801282), based on the genome-wide association studies analysis data associated with the risk of developing prediabetes, in an ethnically homogeneous Kazakh population compared to previously studied populations worldwide. This study utilized a genomic database consisting of 1800 ethnically Kazakh individuals who were considered in healthy condition. Whole-genome genotyping was performed using Illumina OmniChip 2.5-8 arrays, which interrogated approximately 2.5 million single nucleotide polymorphisms. The distribution of genotypes for the TCF7L2 (rs7903146) and PPARG (rs1801282) polymorphisms in the Kazakh sample was found to be in Hardy-Weinberg equilibrium (p > 0.05). The minor G allele of the "Asian" protective polymorphism rs1801282 in the PPARG gene was observed at a frequency of 13.8% in the Kazakh population. This suggests a potentially more significant protective effect of this polymorphism in reducing the risk of prediabetes among Kazakhs. The frequency of the unfavorable T allele of the insulin secretion-disrupting gene TCF7L2 (rs7903146) in Kazakhs was 15.2%. Studying the associations of genetic markers for prediabetes enables the timely identification of "high-risk groups" and facilitates the implementation of effective preventive measures. Further results from replicative genomic research will help identify significant polymorphic variants of genes underlying the alteration of prediabetes status.

Network Pharmacology and in vitro Experimental Verification on Intervention of Oridonin on Non-Small Cell Lung Cancer.

To explore the key target molecules and potential mechanisms of oridonin against non-small cell lung cancer (NSCLC). The target molecules of oridonin were retrieved from SEA, STITCH, SuperPred and TargetPred databases; target genes associated with the treatment of NSCLC were retrieved from GeneCards, DisGeNET and TTD databases. Then, the overlapping target molecules between the drug and the disease were identified. The protein-protein interaction (PPI) was constructed using the STRING database according to overlapping targets, and Cytoscape was used to screen for key targets. Molecular docking verification were performed using AutoDockTools and PyMOL software. Using the DAVID database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. The impact of oridonin on the proliferation and apoptosis of NSCLC cells was assessed using cell counting kit-8, cell proliferation EdU image kit, and Annexin V-FITC/PI apoptosis kit respectively. Moreover, real-time quantitative PCR and Western blot were used to verify the potential mechanisms. Fifty-six target molecules and 12 key target molecules of oridonin involved in NSCLC treatment were identified, including tumor protein 53 (TP53), Caspase-3, signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase kinase 8 (MAPK8), and mammalian target of rapamycin (mTOR). Molecular docking showed that oridonin and its key target molecules bind spontaneously. GO and KEGG enrichment analyses revealed cancer, apoptosis, phosphoinositide-3 kinase/protein kinase B (PI3K/Akt), and other signaling pathways. In vitro experiments showed that oridonin inhibited the proliferation, induced apoptosis, downregulated the expression of Bcl-2 and Akt, and upregulated the expression of Caspase-3. Oridonin can act on multiple targets and pathways to exert its inhibitory effects on NSCLC, and its mechanism may be related to upregulating the expression of Caspase-3 and downregulating the expressions of Akt and Bcl-2.

Identification of BBC3 as a novel indicator for predicting prostate cancer development and olaparib resistance

Prostate cancer (PCa) is a commonly occurring malignancy in elderly men. Olaparib, a poly ADP-ribose polymerase inhibitor, is utilized in PCa treatment. However, patients often develop resistance to olaparib after a period of treatment. Genetic alterations may play a significant role in this resistance, but the specific genes involved remain unclear. This study collected RNA-sequence data from the Gene Expression Omnibus database on both olaparib-sensitive and -resistant PCa cells to identify genes crucial for resistance. Subsequently, the enriched pathways of these genes were analyzed, and a protein–protein interaction (PPI) network was constructed to identify hub genes. The effect of these hub genes on PCa occurrence, progression, and prognosis was assessed using data from The Cancer Genome Atlas and Chinese Prostate Cancer Genome and Epigenome Atlas databases. Finally, this study validated our findings in clinical PCa samples and cells. From the GSE189186 dataset, 50 upregulated genes and 2 downregulated genes were identified in olaparib-resistant C4-2B and LNCaP cells. Utilizing the PPI network, eight upregulated genes (BBC3, TP53I3, FDXR, DDB2, CDKN1A, GADD45A, ZMAT3, and SESN1) were identified as hub genes for olaparib-resistant PCa cells. Furthermore, some of these genes were central to PCa occurrence, with BBC3 also influencing progression and prognosis. Importantly, BBC3 expression was upregulated in clinical PCa samples and affected PCa cells sensitive to olaparib, suggesting its potential as a predictive marker for PCa development and olaparib resistance.

Self-reported cancer-related cognitive impairment is associated with perturbed neurotransmission pathways.

Cancer-related cognitive impairment (CRCI) is reported by 45% of patients with cancer. Significant gaps in knowledge remain regarding the mechanisms that underlie CRCI. Using a data-driven approach, the study purpose was to evaluate for perturbed pathways associated with membership in the High versus the Low CRCI profiles. Patients completed the Attentional Function Index six times over two cycles of chemotherapy. Using findings from a previous latent profile analysis, subgroups of patients with high versus low levels of CRCI were evaluated (i.e., High versus Low CRCI profiles). Gene expression was quantified using either ribonucleic (RNA)-sequencing or microarray analyses and pathway impact analyses were performed. Signaling pathways were defined using the Kyoto Encyclopedia of Genes and Genomes database. A total of 508 patients had data available for analysis. Of the 261 patients in the RNA-sequencing sample, 48.7% were in the High class and 51.3% were in the Low class. Of the 247 patients the microarray sample, 46.6% were in the High class and 53.4% were in the Low class. Pathway impact analyses identified seven perturbed pathways related to neurotransmission (i.e., glutamatergic synapse, GABAergic synapse, dopaminergic synapse, serotonergic synapse, long-term depression, cholinergic synapse, retrograde endocannabinoid signaling). This study is the first to describe associations between self-reported CRCI in patients receiving chemotherapy for breast, gastrointestinal, gynecological, or lung cancer and seven neurotransmission pathways. These findings provide new insights into potential targets for mechanistically based interventions.

Real-world genome profiling in Japanese patients with pancreatic ductal adenocarcinoma focusing on HRD implications.

Pancreatic ductal adenocarcinoma (PDAC) poses significant challenges due to its high mortality, making it a critical area of research. This retrospective observational study aimed to analyze real-world data from comprehensive genome profiling (CGP) of Japanese patients with PDAC, mainly focusing on differences in gene detection rates among panels and the implications for homologous recombination deficiency (HRD) status. This study enrolled 2568 patients with PDAC who had undergone CGP between June 2019 and December 2021 using data from the nationwide Center for Cancer Genomics and Advanced Therapeutics database. Two types of CGP assays (tissue and liquid biopsies) were compared and a higher detection rate of genetic abnormalities in tissue specimens was revealed. HRD-related gene alterations were detected in 23% of patients, with BRCA1/2 mutations accounting for 0.9% and 2.9% of patients, respectively. Treatment outcome analysis indicated that patients with BRCA1/2 mutations had a longer time to treatment discontinuation with FOLFIRINOX than gemcitabine plus nab-paclitaxel as first-line therapy (9.3 vs. 5.6 months, p = 0.028). However, no significant differences were observed in the treatment response among the other HRD-related genes. Logistic regression analysis identified younger age and family history of breast, prostate, and ovarian cancers as predictive factors for HRD-related gene alterations. Despite the lack of progression-free survival data and the inability to discriminate between germline and somatic mutations, this study provides valuable insights into the clinical implications of CGP in Japanese patients with PDAC. Further research is warranted to optimize panel selection and elucidate the efficacy of platinum-based therapies depending on the HRD status.

Bioinformatics Analysis and Expression Features of Terpene Synthase Family in Cymbidium ensifolium

Terpene synthases (TPSs) are crucial for the diversification of terpenes, catalyzing the formation of a wide variety of terpenoid compounds. However, genome-wide systematic characterization of TPS genes in Cymbidium ensifolium has not been reported. Within the genomic database of C. ensifolium, we found 30 CeTPS genes for this investigation. CeTPS genes were irregularly distributed throughout the seven chromosomes and primarily expanded through tandem duplications. The CeTPS proteins were classified into three TPS subfamilies, including 17 TPS-b members, 8 TPS-a members, and 5 TPS-c members. Conserved motif analysis showed that most CeTPSs contained DDxxD and RRX8W motifs. Cis-element analysis of CeTPS gene promoters indicated regulation primarily by plant hormones and stress. Transcriptome analysis revealed that CeTPS1 and CeTPS18 had high expression in C. ensifolium flowers. qRT-PCR results showed that CeTPS1 and CeTPS18 were predominantly expressed during the flowering stage. Furthermore, CeTPS1 and CeTPS18 proteins were localized in the chloroplasts. These results lay the theoretical groundwork for future research on the functions of CeTPSs in terpenoid biosynthesis.

Bioinformatics in Russia: history and present-day landscape.

Bioinformatics has become an interdisciplinary subject due to its universal role in molecular biology research. The current status of Russia's bioinformatics research in Russia is not known. Here, we review the history of bioinformatics in Russia, present the current landscape, and highlight future directions and challenges. Bioinformatics research in Russia is driven by four major industries: information technology, pharmaceuticals, biotechnology, and agriculture. Over the past three decades, despite a delayed start, the field has gained momentum, especially in protein and nucleic acid research. Dedicated and shared centers for genomics, proteomics, and bioinformatics are active in different regions of Russia. Present-day bioinformatics in Russia is characterized by research issues related to genetics, metagenomics, OMICs, medical informatics, computational biology, environmental informatics, and structural bioinformatics. Notable developments are in the fields of software (tools, algorithms, and pipelines), use of high computation power (e.g. by the Siberian Supercomputer Center), and large-scale sequencing projects (the sequencing of 100 000 human genomes). Government funding is increasing, policies are being changed, and a National Genomic Information Database is being established. An increased focus on eukaryotic genome sequencing, the development of a common place for developers and researchers to share tools and data, and the use of biological modeling, machine learning, and biostatistics are key areas for future focus. Universities and research institutes have started to implement bioinformatics modules. A critical mass of bioinformaticians is essential to catch up with the global pace in the discipline.

Unveiling Disparities: Analyzing Hispanic Inclusion in Liver Cancer Research Databases in the United States

AbstractPrimary liver cancer, including hepatocellular carcinoma and intrahepatic cholangiocarcinoma was the sixth leading cause of cancer death in the United States in 2023. Hispanic people constitute approximately 19% of the nation’s total population according to the US Census. Hispanic patients have the highest relative incidence rates of liver cancer compared to non-Hispanic Whites and non-Hispanic Blacks, a disparity frequently overlooked in cancer research. In this study, our primary objective was to analyze the potential underrepresentation of Hispanic individuals in liver cancer research databases. We identified databases that had liver cancer-specific studies and be population-based in the United States. Our search yielded 7 cancer genomic databases, which were analyzed according to incidence percentages across ethnicity and race categories. Our study included 3104 patients; ethnic data was not reported for 13.1% (n = 406) of the patients. Samples were predominantly from individuals who identified as Not Hispanic (81.0%), Hispanic individuals represented 5.9%. Race was reported as follows: non-Hispanic Whites (61.0%), Asians (22.0%), non-Hispanic Blacks (5.4%), Other (3.1%), Native American/American Indian/Alaska Native (0.4%), Pacific Islander/Native Hawaiian (0.2%) and not reported (7.9%). These findings collectively underscore significant disparities in the representation of ethnic and racial groups, particularly Hispanics. Given the present racial and ethnic demographics of the US population and the projected surge in the Hispanic population in forthcoming years, it becomes imperative to address health disparities that may worsen without efforts to enhance proper inclusion in cancer research.

Abstract A080: Improving outcomes: Addressing racial and ethnic disparities in colorectal cancer genomic research

Abstract Colorectal cancer (CRC) is the fourth most common cancer diagnosed in the United States (U.S.). This disease presents notable health disparities among racial and ethnic minorities in the U.S. Native Americans (NA) and non-Hispanic Blacks (NHB) exhibit the highest incidence and mortality rates for CRC compared to non-Hispanic Whites (NHW). These disparities are driven by a combination of factors, including socioeconomic inequalities, access to healthcare, lifestyle habits, and genetic susceptibilities. Minority populations often face delays in diagnosis and treatment, leading to advanced disease stages at presentation and poorer outcomes. Addressing these disparities through cancer genomics is essential for developing effective, personalized treatments that can improve outcomes for underrepresented populations. Comprehensive genomic studies can reveal genetic mutations and biomarkers unique to these groups, facilitating targeted therapies and preventive measures tailored to their specific needs. To address these disparities, we conducted an analysis of U.S. population-based colorectal cancer studies within 3 cancer genomic databases: the National Cancer Institute’s Genomic Data Commons, the AACR Project GENIE, and cBioPortal. We identified 13 studies suitable for inclusion, calculating incidence percentages across all racial and ethnic categories. Our analysis encompassed a total of 20,295 patients. Among the analyzed patients, the racial distribution was as follows: NHW (68.5%), Asians (5.30%), NHB (7.7%), Other (5.6%), NA (0.2%), Pacific Islander/Native Hawaiian (0.07%), and not reported (12.7%). Ethnic data was missing for 24.1% (n=4,895) of the patients. Samples were predominantly from individuals identified as Not Hispanic (68.4%), while Hispanic individuals constituted 7.5%. Our results show significant underrepresentation of NHB, NA and Hispanic patients in CRC genomic databases highlighting a disparity between expected and actual representation. These findings underscore the critical need for inclusive research practices. Addressing these disparities in cancer genomics is imperative to develop equitable, effective treatments and improve health outcomes for all populations. Ensuring diverse representation in genomic databases will enhance the understanding of genetic differences across populations, inform targeted therapies, and ultimately contribute to reducing CRC disparities. By addressing these disparities, we can move towards a future where all populations benefit equally from advancements in CRC treatment and prevention, thus improving survival rates and quality of life for minority groups. Citation Format: Gabriela Arroyo Figueroa, Tim F. Greten, Cecilia Monge. Improving outcomes: Addressing racial and ethnic disparities in colorectal cancer genomic research [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A080.

Abstract B012: Prioritization of ancestry-specific variations in disease data helps to alleviate bias in genomic data

Abstract 95% of sequencing data is from individuals of European descent. Underrepresentation of non- European individuals in genomic resources has limited our understanding of the effects of population-specific variants on complex traits and disease. Human populations have undergone selection for variants beneficial to survival in their environment, resulting in individuals with genetic variants unique to their ancestral populations. While these variants can impact disease occurrence and treatment outcome, genetic ancestry is often unaccounted for in disease modeling. Lack of ancestral population representation in data has led to disparate disease outcomes and treatment. While the primary proposed solution to this problem is more diverse sequencing of patients, these efforts will take years of effort and continual work to maintain the diversity balance. Additionally, they will not solve the issue; clinical trials cannot expect to capture human global diversity at every stage. Here we show we can mitigate data bias by utilizing readily available genomic population databases to target genes with ancestrally relevant variations. Our AI model, PhyloFrame, creates equitable gene signatures from transcriptomic input data. PhyloFrame corrects for ancestral bias in data by utilizing genomic population databases and functional interaction networks to identify genes both relevant to disease and associated with a variant unique to a single ancestry. PhyloFrame uses gnomAD data to quantify genome-wide ancestry-specific allele frequencies from a large cohort of healthy individuals, which PhyloFrame uses to create ancestry-agnostic signatures when modeling disease data. Our model demonstrates the utility of including readily available population-level data from healthy individuals in AI methods to overcome existing genomic data bias. PhyloFrame serves also as a demonstration of how equitable AI methods create gene signatures applicable across ancestries without requiring sample-specific ancestry information. Our model demonstrates how AI can be used to help mitigate ancestral bias in genomic data using preexisting data and contribute to equitable representation in medical research. Citation Format: Leslie A. Smith, Kiley Graim, James A. Cahill. Prioritization of ancestry-specific variations in disease data helps to alleviate bias in genomic data [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B012.

Abstract C123: Exploring the cancer phenotype of a potential CDKN2A founder variant, c.146T>C (p.Ile49Thr), in Hispanic/Latinos of predominately Mexican ancestry

Abstract BACKGROUND: CDKN2A germline pathogenic/likely pathogenic variants (PVs) cause familial atypical multiple mole melanoma syndrome, which increases melanoma (MEL) and pancreatic cancer (PC) risk. The interpretation of genetic test results can be complicated by discordant variant classifications. CDKN2A c.146T>C (ClinVar ID:127523) is such a variant and is classified as likely pathogenic at some laboratories and as uncertain at others. Furthermore, the variant frequency in Hispanic/Latinos (H/Ls) is higher than typically expected for a PV in CDKN2A and some functional studies support that it is a PV. METHODS: Genetic counseling databases at various institutions were queried for demographic, personal and family cancer history data for individuals with known PVs in CDKN2A, with c.146T>C, and c.–2G>A (ClinVar ID:141245), a benign CDKN2A variant (BV) seen in H/Ls to serve as a comparator. The association between personal and/or family history of PC and/or MEL and demographic/clinical characteristics was tested using Fischer exact test, Chi-square test, and post-hoc test with ANOVA. Odds ratios were calculated with multinomial logistic regression. RESULTS: Overall, 219 individuals were identified; 109 with c.146T>C, 60 with other CDKN2A PVs, and 50 with the BV; 82% were female, 76% H/L, and 70% had a personal cancer history – 18% (n=27) had MEL and 10% (n=16) had PC. By variant group, 99% (c.146T>C) and 96% (BV) were H/L; 85% and 84% of Mexican ancestry, respectively. MEL was reported in 38% (n=22) of other PVs, 5% (n=5) of c.146T>C, and not at all in the BV group. Those with c.146T>C were 92% less likely to have MEL than other CDKN2A PVs (p<0.001), with no difference in mean age at diagnosis, 32y vs. 40y, respectively (p=0.71). Seven (12%) of other PVs had PC compared to 6% (n=7) of c.146T>C and 4% (n=2) of the BV. While this difference was not significant (p=0.27), the mean age at diagnosis in c.146T>C was significantly younger than other PVs (32y vs. 71y; p=0.02). When including family history, those with c.146T>C were 80% less likely to have a personal AND family history of MEL than other PVs (p<0.001), but the odds of having both a personal AND family history of PC was not significantly different (p=0.52). CONCLUSION: In the largest CDKN2A c.146T>C study (n=109) to date, MEL was significantly less frequent in individuals with this variant compared to other PVs CDKN2A. A similar, non-significant, trend was seen for PC. Notably, individuals with c.146T>C who developed PC presented at a significantly younger age than individuals with other CDKN2A PVs. The presence of c.146T>C in H/Ls of mostly Mexican ancestry suggests it may be a founder variant. While more research is needed to further refine cancer penetrance and associations, the conservative approach is to manage c.146T>C as per CDKN2A PV guidelines. Given the frequency of this variant in genomic databases, clarifying clinical impact is vital for risk- appropriate management and to reduce existing cancer disparities faced by many H/Ls. Citation Format: Daisy Hernandez, Ashlie Browning, Amber Gemmell, Karlena Lara-Otero, Mariana Niell-Swiller, Kathyrn A. Mraz, Amie Blanco, Yvonne Cardona, Emmeline Chang, Jacob Comeaux, Julie O. Culver, James M. Ford, Natalia Gutierrez, Daniella Kamara, Beth Y. Karlan, Ming Li, Jacqueline Mersch, Qi Nie, Maria L. Wei, Charité N. Ricker. Exploring the cancer phenotype of a potential CDKN2A founder variant, c.146T>C (p.Ile49Thr), in Hispanic/Latinos of predominately Mexican ancestry [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C123.

Saccharomyces Genome Database: Advances in Genome Annotation, Expanded Biochemical Pathways, and Other Key Enhancements.

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here we describe recent updates at SGD, including the two most recent reference genome annotation updates, expanded biochemical pathways representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

RNA Sequencing of Sperm from Healthy Cattle and Horses Reveals the Presence of a Large Bacterial Population.

RNA molecules within ejaculated sperm can be characterized through whole-transcriptome sequencing, enabling the identification of pivotal transcripts that may influence reproductive success. However, the profiling of sperm transcriptomes through next-generation sequencing has several limitations impairing the identification of functional transcripts. In this study, we explored the nature of the RNA sequences present in the sperm transcriptome of two livestock species, cattle and horses, using RNA sequencing (RNA-seq) technology. Through processing of transcriptomic data derived from bovine and equine sperm cell preparations, low mapping rates to the reference genomes were observed, mainly attributed to the presence of ribosomal RNA and bacteria in sperm samples, which led to a reduced sequencing depth of RNAs of interest. To explore the presence of bacteria, we aligned the unmapped reads to a complete database of bacterial genomes and identified bacteria-associated transcripts which were characterized. This analysis examines the limitations associated with sperm transcriptome profiling by reporting the nature of the RNA sequences among which bacterial RNA was found. These findings can aid researchers in understanding spermatozoal RNA-seq data and pave the way for the identification of molecular markers of sperm performance.

Streamlining of Simple Sequence Repeat Data Mining Methodologies and Pipelines for Crop Scanning.

Genetic markers are powerful tools for understanding genetic diversity and the molecular basis of traits, ushering in a new era of molecular breeding in crops. Over the past 50 years, DNA markers have rapidly changed, moving from hybridization-based and second-generation-based to sequence-based markers. Simple sequence repeats (SSRs) are the ideal markers in plant breeding, and they have numerous desirable properties, including their repeatability, codominance, multi-allelic nature, and locus specificity. They can be generated from any species, which requires prior sequence knowledge. SSRs may serve as evolutionary tuning knobs, allowing for rapid identification and adaptation to new circumstances. The evaluations published thus far have mostly ignored SSR polymorphism and gene evolution due to a lack of data regarding the precise placements of SSRs on chromosomes. However, NGS technologies have made it possible to produce high-throughput SSRs for any species using massive volumes of genomic sequence data that can be generated fast and at a minimal cost. Though SNP markers are gradually replacing the erstwhile DNA marker systems, SSRs remain the markers of choice in orphan crops due to the lack of genomic resources at the reference level and their adaptability to resource-limited labor. Several bioinformatic approaches and tools have evolved to handle genomic sequences to identify SSRs and generate primers for genotyping applications in plant breeding projects. This paper includes the currently available methodologies for producing SSR markers, genomic resource databases, and computational tools/pipelines for SSR data mining and primer generation. This review aims to provide a 'one-stop shop' of information to help each new user carefully select tools for identifying and utilizing SSRs in genetic research and breeding programs.

Genetic diversity, biofilm formation, and Vancomycin resistance of clinical Clostridium innocuum isolates

BackgroundClostridium innocuum, previously considered a commensal microbe, is a spore-forming anaerobic bacterium. C. innocuum displays inherent resistance to vancomycin and is associated with extra-intestinal infections, antibiotic-associated diarrhea, and inflammatory bowel disease. This study seeks to establish a multilocus sequence typing (MLST) scheme to explore the correlation between C. innocuum genotyping and its potential pathogenic phenotypes.MethodsFifty-two C. innocuum isolates from Linkou Chang Gung Memorial Hospital (CGMH) in Taiwan and 60 sequence-available C. innocuum isolates from the National Center for Biotechnolgy Information Genome Database were included. The concentrated sequence of housekeeping genes in C. innocuum was determined by amplicon sequencing and used for MLST and phylogenetic analyses. The biofilm production activity of the C. innocuum isolates was determined by crystal violet staining.ResultsOf the 112 C. innocuum isolates, 58 sequence types were identified. Maximum likelihood estimation categorized 52 CGMH isolates into two phylogenetic clades. These isolates were found to be biofilm producers, with isolates in clade I exhibiting significantly higher biofilm production than isolates in clade II. The sub-inhibitory concentration of vancomycin seemed to minimally influence biofilm production by C. innocuum isolates. Nevertheless, C. innocuum embedded in the biofilm structure demonstrated resistance to vancomycin treatments at a concentration greater than 256 µg/mL.ConclusionsThis study suggests that a specific genetic clade of C. innocuum produces a substantial amount of biofilm. Furthermore, this phenotype assists C. innocuum in resisting high concentrations of vancomycin, which may potentially play undefined roles in C. innocuum pathogenesis.

Genomic characterization of an uncommon Delftia acidovorans isolate obtained from aBulgarian immunocompetent outpatient diagnosed with bronchitis.

Delftia acidovorans is an aerobic, non-fermenting Gram-negative bacterium (NFGNB), found in soil, water and hospital environments. It is rarely clinically significant, most commonly affecting hospitalized or immunocompromised patients. The present study aimed to explore the genomic characteristics of a Bulgarian clinical D. acidovorans isolate (designated Dac759) in comparison to all strains of this species with available genomes in the NCBI Genome database (n = 34). Dac759 was obtained in 2021 from the sputum of a 65-year-old female immunocompetent outpatient with bronchitis. Species identification using MALDI-TOF mass spectrometry, antimicrobial susceptibility testing, whole-genome sequencing (WGS), and phylogenomic analysis were performed. The isolate demonstrated high-level resistance to colistin (16 mg L-1); resistance to gentamicin; reduced susceptibility to piperacillin, piperacillin-tazobactam, ceftazidime, cefepime, ciprofloxacin, and levofloxacin; and susceptibility to imipenem, meropenem, amikacin, and tobramycin. The observed genome size (6.43 Mb) and GC content (66.76%) were comparable with the accessible data from sequenced D. acidovorans genomes. A limited number of resistance determinants were identified in the assembled genome as follows: blaOXA-459, emrE, oqxB, and mexCD-oprJ. The phylogenomic analysis indicated a high heterogenicity of the included D. acidovorans genomes. In conclusion, to the best of our knowledge, this is the first documented case of a clinically relevant D. acidovorans isolate in Bulgaria. Unlike the majority of reports in the literature, Dac759 affected a patient with no malignancies or other preexisting comorbidities. With this in mind, its genome sequence is a valuable resource for the fundamental study of uncommon bacterial pathogens of public health importance.

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

A genomic database of all Earth’s eukaryotic species could contribute to many scientific discoveries; however, only a tiny fraction of species have genomic information available. In 2018, scientists across the world united under the Earth BioGenome Project (EBP), aiming to produce a database of high-quality reference genomes containing all ~1.5 million recognized eukaryotic species. As the European node of the EBP, the European Reference Genome Atlas (ERGA) sought to implement a new decentralised, equitable and inclusive model for producing reference genomes. For this, ERGA launched a Pilot Project establishing the first distributed reference genome production infrastructure and testing it on 98 eukaryotic species from 33 European countries. Here we outline the infrastructure and explore its effectiveness for scaling high-quality reference genome production, whilst considering equity and inclusion. The outcomes and lessons learned provide a solid foundation for ERGA while offering key learnings to other transnational, national genomic resource projects and the EBP.