A cold case of hemolytic disease of the fetus and newborn resolved by genomic sequencing and population studies to define a new antigen in the Rh system

BACKGROUND

We report an obstetric case involving an RhD-positive woman who had developed a red blood cell (RBC) antibody that was not detected until after delivery of a newborn, who presented with a positive direct antiglobulin test result. Immunohematology studies suggested that the maternal antibody was directed against a low-prevalence antigen on the paternal and newborn RBCs.

RESULTS

Comprehensive blood group profiling by targeted exome sequencing revealed a novel nonsynonymous single nucleotide variant (SNV) RHCE c.486C>G (GenBank MZ326705) on the RHCE*Ce allele, for both the father and newborn. A subsequent genomic-based study to profile blood groups in an Indigenous Australian population revealed the same SNV in 2 of 247 individuals. Serology testing showed that the maternal antibody reacted specifically with RBCs from these two individuals.

DISCUSSION

The maternal antibody was directed against a novel antigen in the Rh blood group system arising from an RHCE c.486C>G variant on the RHCE*Ce allele linked to RHD*01. The variant predicts a p.Asn162Lys change on the RhCE protein and has been registered as the 56th antigen in the Rh system, ISBT RH 004063.

CONCLUSION

This antibody was of clinical significance, resulting in a mild to moderate hemolytic disease of the fetus and newborn (HDFN). In the past, the cause of such HDFN cases may have remained unresolved. Genomic sequencing combined with population studies now assists in resolving such cases. Further population studies have potential to inform the need to design population-specific red cell antibody typing panels for antibody screening in the Australian population.

Pharmacological induction of chromatin remodeling drives chemosensitization in triple-negative breast cancer

Targeted therapies have improved outcomes for certain cancer subtypes, but cytotoxic chemotherapy remains a mainstay for triple-negative breast cancer (TNBC). The epithelial-to-mesenchymal transition (EMT) is a developmental program co-opted by cancer cells that promotes metastasis and chemoresistance. There are no therapeutic strategies specifically targeting mesenchymal-like cancer cells. We report that the US Food and Drug Administration (FDA)-approved chemotherapeutic eribulin induces ZEB1-SWI/SNF-directed chromatin remodeling to reverse EMT that curtails the metastatic propensity of TNBC preclinical models. Eribulin induces mesenchymal-to-epithelial transition (MET) in primary TNBC in patients, but conventional chemotherapy does not. In the treatment-naive setting, but not after acquired resistance to other agents, eribulin sensitizes TNBC cells to subsequent treatment with other chemotherapeutics. These findings provide an epigenetic mechanism of action of eribulin, supporting its use early in the disease process for MET induction to prevent metastatic progression and chemoresistance. These findings warrant prospective clinical evaluation of the chemosensitizing effects of eribulin in the treatment-naive setting.

Genomic characterisation of clinically significant blood group variants in Aboriginal Australians

BACKGROUND

Hematological disorders are often treated with blood transfusions. Many blood group antigens and variants are population-specific, and for patients with rare blood types, extensive donor screening is required to find suitable matches for transfusion. There is a scarcity of knowledge regarding blood group variants in Aboriginal Australian populations, despite a higher need for transfusion due to the higher prevalence of renal diseases and anaemia.

MATERIALS AND METHODS

In this study, we applied next-generation sequencing and analysis to 245 samples obtained from Aboriginal Australians from South-East Queensland, to predict antigen phenotypes for 36 blood group systems.

RESULTS

We report potential weak antigens in blood group systems RH, FY and JR that have potential clinical implications in transfusion and pregnancy settings. These include partial DIII type 4, weak D type 33, and Del RHD (IVS2-2delA). The rare Rh phenotypes D+ C+ E+ c- e+ and D+ C+ E+ c+ e- were also detected.

DISCUSSION

The comprehensive analyses of blood group genetic variant profiles identified in this study will provide insight and an opportunity to improve Aboriginal health by aiding in the identification of appropriate blood products for population-specific transfusion needs.

VPBrowse: Genome-based representation of MS/MS spectra to quantify 10,000 bovine proteins

SWATH is a data acquisition strategy acclaimed for generating quantitatively accurate and consistent measurements of proteins across multiple samples. Its utility for proteomics studies in nonlaboratory animals, however, is currently compromised by the lack of sufficiently comprehensive and reliable public libraries, either experimental or predicted, and relevant platforms that support their sharing and utilization in an intuitive manner. Here we describe the development of the Veterinary Proteome Browser, VPBrowse (http://browser.proteo.cloud/), an on-line platform for genome-based representation of the Bos taurus proteome, which is equipped with an interactive database and tools for searching, visualization, and building quantitative mass spectrometry assays. In its current version (VPBrowse 1.0), it contains high-quality fragmentation spectra acquired on QToF instrument for over 36,000 proteotypic peptides, the experimental evidence for over 10,000 proteins. Data can be downloaded in different formats to enable analysis using popular software packages for SWATH data processing whilst normalization to iRT scale ensures compatibility with diverse chromatography systems. When applied to published blood plasma dataset from the biomarker discovery study, the resource supported label-free quantification of additional proteins not reported by the authors previously including PSMA4, a tissue leakage protein and a promising candidate biomarker of animal's response to dehorning-related injury.

Novel genetic markers for chronic kidney disease in a geographically isolated population of Indigenous Australians: Individual and multiple phenotype genome-wide association study

BACKGROUND

Chronic kidney disease (CKD) is highly prevalent among Indigenous Australians, especially those in remote regions. The Tiwi population has been isolated from mainland Australia for millennia and exhibits unique genetic characteristics that distinguish them from other Indigenous and non-Indigenous populations. Notably, the rate of end-stage renal disease is up to 20 times greater in this population compared to non-Indigenous populations. Despite the identification of numerous genetic loci associated with kidney disease through GWAS, the Indigenous population such as Tiwi remains severely underrepresented and the increased prevalence of CKD in this population may be due to unique disease-causing alleles/genes.

METHODS

We used albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) to estimate the prevalence of kidney disease in the Tiwi population (N = 492) in comparison to the UK Biobank (UKBB) (N = 134,724) database. We then performed an exploratory factor analysis to identify correlations among 10 CKD-related phenotypes and identify new multi-phenotype factors. We subsequently conducted a genome-wide association study (GWAS) on all single and multiple phenotype factors using mixed linear regression models, adjusted for age, sex, population stratification, and genetic relatedness between individuals.

RESULTS

Based on ACR, 20.3% of the population was at severely increased risk of CKD progression and showed elevated levels of ACR compared to the UKBB population independent of HbA1c. A GWAS of ACR revealed novel association loci in the genes MEG3 (chr14:100812018:T:A), RAB36 (rs11704318), and TIAM2 (rs9689640). Additionally, multiple phenotypes GWAS of ACR, eGFR, urine albumin, and serum creatinine identified a novel variant that mapped to the gene MEIS2 (chr15:37218869:A:G). Most of the identified variants were found to be either absent or rare in the UKBB population.

CONCLUSIONS

Our study highlights the Tiwi population's predisposition towards elevated ACR, and the collection of novel genetic variants associated with kidney function. These associations may prove valuable in the early diagnosis and treatment of renal disease in this underrepresented population. Additionally, further research is needed to comprehensively validate the functions of the identified variants/genes.

Protein-coding potential of non-canonical open reading frames in human transcriptome

In recent years, proteogenomics and ribosome profiling studies have identified a large number of proteins encoded by noncoding regions in the human genome. They are encoded by small open reading frames (sORFs) in the untranslated regions (UTRs) of mRNAs and long non-coding RNAs (lncRNAs). These sORF encoded proteins (SEPs) are often <150AA and show poor evolutionary conservation. A subset of them have been functionally characterized and shown to play an important role in fundamental biological processes including cardiac and muscle function, DNA repair, embryonic development and various human diseases. How many novel protein-coding regions exist in the human genome and what fraction of them are functionally important remains a mystery. In this review, we discuss current progress in unraveling SEPs, approaches used for their identification, their limitations and reliability of these identifications. We also discuss functionally characterized SEPs and their involvement in various biological processes and diseases. Lastly, we provide insights into their distinctive features compared to canonical proteins and challenges associated with annotating these in protein reference databases.

Genetic Characterization of Blood Group Antigens for Polynesian Heritage Norfolk Island Residents

Improvements in blood group genotyping methods have allowed large scale population-based blood group genetics studies, facilitating the discovery of rare blood group antigens. Norfolk Island, an external and isolated territory of Australia, is one example of an underrepresented segment of the broader Australian population. Our study utilized whole genome sequencing data to characterize 43 blood group systems in 108 Norfolk Island residents. Blood group genotypes and phenotypes across the 43 systems were predicted using RBCeq. Predicted frequencies were compared to data available from the 1000G project. Additional copy number variation analysis was performed, investigating deletions outside of RHCE, RHD, and MNS systems. Examination of the ABO blood group system predicted a higher distribution of group A1 (45.37%) compared to group O (35.19%) in residents of the Norfolk Island group, similar to the distribution within European populations (42.94% and 38.97%, respectively). Examination of the Kidd blood group system demonstrated an increased prevalence of variants encoding the weakened Kidd phenotype at a combined prevalence of 12.04%, which is higher than that of the European population (5.96%) but lower than other populations in 1000G. Copy number variation analysis showed deletions within the Chido/Rodgers and ABO blood group systems. This study is the first step towards understanding blood group genotype and antigen distribution on Norfolk Island.

Machine Learning-Based Prediction of Distant Recurrence in Invasive Breast Carcinoma Using Clinicopathological Data: A Cross-Institutional Study

Breast cancer is the most common type of cancer worldwide. Alarmingly, approximately 30% of breast cancer cases result in disease recurrence at distant organs after treatment. Distant recurrence is more common in some subtypes such as invasive breast carcinoma (IBC). While clinicians have utilized several clinicopathological measurements to predict distant recurrences in IBC, no studies have predicted distant recurrences by combining clinicopathological evaluations of IBC tumors pre- and post-therapy with machine learning (ML) models. The goal of our study was to determine whether classification-based ML techniques could predict distant recurrences in IBC patients using key clinicopathological measurements, including pathological staging of the tumor and surrounding lymph nodes assessed both pre- and post-neoadjuvant therapy, response to therapy via standard-of-care imaging, and binary status of adjuvant therapy administered to patients. We trained and tested four clinicopathological ML models using a dataset (144 and 17 patients for training and testing, respectively) from Duke University and validated the best-performing model using an external dataset (8 patients) from Dartmouth Hitchcock Medical Center. The random forest model performed better than the C-support vector classifier, multilayer perceptron, and logistic regression models, yielding AUC values of 1.0 in the testing set and 0.75 in the validation set (p < 0.002) across both institutions, thereby demonstrating the cross-institutional portability and validity of ML models in the field of clinical research in cancer. The top-ranking clinicopathological measurement impacting the prediction of distant recurrences in IBC were identified to be tumor response to neoadjuvant therapy as evaluated via SOC imaging and pathology, which included tumor as well as node staging.

The pharmacogenomic landscape of an Indigenous Australian population

Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a "genomic gap" that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking. Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data. Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing. Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.

Pharmacological Induction of mesenchymal-epithelial transition chemosensitizes breast cancer cells and prevents metastatic progression

The epithelial-mesenchymal transition (EMT) is a developmental program co-opted by tumor cells that aids the initiation of the metastatic cascade. Tumor cells that undergo EMT are relatively chemoresistant, and there are currently no therapeutic avenues specifically targeting cells that have acquired mesenchymal traits. We show that treatment of mesenchymal-like triple-negative breast cancer (TNBC) cells with the microtubule-destabilizing chemotherapeutic eribulin, which is FDA-approved for the treatment of advanced breast cancer, leads to a mesenchymal-epithelial transition (MET). This MET is accompanied by loss of metastatic propensity and sensitization to subsequent treatment with other FDA-approved chemotherapeutics. We uncover a novel epigenetic mechanism of action that supports eribulin pretreatment as a path to MET induction that curtails metastatic progression and the evolution of therapy resistance.

Abstract 6341: ImaGene: A robust AI-based software platform for tumor radiogenomic evaluation and reporting

The field of radiomics has undergone several advancements in approaches to uncovering hidden quantitative features from tumor imaging data for use in guiding clinical decision-making for cancer patients. Radiographic imaging techniques provide insight into the imaging features of tumor regions of interest (ROIs), while immunohistochemistry and sequencing techniques performed on biopsy samples yield omics data. These imaging and omics feature data can then be correlated and modeled using artificial intelligence (AI) techniques to highlight notable associations between tumor genotype and phenotype. Currently, however, the radiogenomics field lacks a unified and robust software platform capable of algorithmically analyzing imaging and omics features using modifiable parameters, detecting significant relationships among these features, and subjecting them to AI-based analysis. To address this gap, we developed ImaGene, a robust AI-based platform that uses omics and imaging features as inputs for different tumor types, performs statistical analyses of the correlations between these data types, and constructs AI models based upon significantly correlated features. It has several modifiable configuration parameters that provide users with complete control over their experiments. For each run, ImaGene produces comprehensive reports that can contribute to the construction of a novel radiogenomic knowledge base, in addition to enabling the deployment and sharing of AI models. To demonstrate the utility of ImaGene, we acquired imaging and omics datasets pertaining to Invasive Breast Cancer (IBC) and Head and Neck Squamous Cell Carcinoma (HNSCC) from public databases and analyzed them with this platform using specific parameters. In both cases, we uncovered significant associations between several imaging features and 11 genes: CRABP1, VRTN, SMTNL2, FABP1, HAND2, HAS1, C4BPA, FAM163A, DSG1, SMTNL2 and KCNJ16 for IBC, and 10 genes: CEACAM6, IGLL1, SERPINA1, NANOG, OCA2, PRLR, ACSM2B, CYP11B1, and VPREB1 for HNSCC. Overall, our software platform is capable of identifying, analyzing, and correlating important features from tumor scans, thereby providing researchers with a reliable and accurate tool for their radiogenomics experiments. We anticipate that ImaGene will become the gold standard for tumor analyses in the field of radiogenomics owing to its ease of use, flexibility, and reproducibility.

Citation Format: Shrey S. Sukhadia, Aayush Tyagi, Vivek Venkatraman, Pritam Mukherjee, Prathosh A.P., Mayur Divate, Olivier Gevaert, Shivashankar H. Nagaraj. ImaGene: A robust AI-based software platform for tumor radiogenomic evaluation and reporting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6341.

The genomic landscape of blood groups in Indigenous Australians in remote communities

Background

Methods and materials

Results

Conclusion

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Deep Learning-Based Pan-Cancer Classification Model Reveals Tissue-of-Origin Specific Gene Expression Signatures

Cancer tissue-of-origin specific biomarkers are needed for effective diagnosis, monitoring, and treatment of cancers. In this study, we analyzed transcriptomics data from 37 cancer types provided by The Cancer Genome Atlas (TCGA) to identify cancer tissue-of-origin specific gene expression signatures. We developed a deep neural network model to classify cancers based on gene expression data. The model achieved a predictive accuracy of >97% across cancer types indicating the presence of distinct cancer tissue-of-origin specific gene expression signatures. We interpreted the model using Shapley additive explanations to identify specific gene signatures that significantly contributed to cancer-type classification. We evaluated the model and the validity of gene signatures using an independent test data set from the International Cancer Genome Consortium. In conclusion, we present a robust neural network model for accurate classification of cancers based on gene expression data and also provide a list of gene signatures that are valuable for developing biomarker panels for determining cancer tissue-of-origin. These gene signatures serve as valuable biomarkers for determining tissue-of-origin for cancers of unknown primary.

RBCeq: A robust and scalable algorithm for accurate genetic blood typing

Background

While blood transfusion is an essential cornerstone of hematological care, patients requiring repetitive transfusion remain at persistent risk of alloimmunization due to the diversity of human blood group polymorphisms. Despite the promise, user friendly methods to accurately identify blood types from next-generation sequencing data are currently lacking. To address this unmet need, we have developed RBCeq, a novel genetic blood typing algorithm to accurately identify 36 blood group systems.

Methods

RBCeq can predict complex blood groups such as RH, and ABO that require identification of small indels and copy number variants. RBCeq also reports clinically significant, rare, and novel variants with potential clinical relevance that may lead to the identification of novel blood group alleles.

Findings

The RBCeq algorithm demonstrated 99·07% concordance when validated on 402 samples which included 29 antigens with serology and 9 antigens with SNP-array validation in 14 blood group systems and 59 antigens validation on manual predicted phenotype from variant call files. We have also developed a user-friendly web server that generates detailed blood typing reports with advanced visualization (https://www.rbceq.org/).

Interpretation

RBCeq will assist blood banks and immunohematology laboratories by overcoming existing methodological limitations like scalability, reproducibility, and accuracy when genotyping and phenotyping in multi-ethnic populations. This Amazon Web Services (AWS) cloud based platform has the potential to reduce pre-transfusion testing time and to increase sample processing throughput, ultimately improving quality of patient care.

Funding

This work was supported in part by Advance Queensland Research Fellowship, MRFF Genomics Health Futures Mission (76,757), and the Australian Red Cross LifeBlood. The Australian governments fund the Australian Red Cross Lifeblood for the provision of blood, blood products and services to the Australian community.

ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting

Summary

Radiographic imaging techniques provide insight into the imaging features of tumor regions of interest, while immunohistochemistry and sequencing techniques performed on biopsy samples yield omics data. Relationships between tumor genotype and phenotype can be identified from these data through traditional correlation analyses and artificial intelligence (AI) models. However, the radiogenomics community lacks a unified software platform with which to conduct such analyses in a reproducible manner. To address this gap, we developed ImaGene, a web-based platform that takes tumor omics and imaging datasets as inputs, performs correlation analysis between them, and constructs AI models. ImaGene has several modifiable configuration parameters and produces a report displaying model diagnostics. To demonstrate the utility of ImaGene, we utilized data for invasive breast carcinoma (IBC) and head and neck squamous cell carcinoma (HNSCC) and identified potential associations between imaging features and nine genes (WT1, LGI3, SP7, DSG1, ORM1, CLDN10, CST1, SMTNL2, and SLC22A31) for IBC and eight genes (NR0B1, PLA2G2A, MAL, CLDN16, PRDM14, VRTN, LRRN1, and MECOM) for HNSCC. ImaGene has the potential to become a standard platform for radiogenomic tumor analyses due to its ease of use, flexibility, and reproducibility, playing a central role in the establishment of an emerging radiogenomic knowledge base.

Availability and implementation

www.ImaGene.pgxguide.org, https://github.com/skr1/Imagene.git.

Supplementary information

Supplementary data are available at https://github.com/skr1/Imagene.git.

BGvar: A comprehensive resource for blood group immunogenetics

BACKGROUND

Blood groups form the basis of effective and safe blood transfusion. There are about 43 well-recognised human blood group systems presently known. Blood groups are molecularly determined by the presence of specific antigens on the red blood cells and are genetically determined and inherited following Mendelian principles. The lack of a comprehensive, relevant, manually compiled and genome-ready dataset of red cell antigens limited the widespread application of genomic technologies to characterise and interpret the blood group complement of an individual from genomic datasets.

MATERIALS AND METHODS

A range of public datasets was used to systematically annotate the variation compendium for its functionality and allele frequencies across global populations. Details on phenotype or relevant clinical importance were collated from reported literature evidence.

RESULTS

We have compiled the Blood Group Associated Genomic Variant Resource (BGvar), a manually curated online resource comprising all known human blood group related allelic variants including a total of 1700 International Society of Blood Transfusion approved alleles and 1706 alleles predicted and curated from literature reports. This repository includes 1682 single nucleotide variations (SNVs), 310 Insertions, Deletions (InDels) and Duplications (Copy Number Variations) and about 1360 combination mutations corresponding to 43 human blood group systems and 2 transcription factors. This compendium also encompasses gene fusion and rearrangement events occurring in human blood group genes.

CONCLUSION

To the best of our knowledge, BGvar is a comprehensive and a user-friendly resource with most relevant collation of blood group alleles in humans. BGvar is accessible online at URL: http://clingen.igib.res.in/bgvar/.

The Gene-Drug Duality: Exploring the Pharmacogenomics of Indigenous Populations

While pharmacogenomic studies have facilitated the rapid expansion of personalized medicine, the benefits of these findings have not been evenly distributed. Genomic datasets pertaining to Indigenous populations are sorely lacking, leaving members of these communities at a higher risk of adverse drug reactions (ADRs), and associated negative outcomes. Australia has one of the largest Indigenous populations in the world. Pharmacogenomic studies of these diverse Indigenous Australian populations have been hampered by a paucity of data. In this article, we discuss the history of pharmacogenomics and highlight the inequalities that must be addressed to ensure equal access to pharmacogenomic-based healthcare. We also review efforts to conduct the pharmacogenomic profiling of chronic diseases among Australian Indigenous populations and survey the impact of the lack of drug safety-related information on potential ADRs among individuals in these communities.

Unlocking capacities of viral genomics for the COVID-19 pandemic response

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.

Unlocking capacities of viral genomics for the COVID-19 pandemic response

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.

Abstract PO-036: A sophisticated bioinformatics framework for integrative study of radiomics and genomics profiles of tumors

The potential for radiomics to support oncology decision-making has grown substantially in recent years, as these scanning techniques have been found to offer unique information regarding the tumor phenotype and microenvironment that is distinct from that provided by genomic or proteomic assays. Radiomic and genomic (or proteomic) data can be correlated with one another, thereby facilitating radiogenomic efforts. Radiogenomically-informed biopsies have the potential to yield better pathological outcomes and can aid in the planning of more appropriate treatment strategies for cancer patients. However, the field lacks a unified software platform wherein radiomic and genomics/proteomic data could be brought together to conduct a variety of correlational analyses and build robust artificial intelligence models that would aid the prediction of genomic/proteomic profiles of tumors from their radiological images. We have built such a comprehensive platform that could be utilized by scientists and clinicians globally to conduct radiogenomic studies for a variety of cancer types, and further validate and deploy it in clinics to aid effective monitoring, diagnosis, and treatment of cancer patients.

Citation Format: Shrey S. Sukhadia, Shivashankar H. Nagaraj, Olivier Gevaert, Sivakumaran Theru Arumugam, Aayush Tyagi, Pritam Mukherjee, A.P. Prathosh. A sophisticated bioinformatics framework for integrative study of radiomics and genomics profiles of tumors [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-036.

Limiting Self-Renewal of the Basal Compartment by PKA Activation Induces Differentiation and Alters the Evolution of Mammary Tumors

Differentiation therapy utilizes our understanding of the hierarchy of cellular systems to pharmacologically induce a shift toward terminal commitment. While this approach has been a paradigm in treating certain hematological malignancies, efforts to translate this success to solid tumors have met with limited success. Mammary-specific activation of PKA in mouse models leads to aberrant differentiation and diminished self-renewing potential of the basal compartment, which harbors mammary repopulating cells. PKA activation results in tumors that are more benign, exhibiting reduced metastatic propensity, loss of tumor-initiating potential, and increased sensitivity to chemotherapy. Analysis of tumor histopathology revealed features of overt differentiation with papillary characteristics. Longitudinal single-cell profiling at the hyperplasia and tumor stages uncovered an altered path of tumor evolution whereby PKA curtails the emergence of aggressive subpopulations. Acting through the repression of SOX4, PKA activation promotes tumor differentiation and represents a possible adjuvant to chemotherapy for certain breast cancers.

Equitable Expanded Carrier Screening Needs Indigenous Clinical and Population Genomic Data

Expanded carrier screening (ECS) for recessive monogenic diseases requires prior knowledge of genomic variation, including DNA variants that cause disease. The composition of pathogenic variants differs greatly among human populations, but historically, research about monogenic diseases has focused mainly on people with European ancestry. By comparison, less is known about pathogenic DNA variants in people from other parts of the world. Consequently, inclusion of currently underrepresented Indigenous and other minority population groups in genomic research is essential to enable equitable outcomes in ECS and other areas of genomic medicine. Here, we discuss this issue in relation to the implementation of ECS in Australia, which is currently being evaluated as part of the national Government's Genomics Health Futures Mission. We argue that significant effort is required to build an evidence base and genomic reference data so that ECS can bring significant clinical benefit for many Aboriginal and/or Torres Strait Islander Australians. These efforts are essential steps to achieving the Australian Government's objectives and its commitment "to leveraging the benefits of genomics in the health system for all Australians." They require culturally safe, community-led research and community involvement embedded within national health and medical genomics programs to ensure that new knowledge is integrated into medicine and health services in ways that address the specific and articulated cultural and health needs of Indigenous people. Until this occurs, people who do not have European ancestry are at risk of being, in relative terms, further disadvantaged.

Comprehensive analysis of the secreted proteome of adult Necator americanus hookworms

The human hookworm Necator americanus infects more than 400 million people worldwide, contributing substantially to the poverty in these regions. Adult stage N. americanus live in the small intestine of the human host where they inject excretory/secretory (ES) products into the mucosa. ES products have been characterized at the proteome level for a number of animal hookworm species, but until now, the difficulty in obtaining sufficient live N. americanus has been an obstacle in characterizing the secretome of this important human pathogen. Herein we describe the ES proteome of N. americanus and utilize this information along with RNA Seq data to conduct the first proteogenomic analysis of a parasitic helminth, significantly improving the available genome and thereby generating a robust description of the parasite secretome. The genome annotation resulted in a revised prediction of 3,425 fewer genes than initially reported, accompanied by a significant increase in the number of exons and introns, total gene length and the percentage of the genome covered by genes. Almost 200 ES proteins were identified by LC-MS/MS with SCP/TAPS proteins, ‘hypothetical’ proteins and proteases among the most abundant families. These proteins were compared to commonly used model species of human parasitic infections, including Ancylostoma caninum, Nippostrongylus brasiliensis and Heligmosomoides polygyrus. SCP/TAPS proteins are immunogenic in nematode infections, so we expressed four of those identified in this study in recombinant form and showed that they are all recognized to varying degrees by serum antibodies from hookworm-infected subjects from a disease-endemic area of Brazil. Our findings provide valuable information on important families of proteins with both known and unknown functions that could be instrumental in host-parasite interactions, including protein families that might be key for parasite survival in the onslaught of robust immune responses, as well as vaccine and diagnostic targets.

Hookworms infect hundreds of millions of people in tropical regions of the world. Adult worms reside in the small bowel where they feed on blood, causing iron-deficiency anemia when present in large numbers and contributing substantially to the poverty in these regions. Hookworms inject excretory/secretory (ES) products into the gut tissue when they feed, and while the protein constituents of ES products have been characterized for a number of animal hookworm species, difficulty in obtaining sufficient live human hookworms has thus far precluded characterization of the secreted proteome. Herein we describe the ES proteins of the major human hookworm, Necator americanus, and utilize this information to significantly improve the available genome sequence. Almost 200 ES proteins were identified and compared to the secreted proteomes of other parasitic roundworms to provide a molecular snapshot of the host-parasite interface. We produced recombinant forms of some of the identified proteins and showed that they are all recognized to varying degrees by antibodies from hookworm-infected subjects. Our work sheds light on important families of proteins that might be key for parasite survival in the human host, and presents a dataset that can now be mined in the search for vaccine, drug and diagnostic targets.

Analysis of the F2LR3 (PAR4) Single Nucleotide Polymorphism (rs773902) in an Indigenous Australian Population

The F2RL3 gene encoding protease activated receptor 4 (PAR4) contains a single nucleotide variant, rs773902, that is functional. The resulting PAR4 variants, Thr120, and Ala120, are known to differently affect platelet reactivity to thrombin. Significant population differences in the frequency of the allele indicate it may be an important determinant in the ethnic differences that exist in thrombosis and hemostasis, and for patient outcomes to PAR antagonist anti-platelet therapies. Here we determined the frequency of rs773902 in an Indigenous Australian group comprising 467 individuals from the Tiwi Islands. These people experience high rates of renal disease that may be related to platelet and PAR4 function and are potential recipients of PAR-antagonist treatments. The rs773902 minor allele frequency (Thr120) in the Tiwi Islanders was 0.32, which is similar to European and Asian groups and substantially lower than Melanesians and some African groups. Logistic regression and allele distortion testing revealed no significant associations between the variant and several markers of renal function, as well as blood glucose and blood pressure. These findings suggest that rs773902 is not an important determinant for renal disease in this Indigenous Australian group. However, the relationships between rs773902 genotype and platelet and drug responsiveness in the Tiwi, and the allele frequency in other Indigenous Australian groups should be evaluated.

A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping

Oncogenesis and cancer can arise as a consequence of a wide range of genomic aberrations including mutations, copy number alterations, expression changes and epigenetic modifications encompassing multiple omics layers. Integrating genomic, transcriptomic, proteomic and epigenomic datasets via multi-omics analysis provides the opportunity to derive a deeper and holistic understanding of the development and progression of cancer. There are two primary approaches to integrating multi-omics data: multi-staged (focused on identifying genes driving cancer) and meta-dimensional (focused on establishing clinically relevant tumour or sample classifications). A number of ready-to-use bioinformatics tools are available to perform both multi-staged and meta-dimensional integration of multi-omics data. In this study, we compared nine different integration tools using real and simulated cancer datasets. The performance of the multi-staged integration tools were assessed at the gene, function and pathway levels, while meta-dimensional integration tools were assessed based on the sample classification performance. Additionally, we discuss the influence of factors such as data representation, sample size, signal and noise on multi-omics data integration. Our results provide current and much needed guidance regarding selection and use of the most appropriate and best performing multi-omics integration tools.

Targeting Epithelial Mesenchymal Plasticity in Pancreatic Cancer: A Compendium of Preclinical Discovery in a Heterogeneous Disease

Pancreatic Ductal Adenocarcinoma (PDAC) is a particularly insidious and aggressive disease that causes significant mortality worldwide. The direct correlation between PDAC incidence, disease progression, and mortality highlights the critical need to understand the mechanisms by which PDAC cells rapidly progress to drive metastatic disease in order to identify actionable vulnerabilities. One such proposed vulnerability is epithelial mesenchymal plasticity (EMP), a process whereby neoplastic epithelial cells delaminate from their neighbours, either collectively or individually, allowing for their subsequent invasion into host tissue. This disruption of tissue homeostasis, particularly in PDAC, further promotes cellular transformation by inducing inflammatory interactions with the stromal compartment, which in turn contributes to intratumoural heterogeneity. This review describes the role of EMP in PDAC, and the preclinical target discovery that has been conducted to identify the molecular regulators and effectors of this EMP program. While inhibition of individual targets may provide therapeutic insights, a single ‘master-key’ remains elusive, making their collective interactions of greater importance in controlling the behaviours’ of heterogeneous tumour cell populations. Much work has been undertaken to understand key transcriptional programs that drive EMP in certain contexts, however, a collaborative appreciation for the subtle, context-dependent programs governing EMP regulation is needed in order to design therapeutic strategies to curb PDAC mortality.

Multi-Omics Characterization of the Spontaneous Mesenchymal-Epithelial Transition in the PMC42 Breast Cancer Cell Lines

Epithelial–mesenchymal plasticity (EMP), encompassing epithelial–mesenchymal transition (EMT) and mesenchymal–epithelial transition (MET), are considered critical events for cancer metastasis. We investigated chromosomal heterogeneity and chromosomal instability (CIN) profiles of two sister PMC42 breast cancer (BC) cell lines to assess the relationship between their karyotypes and EMP phenotypic plasticity. Karyotyping by GTG banding and exome sequencing were aligned with SWATH quantitative proteomics and existing RNA-sequencing data from the two PMC42 cell lines; the mesenchymal, parental PMC42-ET cell line and the spontaneously epithelially shifted PMC42-LA daughter cell line. These morphologically distinct PMC42 cell lines were also compared with five other BC cell lines (MDA-MB-231, SUM-159, T47D, MCF-7 and MDA-MB-468) for their expression of EMP and cell surface markers, and stemness and metabolic profiles. The findings suggest that the epithelially shifted cell line has a significantly altered ploidy of chromosomes 3 and 13, which is reflected in their transcriptomic and proteomic expression profiles. Loss of the TGFβR2 gene from chromosome 3 in the epithelial daughter cell line inhibits its EMT induction by TGF-β stimulus. Thus, integrative ‘omics’ characterization established that the PMC42 system is a relevant MET model and provides insights into the regulation of phenotypic plasticity in breast cancer.

Interrogation of Phenotypic Plasticity between Epithelial and Mesenchymal States in Breast Cancer

Dynamic interconversions between transitional epithelial and mesenchymal states underpin the epithelial mesenchymal plasticity (EMP) seen in some carcinoma cell systems. We have delineated epithelial and mesenchymal subpopulations existing within the PMC42-LA breast cancer cell line by their EpCAM expression. These purified but phenotypically plastic states, EpCAMHigh (epithelial) and EpCAMLow (mesenchymal), have the ability to regain the phenotypic equilibrium of the parental population (i.e., 80% epithelial and 20% mesenchymal) over time, although the rate of reversion in the mesenchymal direction (epithelial-mesenchymal transition; EMT) is higher than that in the epithelial direction (mesenchymal-epithelial transition; MET). Single-cell clonal propagation was implemented to delineate the molecular and cellular features of this intrinsic heterogeneity with respect to EMP flux. The dynamics of the phenotypic proportions of epithelial and mesenchymal states in single-cell generated clones revealed clonal diversity and intrinsic plasticity. Single cell-derived clonal progenies displayed differences in their functional attributes of proliferation, stemness marker (CD44/CD24), migration, invasion and chemo-sensitivity. Interrogation of genomic copy number variations (CNV) with whole exome sequencing (WES) in the context of chromosome count from metaphase spread indicated that chromosomal instability was not influential in driving intrinsic phenotypic plasticity. Overall, these findings reveal the stochastic nature of both the epithelial and mesenchymal subpopulations, and the single cell-derived clones for differential functional attributes.

Whole-genome characterization of chemoresistant ovarian cancer

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

Whole-genome characterization of chemoresistant ovarian cancer

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

PGTools: A Software Suite for Proteogenomic Data Analysis and Visualization

We describe PGTools, an open source software suite for analysis and visualization of proteogenomic data. PGTools comprises applications, libraries, customized databases, and visualization tools for analysis of mass-spectrometry data using combined proteomic and genomic backgrounds. A single command is sufficient to search databases, calculate false discovery rates, group and annotate proteins, generate peptide databases from RNA-Seq transcripts, identify altered proteins associated with cancer, and visualize genome scale peptide data sets using sophisticated visualization tools. We experimentally confirm a subset of proteogenomic peptides in human PANC-1 cells and demonstrate the utility of PGTools using a colorectal cancer data set that led to the identification of 203 novel protein coding regions missed by conventional proteomic approaches. PGTools should be equally useful for individual proteogenomic investigations as well as international initiatives such as chromosome-centric Human Proteome Project (C-HPP). PGTools is available at http://qcmg.org/bioinformatics/PGTools.

Cloning and tissue distribution of novel splice variants of the ovine ghrelin gene

Background

The ghrelin axis is involved in the regulation of metabolism, energy balance, and the immune, cardiovascular and reproductive systems. The manipulation of this axis has potential for improving economically valuable traits in production animals, and polymorphisms in the ghrelin (GHRL) and ghrelin receptor (GHSR) genes have been associated with growth and carcass traits. Here we investigate the structure and expression of the ghrelin gene (GHRL) in sheep, Ovis aries.

Results

We identify two ghrelin mRNA isoforms, which we have designated Δex2 preproghrelin and Δex2,3 preproghrelin. Expression of Δex2,3 preproghrelin is likely to be restricted to ruminants, and would encode truncated ghrelin and a novel C-terminal peptide. Both Δex2 preproghrelin and canonical preproghrelin mRNA isoforms were expressed in a range of tissues. Expression of the Δex2,3 preproghrelin isoform, however, was restricted to white blood cells (WBC; where the wild-type preproghrelin isoform is not co-expressed), and gastrointestinal tissues. Expression of Δex2 preproghrelin and Δex2,3 preproghrelin mRNA was elevated in white blood cells in response to parasitic worm (helminth) infection in genetically susceptible sheep, but not in resistant sheep.

Conclusions

The restricted expression of the novel preproghrelin variants and their distinct WBC expression pattern during parasite infection may indicate a novel link between the ghrelin axis and metabolic and immune function in ruminants.

Proteogenomic analysis of Bradyrhizobium japonicum USDA110 using GenoSuite, an automated multi-algorithmic pipeline

We present GenoSuite, an integrated proteogenomic pipeline to validate, refine and discover protein coding genes using high-throughput mass spectrometry (MS) data from prokaryotes. To demonstrate the effectiveness of GenoSuite, we analyzed proteomics data of Bradyrhizobium japonicum (USDA110), a model organism to study agriculturally important rhizobium-legume symbiosis. Our analysis confirmed 31% of known genes, refined 49 gene models for their translation initiation site (TIS) and discovered 59 novel protein coding genes. Notably, a novel protein which redefined the boundary of a crucial cytochrome P450 system related operon was discovered, known to be highly expressed in the anaerobic symbiotic bacteroids. A focused analysis on N-terminally acetylated peptides indicated downstream TIS for gene blr0594. Finally, ortho-proteogenomic analysis revealed three novel genes in recently sequenced B. japonicum USDA6(T) genome. The discovery of large number of missing genes and correction of gene models have expanded the proteomic landscape of B. japonicum and presents an unparalleled utility of proteogenomic analyses and versatility of GenoSuite for annotating prokaryotic genomes including pathogens.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors

Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.

Molecular cloning and characterisation of ovine dual oxidase 2

The dual oxidases (DUOX1 and DUOX2) are NADPH-dependent hydrogen peroxide-producing enzymes that are reported to function in a physiological capacity and as a component of the mucosal immune response. We have previously reported increased expression of the DUOX2 gene in the gut mucosa of sheep in response to gastrointestinal nematode (GIN) challenge. In this paper, we report the cloning of the full-length ovine DUOX2 transcript, using a PCR based strategy. The ovine DUOX2 transcript includes an ORF of 4644 bases, and encodes a protein with 97% identity to the bovine sequence. We also cloned a fragment of DUOX1 (encompassing nucleotides 2692-2829), and the proximal promoter sequence of DUOX2. Through analysis of sequence data we have confirmed that DUOX1 and DUOX2 are co-located in a head to tail arrangement conserved across many species. Alignment of the sequences to the ovine genome predicts a location of this gene cluster on ovine chromosome 7. We quantified the expression of ovine DUOX1 and DUOX2 transcripts in 24 different sheep tissues, and discovered tissue specific expression signatures. DUOX2 was found to be most highly expressed in tissues of the gastrointestinal tract, while expression of DUOX1 predominated in the bladder. Rapid amplification of cDNA ends (RACE) analysis identified the existence of multiple 5' UTR variants in DUOX2, ranging in size from 32 to 242 nucleotides, with 3 distinct transcribed regions. Real time PCR quantification of the DUOX2 UTR variants revealed that these were differentially expressed between tissues, and at various stages of the response to GIN parasite infection. The collective evidence suggested a complex regulation of DUOX2, prompting a bioinformatic analysis of the proximal promoter regions of ovine DUOX2 to identify potential transcription factor binding sites (TFBS) that may explain the differences in the observed expression of the transcript variants of DUOX2. Possible transcription factor families that may regulate this process were identified as Kruppel-like factors (KLF), ETS-factors, erythroid growth receptor factors (EGRF) and myogenic differentiation factors (MYOD).

Chronic exposure to anabolic steroids induces the muscle expression of oxytocin and a more than fiftyfold increase in circulating oxytocin in cattle

Molecular mechanisms in skeletal muscle associated with anabolic steroid treatment of cattle are unclear and we aimed to characterize transcriptional changes. Cattle were chronically exposed (68 ± 20 days) to a steroid hormone implant containing 200 mg trenbolone acetate and 20 mg estradiol (Revalor-H). Biopsy samples from 48 cattle (half treated) from longissimus dorsi (LD) muscle under local anesthesia were collected. Gene expression levels were profiled by microarray, covering 16,944 unique bovine genes: 121 genes were differentially expressed (DE) due to the implant (99.99% posterior probability of not being false positives). Among DE genes, a decrease in expression of a number of fat metabolism-associated genes, likely reflecting the lipid storage activity of intramuscular adipocytes, was observed. The expression of IGF1 and genes related to the extracellular matrix, slow twitch fibers, and cell cycle (including SOX8, a satellite cell marker) was increased in the treated muscle. Unexpectedly, a very large 21- (microarray) to 97 (real time quantitative PCR)-fold higher expression of the mRNA encoding the neuropeptide hormone oxytocin was observed in treated muscle. We also observed an ∼50-fold higher level of circulating oxytocin in the plasma of treated animals at the time of biopsy. Using a coexpression network strategy OXTR was identified as more likely than IGF1R to be a major mediator of the muscle response to Revalor-H. A re-investigation of in vivo cattle LD muscle samples during early to mid-fetal development identified a >128-fold increased expression of OXT, coincident with myofiber differentiation and fusion. We propose that oxytocin may be involved in mediating the anabolic effects of Revalor-H treatment.

A single nucleotide polymorphism-derived regulatory gene network underlying puberty in 2 tropical breeds of beef cattle

Harsh tropical environments impose serious challenges on poorly adapted species. In beef cattle, tropical adaptation in the form of temperature and disease resistance, coupled with acclimatization to seasonal and limited forage, comes at a cost to production efficiency. Prominent among these costs is delayed onset of puberty, a challenging phenotype to manipulate through traditional breeding mechanisms. Recently, system biology approaches, including gene networks, have been applied to the genetic dissection of complex phenotypes. We aimed at developing and studying gene networks underlying cattle puberty. Our starting material comprises the association results of ~50,000 SNP on 22 traits, including age at puberty, and 2 cattle breed populations: Brahman (n = 843) and Tropical Composite (n = 866). We defined age at puberty as the age at first corpus luteum (AGECL). By capturing the genes harboring mutations minimally associated (P < 0.05) to AGECL or to a set of traits related with AGECL, we derived a gene network for each breed separately and a third network for the combined data set. At the intersection of the 3 networks, we identified candidate genes and pathways that were common to both breeds. Resulting from these analyses, we identified an enrichment of genes involved in axon guidance, cell adhesion, ErbB signaling, and glutamate activity, pathways that are known to affect pulsatile release of GnRH, which is necessary for the onset of puberty. Furthermore, we employed network connectivity and centrality parameters along with a regulatory impact factor metric to identify the key transcription factors (TF) responsible for the molecular regulation of puberty. As a novel finding, we report 5 TF (HIVEP3, TOX, EYA1, NCOA2, and ZFHX4) located in the network intersecting both breeds and interacting with other TF, forming a regulatory network that harmonizes with the recent literature of puberty. Finally, we support our network predictions with evidence derived from gene expression in hypothalamic tissue of adult cows.

The evolution of tropical adaptation: comparing taurine and zebu cattle

Beef cattle breeds consist of three major genetic subdivisions. The taurine group is adapted to temperate environments, and the zebu and Sanga groups are both adapted to tropical environments. With the advent of genotyping and sequencing technologies in agriculture, genome-wide exploration of the genetic basis for the differences in tropical adaptation has only just become possible. In this study, approximately 9000 single nucleotide polymorphism markers were genotyped on 317 animals of a selection of taurine, zebu, and composite breeds to characterize any systematic differences between these groups. We identified 91 intra-breed-class markers; 78 were polymorphic only within the zebu animals, while 13 were polymorphic only in the taurine animals. There were no fixed differences (fixed for alternate alleles between the two breed types) between zebu and taurine animals. We found 14 regions with significantly different allele frequencies between zebu and taurine animals indicative of variable selection pressure or genetic drift. We also found 12 independent regions of differential extended haplotype homozygosity (EHH), indicative of recent selection or rapid fixation of the alternate allele within a short period of time in one of the two breed classes. A preliminary functional genomics analysis of these regions pointed towards signatures of tropical attributes including keratins, heat-shock proteins and heat resistance genes. We anticipate this investigation to be a stepping-stone for future studies to identify genomic regions specific to the two cattle groups, and to subsequently assist in the discrimination between temperate and tropically adapted cattle.

Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle

BACKGROUND

Gene regulation by transcription factors (TF) is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information.

RESULTS

We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs). We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs) and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively.

CONCLUSION

The pivotal implication of our research is two-fold: (1) there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2) this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

The interplay between evolution, regulation and tissue specificity in the Human Hereditary Diseasome

Background

Human disease genes can be distinguished from essential (embryonically lethal) and non-disease genes using gene attributes. Such attributes include gene age, tissue specificity of expression, regulatory capacity, sequence length, rate of sequence variation and capacity for interaction. The resulting information has been used to inform data mining approaches seeking to identify novel disease genes. Given the dynamic nature of this field and the rapid rise in relevant information, we have chosen to perform a single integrated mining approach to explore relationships among gene attributes and thereby characterise evolutionary trends associated with disease genes.

Results

All against all cross comparison of 2,522 disease gene attributes revealed significant relationships existed between the age, disease-association and expression pattern of genes and the tissues within which they are expressed. We found that the over-representation of disease genes among old genes holds for tissue-specific genes, but the correlation between age and disease association vanished when conditioning on tissue-specificity. Of the 32 tissues studied, the genes expressed in pancreas are on average older than the genes expressed in any other tissue, while the testis expressed the lowest proportion of old genes. Following a focussed analysis on the impact of regulatory apparatus on evolution of disease genes, we show that regulators, comprising transcription factors and post-translation modified proteins, are over-represented among ancient disease genes. In addition, we show that the proportion of regulator genes is affected by gene age among disease genes and by tissue-specificity among non-disease genes. Finally, using 55,606 true positive gene interaction data, we find that old disease genes interacts with other old disease genes and interacting new genes interacts with genes originating from higher phylostrata.

Conclusion

This study supports the non-random nature of the human diseasome. We have identified a variety of distinct features and correlations to other molecular attributes that can be used to distinguish the set of disease causing genes. This was achieved by harnessing the power of mining large scale datasets from OMIM and other databases. Ultimately such knowledge may contribute to the identification of novel human disease genes and an enhanced understanding of human biology.

Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data

MOTIVATION

Although transcription factors (TF) play a central regulatory role, their detection from expression data is limited due to their low, and often sparse, expression. In order to fill this gap, we propose a regulatory impact factor (RIF) metric to identify critical TF from gene expression data.

RESULTS

To substantiate the generality of RIF, we explore a set of experiments spanning a wide range of scenarios including breast cancer survival, fat, gonads and sex differentiation. We show that the strength of RIF lies in its ability to simultaneously integrate three sources of information into a single measure: (i) the change in correlation existing between the TF and the differentially expressed (DE) genes; (ii) the amount of differential expression of DE genes; and (iii) the abundance of DE genes. As a result, RIF analysis assigns an extreme score to those TF that are consistently most differentially co-expressed with the highly abundant and highly DE genes (RIF1), and to those TF with the most altered ability to predict the abundance of DE genes (RIF2). We show that RIF analysis alone recovers well-known experimentally validated TF for the processes studied. The TF identified confirm the importance of PPAR signaling in adipose development and the importance of transduction of estrogen signals in breast cancer survival and sexual differentiation. We argue that RIF has universal applicability, and advocate its use as a promising hypotheses generating tool for the systematic identification of novel TF not yet documented as critical.

Needles in the EST haystack: large-scale identification and analysis of excretory-secretory (ES) proteins in parasitic nematodes using expressed sequence tags (ESTs)

Background

Parasitic nematodes of humans, other animals and plants continue to impose a significant public health and economic burden worldwide, due to the diseases they cause. Promising antiparasitic drug and vaccine candidates have been discovered from excreted or secreted (ES) proteins released from the parasite and exposed to the immune system of the host. Mining the entire expressed sequence tag (EST) data available from parasitic nematodes represents an approach to discover such ES targets.

Methods and Findings

In this study, we predicted, using EST2Secretome, a novel, high-throughput, computational workflow system, 4,710 ES proteins from 452,134 ESTs derived from 39 different species of nematodes, parasitic in animals (including humans) or plants. In total, 2,632, 786, and 1,292 ES proteins were predicted for animal-, human-, and plant-parasitic nematodes. Subsequently, we systematically analysed ES proteins using computational methods. Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases. Of the C. elegans homologues, 267 had strong “loss-of-function” phenotypes by RNA interference (RNAi) in this nematode. We could functionally classify 1,948 (41.3%) sequences using the Gene Ontology (GO) terms, establish pathway associations for 573 (12.2%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG), and identify protein interaction partners for 1,774 (37.6%) molecules. We also mapped 758 (16.1%) proteins to protein domains including the nematode-specific protein family “transthyretin-like” and “chromadorea ALT,” considered as vaccine candidates against filariasis in humans.

Conclusions

We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes. This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control.

Excretory-secretory (ES) proteins are an important class of proteins in many organisms, spanning from bacteria to human beings, and are potential drug targets for several diseases. In this study, we first developed a software platform, EST2Secretome, comprised of carefully selected computational tools to identify and analyse ES proteins from expressed sequence tags (ESTs). By employing EST2Secretome, we analysed 4,710 ES proteins derived from 0.5 million ESTs for 39 economically important and disease-causing parasites from the phylum Nematoda. Several known and novel ES proteins that were either parasite- or nematode-specific were discovered, focussing on those that are either absent from or very divergent from similar molecules in their animal or plant hosts. In addition, we found many nematode-specific protein families of domains “transthyretin-like” and “chromadorea ALT,” considered vaccine candidates for filariasis in humans. We report numerous C. elegans homologues with loss-of-function RNAi phenotypes essential for parasite survival and therefore potential targets for parasite intervention. Overall, by developing freely available software to analyse large-scale EST data, we enabled researchers working on parasites for neglected tropical diseases to select specific genes and/or proteins to carry out directed functional assays for demystifying the molecular complexities of host–parasite interactions in a cell.

Proteomics analysis of the excretory/secretory component of the blood-feeding stage of the hookworm, Ancylostoma caninum

Hookworms are blood-feeding intestinal parasites of mammalian hosts and are one of the major human ailments affecting approximately 600 million people worldwide. These parasites form an intimate association with the host and are able to avoid vigorous immune responses in many ways including skewing of the response phenotype to promote parasite survival and longevity. The primary interface between the parasite and the host is the excretory/secretory component, a complex mixture of proteins, carbohydrates, and lipids secreted from the surface or oral openings of the parasite. The composition of this complex mixture is for the most part unknown but is likely to contain proteins important for the parasitic lifestyle and hence suitable as drug or vaccine targets. Using a strategy combining the traditional technology of one-dimensional SDS-PAGE and the newer fractionation technology of OFFGEL electrophoresis we identified 105 proteins from the excretory/secretory products of the blood-feeding stage of the dog hookworm, Ancylostoma caninum. Highly represented among the identified proteins were lectins, including three C-type lectins and three beta-galactoside-specific S-type galectins, as well as a number of proteases belonging to the three major classes found in nematodes, aspartic, cysteine, and metalloproteases. Interestingly 28% of the identified proteins were homologous to activation-associated secreted proteins, a family of cysteine-rich secreted proteins belonging to the sterol carrier protein/Tpx-1/Ag5/PR-1/Sc-7 (TAPS) superfamily. Thirty-four of these proteins were identified suggesting an important role in host-parasite interactions. Other protein families identified included hyaluronidases, lysozyme-like proteins, and transthyretin-like proteins. This work identified a suite of proteins important for the parasitic lifestyle and provides new insight into the biology of hookworm infection.

High-throughput functional annotation and data mining with the Blast2GO suite

Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.

A transcriptomic analysis of the adult stage of the bovine lungworm, Dictyocaulus viviparus

Background

Lungworms of the genus Dictyocaulus (family Dictyocaulidae) are parasitic nematodes of major economic importance. They cause pathological effects and clinical disease in various ruminant hosts, particularly in young animals. Dictyocaulus viviparus, called the bovine lungworm, is a major pathogen of cattle, with severe infections being fatal. In this study, we provide first insights into the transcriptome of the adult stage of D. viviparus through the analysis of expressed sequence tags (ESTs).

Results

Using our EST analysis pipeline, we estimate that the present dataset of 4436 ESTs is derived from 2258 genes based on cluster and comparative genomic analyses of the ESTs. Of the 2258 representative ESTs, 1159 (51.3%) had homologues in the free-living nematode C. elegans, 1174 (51.9%) in parasitic nematodes, 827 (36.6%) in organisms other than nematodes, and 863 (38%) had no significant match to any sequence in the current databases. Of the C. elegans homologues, 569 had observed 'non-wildtype' RNAi phenotypes, including embryonic lethality, maternal sterility, sterility in progeny, larval arrest and slow growth. We could functionally classify 776 (35%) sequences using the Gene Ontologies (GO) and established pathway associations to 696 (31%) sequences in Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, we predicted 85 secreted proteins which could represent potential candidates for developing novel anthelmintics or vaccines.

Conclusion

The bioinformatic analyses of ESTs data for D. viviparus has elucidated sets of relatively conserved and potentially novel genes. The genes discovered in this study should assist research toward a better understanding of the basic molecular biology of D. viviparus, which could lead, in the longer term, to novel intervention strategies. The characterization of the D. viviparus transcriptome also provides a foundation for whole genome sequence analysis and future comparative transcriptomic analyses.

Gender-enriched transcripts in Haemonchus contortus--predicted functions and genetic interactions based on comparative analyses with Caenorhabditis elegans

In the present study, a bioinformatic-microarray approach was employed for the analysis of selected expressed sequence tags (ESTs) from Haemonchus contortus, a key parasitic nematode of small ruminants. Following a bioinformatic analysis of EST data using a semiautomated pipeline, 1885 representative ESTs (rESTs) were selected, to which oligonucleotides (three per EST) were designed and spotted on to a microarray. This microarray was hybridized with cyanine-dye labelled cRNA probes synthesized from RNA from female or male adults of H. contortus. Differential hybridisation was displayed for 301 of the 1885 rESTs ( approximately 16%). Of these, 165 (55%) had significantly greater signal intensities for female cRNA and 136 (45%) for male cRNA. Of these, 113 with increased signals in female or male H. contortus had homologues in Caenorhabditis elegans, predicted to function in metabolism, information storage and processing, cellular processes and signalling, and embryonic and/or larval development. Of the rESTs with no known homologues in C. elegans, 24 ( approximately 40%) had homologues in other nematodes, four had homologues in various other organisms and 30 (52%) had no homology to any sequence in current gene databases. A genetic interaction network was predicted for the C. elegans orthologues of the gender-enriched H. contortus genes, and a focused analysis of a subset revealed a tight network of molecules involved in amino acid, carbohydrate or lipid transport and metabolism, energy production and conversion, translation, ribosomal structure and biogenesis and, importantly, those associated with meiosis and/or mitosis in the germline during oogenesis or spermatogenesis. This study provides a foundation for the molecular, biochemical and functional exploration of selected molecules with differential transcription profiles in H. contortus, for further microarray analyses of transcription in different developmental stages of H. contortus, and for an extended functional analysis once the full genome sequence of this nematode is known.

ESTExplorer: an expressed sequence tag (EST) assembly and annotation platform

The analysis of expressed sequence tag (EST) datasets offers a rapid and cost-effective approach to elucidate the transcriptome of an organism, but requiring several computational methods for assembly and annotation. ESTExplorer is a comprehensive workflow system for EST data management and analysis. The pipeline uses a ‘distributed control approach’ in which the most appropriate bioinformatics tools are implemented over different dedicated processors. Species-specific repeat masking and conceptual translation are in-built. ESTExplorer accepts a set of ESTs in FASTA format which can be analysed using programs selected by the user. After pre-processing and assembly, the dataset is annotated at the nucleotide and protein levels, following conceptual translation. Users may optionally provide ESTExplorer with assembled contigs for annotation purposes. Functionally annotated contigs/ESTs can be analysed individually. The overall outputs are gene ontologies, protein functional identifications in terms of mapping to protein domains and metabolic pathways. ESTExplorer has been applied successfully to annotate large EST datasets from parasitic nematodes and to identify novel genes as potential targets for parasite intervention. ESTExplorer runs on a Linux cluster and is freely available for the academic community at http://estexplorer.biolinfo.org.