Genomic Data Research Articles

CardioGraph: a platform to study variations associated with familiar cardiopathies

BackgroundFamiliar cardiopathies are genetic disorders that affect the heart. Cardiologists face a significant problem when treating patients suffering from these disorders: most DNA variations are novel (i.e., they have not been classified before). To facilitate the analysis of novel variations, we present CardioGraph, a platform specially designed to support the analysis of novel variations and help determine whether they are relevant for diagnosis. To do this, CardioGraph identifies and annotates the consequence of variations and provides contextual information regarding which heart structures, pathways, and biological processes are potentially affected by those variations.MethodsWe conducted our work through three steps. First, we define a data model to support the representation of the heterogeneous information. Second, we instantiate this data model to integrate and represent all the genomics knowledge available for familiar cardiopathies. In this step, we consider genomic data sources and the scientific literature. Third, the design and implementation of the CardioGraph platform. A three-tier structure was used: the database, the backend, and the frontend.ResultsThree main results were obtained: the data model, the knowledge base generated with the instantiation of the data model, and the platform itself. The platform code has been included as supplemental material in this manuscript. Besides, an instance is publicly available in the following link: https://genomics-hub.pros.dsic.upv.es:3090.ConclusionCardioGraph is a platform that supports the analysis of novel variations. Future work will expand the body of knowledge about familiar cardiopathies and include new information about hotspots, functional studies, and previously reported variations.

Efficient Storage and Analysis of Genomic Data: A k-mer Frequency Mapping and Image Representation Method.

k-mer frequencies are crucial for understanding DNA sequence patterns and structure, with applications in motif discovery, genome classification, and short read assembly. However, the exponential increase in the dimension of frequency tables with increasing k-mer length poses storage challenges. In this study, we present a novel method for compressing k-mer data without information loss, aiming to optimize storage and analysis processes. We employed Chaos Game Representation (CGR) to map k-mers to coordinates and used these components to generate raster images of k-mers. The CGR maps were partitioned and labeled based on substrings, with each substring mapped to a subframe, creating a fractal-like structure. The entire k-mer frequency set of each genomic sequence was represented as a single image, with each pixel corresponding to a specific k-mer and its occurrence. This approach reduced file size by up to 16-fold compared to plain text and 3-fold compared to binary format. Furthermore, we demonstrated the feasibility of performing alignment-free similarity analyses on images derived from k-mer frequencies of whole genome sequences from 14 plant species. Our results highlight the potential of this method as a fast and efficient tool for accessing, processing, and analyzing large biological sequence datasets, enabling the retrieval of k-mer frequencies and image reconstruction.

Allometric scaling of somatic mutation and epimutation rates in trees.

How long-lived trees escape "mutational meltdown" despite centuries of continuous growth remains puzzling. Here we integrate recent studies to show that the yearly rate of somatic mutations and epimutations (μY) scales inversely with generation time (G), and follows the same allometric power law found in mammals (μY∝G-1). Deeper insights into the scaling function may permit predictions of somatic (epi)mutation rates from life-history traits without the need for genomic data.

Genomic Data Privacy and the Right to Science: Issues of Balance

The paper examines the confidentiality of genomic data. According to the author, genomic data is a special concept in the field of personal data and requires increased regulatory guarantees of legal protection and safeguards. In addition, the author considers the issue of the grounds for disclosure and use of this type of information. According to the researcher, this is possible only if there is a public interest in conducting scientific research that contributes to the implementation of the health function by the state. The right to science, enshrined in the Universal Declaration of Human Rights of 1948, can serve as a regulatory basis for this. The author notes that this right has not yet been established at the level of national legislation, which significantly complicates its understanding and definition of restrictions in its implementation. The paper also emphasizes the uniqueness of genomic information, which is characterized by features of identifiability and relative danger. These features are specified by the author in terms of the purpose and scope of the use of genetic data, their informational content, as well as the degree of their influence on the rights of the relevant person. In conclusion, the author puts forward am idea of one best way to balance the right to science and genomic data privacy, through which it will be possible to ensure both effective legal protection and a stable course of scientific evolution and progress.

Genome-based discovery of pachysiphine synthases in Tabernaemontana elegans.

Plant-specialized metabolism represents an inexhaustible source of active molecules, some of which have been used in human health for decades. Among these, monoterpene indole alkaloids (MIAs) include a wide range of valuable compounds with anticancer, antihypertensive, or neuroactive properties. This is particularly the case for the pachysiphine derivatives which show interesting antitumor and anti-Alzheimer activities but accumulate at very low levels in several Tabernaemontana species. Unfortunately, genome data in Tabernaemontanaceae are lacking and knowledge on the biogenesis of pachysiphine-related MIAs in planta remains scarce, limiting the prospects for the biotechnological supply of many pachysiphine-derived biopharmaceuticals. Here, we report a raw version of the toad tree (Tabernaemontana elegans) genome sequence. These new genomic resources led to the identification and characterization of a couple of genes encoding cytochrome P450 with pachysiphine synthase activity. Our phylogenomic and docking analyses highlight the different evolutionary processes that have been recruited to epoxidize the pachysiphine precursor tabersonine at a specific position and in a dedicated orientation, thus enriching our understanding of the diversification and speciation of the MIA metabolism in plants. These gene discoveries also allowed us to engineer the synthesis of MIAs in yeast through the combinatorial association of metabolic enzymes resulting in the tailor-made synthesis of non-natural MIAs. Overall, this work represents a step forward for the future supply of pachysiphine-derived drugs by microbial cell factories.

Parameter Estimation of Host Genomic and Gut Microbiota Contribution to Growth and Feed Efficiency Traits in Meat Rabbits.

Rabbits can efficiently utilize plant fibers that are indigestible to humans, and hence may contribute to the alleviation of feed-food competition. Therefore, it is economically and ecologically important to genetically improve the growth performance and feed efficiency of meat rabbits. In this study, we combined pedigree, genomic, and gut microbiota data to estimate genetic and microbial parameters for nine growth and feed efficiency traits of 739 New Zealand White rabbits, including body weight (BW) at 35 (BW35), 70 (BW70), and 84 (BW84) days of age, and average daily gain (ADG), feed conversion ratio (FCR), and residual feed intake (RFI) within two age intervals of 35-70 days (ADG70, FCR70, and RFI70) and 35-84 days (ADG84, FCR84, and RFI84). Based on single-step genomic best linear unbiased prediction, three BW traits and two ADG traits had the high estimates (±standard error, SE) of heritability, ranging from 0.44 ± 0.13 of BW35 to 0.66 ± 0.08 of BW70. Moderate heritabilities were observed for RFI70 (0.22 ± 0.07) and RFI84 (0.29 ± 0.07), whereas the estimates did not significantly deviate from zero for the two FCR traits. There was moderate positive genetic correlation (±SE) between BW70 and ADG70 (0.579 ± 0.086), but BW70 did not correlate with RFI70. Based on microbial best linear unbiased prediction, the estimates of microbiability did not significantly deviate from zero for any trait. Based on the combined use of genomic and gut microbiota data, the parameters obtained in this study could help us to implement efficient breeding schemes in meat rabbits.

Study on sentinel hosts for surveillance of future COVID-19-like outbreaks

The spread of SARS-CoV-2 to animals has the potential to evolve independently. In this study, we distinguished several sentinel animal species and genera for monitoring the re-emergence of COVID-19 or the new outbreak of COVID-19-like disease. We analyzed SARS-CoV-2 genomic data from human and nonhuman mammals in the taxonomic hierarchies of species, genus, family and order of their host. We find that SARS-CoV-2 carried by domestic dog (Canis lupus familiaris), domestic cat (Felis catus), mink (Neovison vison), and white-tailed deer (Odocoileus virginianus) cluster closely to human-origin viruses and show no differences in the majority of amino acids, but have the most positively selected sites and should be monitored to prevent the re-emergence of COVID-19 caused by novel variants of SARS-CoV-2. Viruses from the genera Panthera (especially lion (Panthera leo)), Manis and Rhinolophus differ significantly from human-origin viruses, and long-term surveillance should be undertaken to prevent the future COVID-19-like outbreaks. Investigation of the variation dynamics of sites 142, 501, 655, 681 and 950 within the S protein may be necessary to predict the novel animal SARS-CoV-2 variants.

Genetic structure and common ancestry expose the dingo-dog hybrid myth

Abstract The evolutionary history of canids has been shown to be complex, with hybridization and domestication confounding our understanding of speciation among various canid lineages. The dingo is a recent canid lineage that was completely isolated from other canids for over 5000 years on the Australian mainland, but the introduction of domestic dogs in 1788 has placed doubt on its independence, with recent studies highlighting hybridization between dingoes and domestic dogs. Using genomic single nucleotide polymorphism data from 434 Australian canid samples, we explicitly test for introgression between closely related canid groups and dingoes. We found no evidence of introgression between dingoes and domestic dogs and show that previous work has likely mischaracterized shared ancestral genetic variation as evidence for hybridization. Further, New Guinea Singing Dogs are the only canid group that significantly shared genetic variation with dingoes, which fits with our understanding of previous phylogenetic analyses. Despite more recent sympatric distributions with dogs, dingoes have likely maintained their independence since their arrival in Australia, even in areas with high lethal control, indicating that their evolutionary trajectory is currently being conserved. The future conservation of the dingo lineage will require policies that promote coexistence pathways between humans and dingoes that protect rangeland systems and the dingoes’ evolutionary future.

Leveraging the variational Bayes autoencoder for survival analysis

Survival analysis in medical research has witnessed a growing interest in applying deep learning techniques to model complex, high-dimensional, heterogeneous, incomplete, and censored data. Current methods make assumptions about the relations between data that may not be valid in practice. Therefore, we introduce SAVAE (Survival Analysis Variational Autoencoder). SAVAE, based on Variational Autoencoders, contributes significantly to the field by introducing a tailored Evidence Lower BOund formulation, supporting various parametric distributions for covariates and survival time (if the log-likelihood is differentiable). It offers a general method that demonstrates robustness and stability through different experiments. Our proposal effectively estimates time-to-event, accounting for censoring, covariate interactions, and time-varying risk associations. We validate our model in diverse datasets, including genomic, clinical, and demographic tabular data, with varying levels of censoring. This approach demonstrates competitive performance compared to state-of-the-art techniques, as assessed by the Concordance Index and the Integrated Brier Score. SAVAE also offers an interpretable model that parametrically models covariates and time. Moreover, its generative architecture facilitates further applications such as clustering, data imputation, and synthetic patient data generation through latent space inference from survival data. This approach fosters data sharing and collaboration, improving medical research and personalized patient care.

Harnessing Genomic Resources and Molecular Breeding Techniques for Advancing Crop Resilience and Productivity

Crop improvement and adaptation are critical to ensure global food security in the face of climate change, population growth, and resource limitations. Exploiting genomic resources and molecular breeding techniques offers immense potential to accelerate the development of resilient, high-yielding crop varieties. This review provides an overview of the current state and future prospects of leveraging genomics and molecular breeding for crop improvement, with a focus on major food crops. We discuss key genomic resources such as reference genomes, transcriptomes, and pan-genomes, as well as powerful molecular breeding approaches like marker-assisted selection, genomic selection, and genome editing. Integrating these tools into crop breeding pipelines can greatly enhance the precision and efficiency of developing improved varieties with desirable traits such as abiotic stress tolerance, disease resistance, and enhanced nutritional quality. We also highlight successful examples of applying these techniques in crops like rice, wheat, maize, and legumes. Furthermore, we explore the role of big data, machine learning, and systems biology in extracting actionable insights from the vast genomic data being generated. Finally, we discuss the challenges and opportunities in translating genomic discoveries into improved crop varieties, emphasizing the need for multidisciplinary collaborations, capacity building, and public-private partnerships. Harnessing the power of genomics and molecular breeding will be pivotal in developing climate-resilient crops to feed the growing global population sustainably.

Promise and Peril of a Genotype-First Approach to Mendelian Cardiovascular Disease.

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard-of-care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in-depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype-first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population-based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true-positive and false-positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype-first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Abstract B005: Denosumab Enhances Cytotoxic T Cell Infiltration by supressing SPP1 Expression in Giant Cell Tumour of Bone

Abstract Denosumab, a RANKL inhibitor, is primarily used to prevent osteoclastogenesis for the treatment of conditions like osteoporosis, bone metastasis, and giant cell tumor of bone (GCTB). RANKL is also key in immunity, activating NFκB and its target genes, including the osteopontin-coding gene SPP1, which is linked with CXCL9:SPP1 macrophage polarization and prognosis. Retrospective studies of bone metastasis have demonstrated improved clinical outcomes when immune checkpoint inhibitors (ICIs) are combined with denosumab. We undertook a study to explore denosumab's direct role in anti-tumor immunity. Single-cell RNA sequencing was performed on nine primary human GCTB samples, including three untreated and six treated solely with denosumab, to exclude confounding treatment factors linked with bone metastasis samples. Furthermore, we utilized immunohistochemistry staining from paired pre- and post-denosumab treated samples from a cohort of nine GCTB patients and conducted pan-cancer analysis on primary tumors, spanning 31 distinct types of cancers, sourced from the Genomic Data Commons Data Portal. Our single-cell analysis of GCTB resulted in a comprehensive cell atlas of this rare disease, revealing denosumab's role in inhibiting SPP1 expression and augmenting cytotoxic T cell infiltration. This was confirmed in nine pairs of pre- and post-denosumab treated GCTB samples using immunohistochemistry staining. The pan-cancer analysis indicated a negative correlation between SPP1 expression and CD8A levels across most tumor types, with the CD8A/SPP1 ratio correlating with clinical outcomes in 14 cancer types. Our research provides robust clinical evidence that denosumab improves anti-tumor immunity by inhibiting SPP1 expression, presenting a significant step towards patient selection for combined ICI and denosumab therapy. Citation Format: Zezhuo Su, Maximus Chun Fai Yeung, Jason Pui Yin CHEUNG, Kelvin Sin Chi Cheung. Denosumab Enhances Cytotoxic T Cell Infiltration by supressing SPP1 Expression in Giant Cell Tumour of Bone [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr B005.

Variable habitat use supports fine-scale population differentiation of a freshwater piscivore (northern pike, Esox lucius) along salinity gradients in brackish lagoons.

In mobile animals, selection pressures resulting from spatio-temporally varying ecological factors often drive adaptations in migration behavior and associated physiological phenotypes. These adaptations may manifest in ecologically and genetically distinct ecotypes within populations. We studied a meta-population of northern pike (Esox lucius) in brackish environments and examined intrapopulation divergence along environmental gradients. Behavioral phenotypes in habitat use were characterized via otolith microchemistry in 120 individuals sampled from brackish lagoons and adjacent freshwater tributaries. We genotyped 1514 individual pike at 33highly informative genetic markers. The relationship between behavioral phenotype and genotype was examined in a subset of 101 pikes for which both phenotypic and genomic data were available. Thermosaline differences between juvenile and adult life stages indicated ontogenetic shifts from warm, low-saline early habitats towards colder, higher-saline adult habitats. Four behavioral phenotypes were found: Freshwater residents, anadromous, brackish residents, and cross-habitat individuals, the latter showing intermediary habitat use between brackish and freshwater areas. Underlying the behavioral phenotypes were four genotypes,putative freshwater, putativeanadromous, and two putativelybrackish genotypes. Through phenotype-genotype matching, three ecotypes were identified: (i) a brackish resident ecotype, (ii) a freshwater ecotype expressing freshwater residency or anadromy, and (iii) a previously undescribed intermediary cross-habitat ecotype adapted to intermediate salinities, showing limited reliance on freshwater. Life-time growth of all ecotypes was similar, suggesting comparable fitness. Bycombining genetic data with lifelong habitat use and growth as a fitness surrogate, our study revealed strong differentiation in response to abiotic environmental gradients, primarily salinity, indicating ecotype diversity in coastal northern pike is higher than previously believed.

Pheochromocytoma-Paraganglioma Syndrome: A Multiform Disease with Different Genotype and Phenotype Features.

Pheochromocytoma and paraganglioma (PPGL) are rare tumors derived from the adrenal medulla and extra-adrenal chromaffin cells. Diagnosis is often challenging due to the great variability in clinical presentation; the complexity of management due to the dangerous effects of catecholamine excess and the potentially malignant behavior require in-depth knowledge of the pathology and multidisciplinary management. Nowadays, diagnostic ability has certainly improved and guidelines and consensus documents for treatment and follow-up are available. A major impulse to the development of this knowledge has come from the new findings on the genetic and molecular characteristics of PPGLs. Germline mutation in susceptibility genes is detected in 40% of subjects, with a mutation frequency of 10-12% also in patients with sporadic presentation and genetic testing should be incorporated within clinical care. PPGL susceptibility genes include "old genes" associated with Neurofibromatosis type 1 (NF1 gene), Von Hippel Lindau syndrome (VHL gene) and Multiple Endocrine Neoplasia type 2 syndrome (RET gene), the family of SDHx genes (SDHA, SDHB, SDHC, SDHD, SDHAF2), and genes less frequently involved such as TMEM, MAX, and FH. Each gene has a different risk of relapse, malignancy, and other organ involvement; for mutation carriers, affected or asymptomatic, it is possible to define a tailored long-life surveillance program according to the gene involved. In addition, molecular characterization of the tumor has allowed the identification of somatic mutations in other driver genes, bringing to 70% the PPGLs for which we know the mechanisms of tumorigenesis. This has expanded the catalog of tumor driver genes, which are identifiable in up to 70% of patients Integrated genomic and transcriptomic data over the last 10 years have revealed three distinct major molecular signatures, triggered by pathogenic variants in susceptibility genes and characterized by the activation of a specific oncogenic signaling: the pseudo hypoxic, the kinase, and the Wnt signaling pathways. These molecular clusters show a different biochemical phenotype and clinical behavior; they may also represent the prerequisite for implementing customized therapy and follow-up.

Training deep learning models on personalized genomic sequences improves variant effect prediction.

Sequence-to-function models have broad applications in interpreting the molecular impact of genetic variation, yet have been criticized for poor performance in this task. Here we show that training models on functional genomic data with matched personal genomes improves their performance at variant effect prediction. Variant effect representations are retained even when transfer learning models to unseen cellular contexts and experimental readouts. Our results have implications for interpreting trait-associated genetic variation.

Ethical governance for genomic data science in the cloud.

Ethical governance for genomic data science in the cloud.

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from thirteen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Persistence Over Millennia Through Extreme Clonal Longevity: Phylogenomic Insight Into History of One of the World's Rarest Plant Species

ABSTRACTAimThe evolutionary history of European alpine plant species with medium to large geographical ranges is relatively well explored. Here, we investigate the genetic structure and diversity of an extremely narrow endemic and one of the world's rarest plants.LocationEastern Carpathians, Romania.TaxonAndryala laevitomentosa (Asteraceae), an evolutionarily isolated herb species with a worldwide range limited to five micropopulations distributed along a 1.8 km long mountain ridge.MethodsWe used three plastid loci, nuclear ribosomal ITS and genome‐wide, mostly nuclear 26,272 Single‐Nucleotide Polymorphism (SNPs) obtained from RAD‐seq data. We assessed haplotype and genotype diversity, dated the resulting phylogeographic structure, quantified seed production and inferred vegetative propagation.ResultsMaternally inherited plastid markers and nuclear genomic data revealed a concordant pattern: (i) limited genetic diversity, with seven cpDNA haplotypes and 11 RAD‐seq multilocus genotypes; (ii) a strong geographic structure corresponding to spatially isolated genets (clones). The species is likely of early Pleistocene origin (c. 2 Mya), and the estimated age of individual clones varied from c. 24 to 64 Kya. The average seed set assessed over 3 years was only 0.4%. However, the species reproduces veg by axillary and adventitious rosettes formed on rhizomes and roots, respectively.Main ConclusionsThe strong trade‐off between sexual and vegetative reproduction explains not only a deep and ancient phylogeographic structure but also the rarity of the species. Its survival depends almost entirely on vegetative reproduction. The genets of A. laevitomentosa are amongst the oldest clones ever documented in angiosperms. The persistence of these clones in situ for tens of thousands of years suggests an exceptional ability of this species to adapt to major climatic oscillations throughout the Pleistocene and Holocene and challenge our perception of the extent of resilience in plants.

Engineering the Substrate Specificity of UDP-Glycosyltransferases for Synthesizing Triterpenoid Glycosides with a Linear Trisaccharide as Aided by Ancestral Sequence Reconstruction.

Triterpenoids have wide applications in the pharmaceutical and agricultural industries. The glycosylation of triterpenoids catalyzed by UDP-glycosyltransferases (UGTs) is a crucial method for producing valuable derivatives with enhanced functions. However, only a few UDP-glucosyltransferases have been reported to synthesize the rare triterpenoids with linear-chain trisaccharide at C3-OH. This study revealed that the UGT91H subfamily primarily contributed to the 2"-O-glycosylation of triterpenoids with high regioselectivity, then the substrate scope was further expanded by ancestral sequence reconstruction (ASR). With ancestral enzyme UGT91H_A1 as a model, the sequence-structure-function relationship was explored. A RTAS loop (R212/T213/A214/S215) was identified to affect the substrate specificity of UGT91H_A1. Transferring this RTAS loop to the corresponding position of UGT91H enzymes successfully expanded their substrate spectra. The functional role of RTAS loop was further elucidated by molecular dynamics simulation and quantum mechanical computation. UGT91H_A1 was applied to the low-cost synthesis of terpenoid rhamnosides with a linear trisaccharide in combining with a self-sufficient UDP-rhamnose regeneration system. Finally, we developed a phylogeny-based platform to efficiently mining new UGT91Hs from plant genomic data. This study provided robust biocatalysts for synthesizing various triterpenoid glycosides with a linear trisaccharide and demonstrated ASR as an efficient tool in engineering the function of UDP-glycosyltransferases.

Genome-wide identification of Aux/IAA gene family members in grape and functional analysis of VaIAA3 in response to cold stress.

Twenty-five VvIAA genes and eighteen VaIAA genes were identified from Pinot Noir and Shanputao, respectively. The overexpression of VaIAA3 in transgenic Arabidopsis increased cold tolerance by regulating auxin, ABA and ethylene signaling. Aux/IAA genes are key genes involved in regulating auxin signal transduction in plants. Although IAA genes have been characterized in various plant species, the role of IAA genes in grape cold resistance is unclear. To further explore the members of the Aux/IAA gene family in grape and their functions, in this study, using genomic data for Pinot Noir (Vitis vinifera cv. 'Pinot Noir') and Shanputao (Vitis amurensis), 25 VvIAA genes and 18 VaIAA genes were identified. The VaIAA genes presented different expression patterns at five different temperatures (28 ± 1 °C, 5 ± 1 °C, 0 ± 1 °C, -5 ± 1 °C, and -10 ± 1 °C) according to qRT‑PCR results. VaIAA3 was selected as a candidate gene for further functional analysis because of its high expression level under low-temperature stress. Subcellular localization experiments revealed that VaIAA3 was localized in the nucleus. Additionally, under 4 °C treatment for 24 h, relative expression level of VaIAA3, antioxidant enzyme activity, survival rate, and cold-responsive gene expression in three transgenic lines (OE-1, OE-2, OE-3) were greater, whereas relative electrolytic conductivity (REC), malondialdehyde (MDA) content and hydrogen peroxide (H2O2) content were lower than those of the wild type (WT). Transcriptome sequencing analysis revealed that VaIAA3 regulated cold stress resistance in Arabidopsis thaliana (Arabidopsis) through pathways involving auxin, ABA, JA, or ethylene. Importantly, heterologous overexpression of VaIAA3 increased the resistance of Arabidopsis to cold stress, which provides a theoretical basis for the further use of VaIAA3 to improve cold resistance in grape.