Biology subjects

Soto, J.

Publications and source records attributed to Soto, J..

17 recordsLinked to original sources

bioRxiv2026

Deformability screening identifies NUDT5 as a mediator of cellular mechanobiology

How cells deform, sense, and respond to mechanical cues drives physiological and disease processes ranging from development to cancer metastasis; however, unbiased approaches to identify mechanical mediators are lacking. We screened 1280 compounds to identify modulators of cancer cell deformability using a cellular filtration assay and identified 92 compounds that significantly reduced deformability of ovarian cancer cells; top hits also reduced migration and invasion. Connectivity mapping of the top 21 compounds identified NUDT5 (Nudix hydrolase 5) as a predicted mechanical mediator; transcriptomic analyses implicated NUDT5 in mechanobiology and metabolic processes. We confirmed that NUDT5 mediates intracellular ATP and cellular mechanical behaviors, including morphology and deformability. In ovarian cancer, increased NUDT5 levels were associated with higher tumor stage and worse patient survival; NUDT5 inhibition reduced migration and colony formation in vitro and peritoneal tumor burden in mice. These findings establish deformability-based screening as a platform for discovering mechanical mediators and identify NUDT5 as a therapeutic target in ovarian cancer. TeaserScreening cells based on deformability provides an unbiased approach to identify NUDT5 as a mediator of cell mechanics

cell biology↗

bioRxiv2026

A multi-agent workflow converts CAR-T patient evidence into experimentally testable hypotheses

Clinical studies of chimeric antigen receptor (CAR)-T therapy generate diverse molecular and clinical evidence that remains fragmented across publications, public repositories and patient-derived datasets, limiting systematic therapeutic discovery. Here we present BioPathfinder, an evidence-guided multi-agent workflow for closed-loop biomedical discovery. BioPathfinder constructs a provenance-aware knowledge resource linking publications with patient single-cell RNA sequencing (scRNA-seq) datasets and clinical metadata, and uses role-specialized large language model agents to generate, review and prioritize diverse, falsifiable and dataset-aware mechanistic hypotheses for computational and experimental validation. Applied to a curated corpus of CAR-T-treated patient studies and matched scRNA-seq datasets, BioPathfinder identified candidate mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. The workflow prioritized the hypothesis that genes associated with an NK-like transition programme could be targeted to reduce CAR-T exhaustion and improve persistence. Analysis of patient scRNA-seq datasets showed enrichment of this programme in exhausted post-infusion CAR-T cells. Virtual perturbation prioritized transition-associated receptor genes, including KLRC1, KLRD1 and KLRG1, and expert review selected KLRC1, encoding NKG2A, for experimental validation. In vitro and in vivo chronic-stimulation models showed that NKG2A marked activated, exhaustion-associated CD8 CAR-T cells, whereas NKG2A blockade enhanced antitumour activity and persistence-associated functional readouts in vivo. BioPathfinder establishes a generalizable framework that transforms fragmented clinical single-cell evidence into experimentally validated therapeutic hypotheses, providing a scalable strategy for AI-guided biomedical discovery. HIGHLIGHTSO_LIBioPathfinder integrates fragmented CAR-T clinical studies, patient scRNA-seq datasets and metadata into a provenance-aware evidence resource for AI-guided hypothesis discovery. C_LIO_LIA multi-agent workflow generates, critiques and prioritizes diverse, falsifiable, dataset-aware mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. C_LIO_LIBioPathfinder prioritizes KLRC1/NKG2A as a therapeutic target, and experimental validation demonstrates that NKG2A blockade enhances CAR-T persistence and antitumour function. C_LI

bioengineering↗

bioRxiv2025

Development and validation of HIV SMRTcap for the characterization of HIV-1 reservoirs across tissues and subtypes

Human Immunodeficiency Virus type 1 (HIV-1) is responsible for the global HIV/AIDS epidemic and the establishment of an integrated HIV-1 reservoir remains the primary obstacle to cure. Upon therapy interruption, reactivation of the persistent HIV-1 reservoir propagates viral rebound and mediates continued immunological decline. While furthering understanding of the HIV-1 reservoir is essential for HIV-1 cure, commonly used sequencing strategies are often limited by the reliance on short-read sequencing across separate assays to determine integration sites and proviral integrity - something that does not always adequately resolve complex human genomic repeats or low complexity regions. Simultaneous identification of proviral integration sites and proviral integrity at the single molecule level would enable HIV-1 reservoir characterization with minimal imputation or bioinformatic reconstruction. Here we present HIV Single Molecule Real Time Capture (HIV SMRTcap), a novel molecular and computational pipeline that directly and simultaneously identifies HIV-1 integration sites, defines proviral integrity, and characterizes clonal expansion of HIV-1 provirus-containing cells with single molecule resolution. In combination with long-read, single-molecule, real-time (SMRT) sequencing and custom analytic pipelines, HIV SMRTcap enables a highly comprehensive characterization of HIV-1 reservoirs. Moreover, we demonstrate here that HIV SMRTcap performs robustly across the major global subtypes (HIV-1 subtype A, B, C, D and A/D recombinant viruses), and can use both cell- and tissue-derived inputs, including samples from antiretroviral therapy (ART) treated individuals with undetectable viral loads. Our results demonstrate that HIV SMRTcap serves as a comprehensive, robust method for unbiased HIV-1 reservoir characterization. Used alone, or in combination with single-cell based methods, HIV SMRTcap will enable novel exploration of viral reservoirs across subtypes and in tissue-specific compartments, providing critical information needed to inform HIV-1 cure.

genomics↗

bioRxiv2024

Genetic architecture of the thermal tolerance landscape of Drosophila melanogaster

Increased environmental temperatures associated with global warming strongly impact the natural populations of ectothermic species. Therefore, it is crucial to understand the genetic foundations and evolutionary potential of heat tolerance. However, heat tolerance and its genetic components depend on the methodology, making it difficult to predict the adaptive responses to global warming. Here, we measured the knockdown time for 100 lines from the Drosophila Genetic Reference Panel (DGRP) at four different static temperatures, and we estimated their thermal death time (TDT) curves, which incorporate the magnitude and the time of exposure to thermal stress. Through quantitative genetic analyses, it was observed that the knockdown time showed a significant heritability at different temperatures and that its genetic correlations decreased as temperatures were dissimilar. Significant genotype-by-sex and genotype-by-environment interactions were noted for knockdown time. We also discovered heritable variation for the two parameters of TDT: CTmax and thermal sensitivity. Taking advantage of the DGRP, we performed a GWAS and identified multiple variants positively associated with the TDT parameters, which map to genes related to signaling and developmental functions. We performed functional validations for some candidate genes using RNAi, which revealed that genes such as mam, KNCQ, or robo3 affect the knockdown time at a specific temperature but are not associated with the TDT parameters. Ultimately, the thermal tolerance landscape must possess the ability to adapt to the selective pressures caused by global warming. Genetic variation of phenotypic plasticity and sexually antagonistic pleiotropy should also facilitate the adaptive process and maintain the genetic diversity in Drosophila populations.

evolutionary biology↗

bioRxiv2024

Viscoelastic Extracellular Matrix Enhances Epigenetic Remodeling and Cellular Plasticity

Extracellular matrices of living tissues exhibit viscoelastic properties, yet how these properties regulate chromatin and the epigenome remains unclear. Here, we show that viscoelastic substrates induce changes in nuclear architecture and epigenome, with more pronounced effects on softer surfaces. Fibroblasts on viscoelastic substrates display larger nuclei, lower chromatin compaction, and differential expression of distinct sets of genes related to the cytoskeleton and nuclear function compared to those on purely elastic surfaces. Slow-relaxing viscoelastic substrates reduce lamin A/C expression and enhance nuclear remodeling. These structural changes are accompanied by a global increase in euchromatin marks and local increase in chromatin accessibility at cis-regulatory elements associated with neuronal and pluripotent genes. Consequently, viscoelastic substrates improve the reprogramming efficiency from fibroblasts into neurons and induced pluripotent stem cells. Collectively, our findings unravel the roles of matrix viscoelasticity in epigenetic regulation and cell reprogramming, with implications for designing smart materials for cell fate engineering.

cell biology↗

bioRxiv2023

Engineering Programmable Material-To-Cell Pathways Via Synthetic Notch Receptors To Spatially Control Cellular Phenotypes In Multi-Cellular Constructs

Synthetic Notch (synNotch) receptors are modular synthetic components that are genetically engineered into mammalian cells to detect signals presented by neighboring cells and respond by activating prescribed transcriptional programs. To date, synNotch has been used to program therapeutic cells and pattern morphogenesis in multicellular systems. However, cell-presented ligands have limited versatility for applications that require spatial precision, such as tissue engineering. To address this, we developed a suite of materials to activate synNotch receptors and serve as generalizable platforms for generating user-defined material-to-cell signaling pathways. First, we demonstrate that synNotch ligands, such as GFP, can be conjugated to cell- generated ECM proteins via genetic engineering of fibronectin produced by fibroblasts. We then used enzymatic or click chemistry to covalently link synNotch ligands to gelatin polymers to activate synNotch receptors in cells grown on or within a hydrogel. To achieve microscale control over synNotch activation in cell monolayers, we microcontact printed synNotch ligands onto a surface. We also patterned tissues comprising cells with up to three distinct phenotypes by engineering cells with two distinct synthetic pathways and culturing them on surfaces microfluidically patterned with two synNotch ligands. We showcase this technology by co-transdifferentiating fibroblasts into skeletal muscle or endothelial cell precursors in user-defined spatial patterns towards the engineering of muscle tissue with prescribed vascular networks. Collectively, this suite of approaches extends the synNotch toolkit and provides novel avenues for spatially controlling cellular phenotypes in mammalian multicellular systems, with many broad applications in developmental biology, synthetic morphogenesis, human tissue modeling, and regenerative medicine.

synthetic biology↗

bioRxiv2022

FLAIRR-seq: A novel method for single molecule resolution of near full-length immunoglobulin heavy chain repertoires

Current Adaptive Immune Receptor Repertoire Sequencing (AIRR-seq) strategies resolve expressed antibody (Ab) transcripts with limited resolution of the constant region. Here we present a novel near full-length AIRR-seq (FLAIRR-Seq) method that utilizes targeted amplification by 5 rapid amplification of cDNA ends (RACE), combined with single molecule, real-time sequencing to generate highly accurate (>Q40, 99.99%) IG heavy chain transcripts. FLAIRR-seq was benchmarked by comparing IG heavy chain variable (IGHV), diversity (IGHD), and joining (IGHJ) gene usage, complementarity-determining region 3 (CDR3) length, and somatic hypermutation to matched datasets generated with standard 5 RACE AIRR-seq and full-length isoform sequencing. Together these data demonstrate robust, unbiased FLAIRR-seq performance using RNA samples derived from peripheral blood mononuclear cells, purified B cells, and whole blood, which recapitulated results generated by commonly used methods, while additionally resolving novel IG heavy chain constant (IGHC) gene features. FLAIRR-seq data provides, for the first time, simultaneous, single-molecule characterization of IGHV, IGHD, IGHJ, and IGHC region genes and alleles, allele-resolved subisotype definition, and high-resolution identification of class-switch recombination within a clonal lineage. In conjunction with genomic sequencing and genotyping of IGHC genes, FLAIRR-seq of the IgM and IgG repertoires from 10 individuals resulted in the identification of 32 unique IGHC alleles, 28 (87%) of which were previously uncharacterized. Together, these data demonstrate the capabilities of FLAIRR-seq to characterize IGHV, IGHD, IGHJ, and IGHC gene diversity for the most comprehensive view of bulk expressed Ab repertoires to date.

immunology↗

bioRxiv2021

Mitochondrial DNA variation across 56,434 individuals in gnomAD

Databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, genetic databases such as the Genome Aggregation Database (gnomAD) have ignored the mitochondrial genome (mtDNA). Here we present a pipeline to call mtDNA variants that addresses three technical challenges: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded samples prone to NUMT misalignment (few mtDNA copies per cell), cell line artifacts (many mtDNA copies per cell), or with contamination and we reported variants with heteroplasmy greater than 10%. We applied this pipeline to 56,434 whole genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mitochondrial population allele frequencies are publicly available at gnomad.broadinstitute.org and will aid in diagnostic interpretation and research studies.

genomics↗

bioRxiv2021

Transient nuclear deformation primes epigenetic state and promotes cell reprogramming

Cell reprogramming has wide applications in tissue regeneration, disease modeling and personalized medicine, but low reprogramming efficiency remains a challenge. In addition to biochemical cues, biophysical factors can modulate the epigenetic state and a variety of cell functions. However, how biophysical factors help overcome the epigenetic barrier for cell reprogramming are not well understood. Here we utilized microfluidic channels to induce a transient deformation of the cell nucleus, which caused the disassembly of the nuclear lamina and a downregulation of DNA methylation and histone (H3K9) for 12-24 hours. These global decreases of heterochromatin marks at the early stage of cell reprogramming strikingly enhanced the conversion of fibroblasts into neurons and induced pluripotent stem cells. Consistently, inhibition of DNA methylation and H3K9 methylation partially mimicked the effects of mechanical squeezing on iN reprogramming efficiency. Knocking down lamin A had similar effects to squeezing on enhancing the reprogramming efficiency. Based on these findings, we developed a scalable microfluidic system that enabled a continuous cell processing to effectively prime the epigenetic state for cell reprogramming, demonstrating the potential of mechano-biotechnology for cell engineering.

biophysics↗

bioRxiv2021

Dynamic Consequences of Specificity within the Cytidine Repressor DNA-Binding Domain

The E. coli cytidine repressor (CytR) is a member of the LacR family of bacterial repressors that regulates nine operons with distinct spacing and orientations of recognition sites. Understanding the structural features of the CytR DNA-binding domain (DBD) when bound to DNA is critical to understanding differential mechanisms of gene regulation. We previously reported the structure of the CytR DBD monomer bound specifically to half-site DNA and found that the DBD exists as a three-helix bundle containing a canonical helix-turn-helix motif, similar to other proteins that interact with DNA [Moody, et al (2011), Biochemistry 50:6622-32]. We also studied the free state of the monomer and found that since NMR spectra show it populates up to four distinct conformations, the free state exists as an intrinsically disordered protein (IDP). Here, we present further analysis of the DBD structure and dynamics in the context of full-site operator or nonspecific DNA. DBDs bound to full-site DNA show one set of NMR signals, consistent with fast exchange between the two binding sites. When bound to full-length DNA, we observed only slight changes in structure compared to the monomer structure and no folding of the hinge helix. Notably, the CytR DBD behaves quite differently when bound to nonspecific DNA compared to LacR. A dearth of NOEs and complete lack of protection from hydrogen exchange are consistent with the protein populating a flexible, molten state when associated with DNA nonspecifically, similar to fuzzy complexes. The CytR DBD structure is significantly more stable when bound specifically to the udp half-site substrate. For CytR, the transition from nonspecific association to specific recognition results in substantial changes in protein mobility that are coupled to structural rearrangements. These effects are more pronounced in the CytR DBD compared to other LacR family members.

biophysics↗

bioRxiv2021

NMR Hydrogen Exchange and Relaxation Reveal Positions Stabilized by p53 Rescue Mutants N239Y and N235K

Inactivation of p53 is found in over 50% of all cancers; p53 disfunction is often caused by a single missense mutation localized in the DNA binding domain (DBD). Rescue mutants N235K and N239Y stabilize and restore function to multiple p53 cancer mutants. Here, we use NMR to compare protein dynamics between WT and rescue mutants to understand the mechanism of stabilization. We measured and compared folding dynamics by calculating protection factors (PFs) from NMR hydrogen exchange rates of backbone amides. We find that both rescue mutants impose a global stabilizing effect that dampens their motions compared to WT DBD, predominantly in the {beta}-sandwich. However, a few regions become more flexible in rescue mutants. Notably, positions that have increased PFs map to cancer mutants rescued by each mutant. We also compared relaxation results to obtain flexibility information in the ps to ns timescale regime. Protein sequence analysis was used to determine the occurrence of these rescue mutants in nature and showed that 235K is found in mice and rats, but there is no evidence of 239Y occurring naturally in any species. Understanding the mechanism by which stabilizing mutants rescue p53 may reveal novel avenues for the development of cancer therapeutics. Our findings suggest that cancer therapeutics aimed at restoring p53 function could consider protein dynamics as a metric of drug efficacy. Statement of SignificanceTwo mutations (N235K and N239Y) within the DNA binding domain of p53 are known to reverse the effects of multiple cancer mutants. However, the mechanism of rescue is not clear since the crystal structures of these mutants are virtually identical to that of the WT. Here we use NMR methods to show that the protein dynamics of the rescue mutants are significantly different compared to WT, allowing us to describe the stability on a per-residue basis. Although these mutations are only four residues apart, they stabilize the structure distinctly in different regions, consistent with the specific cancer mutations they to which they restore function.

biophysics↗

bioRxiv2020

Markov State Models and NMR Uncover an Overlooked Allosteric Loop in p53

The tumor suppressor p53 is the most frequently mutated gene in human cancer, and thus reactivation of mutated p53 is a promising avenue for cancer therapy. Analysis of wildtype p53 and the Y220C cancer mutant long-timescale molecular dynamics simulations with Markov state models and validation by NMR relaxation studies has uncovered the involvement of loop L6 in the slowest motions of the protein. Due to its distant location from the DNA-binding surface, the conformational dynamics of this loop has so far remained largely unexplored. We observe mutation-induced stabilization of alternate L6 conformations, distinct from all experimentally-determined structures, in which the loop is both extended and located further away from the DNA-interacting surface. Additionally, the effect of the L6-adjacent Y220C mutation on the conformational landscape of the functionally-important loop L1 suggests an allosteric role to this dynamic loop and the inactivation mechanism of the mutation. Finally, the simulations reveal a novel Y220C cryptic pocket that can be targeted for p53 rescue efforts. Our approach exemplifies the power of the MSM methodology for uncovering intrinsic dynamic and kinetic differences among distinct protein ensembles, such as for the investigation of mutation effects on protein function.

biophysics↗

bioRxiv2020

Tamoxifen reduces inflammatory infiltration of neutrophils in the airways.

ABSTRACTTamoxifen is a drug of choice for treatment of breast cancer but it has also been reported to bear anti-inflammatory activity. Previously, we have observed that tamoxifen treatment successfully reduced inflammation in horses affected by equine asthma syndrome. More notorious, tamoxifen was effective at reducing the infiltration of neutrophils in the inflamed airways by a mechanism that increases efferocytosis, allowing the resolution of inflammation. Due to the emerging increase in patients with chronic inflammatory lung diseases, there is an urgent need for therapies that help reduce airway inflammation. Thus we tested the effect of tamoxifen on airway neutrophil infiltration by using three different mouse models for acute and chronic inflammation of the lung. We found that the drug was able to produce a significant reduction in neutrophils in all scenarios. Ussing chamber experiments demonstrated that tamoxifen has no effect on fluid secretion and absorption, discarding a possible reduction in mucociliary clearance due to the known ion-channel blocking effects of tamoxifen. Since this drug has been largely used in human medicine, tamoxifen might be a “low hanging fruit” for a novel anti-inflammatory therapy for airway diseases characterized by neutrophilic inflammation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2019

Somatic Truth Data from Cell Lineage

Existing somatic benchmark datasets for human sequencing data use germline variants, synthetic methods, or expensive validations, none of which are satisfactory for providing a large collection of true somatic variation across a whole genome. Here we propose a dataset of short somatic mutations, that are validated using a known cell lineage. The dataset contains 56,974 (2,687 unique) Single Nucleotide Variations (SNV), 6,370 (316 unique) small Insertions and Deletions (Indels), and 144 (8 unique) Copy Number Variants (CNV) across 98 in silico mixed truth sets with a high confidence region covering 2.7 gigabases per mixture. The data is publicly available for use as a benchmarking dataset for somatic short mutation discovery pipelines.

bioinformatics↗

bioRxiv2019

High-throughput single nucleotide polymorphism (SNP) discovery and validation through whole-genome resequencing of hundreds of individuals in Nile tilapia (Oreochromis niloticus)

Nile Tilapia (Oreochromis niloticus) is the second most important farmed fish in the world and a sustainable source of protein for human consumption. Several genetic improvement programs have been established for this species in the world and so far, they are mainly based on conventional selection using genealogical and phenotypic information to estimate the genetic merit of breeders and make selection decisions. Genome-wide information can be exploited to efficiently incorporate traits that are difficult to measure in the breeding goal. Thus, SNPs are required to investigate phenotype-genotype associations and determine the genomic basis of economically important traits. We performed de novo SNP discovery in three different populations of farmed tilapias. A total of 29.9 million non-redundant SNPs were identified through Illumina (HiSeq 2500) whole-genome resequencing of 326 individual samples. After applying several filtering steps including removing SNP based on genotype and site quality, presence of Mendelian errors, and non unique position in the genome, a total of high quality 50,000 SNP were selected for validation purposes. These SNPs were highly informative in the three populations analyzed showing between 43,869 (94%) and 46,139 (99%) SNP in HWE; 37,843 (76%) and 45,171(90%) SNP with a MAF higher than 0.05 and; 43,450 (87%) and 46,570 (93%) SNPs with a MAF higher than 0.01. The final list of 50K SNPs will be very useful for the dissection of economically relevant traits, enhancing breeding programs through genomic selection as well as supporting genetic studies in farmed populations Nile tilapia using dense genome-wide information.

genomics↗

bioRxiv2019

Fine mapping using whole-genome sequencing confirms anti Mullerian hormone as a major gene for sex determination in farmed Nile tilapia (Oreochromis niloticus L.)

Nile tilapia (Oreochromis niloticus) is one of the most cultivated and economically important species in world aquaculture. Faster male development during grow-out phase is considered a major problem that generate heterogeneous sizes of fish at harvest. Identifying genomic regions associated with sex determination in Nile tilapia is a research topic of great interest. The objective of this study was to identify genomic variants associated with sex determination in three commercial populations of Nile tilapia. Whole-genome sequencing of 326 individuals was performed, and a total of 2.4 million high-quality bi-allelic single nucleotide polymorphisms (SNPs) were identified. A genome-wide association study (GWAS) was conducted to identify markers associated with the binary sexual trait (males = 0; females = 1). A mixed logistic regression GWAS model was fitted and a genome-wide significant signal comprising 36 SNPs, located on chromosome 23 spanning a genomic region of 536 kb, was identified. Ten out of these 36 genetic variants, intercept the anti-Mullerian hormone gene. Other significant SNPs were located in the neighboring Amh gene region. This gene has been strongly associated with sex determination in several vertebrate species, playing an essential role in the differentiation of male and female reproductive tissue in early stages of development. This finding provides useful information to better understand the genetic mechanisms underlying sex determination in Nile tilapia.

genomics↗

bioRxiv2019

Genome-wide association study and low-cost genomic predictions for growth and fillet yield in Nile tilapia (Oreochromis niloticus)

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in tilapia breeding programs.

genomics↗