Aroa Suárez‐Vega

Universidad de León

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Beatriz Gutiérrez‐Gil

Universidad de León

J. J. Arranz

Universidad de León

Pablo A. S. Fonseca

Universidad de León

Cristina Esteban‐Blanco

CIC bioGUNE

ÁC

Ángela Cánovas

University of Guelph

Juan-José Arranz

Universidad de León

Praveen Chitneedi

Research Institute for Farm Animal Biology (FBN)

R. Pelayo

Universidad de León

H. Marina

Universidad de León

Julio Javier Díez

Universidad de Valladolid

Cooperative Institutions

Universidad de León

University of Guelph

Universidad de León

Consejo Superior de Investigaciones Científicas

University of Alberta

Instituto de Ganadería de Montaña

Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria

Teagasc - The Irish Agriculture and Food Development Authority

Commonwealth Scientific and Industrial Research Organisation

Agriculture and Food

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Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep

Journal of Dairy Science (2022)

H. Marina R. Pelayo Beatriz Gutiérrez‐Gil Aroa Suárez‐Vega Cristina Esteban‐Blanco

The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.

SNP

Genomic Selection

SNP genotyping

Imputation (statistics)

10.3168/jds.2021-21601

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Citations (7)

Additional file 6 of Unravelling transmission ratio distortion across the bovine genome: identification of candidate regions for reproduction defects

Figshare (2023)

Samir Id‐Lahoucine J. Casellas Aroa Suárez‐Vega Pablo A. S. Fonseca Flávio S. Schenkel

Additional file 6: Supplementarymaterial 6. Diseases and functions associated with the positional candidate genes mapped within TRDregions.

Identification

Distortion (music)

10.6084/m9.figshare.23650142

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Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

Journal of Dairy Science (2020)

Stephanie Lam F. Miglior Pablo A. S. Fonseca Isabel Gómez‐Redondo J. Zeidan

The identification of functional genetic variants and associated candidate genes linked to feed efficiency may help improve selection for feed efficiency in dairy cattle, providing economic and environmental benefits for the dairy industry. This study used RNA-sequencing data obtained from liver tissue from 9 Holstein cows [n = 5 low residual feed intake (RFI), n = 4 high RFI] and 10 Jersey cows (n = 5 low RFI, n = 5 high RFI), which were selected from a single population of 200 animals. Using RNA-sequencing, 3 analyses were performed to identify: (1) variants within low or high RFI Holstein cattle; (2) variants within low or high RFI Jersey cattle; and (3) variants within low or high RFI groups, which are common across both Holstein and Jersey cattle breeds. From each analysis, all variants were filtered for moderate, modifier, or high functional effect, and co-localized quantitative trait loci (QTL) classes, enriched biological processes, and co-localized genes related to these variants, were identified. The overlapping of the resulting genes co-localized with functional SNP from each analysis in both breeds for low or high RFI groups were compared. For the first two analyses, the total number of candidate genes associated with moderate, modifier, or high functional effect variants fixed within low or high RFI groups were 2,810 and 3,390 for Holstein and Jersey breeds, respectively. The major QTL classes co-localized with these variants included milk and reproduction QTL for the Holstein breed, and milk, production, and reproduction QTL for the Jersey breed. For the third analysis, the common variants across both Holstein and Jersey breeds, uniquely fixed within low or high RFI groups were identified, revealing a total of 86,209 and 111,126 functional variants in low and high RFI groups, respectively. Across all 3 analyses for low and high RFI cattle, 12 and 31 co-localized genes were overlapping, respectively. Among the overlapping genes across breeds, 9 were commonly detected in both the low and high RFI groups (INSRR, CSK, DYNC1H1, GAB1, KAT2B, RXRA, SHC1, TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.

Residual feed intake

Candidate gene

Holstein Cattle

SNP

10.3168/jds.2020-18241

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Citations (25)

Unrevealing functional candidate genes for bovine fertility through RNA sequencing meta-analysis and regulatory elements networks of co-expressed genes and lncRNAs

Functional & Integrative Genomics (2022)

Pablo A. S. Fonseca Aroa Suárez‐Vega Ángela Cánovas

Candidate gene

Gene regulatory network

10.1007/s10142-022-00893-1

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Citations (10)

PRELIMINARY USE OF KAHOOT AS AN INTERACTIVE TOOL FOR SELF-ASSESSMENT OF THEORETICAL CONCEPTS RELATED TO ANIMAL BREEDING

EDULEARN proceedings (2020)

Beatriz Gutiérrez‐Gil Aroa Suárez‐Vega J. J. Arranz

PRELIMINARY USE OF KAHOOT AS AN INTERACTIVE TOOL FOR SELF-ASSESSMENT OF THEORETICAL CONCEPTS RELATED TO ANIMAL BREEDING

10.21125/edulearn.2020.1556

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MOESM3 of Exploring the mechanisms of resistance to Teladorsagia circumcincta infection in sheep through transcriptome analysis of abomasal mucosa and abomasal lymph nodes

Figshare (2018)

Praveen Chitneedi Aroa Suárez‐Vega María Martínez Valladares J. J. Arranz Beatriz Gutiérrez‐Gil

Additional file 3. Gene-set enrichment analysis (GO) for the highly expressed genes in both tissues studied. Significant terms from the Gene Ontology (GO) enrichment analysis performed for the genes identified as highly expressed genes (≥ 500 FPKM) in both tissues studied, abomasal mucosa and abomasal lymph node tissue.

Teladorsagia circumcincta

10.6084/m9.figshare.6197411

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Additional file 4: of Variant discovery in the sheep milk transcriptome using RNA sequencing

Figshare (2017)

Aroa Suárez‐Vega Beatriz Gutiérrez‐Gil Christophe Klopp Gwenola Tosser‐Klopp J. J. Arranz

Title of data: Functionally relevant variants found in the genes in “NOD-like receptor signaling pathway”, “Protein processing in endoplasmic reticulum”, “RNA tansport” and “Fatty acid elongation in mitochondria” KEGG pathways. Description of data: Worksheet providing the description and phenotypes of the functionally relevant variants found in the genes in “NOD-like receptor signaling pathway”, “Protein processing in endoplasmic reticulum”, “RNA tansport“and “Fatty acid elongation in mitochondria” KEGG pathways. (XLSX 15 kb)

RNA-Seq

10.6084/m9.figshare.c.3692884_d2

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Additional file 2: of Variant discovery in the sheep milk transcriptome using RNA sequencing

Figshare (2017)

Aroa Suárez‐Vega Beatriz Gutiérrez‐Gil Christophe Klopp Gwenola Tosser‐Klopp J. J. Arranz

Title of data: Genes in QTL regions containing relevant functional variants. Description of data: Worksheet providing the list of genes within QTL regions, which contain variants with functional interest. (XLSX 15 kb)

RNA-Seq

10.6084/m9.figshare.c.3692884_d4

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Identification of Long Non-Coding RNAs Linked to Parasite Host Immune Response in Sheep

Aroa Suárez‐Vega S. E. Dixon Niel A. Karrow Paula Menzies Bonnie A. Mallard

Identification

Host response

Source

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Study on the concordance between different SNP‐genotyping platforms in sheep

Animal Genetics (2021)

H. Marina Praveen Chitneedi R. Pelayo Aroa Suárez‐Vega Cristina Esteban‐Blanco

Summary Different SNP genotyping technologies are commonly used in multiple studies to perform QTL detection, genotype imputation, and genomic predictions. Therefore, genotyping errors cannot be ignored, as they can reduce the accuracy of different procedures applied in genomic selection, such as genomic imputation, genomic predictions, and false‐positive results in genome‐wide association studies. Currently, whole‐genome resequencing (WGR) also offers the potential for variant calling analysis and high‐throughput genotyping. WGR might overshadow array‐based genotyping technologies due to the larger amount and precision of the genomic information provided; however, its comparatively higher price per individual still limits its use in larger populations. Thus, the objective of this work was to evaluate the accuracy of the two most popular SNP‐chip technologies, namely, Affymetrix and Illumina, for high‐throughput genotyping in sheep considering high‐coverage WGR datasets as references. Analyses were performed using two reference sheep genome assemblies, the popular Oar_v3.1 reference genome and the latest available version Oar_rambouillet_v1.0. Our results demonstrate that the genotypes from both platforms are suggested to have high concordance rates with the genotypes determined from reference WGR datasets (96.59% and 99.51% for Affymetrix and Illumina technologies, respectively). The concordance results provided in the current study can pinpoint low reproducible markers across multiple platforms used for sheep genotyping data. Comparing results using two reference genome assemblies also informs how genome assembly quality can influence genotype concordance rates among different genotyping platforms. Moreover, we describe an efficient pipeline to test the reliability of markers included in sheep SNP‐chip panels against WGR datasets available on public databases. This pipeline may be helpful for discarding low‐reliability markers before exploiting genomic information for gene mapping analyses or genomic prediction.

Imputation (statistics)

Concordance

SNP genotyping

Genome-wide Association Study

SNP

SNP array

10.1111/age.13139

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Citations (5)