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Articles, 13 records found
Research literature, 1 records found
Articles 13 records found  1 - 10next  jump to record:
1.
12 p, 1.9 MB Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season / Knab, Amy M. (Queens University of Charlotte. Department of Kinesiology) ; Nieman, David C. (Appalachian State University. North Carolina Research Campus) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Groen, Arnoud J. (ProteiQ Biosciences GmbH) ; Pugachev, Artyom (ProteiQ Biosciences GmbH)
Purpose: To evaluate relationships of proteomics data, athlete-reported illness, athlete training distress (TDS), and coaches' ratings of distress and performance over the course of the competitive season. [...]
2020 - 10.3389/fphys.2020.00373
Frontiers in physiology, Vol. 11 (May 2020) , art. 373  
2.
14 p, 1.1 MB Automatic Fruit Morphology Phenome and Genetic Analysis : An Application in the Octoploid Strawberry / Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Monfort, Amparo (Centre de Recerca en Agrigenòmica) ; Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Automatizing phenotype measurement will decisively contribute to increase plant breeding efficiency. Among phenotypes, morphological traits are relevant in many fruit breeding programs, as appearance influences consumer preference. [...]
2021 - 10.34133/2021/9812910
Plant Phenomics, Vol. 2021 (May 2021) , art. ID9812910  
3.
1 p, 276.2 KB Corrigendum to "Automatic Fruit Morphology Phenome and Genetic Analysis : An Application in the Octoploid Strawberry" / Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Monfort, Amparo (Institut de Recerca i Tecnologia Agroalimentàries) ; Perez-Enciso, Miguel (Institució Catalana de Recerca i Estudis Avançats)
2022 - 10.34133/2022/9873618
Plant Phenomics, Vol. 2022 (January 2022) , art. ID9873618  
4.
11 p, 2.0 MB Leveraging host-genetics and gut microbiota to determine immunocompetence in pigs / Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Pérez-Pascual, David (UMR CNRS2001. Unité de Génétique des Biofilms, Institut Pasteur) ; Alexandre, Pamela A. (Agriculture and Food. CSIRO) ; Reverter, Antonio (Agriculture and Food. CSIRO) ; Dalmau Bueno, Antoni (Institut de Recerca i Tecnologia Agroalimentàries) ; Quintanilla, Raquel (Institut de Recerca i Tecnologia Agroalimentàries) ; Ballester Devis, Maria (Institut de Recerca i Tecnologia Agroalimentàries)
The gut microbiota influences host performance playing a relevant role in homeostasis and function of the immune system. The aim of the present work was to identify microbial signatures linked to immunity traits and to characterize the contribution of host-genome and gut microbiota to the immunocompetence in healthy pigs. [...]
2021 - 10.1186/s42523-021-00138-9
Animal Microbiome, Vol. 3 (October 2021) , art. 74  
5.
12 p, 12.8 MB Gut eukaryotic communities in pigs : diversity, composition and host genetics contribution / Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries) ; Prenafeta-Boldú, Francesc (Institut de Recerca i Tecnologia Agroalimentàries) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Gonzalez-Rodriguez, Olga (Institut de Recerca i Tecnologia Agroalimentàries) ; Dalmau Bueno, Antoni (Institut de Recerca i Tecnologia Agroalimentàries) ; Quintanilla, Raquel (Institut de Recerca i Tecnologia Agroalimentàries) ; Ballester Devis, Maria (Institut de Recerca i Tecnologia Agroalimentàries)
Background. The pig gut microbiome harbors thousands of species of archaea, bacteria, viruses and eukaryotes such as protists and fungi. However, since the majority of published studies have been focused on prokaryotes, little is known about the diversity, host-genetic control, and contributions to host performance of the gut eukaryotic counterparts. [...]
2020 - 10.1186/s42523-020-00038-4
Animal Microbiome, Vol. 2 (May 2020) , art. 18  
6.
39 p, 756.7 KB A pilot RNA-seq study in 40 Pietrain ejaculates to characterize the porcine sperm microbiome / Gòdia, Marta (Centre de Recerca en Agrigenòmica) ; Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Darwich Soliva, Laila (Institut de Recerca i Tecnologia Agroalimentàries. Centre de Recerca en Sanitat Animal) ; López, Samantha (Universitat de Barcelona. Departament de Física de la Matèria Condensada) ; Rodríguez-Gil, Joan E. (Universitat Autònoma de Barcelona. Departament de Medicina i Cirurgia Animals) ; Yeste Oliveras, Marc (Universitat de Girona. Institut de Tecnologia Agroalimentària) ; Sánchez Bonastre, Armando (Centre de Recerca en Agrigenòmica) ; Clop, Alex (Centre de Recerca en Agrigenòmica)
The microbiome plays a key role in homeostasis and health and it has been also linked to fertility and semen quality in several animal species including swine. Despite the more than likely importance of sperm bacteria on the boar's reproductive ability and the dissemination of pathogens and antimicrobial resistance genes, the high throughput characterization of the swine sperm microbiome remains scarce. [...]
2020 - 10.1016/j.theriogenology.2020.08.001
Theriogenology, Vol. 157 (November 2020) , p. 525-533
2 documents
7.
14 p, 1.9 MB Exploring deep learning for complex trait genomic prediction in polyploid outcrossing species / Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Gezan, Salvador Alejandro (University of Florida. School of Forest Resources and Conservation (USA)) ; Ferrão, Luis Felipe V. (University of Florida. Horticultural Sciences Department (USA)) ; Osorio, Luis F. (University of Florida. IFAS Gulf Coast Research and Education Center (USA)) ; Monfort, Amparo (Centre de Recerca en Agrigenòmica) ; Muñoz, Patricio R. (University of Florida. Horticultural Sciences Department (USA)) ; Whitaker, Vance M. (University of Florida. IFAS Gulf Coast Research and Education Center (USA)) ; Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. [...]
2020 - 10.3389/fpls.2020.00025
Frontiers in plant science, Vol. 11 (February 2020) , art. 25  
8.
9 p, 1.0 MB Estimating conformational traits in dairy cattle with deepAPS : A two-step deep learning automated phenotyping and segmentation approach / Nye, Jessica (Centre de Recerca en Agrigenòmica) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Assessing conformation features in an accurate and rapid manner remains a challenge in the dairy industry. While recent developments in computer vision has greatly improved automated background removal, these methods have not been fully translated to biological studies. [...]
2020 - 10.3389/fgene.2020.00513
Frontiers in genetics, Vol. 11 (May 2020) , art. 513  
9.
2 p, 462.8 KB Link-HD : a versatile framework to explore and integrate heterogeneous microbial communities / Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Renand, Gilles (Université Paris-Saclay. Institut National de la Recherche Agronomique. Génétique Animale et Biologie Intégrative (France)) ; Morgavi, Diego P. (Institut National de la Recherche Agronomique (França)) ; Ramayo-Caldas, Yuliaxis (Université Paris-Saclay. Institut National de la Recherche Agronomique. Génétique Animale et Biologie Intégrative (France))
Motivation: We present Link-HD, an approach to integrate multiple datasets. Link-HD is a generalization of 'Structuration des Tableaux A Trois Indices de la Statistique-Analyse Conjointe de Tableaux', a family of methods designed to integrate information from heterogeneous data. [...]
2020 - 10.1093/bioinformatics/btz862
Bioinformatics, Vol. 36, Issue 7 (April 2020) , p. 2298-2299  
10.
11 p, 594.5 KB Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows / Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Popova, Milka (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France)) ; Estellé, Jordi (Université Paris-Saclay. Institut National de la Recherche Agronomique. Génétique Animale et Biologie Intégrative (France)) ; Bernard, Aurelien (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France)) ; Pons, Nicolas (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ; Bellot, Pau (Centre de Recerca en Agrigenòmica) ; Mach, Núria (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France)) ; Rau, Andrea (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France)) ; Roume, Hugo (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ; Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica) ; Faverdin, Philippe (Institut National de la Recherche Agronomique (França)) ; Edouard, Nadège (Institut National de la Recherche Agronomique (França)) ; Ehrlich, Dusko (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ; Morgavi, Diego P. (Université Clermont Auvergne. Institut National de la Recherche Agronomique (France)) ; Renand, Gilles (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France))
Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. [...]
2020 - 10.1111/jbg.12427
Journal of Animal Breeding and Genetics, Vol. 137, Issue 1 (January 2020) , p. 49-59  

Articles : 13 records found   1 - 10next  jump to record:
Research literature 1 records found  
1.
180 p, 5.0 MB Deep and shallow learning solutions for modern agriculture / Zingaretti, Laura M. ; Perez-Enciso, Miguel, dir. ; Monfort, Amparo, dir. ; Casillas Viladerrams, Sònia, dir.
L'agricultura moderna depèn àmpliament de l'ús de sofisticades eines informàtiques per analitzar dades massives, tant genotípiques com fenotípiques. La selecció genòmica (SG), que consisteix en predir característiques complexes utilitzant marcadors genètics d'ampli espectre, ha estat aprofitada pels milloradors de plantes i animals, al llarg de les últimes dècades, per produir un considerable augment del guany genètic, reduint el nombre de mostres a testar al camp. [...]
La agricultura moderna depende ampliamente del uso de sofisticadas herramientas informáticas para analizar datos masivos, tanto genotípicos como fenotípicos. La selección genómica (SG), que consiste en predecir rasgos complejos utilizando marcadores genéticos de amplio espectro, ha sido aprovechada por los mejoradores de plantas y animales a lo largo de las últimas décadas, para producir un considerable aumento de la ganancia genética, reduciendo el número de muestras a testear en el campo. [...]
Modern agriculture relies heavily on sophisticated computational tools that involve genomics and phenomics data at a large scale. As for genomics, over the past few decades, plant and animal breeders have taken advantage of genomic selection (GS), which is the breeding strategy that consists of predicting complex traits using genomic wide genetic markers. [...]

2021  

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