e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Genome-wide association study of temperament and tenderness using different Bayesian approaches in a Nellore-Angus crossbred population


Genomic prediction models using Bayesian inference determine marker associations based on available data. The objective of this study was to evaluate marker associations for two traits using different Bayesian models applied to a crossbred population. Nellore-Angus F-2, F-3 and half-sibling calves were used with records for overall temperament at weaning (TEMP; a subjective scoring system on a 1-9 scale, where 1 is docile or calm and 9 is wild or unruly; n=769) and Warner-Bratzler shear force (WBSF; a measure of tenderness; n=387). After quality control filtering, there were 34,913 SNP markers distributed across the genome available for use (excluding the Y chromosome). An unknown proportion of these markers (designated as pi) were assumed not to contribute to the variation in these traits. Bayesian methods employed were BayesC to estimate the ideal pi (i.e., value that used as few markers as possible while maintaining heritability, designated as pi). For WBSF or TEMP, pi=0.995 or 0.997, respectively. Then BayesB (using pi) or BayesC (using pi=0 or pi) were fitted to estimate SNP marker effects. Markers were mapped to genes closest to their placement on Bos taurus UMD 3.1 assembly and grouped into 1 Mb windows to identify associated regions, where association was determined based on the posterior probability of association of that window being greater than 0.75. No regions associated with either trait were found using it, but with pi=0, 37 and 147 regions were found to account for more variation than expected under an infinitesimal model for TEMP and WBSF, respectively. Genes from windows identified as associated were used to conduct enrichment analyses. Significant ontology terms related to sodium ion transport and activity, especially voltage-gated channel activity were identified for TEMP, which could be identifying genetic differences between nervous system response to environment and stress stimuli in this population. For WBSF, significant ontology terms related to activity of serine peptidases were identified, but little is known about their true role in muscle tenderness, although they are known to be expressed in muscle. (C) 2013 Elsevier B.V. All rights reserved.

  • US
  • Texas_A&M_Univ_College_Station (US)
  • Iowa_State_Univ (US)
Data keywords
  • ontology
Agriculture keywords
  • cattle
Data topic
  • big data
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Texas_A&M_Univ_College_Station (US)
  • Iowa_State_Univ (US)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.