Deliverable 1.1 - SNP-chip tool validation
This deliverable describes a major task in WP1 “Selective Breeding for Robust Fish” to design, implement and validate a SNP-array that will serve as a basic tool for selective breeding in both species. SNP-chips have already been developed and applied to improve livestock in traditionally domesticat...
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ftzenodo:oai:zenodo.org:4549062 2024-09-09T19:30:39+00:00 Deliverable 1.1 - SNP-chip tool validation Manousaki Tereza Tsakogiannis Alexandros Ekonomaki Katerina Terzoglou Vasso Tsigenopoulos Costas Ferraresso Serena Pauletto Marianna Bargelonni Luca Colli Antonio Tzokas Kostas Papaharisis Leonidas Caggiano Massimo Barić Renata Mazzora Carlos Ojeda Javier 2020-08-14 https://doi.org/10.5281/zenodo.4549062 eng eng Zenodo https://zenodo.org/communities/performfish https://zenodo.org/communities/eu https://doi.org/10.5281/zenodo.4549061 https://doi.org/10.5281/zenodo.4549062 oai:zenodo.org:4549062 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/report 2020 ftzenodo https://doi.org/10.5281/zenodo.454906210.5281/zenodo.4549061 2024-07-27T01:35:29Z This deliverable describes a major task in WP1 “Selective Breeding for Robust Fish” to design, implement and validate a SNP-array that will serve as a basic tool for selective breeding in both species. SNP-chips have already been developed and applied to improve livestock in traditionally domesticated terrestrial animals such as cow (see Nikolazzi et al. 2014 for an overview), chicken (Groenen et al. 2011; Kranis et al. 2013), pig (Ramos et al. 2009) and goat (Tosser-Klopp et al.2014). Regarding fish, previous experience on SNP-chip development comes among others from the Atlantic salmon (Houston et al. 2014; Yanez et al. 2014), common carp (Xu et al. 2014) and rainbow trout (Palti et al. 2015). Especially for the Atlantic salmon, the chip application has led to GWAS analysis (Correa et al. 2015; Tsai et al. 2015) illustrating the advantages of such a tool. Till now, the chosen strategies from different studies include either sequencing a part of the genome (e.g. RNASeq, GBS) of many individuals or whole genome re-sequencing of fewer individuals. The former provides higher coverage of the sequenced moiety of the genome, while the latter identifies many more markers evenly distributed across the genome with lower coverage. In this deliverable, farmed as well as wild populations’ samples of both European sea bass (BSS) and gilthead sea bream (SBG) were collected under the responsibility of HCMR and UNIPD, respectively. Samples covered the full range from the Atlantic Ocean to the Eastern Mediterranean; some additional domesticated populations were provided through the MedAID consortium. The samples were deeply sequenced using the technique PoolSeq (Hivert et al. 2018) which resulted in the discovery of SNPs genome-wide. Following multiple bioinformatic filters, a total of 29,888 and 29,807 SNP markers for BSS and SBG, respectively, have been included in the Med_Fish SNP chip. Both sequencing and bioinformatic analysis effort in means of costs and human resources were jointly undertaken by the PerformFISH and ... Report Atlantic salmon Zenodo Correa ENVELOPE(-61.500,-61.500,-64.400,-64.400) Ramos ENVELOPE(-59.700,-59.700,-62.500,-62.500) |
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ftzenodo |
language |
English |
description |
This deliverable describes a major task in WP1 “Selective Breeding for Robust Fish” to design, implement and validate a SNP-array that will serve as a basic tool for selective breeding in both species. SNP-chips have already been developed and applied to improve livestock in traditionally domesticated terrestrial animals such as cow (see Nikolazzi et al. 2014 for an overview), chicken (Groenen et al. 2011; Kranis et al. 2013), pig (Ramos et al. 2009) and goat (Tosser-Klopp et al.2014). Regarding fish, previous experience on SNP-chip development comes among others from the Atlantic salmon (Houston et al. 2014; Yanez et al. 2014), common carp (Xu et al. 2014) and rainbow trout (Palti et al. 2015). Especially for the Atlantic salmon, the chip application has led to GWAS analysis (Correa et al. 2015; Tsai et al. 2015) illustrating the advantages of such a tool. Till now, the chosen strategies from different studies include either sequencing a part of the genome (e.g. RNASeq, GBS) of many individuals or whole genome re-sequencing of fewer individuals. The former provides higher coverage of the sequenced moiety of the genome, while the latter identifies many more markers evenly distributed across the genome with lower coverage. In this deliverable, farmed as well as wild populations’ samples of both European sea bass (BSS) and gilthead sea bream (SBG) were collected under the responsibility of HCMR and UNIPD, respectively. Samples covered the full range from the Atlantic Ocean to the Eastern Mediterranean; some additional domesticated populations were provided through the MedAID consortium. The samples were deeply sequenced using the technique PoolSeq (Hivert et al. 2018) which resulted in the discovery of SNPs genome-wide. Following multiple bioinformatic filters, a total of 29,888 and 29,807 SNP markers for BSS and SBG, respectively, have been included in the Med_Fish SNP chip. Both sequencing and bioinformatic analysis effort in means of costs and human resources were jointly undertaken by the PerformFISH and ... |
format |
Report |
author |
Manousaki Tereza Tsakogiannis Alexandros Ekonomaki Katerina Terzoglou Vasso Tsigenopoulos Costas Ferraresso Serena Pauletto Marianna Bargelonni Luca Colli Antonio Tzokas Kostas Papaharisis Leonidas Caggiano Massimo Barić Renata Mazzora Carlos Ojeda Javier |
spellingShingle |
Manousaki Tereza Tsakogiannis Alexandros Ekonomaki Katerina Terzoglou Vasso Tsigenopoulos Costas Ferraresso Serena Pauletto Marianna Bargelonni Luca Colli Antonio Tzokas Kostas Papaharisis Leonidas Caggiano Massimo Barić Renata Mazzora Carlos Ojeda Javier Deliverable 1.1 - SNP-chip tool validation |
author_facet |
Manousaki Tereza Tsakogiannis Alexandros Ekonomaki Katerina Terzoglou Vasso Tsigenopoulos Costas Ferraresso Serena Pauletto Marianna Bargelonni Luca Colli Antonio Tzokas Kostas Papaharisis Leonidas Caggiano Massimo Barić Renata Mazzora Carlos Ojeda Javier |
author_sort |
Manousaki Tereza |
title |
Deliverable 1.1 - SNP-chip tool validation |
title_short |
Deliverable 1.1 - SNP-chip tool validation |
title_full |
Deliverable 1.1 - SNP-chip tool validation |
title_fullStr |
Deliverable 1.1 - SNP-chip tool validation |
title_full_unstemmed |
Deliverable 1.1 - SNP-chip tool validation |
title_sort |
deliverable 1.1 - snp-chip tool validation |
publisher |
Zenodo |
publishDate |
2020 |
url |
https://doi.org/10.5281/zenodo.4549062 |
long_lat |
ENVELOPE(-61.500,-61.500,-64.400,-64.400) ENVELOPE(-59.700,-59.700,-62.500,-62.500) |
geographic |
Correa Ramos |
geographic_facet |
Correa Ramos |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
https://zenodo.org/communities/performfish https://zenodo.org/communities/eu https://doi.org/10.5281/zenodo.4549061 https://doi.org/10.5281/zenodo.4549062 oai:zenodo.org:4549062 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.454906210.5281/zenodo.4549061 |
_version_ |
1809899647912640512 |