Illumina NovaSeq 6000 paired end sequencing; GGA_INRAE-InstitutAgro_EFFICACE-GEroNIMO_2023_RNAseq
RNA sequencing data were generated for better understanding the genetic control of long-career layer production by combining multi-phenotypes and multi-genomic approaches such as QTL, cis-eQTL, meQTL and other regulatory element detection. This study is part of the french EFFICACE project and the european GEroNIMO project, both related to the FAANG project,  promoting rapid prepublication of data to support the research community. RNA-seq data were analyzed considering  protein coding genes and non-coding genes. These data are released under Fort Lauderdale principles, as confirmed in the Toronto Statement (Toronto International Data Release Workshop. Birney et al. 2009. Pre-publication data sharing. Nature 461:168-170). Any use of this dataset must abide by the FAANG data sharing principles. Data producers reserve the right to make the first publication of a global analysis of this data. If you are unsure if you are allowed to publish on this dataset, please contact sandrine.lagarrigue@institut-agro.fr and faang@iastate.edu to enquire. The full guidelines can be found at http://www.faang.org/data-share-principle”.
http://support.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/samplepreps_truseq/truseqstrandedtotalrna/truseq-stranded-total-rna-sample-prep-guide-15031048-e.pdf