Data Set Group2: TIGEM Human Retina RNA-Seq (Sep16) RPKM log2

Data Set: TIGEM Human Retina RNA-Seq (Sep16) RPKM log2 GN Accession: GN802 GEO Series: No Geo series yet Title: An atlas of gene expression and gene co-regulation in the human retina Organism: Human (Homo sapiens, hg19) Group: TIGEM-Retina-RNA-Seq Tissue: Retina mRNA Dataset Status: Public Platforms: Illumina HiSeq1000 platform Normalization: RNA-seq

Contact Information Michele Pinelli Telethon Institute of Genetics and Medicine (TIGEM) Via Campi Flegrei 34 Pozzuoli, Naples 80078 Italy Tel. banfi@tigem.it Website Download datasets and supplementary data files GN802_IndividualDataAnnotated_rev090116.txt (N/A)

Specifics of this Data Set:

Summary:

Citation: ​ Pinelli M, Carissimo A, Cutillo L, Lai CH, Mutarelli M, Moretti MN, Singh MV, Karali M, Carrella D, Pizzo M, Russo F, Ferrari S, Ponzin D, Angelini C, Banfi S, di Bernardo D (2016) An atlas of gene expression and gene co-regulation in the human retina. Nucleic acids research 44 (12), 5773-5784   The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it).

About the cases used to generate this set of data:

Human retina sample collection Retina samples were collected at Fondazione Banca degli Occhi del Veneto (FBOV) from 50 different donors for cornea transplantation in compliance with the tenets of the Declaration of Helsinki and after an informed consent allowing the use of tissues for research purposes was signed by the donor's next of kin (for a description of donors Supplementary Table S1). Each harvested tissue was accompanied with the FBOV progressive number and with details on the age and gender of donor, the cause of death and the total post-mortem time (T). To limit the possible effects of post-mortem time on RNA integrity and transcriptomic profiles, retinal tissues were isolated only from eye bulbs with a total post-mortem interval (T) ≤ 26 h. The average post-mortem time of the samples was 20.5 h (ranging from 6 to 26 h). For the same reason, bulbs deriving from multi-organ donors were excluded from the analysis. In order to limit cross-contamination with adjacent tissues, we established a protocol for the dissection of the retina from the eye bulbs (14). The dissected retinal tissue was visually inspected to exclude any cross-contamination with the pigmented RPE/choroid and was immediately submerged in RNA Stabilization Reagent (RNA later; QIAGEN).

About the tissue used to generate this set of data:

About the array platform:

About data values and data processing:

Data analysis The exploratory analysis, whose steps are shown in Figure 1, was carried out with the ‘tuxedo’ software suite (Trapnell et al., 2010) and led to the definition of the Observed Transcriptome (ObsT). The conservative analysis (Figure 1) was carried out by running the RNA-Seq by Expectation-Maximization (RSEM) package (Li & Dewey, 2011) and led to the definition of the RefT.

Notes:

Experiment Type:

RNA extraction, library preparation and sequencing Total RNA was extracted from the 50 human retina samples using the miRNeasy Kit (QIAGEN) according to the manufacturer's instructions. RNA was quantified using a NanoDrop ND-8000 spectrophotometer (NanoDrop Technologies) and the integrity was evaluated using an RNA 6000 Nano chip on a Bioanalyzer (Agilent Technologies). The RNA of the 50 samples had an average RNA integrity number (RIN) of 8.7 (ranging from 7.2 to 9.7). Libraries were prepared according to manufacturer's instructions (TruSeq RNA Sample Preparation kit) with an initial amount of 4 μg of total RNA. Quality control of library templates was performed using a High Sensitivity DNA Assay kit (Agilent Technologies) on a Bioanalyzer (Agilent Technologies). Qubit quantification platform was used to normalize samples for the library preparation (Qubit 2.0 Fluorometer, Life Technologies). Libraries were sequenced via a paired-end chemistry on an Illumina HiSeq1000 platform with an average yield of ∼6 Mb.

Contributor:

Michele Pinelli1,†,  Annamaria Carissimo1,†,  Luisa Cutillo1,2,†,  Ching-Hung Lai1,†,  Margherita Mutarelli1,†,  Maria Nicoletta Moretti1,†,  Marwah Veer Singh1,  Marianthi Karali1,  Diego Carrella1,  Mariateresa Pizzo1,  Francesco Russo3,  Stefano Ferrari4,  Diego Ponzin4,  Claudia Angelini3,  Sandro Banfi1,5,* and  Diego di Bernardo1,6,* -Author Affiliations 1Telethon Institute of Genetics and Medicine (TIGEM), Via Campi Flegrei 34, 80078 Pozzuoli, Italy 2Dipartimento Studi Aziendali e Quantitativi (DISAQ), Università degli studi di Napoli ‘Parthenope’, Via Generale Parisi, 80132 Napoli, Italy 3Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerca, Via Pietro Castellino 111, 80131 Napoli, Italy 4Fondazione Banca degli Occhi del Veneto, Via Paccagnella 11, 30174 Zelarino (Venice), Italy 5Medical Genetics, Department of Biochemistry, Biophysics and General Pathology, Second University of Naples, via Luigi De Crecchio 7, 80138 Naples (NA), Italy 6Dept. Of Chemical, Materials and Industrial Production Engineering, University of Naples ‘Federico II’, Piazzale Tecchio 80, 80125 Naples, Italy +Author Notes ↵*To whom correspondence should be addressed. Tel: +39 81 192 30 600; Fax: +39 81 192 30 651; Email: dibernardo@tigem.it ↵Correspondence may also be addressed to Sandro Banfi. Tel: +39 81 192 30 600; Fax: +39 81 192 30 651; Email: banfi@tigem.it ↵†These authors contributed equally to this work as the first authors.

Citation:

Data source acknowledgment:

The authors are grateful to Mohit Parekh from the Fondazione Banca degli Occhi del Veneto (FBOV) for the collection of human retina samples. The authors would also like to thank Manuela Dionisi (technician) and Vincenzo Nigro (Head) of the Next Generation Sequencing Facility (TIGEM). This work was supported by FondazioneTelethon Grant (TGM11SB2) to SB and (TGM11SB1) toDdB and to the EU FP7 Radiant project (305626) to DdB.

Study Id:

252

• The UT Center for Integrative and Translational Genomics
• NIGMS Systems Genetics and Precision Medicine project (R01 GM123489, 2017-2021)
• NIDA NIDA Core Center of Excellence in Transcriptomics, Systems Genetics, and the Addictome (P30 DA044223, 2017-2022)
• NIA Translational Systems Genetics of Mitochondria, Metabolism, and Aging (R01AG043930, 2013-2018)
• NIAAA Integrative Neuroscience Initiative on Alcoholism (U01 AA016662, U01 AA013499, U24 AA013513, U01 AA014425, 2006-2017)
• NIDA, NIMH, and NIAAA (P20-DA 21131, 2001-2012)
• NCI MMHCC (U01CA105417), NCRR, BIRN, (U24 RR021760)