title: Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens.
abstract: BACKGROUND
  RNA-Seq is the recently developed high-throughput sequencing technology for profiling the entire transcriptome in any organism. It has several major advantages over current hybridization-based approach such as microarrays. However, the cost per sample by RNA-Seq is still prohibitive for most laboratories. With continued improvement in sequence output, it would be cost-effective if multiple samples are multiplexed and sequenced in a single lane with sufficient transcriptome coverage. The objective of this analysis is to evaluate what sequencing depth might be sufficient to interrogate gene expression profiling in the chicken by RNA-Seq.
  
  
  RESULTS
  Two cDNA libraries from chicken lungs were sequenced initially, and 4.9 million (M) and 1.6 M (60 bp) reads were generated, respectively. With significant improvements in sequencing technology, two technical replicate cDNA libraries were re-sequenced. Totals of 29.6 M and 28.7 M (75 bp) reads were obtained with the two samples. More than 90% of annotated genes were detected in the data sets with 28.7-29.6 M reads, while only 68% of genes were detected in the data set with 1.6 M reads. The correlation coefficients of gene expression between technical replicates within the same sample were 0.9458 and 0.8442. To evaluate the appropriate depth needed for mRNA profiling, a random sampling method was used to generate different number of reads from each sample. There was a significant increase in correlation coefficients from a sequencing depth of 1.6 M to 10 M for all genes except highly abundant genes. No significant improvement was observed from the depth of 10 M to 20 M (75 bp) reads.
  
  
  CONCLUSIONS
  The analysis from the current study demonstrated that 30 M (75 bp) reads is sufficient to detect all annotated genes in chicken lungs. Ten million (75 bp) reads could detect about 80% of annotated chicken genes, and RNA-Seq at this depth can serve as a replacement of microarray technology. Furthermore, the depth of sequencing had a significant impact on measuring gene expression of low abundant genes. Finally, the combination of experimental and simulation approaches is a powerful approach to address the relationship between the depth of sequencing and transcriptome coverage.
authors.affiliation: Department of Poultry Science, Texas A &M University College Station, TX 77843-2472, USA. hjzhou@poultry.tamu.edu.
authors.forename: Ying
authors.initials: Y
authors.lastname: Wang
authors.forename: Noushin
authors.initials: N
authors.lastname: Ghaffari
authors.forename: Charles D
authors.initials: CD
authors.lastname: Johnson
authors.forename: Ulisses M
authors.initials: UM
authors.lastname: Braga-Neto
authors.forename: Hui
authors.initials: H
authors.lastname: Wang
authors.forename: Rui
authors.initials: R
authors.lastname: Chen
authors.forename: Huaijun
authors.initials: H
authors.lastname: Zhou
mesh_terms: D000818:Animals; D002645:Chickens / Q000235:genetics*; D020869:Gene Expression Profiling; D015723:Gene Library; D059014:High-Throughput Nucleotide Sequencing; D008168:Lung / Q000378:metabolism*; D058977:Molecular Sequence Annotation; D012333:RNA, Messenger / Q000235:genetics; D017423:Sequence Analysis, RNA
chemical_list: D012333:RNA, Messenger