Computational protocol: Transcriptome analysis reveals potential mechanisms underlying differential heart development in fast- and slow-growing broilers under heat stress

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Protocol publication

[…] Eggs of Ross 708 broilers from Mountaire farm in Millsboro, Delaware, and eggs of Illinois broilers from University of Illinois at Urbana-Champaign were hatched at the University of Delaware. After hatch, twenty male broilers from each line were randomly selected for this study to minimize gender specific effects, because male broilers are more susceptible to cardiac dysfunction than females []. The selected male broilers were initially maintained with ad libitum access to feed and drink in large colony houses warmed to 33 °C and the temperature was reduced by 3 °C each week until the house temperature reached 24 °C at 21 days posthatch. After 21 days posthatch, each broiler line was separated to two groups (n = 8-11 per group) with one group remain in the thermoneutral condition and the other group treated by heat stress (HS) in the range of 35–37 °C for 8 h/day. After euthanizing by cervical dislocation at 42 days of age, body and heart weights of the broilers were measured, and differences among groups were analyzed through two-way analysis of variance (ANOVA) and post hoc least significant difference (LSD) test in JMP Pro 12.0.1 (SAS Institute, Cary, NC). Finally, five to six broilers were selected from each group, and their left ventricles were collected, flash frozen in liquid nitrogen and stored at −80 °C for subsequent RNA isolation. [...] A series of applications in Discovery Environment of iPlant Collabrative (, including FastQC (version 0.10.1), TopHat2-SE with TopHat (version 2.0.9) and Bowtie (version 2.1.0), and HTSeq-with-BAM-input with HTSeq (version 0.5.4) were utilized to for RNA-seq analysis. After quality assessment of the reads using FastQC, all libraries were of good quality with Phred score larger than 30 in nearly 100% of bases. Sequence reads in each library were mapped to Gallus gallus Galgal4.81 reference genome using TopHat2-SE with default parameters. The mapped reads per exon were then counted using HTSeq-with-BAM-input program with default parameters. The number of reads per gene was finally calculated and shown in the output file with Ensembl gene ID.Principal component analysis (PCA) was performed using the Bioconductor package DEseq2 (version 1.10.1) in R software (version 3.1.3) based on variance-stabilized normalized read counts []. Differentially expressed (DE) genes between treatments and lines were obtained through analysis using edgeR (version 3.12.0). To minimize the effect of technical bias on the result, trimmed mean of M-values method was utilized to normalize numbers of reads in edge R []. A general linear model including treatment and line effects were fit to the data in edgeR. Log2 fold change (log2FC) and false discovery rate (FDR) determined by Benjamini-Hochberg method were calculated to filter significant DE genes. The genes with |log2FC| > 1 and FDR < 0.1 were defined as significant DE genes in a pair-wise comparison between different treatments or lines. To visualize the effect of heat stress, contrast (Ross_HS - Illinois_HS) - (Ross_Thermoneutral – Illinois_Thermoneutral) was used to compare the heat stress groups between the two lines. With the DE genes in each pair-wise comparison, changes in canonical pathways, regulation of cellular activities, and functions of organs were analyzed and predicted using Ingenuity pathway analysis (IPA) software (Ingenuity Systems, Redwood City, CA). […]

Pipeline specifications

Software tools JMP Pro, FastQC, TopHat, Bowtie, HTSeq, DESeq2, edgeR, IPA
Applications Miscellaneous, RNA-seq analysis
Diseases Heart Diseases, Heart Failure