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In this study, Chicken Genome Arrays were used to construct an adipose …
Biology Articles » Methods & Techniques » Profiling of chicken adipose tissue gene expression by genome array » Figures
Figure 1 The separation of AFP between fat and lean lines. The lean and fat chicken lines derived from a commercial Arbor Acres (AA) grandsire line were created at the Northeast Agricultural University Animal Breeding Center in 1996. They have been selected for 8 generations up to 2004. The selection criteria were the proportion of abdominal fat and levels of very low density lipoproptein (VLDL) in males at 7 weeks of age. Significant differences in AFW and AFP between the two lines were apparent from the 4th generation. Selection was continued for 8 generations, with 15 sires and 4 hens per sire in each line for the G0 to G5 generations and 25 sires and 4 dams per sire in each line for generations G6 to G8. The number of fat line chickens from G1 to G8 was: 82, 88, 75, 81, 80, 78, 179, 165, respectively; and in lean line from G1 to G8: 124, 133, 127, 141, 139, 145, 258, 219, respectively. G represents generation. **p
Figure 2 Comparison of BW, AFW and AFP in chickens used in the study. The birds were kept in similar environmental conditions and had access to feed and water ad libitum, and were fed with a commercial corn-soybean-based diet that met all NRC requirements for 7 weeks. BW was measured after 12 hours fasting, then the birds were slaughtered and the abdominal fat was isolated and weighed. The AFP was calculated as AFP (%) = AFW (g)/BW (g). BW, AFW and AFP data for the ten birds are shown in Table 1. BW is not significantly different between the two lines, but AFW and AFP differ significantly. Data are mean ± SD (n = 5). **p
Figure 3 The distribution of genes expressed in adipose tissue calculated by JMP. Raw data sets were normalized to total fluorescence, which represents the total amount of cRNA hybridized to a microarray using the software Affymetrix Microarray Suite 4.0. Data sets were excluded if the absolute call (Abs Call) was A (absent) or M (Marginal) according to the detection p-value in all arrays. Only expressed transcripts (the Abs Call was P, present) were used in the analysis. The y-axis is the signal intensity after normalization, which represents the relative expression level of genes. The signal intensity of most genes was under 10,000, that most genes are poorly expressed in chicken adipose tissue at 7 weeks.
Figure 4 The hierarchical clustering results of five fat line and five lean line chickens. A: hierarchical clustering results for five fat line chickens. B: hierarchical clustering result for five lean line chickens. The data used for clustering were normalized data that excluded the "not expressed" genes. R represents the coefficient of correlation among individuals. The fat chicken line shared about 87% consistency, while the lean chicken line shared about 77% consistency. Sample 7-3-16 shared only 59% consistency with the other fat line chickens, so it was excluded from the subsequent screening of differentially expressed genes.
Figure 5 SAM Plot for Delta = 0.8. Differentially expressed genes were identified from normalized data using the Significance Analysis of Microarrays (SAM) algorithm implemented in a TIGR MultiExperiment Viewer. A cutoff value delta, depending on an arbitrary false positive rate, was chosen to identify significantly differentially expressed genes. For this analysis, a delta value of 0.8 was used, giving a reasonable cutoff of 3.13 and 4.73 in d-scores.
Figure 6 Cluster image of 230 significant differentially expressed genes. A total of 230 differentially expressed genes were identified by SAM algorithm: 153 were up-regulated and 77 were down-regulated in fat chickens compared to lean chickens. Colored bars indicate relative expression levels. Genes that are expressed at higher levels are assigned progressively brighter shades of red, while genes expressed at low levels are assigned shades of green.
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