Limits...
Hydrophobicity and aromaticity are primary factors shaping variation in amino acid usage of chicken proteome.

Rao Y, Wang Z, Chai X, Nie Q, Zhang X - PLoS ONE (2014)

Bottom Line: Correspondence analyses demonstrated that the main factors responsible for the variation of amino acid usage in chicken are hydrophobicity, aromaticity and genomic GC content.Gene expression level also influenced the amino acid usage significantly.We argued that the amino acid usage of chicken proteome likely reflects a balance or near balance between the action of selection, mutation, and genetic drift.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Technology, Nanchang Normal University, Nanchang, Jiangxi, China; Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China.

ABSTRACT
Amino acids are utilized with different frequencies both among species and among genes within the same genome. Up to date, no study on the amino acid usage pattern of chicken has been performed. In the present study, we carried out a systematic examination of the amino acid usage in the chicken proteome. Our data indicated that the relative amino acid usage is positively correlated with the tRNA gene copy number. GC contents, including GC1, GC2, GC3, GC content of CDS and GC content of the introns, were correlated with the most of the amino acid usage, especially for GC rich and GC poor amino acids, however, multiple linear regression analyses indicated that only approximately 10-40% variation of amino acid usage can be explained by GC content for GC rich and GC poor amino acids. For other intermediate GC content amino acids, only approximately 10% variation can be explained. Correspondence analyses demonstrated that the main factors responsible for the variation of amino acid usage in chicken are hydrophobicity, aromaticity and genomic GC content. Gene expression level also influenced the amino acid usage significantly. We argued that the amino acid usage of chicken proteome likely reflects a balance or near balance between the action of selection, mutation, and genetic drift.

Show MeSH

Related in: MedlinePlus

Relationship between gene expression level and Axis 1, Axis 3, and Axis4.Chicken expression data was taken from a previous work [20], including 19 tissues i.e. blood, brain, bursa of fabricius, cecum, connective tissue, embryonic tissue, epiphyseal growth plate, gonad, head, heart, limb, liver, muscle, ovary, pancreas, spleen, testis, and thymus. For a given gene, expression level is the number of EST counts in all tissues (transformed to denary logarithm). a. Axis 1 is negatively correlated with gene expression level (r  =  −0.1471, P <0.0001). b. Axis 3 is negatively correlated with gene expression level (r  =  −0.1664, P <0.0001); c. Axis 4 is negatively correlated with gene expression level (r  =  −0.1578, P <0.0001).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4199684&req=5

pone-0110381-g005: Relationship between gene expression level and Axis 1, Axis 3, and Axis4.Chicken expression data was taken from a previous work [20], including 19 tissues i.e. blood, brain, bursa of fabricius, cecum, connective tissue, embryonic tissue, epiphyseal growth plate, gonad, head, heart, limb, liver, muscle, ovary, pancreas, spleen, testis, and thymus. For a given gene, expression level is the number of EST counts in all tissues (transformed to denary logarithm). a. Axis 1 is negatively correlated with gene expression level (r  =  −0.1471, P <0.0001). b. Axis 3 is negatively correlated with gene expression level (r  =  −0.1664, P <0.0001); c. Axis 4 is negatively correlated with gene expression level (r  =  −0.1578, P <0.0001).

Mentions: Axis 2 accounts for 15.2% of the total variability, which is positively correlated with the GC1(r  =  0.4509, P <0.0001), GC2 (r  =  0.7782, P <0.0001), GC3(r  =  0.1361, P <0.0001) and GCcds (r  =  0.4608, P <0.0001), but with higher coefficients than Axis 1 except for GC3 (see figure 4). This axis also shows a negative correlation with the GRAVY score of proteins (r  =  −0.4550, P <0.0001) and the Aromo score of proteins (r  =  −0.5428, P<0.0001). The third and fourth axes represented 8.6%, and 7.9% of the total variability, respectively. Both axis 3 and axis 4 show a negative correlation with the gene expression level almost as well as does axis 1 (see figure 5. Axis 3 vs. expression level, r  =  −0.1664, P <0.0001; Axis 4 vs. expression level, r  =  −0.1578, P <0.0001). This implies that gene expression level also has somewhat impact on amino acid usage in chicken. Regression analyses among Axis 3, Axis 4 and the RAAU for each amino acid indicated that Axis 3 significantly correlated with the RAAU of Cys (r  =  0.6912, P <0.0001) and Ala (r  =  0.5391, P <0.0001), Axis 4 significantly correlated with the RAAU of Leu (r  =  0.5373, P <0.0001), Ser (r  =  0.4423, P <0.0001), and Gly (r  =  −0.4430, P <0.0001), suggesting that these amino acid usage are main contributors to Axis 3 and Axis 4 (see Figure S1 and Figure S2).


Hydrophobicity and aromaticity are primary factors shaping variation in amino acid usage of chicken proteome.

Rao Y, Wang Z, Chai X, Nie Q, Zhang X - PLoS ONE (2014)

Relationship between gene expression level and Axis 1, Axis 3, and Axis4.Chicken expression data was taken from a previous work [20], including 19 tissues i.e. blood, brain, bursa of fabricius, cecum, connective tissue, embryonic tissue, epiphyseal growth plate, gonad, head, heart, limb, liver, muscle, ovary, pancreas, spleen, testis, and thymus. For a given gene, expression level is the number of EST counts in all tissues (transformed to denary logarithm). a. Axis 1 is negatively correlated with gene expression level (r  =  −0.1471, P <0.0001). b. Axis 3 is negatively correlated with gene expression level (r  =  −0.1664, P <0.0001); c. Axis 4 is negatively correlated with gene expression level (r  =  −0.1578, P <0.0001).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4199684&req=5

pone-0110381-g005: Relationship between gene expression level and Axis 1, Axis 3, and Axis4.Chicken expression data was taken from a previous work [20], including 19 tissues i.e. blood, brain, bursa of fabricius, cecum, connective tissue, embryonic tissue, epiphyseal growth plate, gonad, head, heart, limb, liver, muscle, ovary, pancreas, spleen, testis, and thymus. For a given gene, expression level is the number of EST counts in all tissues (transformed to denary logarithm). a. Axis 1 is negatively correlated with gene expression level (r  =  −0.1471, P <0.0001). b. Axis 3 is negatively correlated with gene expression level (r  =  −0.1664, P <0.0001); c. Axis 4 is negatively correlated with gene expression level (r  =  −0.1578, P <0.0001).
Mentions: Axis 2 accounts for 15.2% of the total variability, which is positively correlated with the GC1(r  =  0.4509, P <0.0001), GC2 (r  =  0.7782, P <0.0001), GC3(r  =  0.1361, P <0.0001) and GCcds (r  =  0.4608, P <0.0001), but with higher coefficients than Axis 1 except for GC3 (see figure 4). This axis also shows a negative correlation with the GRAVY score of proteins (r  =  −0.4550, P <0.0001) and the Aromo score of proteins (r  =  −0.5428, P<0.0001). The third and fourth axes represented 8.6%, and 7.9% of the total variability, respectively. Both axis 3 and axis 4 show a negative correlation with the gene expression level almost as well as does axis 1 (see figure 5. Axis 3 vs. expression level, r  =  −0.1664, P <0.0001; Axis 4 vs. expression level, r  =  −0.1578, P <0.0001). This implies that gene expression level also has somewhat impact on amino acid usage in chicken. Regression analyses among Axis 3, Axis 4 and the RAAU for each amino acid indicated that Axis 3 significantly correlated with the RAAU of Cys (r  =  0.6912, P <0.0001) and Ala (r  =  0.5391, P <0.0001), Axis 4 significantly correlated with the RAAU of Leu (r  =  0.5373, P <0.0001), Ser (r  =  0.4423, P <0.0001), and Gly (r  =  −0.4430, P <0.0001), suggesting that these amino acid usage are main contributors to Axis 3 and Axis 4 (see Figure S1 and Figure S2).

Bottom Line: Correspondence analyses demonstrated that the main factors responsible for the variation of amino acid usage in chicken are hydrophobicity, aromaticity and genomic GC content.Gene expression level also influenced the amino acid usage significantly.We argued that the amino acid usage of chicken proteome likely reflects a balance or near balance between the action of selection, mutation, and genetic drift.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Technology, Nanchang Normal University, Nanchang, Jiangxi, China; Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China.

ABSTRACT
Amino acids are utilized with different frequencies both among species and among genes within the same genome. Up to date, no study on the amino acid usage pattern of chicken has been performed. In the present study, we carried out a systematic examination of the amino acid usage in the chicken proteome. Our data indicated that the relative amino acid usage is positively correlated with the tRNA gene copy number. GC contents, including GC1, GC2, GC3, GC content of CDS and GC content of the introns, were correlated with the most of the amino acid usage, especially for GC rich and GC poor amino acids, however, multiple linear regression analyses indicated that only approximately 10-40% variation of amino acid usage can be explained by GC content for GC rich and GC poor amino acids. For other intermediate GC content amino acids, only approximately 10% variation can be explained. Correspondence analyses demonstrated that the main factors responsible for the variation of amino acid usage in chicken are hydrophobicity, aromaticity and genomic GC content. Gene expression level also influenced the amino acid usage significantly. We argued that the amino acid usage of chicken proteome likely reflects a balance or near balance between the action of selection, mutation, and genetic drift.

Show MeSH
Related in: MedlinePlus