Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Apr 18;3(1):8.
doi: 10.1186/2043-9113-3-8.

Characteristics of Cross-Hybridization and Cross-Alignment of Expression in Pseudo-Xenograft Samples by RNA-Seq and Microarrays

Affiliations
Free PMC article

Characteristics of Cross-Hybridization and Cross-Alignment of Expression in Pseudo-Xenograft Samples by RNA-Seq and Microarrays

Camilo Valdes et al. J Clin Bioinforma. .
Free PMC article

Abstract

Background: Exploring stromal changes associated with tumor growth and development is a growing area of oncologic research. In order to study molecular changes in the stroma it is recommended to separate tumor tissue from stromal tissue. This is relevant to xenograft models where tumors can be small and difficult to separate from host tissue. We introduce a novel definition of cross-alignment/cross-hybridization to compare qualitatively the ability of high-throughput mRNA sequencing, RNA-Seq, and microarrays to detect tumor and stromal expression from mixed 'pseudo-xenograft' samples vis-à-vis genes and pathways in cross-alignment (RNA-Seq) and cross-hybridization (microarrays). Samples consisted of normal mouse lung and human breast cancer cells; these were combined in fixed proportions to create a titration series of 25% steps. Our definition identifies genes in a given species (human or mouse) with undetectable expression in same-species RNA but detectable expression in cross-species RNA. We demonstrate the comparative value of this method and discuss its potential contribution in cancer research.

Results: Our method can identify genes from either species that demonstrate cross-hybridization and/or cross-alignment properties. Surprisingly, the set of genes identified using a simpler and more common approach (using a 'pure' cross-species sample and calling all detected genes as 'crossers') is not a superset of the genes identified using our technique. The observed levels of cross-hybridization are relatively low: 5.3% of human genes detected in mouse, and 3.5% of mouse genes detected in human. Observed levels of cross-alignment are practically comparable to the levels of cross-hybridization: 6.5% of human genes detected in mouse, and 2.3% of mouse genes detected in human. We also observed a relatively high percentage of orthologs: 40.3% of cross-hybridizing genes, and 32.2% of cross-aligning genes.Normalizing the gene catalog to use Consensus Coding Sequence (CCDS) IDs (Genome Res 19:1316-1323, 2009), our results show that the observed levels of cross-hybridization are low: 2.7% of human CCDS IDs are detected in mouse, and 2.4% of mouse CCDS IDs are detected in human. Levels of cross-alignment using the RNA-Seq data are comparable for the mouse, 2.2% of mouse CCDS IDs detected in human, and 9.9% of human CCDS IDs detected in mouse. However, the lists of cross-aligning/cross-hybridizing genes contain many that are of specific interest to oncologic researchers.

Conclusions: The conservative definition that we propose identifies genes in mouse whose expression can be attributed to human RNA, and vice versa, as well as revealing genes with cross-alignment/cross-hybridization properties which could not be identified using a simpler but more established approach. The overall percentage of genes affected by cross-hybridization/cross-alignment is small, but includes genes that are of interest to oncologic researchers. Which platform to use with mixed xenograft samples, microarrays or RNA-Seq, appears to be primarily a question of cost and whether the detection and measurement of expression of specific genes of interest are likely to be affected by cross-hybridization or cross-alignment.

Figures

Figure 1
Figure 1
Human and mouse genes detected by microarrays. a. Human and mouse genes detected by microarrays. Percentage of genes, on average, within each sample type detected by the microarray chips. Blue bars represent the percentage of human genes that are detected in the human microarray chip; yellow bars represent the percentage of mouse genes detected in the mouse microarray chip. b. Human and mouse Ensembl genes detected by RNA-Seq. Percentage of genes detected, on average, within each sample type by RNA-Seq. Blue bars represent the percentage of human genes detected by aligning to the human reference; yellow bars represent the percentage of mouse genes detected by aligning to the mouse reference.
Figure 2
Figure 2
Human and mouse CCDS Ids detected by microarrays. a. Human and mouse CCDS IDs detected by microarrays. Percentage of CCDS IDs within each sample type detected by the microarray chips. Blue bars represent the percentage of human CCDS IDs that are detected in the human microarray chip; green bars represent the percentage of mouse CCDS IDs detected in the mouse microarray chip. b. Human and mouse CCDS IDs detected by RNA-Seq. Percentage of CCDS IDs detected within each sample type by RNA-Seq. Blue bars represent the percentage of human CCDS IDs detected by aligning to the human reference; green bars represent the percentage of mouse CCDS IDs detected by aligning to the mouse reference.
Figure 3
Figure 3
Detection by both technologies. Symmetrical Venn-diagrams of CCDS ID’s detected by both RNA-Seq and microarrays in human and mouse. ‘A’ is the 100% human sample, ‘B’ is the 75% human and 25% mouse sample, ‘C’ is the 50% human and 50% mouse sample, ‘D’ is the 25% human and 75% mouse sample, and ‘D’ is the 100% mouse sample. The middle region is the number of CCDS IDs that are detected across all samples.
Figure 4
Figure 4
Gene levels of cross-hybridization. Cross-hybridizing detected genes from the disjoint gene catalog using the microarray platform. (a) Percentage of human genes that are detected in each sample using the human microarray chip. (b) Percentage of mouse genes that are detected in each sample using the mouse microarray chip. (c) genes that cross-hybridize are identified by subtracting the genes detected in a homogeneous tissue sample (the “A” set) from the union of the mixed tissue samples (B,C, &D).
Figure 5
Figure 5
Gene levels of cross-alignment. Cross-aligning genes detected from the disjoint gene catalog using RNA-Seq. (a) Percentage of human genes that are detected in each sample when aligning to the human reference. (b) Percentage of mouse genes that are detected in each sample when aligning to the mouse reference. (c) genes that cross-align are identified by subtracting the genes detected in a homogeneous tissue sample (the “A” set) from the union of the mixed tissue samples (B,C, &D).
Figure 6
Figure 6
CCDS levels of cross-hybridization. Cross-hybridizing CCDS IDs detected using the microarray platform. (a) Percentage of human CCDS IDs that are detected in each sample using the human microarray chip. (b) Percentage of mouse CCDS IDs that are detected in each sample using the mouse microarray chip. (c) CCDS IDs that cross-hybridize are identified by subtracting the CCDS IDs detected in a homogeneous tissue sample (the “A” set) from the union of the mixed tissue samples (B,C, &D).
Figure 7
Figure 7
CCDS levels of cross-alignment. Cross-aligning CCDS IDs detected using RNA-Seq. (a) Percentage of human CCDS IDs that are detected in each sample when aligning to the human reference. (b) Percentage of mouse CCDS IDs that are detected in each sample when aligning to the mouse reference. (c) CCDS IDs that cross-align are identified by subtracting the CCDS IDs detected in a homogeneous tissue sample (the “A” set) from the union of the mixed tissue samples (B,C, &D).
Figure 8
Figure 8
Orthologs. Outer bands are human (hs) and mouse (mm) chromosome ideograms. CCDS density across both genomes is depicted in the blue and purple tracks. Orange marks are cross-alignments and cross-hybridizations detected by RNA-Seq; green marks are cross-alignments and cross-hybridizations detected by microarrays. Arcs connect orthologous CCDS IDs that belong to both the cross-alignments and cross-hybridizations sets for each technology – RNA-Seq and microarrays.
Figure 9
Figure 9
Enriched cancer gene pathways. Pathway analysis was performed using MetaCore software from GeneGo Inc. We examined biological pathways over-represented by the genes in each human and mouse cross-hybridizing and cross-aligning CCDS lists. Distinctly different genes and biological pathways appear as cross-hybridizing & cross-aligning depending upon the platform and tissue type.
Figure 10
Figure 10
EMT Pathway. The top scored GeneGO pathway map (lowest p-value) for the human cross-aligning CCDS set is a development pathway: regulation of epithelial to mesenchymal transition (EMT). Upward thermometers with a red color are up-regulated genes, and downward blue thermometers indicated down-regulated genes.

Similar articles

See all similar articles

Cited by 3 articles

References

    1. Cloonan N, Forrest ARR, Kolle G, Gardiner BBA, Faulkner GJ, Brown MK, Taylor DF, Steptoe AL, Wani S, Bethel G, Robertson AJ, Perkins AC, Bruce SJ, Lee CC, Ranade SS, Peckham HE, Manning JM, McKernan KJ, Grimmond SM. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods. 2008;5:613–619. doi: 10.1038/nmeth.1223. - DOI - PubMed
    1. Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res. 2008;18:1509–1517. doi: 10.1101/gr.079558.108. - DOI - PMC - PubMed
    1. Tlsty TD, Coussens LM. Tumor stroma and regulation of cancer development. - DOI - PubMed
    1. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5:621–628. doi: 10.1038/nmeth.1226. - DOI - PubMed
    1. Hu M, Polyak K. Microenvironmental regulation of cancer development. Curr Opin Genet Dev. 2008;18:27–34. doi: 10.1016/j.gde.2007.12.006. - DOI - PMC - PubMed

LinkOut - more resources

Feedback