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EXAMPLE DATASETS

Example Datasets 1: Human genes exhibiting expression changes in response to Zika virus (ZIKV) infection
[ precomputed result 1.1 / result 1.2 ]

A previous ZIKV outbreak in Brazil was associated with a marked increase in the number of infants born with microcephaly (Mlakar, et al., 2016). Although it is known that ZIKV can be transmitted from mother to child (Mysorekar and Diamond, 2016), it was unclear whether ZIKV directly causes microcephaly (Mlakar, et al., 2016; Pacheco, et al., 2016; Rasmussen, et al., 2016). This gene set was defined based on differentially expressed genes that were identified by Tang, et al. (2016) between Zika virus-infected (ZIKV) and mock-infected human embryonic cortical neural progenitor cells (hNPCs). Following an analysis of this gene set by modPhEA (Example 1.1), several human phenotypes were enriched, including those related to cranial development (e.g., “Abnormality of skull size“ [HP:0000240, FDR-corrected P < 10-13], “Abnormality of the calvaria“ [HP:0002683, FDR-corrected P < 10-3], etc.) and brain development (e.g., “Abnormality of brain morphology“ [HP:0012443, FDR-corrected P < 10-16], “Microcephaly“ [HP:0000252, FDR-corrected P < 10-3], etc.). Consistent with these findings based on human phenotypes, an analysis of mouse phenotypes (Example 1.2) also showed enriched phenotypes of “abnormal cranium size“ (MP:0010031, FDR-corrected P = 0.014), “abnormal brain development“ (MP:0000913, FDR-corrected P < 10-2), etc. These results suggest a molecular basis and a direct contribution of ZIKV infection to microcephaly.

It should be noted that phenotypes related to abnormal limb development were also identified in both analyses based on human phenotypes (e.g., “Abnormal appendicular skeleton morphology“ [HP:0011844, FDR-corrected P < 10-2]) and mouse phenotypes (e.g., “Abnormal limb morphology“ [MP:0002109, FDR-corrected P < 10-3]). Intriguingly, deformed limbs have recently been reported in newborns infected by ZIKV (van der Linden, et al., 2016). Thus, unexpected phenotypes reported by modPhEA may be clinically important.

Example Datasets 2: Budding yeast genes (Example Dataset 2.1) and fission yeast (Schizosaccharomyces pombe) genes (Example Dataset 2.2) arising from lineage-specific duplication events after the divergence of budding and fission yeasts.
[ precomputed result 2.1 / result 2.2 ]

Gene duplication has been proposed to be an important mechanism underlying organismal adaptation (Ohno, 1970; Zhang, 2003), including that of yeasts (Qian and Zhang, 2014). Based on orthology information annotated by Ensembl Fungi v29 (http://fungi.ensembl.org), a list of paralogs in the budding yeast genome and a list of paralogs in the fission yeast genome that arose after the latest common ancestor of these two yeast species were obtained. Enriched analyses of these two lists of genes (paralogs), defined as Example Datasets 2.1 and 2.2, respectively, were conducted based on the budding yeast phenotypes. Budding yeast can thrive under strictly anaerobic conditions, while fission yeast cannot (Heslot, et al., 1970). Correspondingly, the enriched phenotypic term, “anaerobic metabolism (APO:0000210, FDR-corrected P = 0.003)“, was identified for duplicated genes in the budding yeast lineage (Example Datasets 2.1). In addition, the enriched term, “resistance to chemicals“ (APO:0000087, FDR-corrected P < 10-5), that was identified in this gene set may be related to the more advanced metabolic capacity of budding yeast in fermentation, during which yeast cells are exposed to various stresses. The analysis of genes duplicated in the fission yeast lineage (Example Dataset 2.2) identified two enriched terms, “spore wall formation“ (APO:0000043, FDR-corrected P = 0.033) and “interaction with host/environment“ (APO:0000287, FDR-corrected P = 0.028). These two phenotypes are consistent with a lineage-specific adaptation of fission yeast that includes the survival of fission yeast as spores in the gut of insect vectors (Coluccio, et al., 2008).

Example Dataset 3: zebrafish orthologs showing reduced expression in eyes of cave-dwelling Sinocyclocheilus species
[ precomputed result 3 ]

Normal eyes characterize the surface-dwelling Sinocyclocheilus (Cypriniformes: Cyprinidae) teleost fish species (S. angustiporus), while the cave-dwelling Sinocyclocheilus species (S. anophthalmus) has small eyes that are buried deeply within adipose tissue that is covered with skin. To understand the molecular basis of these differences, whole-eye transcriptomes for both S. angustiporus and S. anophthalmus were profiled (Meng, et al., 2013). Genes with an RNA-seq signal that was decreased by > 50% in the eyes of S. anophthalmus compared with the eyes of S. anophthalmus were identified and defined as this gene set. When an enrichment analysis of zebrafish phenotypes was performed with modPhEA, “eye photoreceptor cell“ (ZFA:0009154, FDR-corrected P = 0.027) and “retinal cone cell“ (ZFA:0009262, FDR-corrected P = 0.028) were identified. These two phenotypic terms are consistent with the reduced retinal cell density and photoreceptor cell height that histologically characterize S. anophthalmus eyes according to Meng, et al. (2013).

In addition to the above two terms, this gene set of reduced mRNA expression is enriched in phenotypes manifested in “epiphysis“ (ZFA:0000019, FDR-corrected P = 0.05), a circadian clock pace maker that contains photoreceptor cells. Interestingly, a recent study comparing genomes of three Sinocyclocheilus species found that Skp1-Cul1-Fbxl3 (SCF) protein complex, the most relevant in clock mechanism in mammals, has been degenerated in S. anophthalmus (Yang, et al., 2016). In the future, it will be interesting to examine if S. anophthalmus lacks circadian rhythms.

Example Dataset 4:C. elegans genes expressed in gonads
[ precomputed result 4 ]

The transcriptomes and proteomes of fruit fly and nematode were simultaneously compared in a previous study, and the results suggest that the evolution of the transcriptome is largely neutral (Schrimpf, et al., 2009). That is, protein expression appears to be largely controlled at the level of protein translation, and mRNA expression signals do not necessarily predict gene functions. When an enrichment analysis was performed for genes expressed in an isolated gonad of C. elegans as determined by RNA-seq (Ortiz, et al., 2014), many phenotypes were identified, including: gonad morphology (e.g., “gonad morphology variant“ [WBPhenotype:0001355, FDR-corrected P < 10-54]) and fertility (e.g., “fertility reduced“ [WBPhenotype:0001384], FDR-corrected P < 10-88). Therefore, in contrast with the neutral model of transcriptome evolution that has been proposed (Khaitovich, et al., 2004; Schrimpf, et al., 2009), our results from modPhEA indicate that mRNA expression levels strongly influence functions of the tissue in which the genes are expressed.

Example Dataset 5: Genes that are highly expressed after a blood-meal by malaria vector mosquito.
[ precomputed result 5 ]

Blood-feeding behavior is an important characteristic of mosquitos. To elucidate the genetic components associated with the hematophagy of these animals, microarray data for the malaria mosquito (Anopheles gambiae) (Marinotti, et al., 2005) were downloaded. The top 20% of the mosquito genes that exhibited the greatest increases in gene expression after a blood meal were defined. The remaining 80% of the A. gambiae genes were used as background data for performing an enrichment analysis of fruit fly phenotypes. Consistent with our current understanding that mosquito hematophagy is required for oocyte development, the results indicated that enrichment of this gene set included several reproduction-related phenotypes (e.g., “female sterile“ [FBcv:0000366, FDR-corrected P < 10-8]) and cell cycle-related phenotypes (e.g., “cell cycle defective“ [FBcv:0000671, FDR-corrected P < 10-6]). This example dataset and its results have been presented and discussed in our previous study (Weng and Liao, 2011).

Example Dataset 6: Highly expressed human genes in vascular smooth muscle cells of patients with giant cell arteritis (GCA).
[ precomputed result 6 ]

Human diseases can be characterized by phenotypic abnormalities described with human phenotype ontology (HPO) terms. For example, GCA has been described by Groza, et al. (2015) with the human phenotypic terms, vasculitis (HP:0002633), granulomatosis (HP:0002955), amaurosis fugax (HP:0100576), facial palsy (HP: 0010628), renal amyloidosis (HP: 0001917), dysphagia (HP: 0002015), trismus (HP: 0000211), and encephalopathy (HP: 0001298). Accordingly, we customized a phenotype, “giant cell arteritis (GCA)“, by combining the above seven HPO terms. The gene set provided in this example contains genes with a processed expression signal > 8 in at least one of the vascular smooth muscle cell samples analyzed from GCA patients (downloaded from GSE63425 of NCBI GEO). The analysis conducted by modPhEA showed that this gene set is enriched with the customized term, “giant cell arteritis (GCA)“ (P < 10-3).  

REFERENCES

Coluccio, A.E., et al. (2008) The yeast spore wall enables spores to survive passage through the digestive tract of Drosophila. PLoS One, 3.

Groza, T., et al. (2015) The Human Phenotype Ontology: semantic unification of common and rare disease. Am J Hum Genet, 97, 111-124.

Heslot, H., Goffeau, A. and Louis, C. (1970) Respiratory metabolism of a "petite negative"yeast Schizosaccharomyces pombe 972h. J Bacteriol, 104, 473-481.

Khaitovich, P., et al. (2004) A neutral model of transcriptome evolution. PLoS Biol, 2, 682-689.

Marinotti, O., et al. (2005) Microarray analysis of genes showing variable expression following a blood meal in Anopheles gambiae. Insect Mol Biol, 14, 365-373.

Meng, F., et al. (2013) Evolution of the eye transcriptome under constant darkness in Sinocyclocheilus cavefish. Mol Biol Evol, 30, 1527-1543.

Mlakar, J., et al. (2016) Zika virus associated with microcephaly. N Engl J Med, 374, 951-958.

Mysorekar, I.U. and Diamond, M.S. (2016) Modeling Zika virus infection in pregnancy. N Engl J Med, 375, 481-484.

Ohno, S. (1970) Evolution by gene duplication. Springer-Verlag, New York

Ortiz, M.A., et al. (2014) A new dataset of spermatogenic vs. oogenic transcriptomes in the nematode Caenorhabditis elegans. G3 (Bethesda), 4, 1765-1772.

Pacheco, O., et al. (2016) Zika virus disease in Colombia - preliminary report. N Engl J Med.

Qian, W. and Zhang, J. (2014) Genomic evidence for adaptation by gene duplication. Genome Res, 24, 1356-1362.

Rasmussen, S.A., et al. (2016) Zika Virus and Birth Defects--Reviewing the Evidence for Causality. N Engl J Med, 374, 1981-1987.

Schrimpf, S.P., et al. (2009) Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes. PLoS Biol, 7, e48.

Tang, H., et al. (2016) Zika virus infects human cortical neural progenitors and attenuates their growth. Cell Stem Cell, 18, 587-590.

van der Linden, V., et al. (2016) Congenital Zika syndrome with arthrogryposis: retrospective case series study. BMJ, 354, i3899.

Weng, M.-P. and Liao, B.-Y. (2011) DroPhEA: Drosophila phenotype enrichment analysis for insect functional genomics. Bioinformatics, 27, 3218-3219.

Yang, J.X., et al. (2016) The Sinocyclocheilus cavefish genome provides insights into cave adaptation. BMC Biol, 14.

Zhang, J. (2003) Evolution by gene duplication: an update. Trends Ecol Evol, 18, 292-298.