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Copy number variation analysis identifies novel CAKUT candidate genes in children with a solitary functioning kidney.

Westland R, Verbitsky M, Vukojevic K, Perry BJ, Fasel DA, Zwijnenburg PJ, Bökenkamp A, Gille JJ, Saraga-Babic M, Ghiggeri GM, D'Agati VD, Schreuder MF, Gharavi AG, van Wijk JA, Sanna-Cherchi S - Kidney Int. (2015)

Bottom Line: Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult.Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes.Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations.

View Article: PubMed Central - PubMed

Affiliation: Division of Nephrology, Columbia University, New York, New York, USA.

ABSTRACT

Copy number variations associate with different developmental phenotypes and represent a major cause of congenital anomalies of the kidney and urinary tract (CAKUT). Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult. Here we studied the role of rare copy number variations in 80 patients from the KIMONO study cohort for which pathogenic mutations in three genes commonly implicated in CAKUT were excluded. In total, 13 known or novel genomic imbalances in 11 of 80 patients were absent or extremely rare in 23,362 population controls. To identify the most likely genetic drivers for the CAKUT phenotype underlying these rare copy number variations, we used a systematic in silico approach based on frequency in a large data set of controls, annotation with publicly available databases for developmental diseases, tolerance and haploinsufficiency scores, and gene expression profile in the developing kidney and urinary tract. Five novel candidate genes for CAKUT were identified that showed specific expression in the human and mouse developing urinary tract. Among these genes, DLG1 and KIF12 are likely novel susceptibility genes for CAKUT in humans. Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes. Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations.

No MeSH data available.


Related in: MedlinePlus

From CNVs to candidate genes for CAKUTAll identified CNVs (N) were included in the analysis. For all novel, rare CNVs, deletions and duplications that showed significant overlap to pathogenic or uncertain pathogenic CNVs in public databases were included (see Supplementary Figure 1 and Supplementary Table 6). After annotation of gene content (n), genes that displayed rare truncating variants (deletions) and rare missense variants (duplications) in the Exome Variant Sever Database (http://evs.gs.washington.edu/EVS) were selected. We then assessed haploinsufficiency (HI-)LOD-scores and residual variation intolerance (RVI) scores for the prioritized genes (threshold values: HI LOD ≥2 and/or RVI-score <10th percentile) and included the prioritized genes within single gene CNVs as well as those genes that are implicated in renal disease. One gene met >1 threshold value for inclusion (DLG1). Gene expression profiles in the developing mouse kidney for all high-priority genes were evaluated by using GUDMAP (http://www.gudmap.org) and Genepaint (http://www.genepaint.org/) databases. Finally, we performed immunofluorescence studies in an E14.5 mouse kidney. By using this systematic bioinformatic approach, we prioritized 5 candidate genes for CAKUT.CAKUT, congenital anomalies of the kidney and urinary tract; CNV, copy number variation and LOD, logarithm of the odds. Web-resources: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER; http://decipher.sanger.ac.uk/); International Standards For Cytogenomic Arrays Consortium (ISCA; https://www.iscaconsortium.org/).
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Figure 1: From CNVs to candidate genes for CAKUTAll identified CNVs (N) were included in the analysis. For all novel, rare CNVs, deletions and duplications that showed significant overlap to pathogenic or uncertain pathogenic CNVs in public databases were included (see Supplementary Figure 1 and Supplementary Table 6). After annotation of gene content (n), genes that displayed rare truncating variants (deletions) and rare missense variants (duplications) in the Exome Variant Sever Database (http://evs.gs.washington.edu/EVS) were selected. We then assessed haploinsufficiency (HI-)LOD-scores and residual variation intolerance (RVI) scores for the prioritized genes (threshold values: HI LOD ≥2 and/or RVI-score <10th percentile) and included the prioritized genes within single gene CNVs as well as those genes that are implicated in renal disease. One gene met >1 threshold value for inclusion (DLG1). Gene expression profiles in the developing mouse kidney for all high-priority genes were evaluated by using GUDMAP (http://www.gudmap.org) and Genepaint (http://www.genepaint.org/) databases. Finally, we performed immunofluorescence studies in an E14.5 mouse kidney. By using this systematic bioinformatic approach, we prioritized 5 candidate genes for CAKUT.CAKUT, congenital anomalies of the kidney and urinary tract; CNV, copy number variation and LOD, logarithm of the odds. Web-resources: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER; http://decipher.sanger.ac.uk/); International Standards For Cytogenomic Arrays Consortium (ISCA; https://www.iscaconsortium.org/).

Mentions: To define the candidate genetic drivers of the CNV phenotype for the 13 known or novel genomic disorders, we established a systematic in silico approach by using publicly available databases and bioinformatic resources (Figure 1, methods, and supplementary methods). The 13 identified large, rare, genic CNVs included a total of 151 genes. All genes underlying the CNVs overlapping with known genomic disorders were retained (n=119). Novel rare CNVs were annotated against the International Standards for Cytogenomic Arrays Consortium (ISCA) database and Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER) to select CNVs that overlapped with variants of likely pathogenic significance (Supplementary Table 6 and Supplemental Figure 1). After alignment, we discarded the deletion on chromosome 1q44 and the duplication on chromosome 3p26 from our gene prioritization pipeline, as both CNVs showed significant overlap with benign ISCA variants (Supplementary Figure 1). In total, 137 genes were assessed for their potential pathogenic role. We cross-annotated our genes with the Exome Variant Server (EVS) and included all deleted genes that carry truncating mutations in <1:1,000 individuals and all duplicated genes that carry deleterious missense variants in <5:1,000 individuals (Supplementary Table 7 and 8, respectively). We chose these criteria to eliminate genes that harbor an excessive burden of rare deleterious variants. The resulting 32 genes were then interrogated for the haploinsufficiency logarithm of the odds (HI-LOD) score34 (only the genes underlying deletions) and the residual variation intolerance (RVI)-score35 (Supplementary Tables 9 [whole deletions] and 10–11 [prioritized genes], respectively). We defined a HI-LOD score ≥2 or the 10th percentile of the calculated RVI-score as threshold values for genes that are more likely to result in a phenotype when mutated. Using these criteria we identified two genes. We next included all single-gene CNVs in our systematic approach, as these variants may directly point to the genetic defect (n=2). Finally, we included all genes that are implicated in renal disease and genes for which mutations in murine orthologs lead to abnormal kidney and urinary tract development (n=2, from which 1 overlapped [DLG1] with our previous criteria). The resulting list included five high-priority candidate genes: DLG1 (MIM601014), EDA2R (MIM300276), KIF12 (MIM611278), PCDH9 (MIM605514), and TRAF7 (MIM606692) (Table 3). Consistent with the results from our filtering pipeline, truncating variants are extremely rare in these genes according to the EVS database (Supplementary Table 12), suggesting that deleterious mutations have been eliminated by purifying selection.


Copy number variation analysis identifies novel CAKUT candidate genes in children with a solitary functioning kidney.

Westland R, Verbitsky M, Vukojevic K, Perry BJ, Fasel DA, Zwijnenburg PJ, Bökenkamp A, Gille JJ, Saraga-Babic M, Ghiggeri GM, D'Agati VD, Schreuder MF, Gharavi AG, van Wijk JA, Sanna-Cherchi S - Kidney Int. (2015)

From CNVs to candidate genes for CAKUTAll identified CNVs (N) were included in the analysis. For all novel, rare CNVs, deletions and duplications that showed significant overlap to pathogenic or uncertain pathogenic CNVs in public databases were included (see Supplementary Figure 1 and Supplementary Table 6). After annotation of gene content (n), genes that displayed rare truncating variants (deletions) and rare missense variants (duplications) in the Exome Variant Sever Database (http://evs.gs.washington.edu/EVS) were selected. We then assessed haploinsufficiency (HI-)LOD-scores and residual variation intolerance (RVI) scores for the prioritized genes (threshold values: HI LOD ≥2 and/or RVI-score <10th percentile) and included the prioritized genes within single gene CNVs as well as those genes that are implicated in renal disease. One gene met >1 threshold value for inclusion (DLG1). Gene expression profiles in the developing mouse kidney for all high-priority genes were evaluated by using GUDMAP (http://www.gudmap.org) and Genepaint (http://www.genepaint.org/) databases. Finally, we performed immunofluorescence studies in an E14.5 mouse kidney. By using this systematic bioinformatic approach, we prioritized 5 candidate genes for CAKUT.CAKUT, congenital anomalies of the kidney and urinary tract; CNV, copy number variation and LOD, logarithm of the odds. Web-resources: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER; http://decipher.sanger.ac.uk/); International Standards For Cytogenomic Arrays Consortium (ISCA; https://www.iscaconsortium.org/).
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Figure 1: From CNVs to candidate genes for CAKUTAll identified CNVs (N) were included in the analysis. For all novel, rare CNVs, deletions and duplications that showed significant overlap to pathogenic or uncertain pathogenic CNVs in public databases were included (see Supplementary Figure 1 and Supplementary Table 6). After annotation of gene content (n), genes that displayed rare truncating variants (deletions) and rare missense variants (duplications) in the Exome Variant Sever Database (http://evs.gs.washington.edu/EVS) were selected. We then assessed haploinsufficiency (HI-)LOD-scores and residual variation intolerance (RVI) scores for the prioritized genes (threshold values: HI LOD ≥2 and/or RVI-score <10th percentile) and included the prioritized genes within single gene CNVs as well as those genes that are implicated in renal disease. One gene met >1 threshold value for inclusion (DLG1). Gene expression profiles in the developing mouse kidney for all high-priority genes were evaluated by using GUDMAP (http://www.gudmap.org) and Genepaint (http://www.genepaint.org/) databases. Finally, we performed immunofluorescence studies in an E14.5 mouse kidney. By using this systematic bioinformatic approach, we prioritized 5 candidate genes for CAKUT.CAKUT, congenital anomalies of the kidney and urinary tract; CNV, copy number variation and LOD, logarithm of the odds. Web-resources: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER; http://decipher.sanger.ac.uk/); International Standards For Cytogenomic Arrays Consortium (ISCA; https://www.iscaconsortium.org/).
Mentions: To define the candidate genetic drivers of the CNV phenotype for the 13 known or novel genomic disorders, we established a systematic in silico approach by using publicly available databases and bioinformatic resources (Figure 1, methods, and supplementary methods). The 13 identified large, rare, genic CNVs included a total of 151 genes. All genes underlying the CNVs overlapping with known genomic disorders were retained (n=119). Novel rare CNVs were annotated against the International Standards for Cytogenomic Arrays Consortium (ISCA) database and Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources Consortium (DECIPHER) to select CNVs that overlapped with variants of likely pathogenic significance (Supplementary Table 6 and Supplemental Figure 1). After alignment, we discarded the deletion on chromosome 1q44 and the duplication on chromosome 3p26 from our gene prioritization pipeline, as both CNVs showed significant overlap with benign ISCA variants (Supplementary Figure 1). In total, 137 genes were assessed for their potential pathogenic role. We cross-annotated our genes with the Exome Variant Server (EVS) and included all deleted genes that carry truncating mutations in <1:1,000 individuals and all duplicated genes that carry deleterious missense variants in <5:1,000 individuals (Supplementary Table 7 and 8, respectively). We chose these criteria to eliminate genes that harbor an excessive burden of rare deleterious variants. The resulting 32 genes were then interrogated for the haploinsufficiency logarithm of the odds (HI-LOD) score34 (only the genes underlying deletions) and the residual variation intolerance (RVI)-score35 (Supplementary Tables 9 [whole deletions] and 10–11 [prioritized genes], respectively). We defined a HI-LOD score ≥2 or the 10th percentile of the calculated RVI-score as threshold values for genes that are more likely to result in a phenotype when mutated. Using these criteria we identified two genes. We next included all single-gene CNVs in our systematic approach, as these variants may directly point to the genetic defect (n=2). Finally, we included all genes that are implicated in renal disease and genes for which mutations in murine orthologs lead to abnormal kidney and urinary tract development (n=2, from which 1 overlapped [DLG1] with our previous criteria). The resulting list included five high-priority candidate genes: DLG1 (MIM601014), EDA2R (MIM300276), KIF12 (MIM611278), PCDH9 (MIM605514), and TRAF7 (MIM606692) (Table 3). Consistent with the results from our filtering pipeline, truncating variants are extremely rare in these genes according to the EVS database (Supplementary Table 12), suggesting that deleterious mutations have been eliminated by purifying selection.

Bottom Line: Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult.Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes.Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations.

View Article: PubMed Central - PubMed

Affiliation: Division of Nephrology, Columbia University, New York, New York, USA.

ABSTRACT

Copy number variations associate with different developmental phenotypes and represent a major cause of congenital anomalies of the kidney and urinary tract (CAKUT). Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult. Here we studied the role of rare copy number variations in 80 patients from the KIMONO study cohort for which pathogenic mutations in three genes commonly implicated in CAKUT were excluded. In total, 13 known or novel genomic imbalances in 11 of 80 patients were absent or extremely rare in 23,362 population controls. To identify the most likely genetic drivers for the CAKUT phenotype underlying these rare copy number variations, we used a systematic in silico approach based on frequency in a large data set of controls, annotation with publicly available databases for developmental diseases, tolerance and haploinsufficiency scores, and gene expression profile in the developing kidney and urinary tract. Five novel candidate genes for CAKUT were identified that showed specific expression in the human and mouse developing urinary tract. Among these genes, DLG1 and KIF12 are likely novel susceptibility genes for CAKUT in humans. Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes. Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations.

No MeSH data available.


Related in: MedlinePlus