a network is generated by determining the first- and second - order interactions of cd proteins associated with a given morphological subgroup in a human protein interaction network consisting of refined experimental proteomics data . this network is described in high detail in lage et al ( 2007 , 2008 ) , and online ( http://www.cbs.dtu.dk/suppl/dgf/ ) . interactions of the cd proteins are integrated into a network by always including direct interactions between cd proteins , and only including indirect interactions mediated through proteins with q percent of its interactions to the cd set . various thresholds for q are iteratively tested and value of q for the final network is chosen based on which value gives the optimal network significance , this procedure is described in detail in bergholdt et al ( 2007 ) and d'hertog et al ( 2007 ) . the method for determining network significances can be seen below . detailed views of the networks can be seen in supplementary figures s1 , s2 , s3 and s4 . the significance of each of the generated 19 networks was determined by randomization testing as described in detail earlier ( bergholdt et al , 2007 ; d'hertog et al , 2007 ) . specifically , for an input set of ninput proteins yielding an interaction network ( connected component ) with g input proteins and t total proteins , a network score ( nsinput ) was determined . this network score is the fraction of input proteins of all proteins in the network ( g / t ) . we then determined the significance of the network score by empirically estimating the probability of observing a similar or better network score in networks generated by using 10 000 random input sets of size ninput . the random gene sets were chosen so the degree distribution of proteins in the random sets approximate the input set . as each query generates a varying number of networks ( connected components ) the probability estimates can be calculated from the total amount of networks produced by all 10 000 randomizations that have a network score > nsinput . for this reason , network p - values can be lower than the amount of random queries . all network p - values can be seen in supplementary figures s1 , s2 , s3 and s4 below the title of the network . to rule out the chance of functional bias in the cd set a set of raw candidates were determined by querying all proteins in our interaction network for the amount of interactions to the cd set and determining the hypergeometric probability of this interaction profile . out of all proteins in the proteome , 49 novel candidates had a significant interaction profile to the cd proteins after adjustment for multiple testing ( described in detail in supplementary information and supplementary figure s5 ) . we then used the functional networks assigned to each morphological subgroup to determine the most likely developmental function of the candidates . this was done by identifying the specific subnetworks to which the interactions of the candidates were most significant ( as described in supplementary information and supplementary figure s6 ) . in all , 12 of the 49 candidates were chosen for ih analysis based on the overlap between morphological subgroups and the developmental stages present in our panel of embryonic hearts available for validation experiments . human embryonic tissues were collected from legal abortions , according to the helsinki declaration ii , and their use was approved by the local science ethics committee . embryonic or fetal age was based on measurement of crown - rump length . immediately after dissection , the samples were snap frozen in liquid nitrogen or treated with rna later according to the manufacturer 's instructions ( ambion , austin , tx ) . samples for ih were dissected into appropriate tissue blocks and fixed for 1224 h at 4 c in either 10% neutral - buffered formalin , 4% formol - calcium , lillie 's or bouin 's fixatives . serial sections , 35 m thick , were cut in transverse , sagittal or horizontal planes and placed on silanized slides . sections were deparaffinized and rehydrated in xylene followed by a series of graded alcohols according to the established procedures . the sections were treated with a fresh 0.5% solution of hydrogen peroxide in methanol for 15 min to quench endogenous peroxidase and then rinsed in tris - buffered saline ( tbs , 5 mm tris  hcl , 146 mm nacl , ph 7.6 ) . non - specific binding was inhibited by incubation for 30 min with blocking buffer ( chemmate antibody diluent s2022 , dakocytomation , glostrup , denmark ) at room temperature . the sections were then incubated overnight at 4c with the primary antibody in blocking buffer ( chemmate antibody diluent s2022 , dakocytomation ) . the sections were washed with tbs and then incubated for 30 min with a peroxidase - labeled secondary antibody . the sections were washed with tbs , followed by incubation for 10 min with 3,3-diamino - benzidine chromogen solution . the sections were dehydrated in graded alcohols followed by xylene and coverslipped with dpx mounting media . specificity of the antibodies were determined by their ability to stain specific cell populations in the tissue sections ( examples are shown in supplementary figures s7s12 ) . the following primary antibodies were used : anti - ptgs2 ( 35 - 8200 , invitrogen ) , anti - mapk8 ( sc-6254 , santa cruz biotechnology , santa cruz , ca ) , anti - cav3 ( 610421 , bd transduction laboratories , franklin lakes , nj ) , anti - mapk3 ( sc-7383 , santa cruz biotechnology ) , anti - src ( at-7016 , mbl international , woborn , ma ) , anti - jag2 ( sc-8157 , santa cruz biotechnology ) , anti - dll1 ( sc-9102 , santa cruz biotechnology ) , anti - notch3 ( sc-7474 , santa cruz biotechnology ) , anti - notch4 ( sc-5594 , santa cruz biotechnology ) , anti - bmx ( ab73887 , abcam , cambridge , uk ) , anti - ptk2b ( ab78119 , abcam ) , anti - bmp4 ( ab31165 , abcam ) , anti - egfr ( # 2232 , cell signaling technology , boston , ma ) . pcr for this analysis because it is considered to be the most accurate and sensitive method for detecting rna differences also at very small amounts ( lang et al , 2009 ) . total rna was isolated from tissues using trizol reagent ( invitrogen , taastrup , denmark ) and cdna synthesized with superscript ii ( rnase h ) reverse transcriptase ( invitrogen ) according to the manufacturer 's instructions . qpcr analysis was carried out on an abi 7500 fast real - time pcr system using a lightcycler faststart dna master sybr greeni kit ( roche , hvidovre , denmark ) . primer sequences used for qpcr analysis are available on request . to exclude that polymorphic gene expression between the individual developing hearts could account for the observed differential expression trends reported by qpcr , we also used polony multiplex analysis of gene expression ( kim et al , 2007 ) to measure the expression of the 49 candidates in right ventricular outflow tract from tof patients at the time of primary surgical repair and left ventricle collected from patients with either heart failure or diabetic cardiomyopathy . the expression levels of the candidates were compared with the expression levels of a different set of 49 randomly chosen controls after normalizing both gene sets against gene expression in glioblastoma tissue . here , the heart developmental candidates were significantly higher expressed in heart tissue than the controls ( p=0.016 ) ( see supplementary information and supplementary figure s13 ) . a network is generated by determining the first- and second - order interactions of cd proteins associated with a given morphological subgroup in a human protein interaction network consisting of refined experimental proteomics data . this network is described in high detail in lage et al ( 2007 , 2008 ) , and online ( http://www.cbs.dtu.dk/suppl/dgf/ ) . interactions of the cd proteins are integrated into a network by always including direct interactions between cd proteins , and only including indirect interactions mediated through proteins with q percent of its interactions to the cd set . various thresholds for q are iteratively tested and value of q for the final network is chosen based on which value gives the optimal network significance , this procedure is described in detail in bergholdt et al ( 2007 ) and d'hertog et al ( 2007 ) . the method for determining network significances can be seen below . detailed views of the networks can be seen in supplementary figures s1 , s2 , s3 and s4 . the significance of each of the generated 19 networks was determined by randomization testing as described in detail earlier ( bergholdt et al , 2007 ; d'hertog et al , 2007 ) . specifically , for an input set of ninput proteins yielding an interaction network ( connected component ) with g input proteins and t total proteins , a network score ( nsinput ) was determined . this network score is the fraction of input proteins of all proteins in the network ( g / t ) . we then determined the significance of the network score by empirically estimating the probability of observing a similar or better network score in networks generated by using 10 000 random input sets of size ninput . the random gene sets were chosen so the degree distribution of proteins in the random sets approximate the input set . as each query generates a varying number of networks ( connected components ) the probability estimates can be calculated from the total amount of networks produced by all 10 000 randomizations that have a network score > nsinput . for this reason , network p - values can be lower than the amount of random queries . all network p - values can be seen in supplementary figures s1 , s2 , s3 and s4 below the title of the network . to rule out the chance of functional bias in the cd set a set of raw candidates were determined by querying all proteins in our interaction network for the amount of interactions to the cd set and determining the hypergeometric probability of this interaction profile . out of all proteins in the proteome , 49 novel candidates had a significant interaction profile to the cd proteins after adjustment for multiple testing ( described in detail in supplementary information and supplementary figure s5 ) . we then used the functional networks assigned to each morphological subgroup to determine the most likely developmental function of the candidates . this was done by identifying the specific subnetworks to which the interactions of the candidates were most significant ( as described in supplementary information and supplementary figure s6 ) . in all , 12 of the 49 candidates were chosen for ih analysis based on the overlap between morphological subgroups and the developmental stages present in our panel of embryonic hearts available for validation experiments . human embryonic tissues were collected from legal abortions , according to the helsinki declaration ii , and their use was approved by the local science ethics committee . embryonic or fetal age was based on measurement of crown - rump length . immediately after dissection , the samples were snap frozen in liquid nitrogen or treated with rna later according to the manufacturer 's instructions ( ambion , austin , tx ) . samples for ih were dissected into appropriate tissue blocks and fixed for 1224 h at 4 c in either 10% neutral - buffered formalin , 4% formol - calcium , lillie 's or bouin 's fixatives . serial sections , 35 m thick , were cut in transverse , sagittal or horizontal planes and placed on silanized slides . sections were deparaffinized and rehydrated in xylene followed by a series of graded alcohols according to the established procedures . the sections were treated with a fresh 0.5% solution of hydrogen peroxide in methanol for 15 min to quench endogenous peroxidase and then rinsed in tris - buffered saline ( tbs , 5 mm tris  hcl , 146 mm nacl , ph 7.6 ) . non - specific binding was inhibited by incubation for 30 min with blocking buffer ( chemmate antibody diluent s2022 , dakocytomation , glostrup , denmark ) at room temperature . the sections were then incubated overnight at 4c with the primary antibody in blocking buffer ( chemmate antibody diluent s2022 , dakocytomation ) . the sections were washed with tbs and then incubated for 30 min with a peroxidase - labeled secondary antibody . the sections were washed with tbs , followed by incubation for 10 min with 3,3-diamino - benzidine chromogen solution . the sections were dehydrated in graded alcohols followed by xylene and coverslipped with dpx mounting media . specificity of the antibodies were determined by their ability to stain specific cell populations in the tissue sections ( examples are shown in supplementary figures s7s12 ) . the following primary antibodies were used : anti - ptgs2 ( 35 - 8200 , invitrogen ) , anti - mapk8 ( sc-6254 , santa cruz biotechnology , santa cruz , ca ) , anti - cav3 ( 610421 , bd transduction laboratories , franklin lakes , nj ) , anti - mapk3 ( sc-7383 , santa cruz biotechnology ) , anti - src ( at-7016 , mbl international , woborn , ma ) , anti - jag2 ( sc-8157 , santa cruz biotechnology ) , anti - dll1 ( sc-9102 , santa cruz biotechnology ) , anti - notch3 ( sc-7474 , santa cruz biotechnology ) , anti - notch4 ( sc-5594 , santa cruz biotechnology ) , anti - bmx ( ab73887 , abcam , cambridge , uk ) , anti - ptk2b ( ab78119 , abcam ) , anti - bmp4 ( ab31165 , abcam ) , anti - egfr ( # 2232 , cell signaling technology , boston , ma ) . we chose quantitative real - time quantitative rt  pcr for this analysis because it is considered to be the most accurate and sensitive method for detecting rna differences also at very small amounts ( lang et al , 2009 ) . total rna was isolated from tissues using trizol reagent ( invitrogen , taastrup , denmark ) and cdna synthesized with superscript ii ( rnase h ) reverse transcriptase ( invitrogen ) according to the manufacturer 's instructions . qpcr analysis was carried out on an abi 7500 fast real - time pcr system using a lightcycler faststart dna master sybr greeni kit ( roche , hvidovre , denmark ) . primer sequences used for qpcr analysis are available on request . to exclude that polymorphic gene expression between the individual developing hearts could account for the observed differential expression trends reported by qpcr , we also used polony multiplex analysis of gene expression ( kim et al , 2007 ) to measure the expression of the 49 candidates in right ventricular outflow tract from tof patients at the time of primary surgical repair and left ventricle collected from patients with either heart failure or diabetic cardiomyopathy . the expression levels of the candidates were compared with the expression levels of a different set of 49 randomly chosen controls after normalizing both gene sets against gene expression in glioblastoma tissue . here , the heart developmental candidates were significantly higher expressed in heart tissue than the controls ( p=0.016 ) ( see supplementary information and supplementary figure s13 ) .
aberrant organ development is associated with a wide spectrum of disorders , from schizophrenia to congenital heart disease , but systems - level insight into the underlying processes is very limited . using heart morphogenesis as general model for dissecting the functional architecture of organ development , we combined detailed phenotype information from deleterious mutations in 255 genes with high - confidence experimental interactome data , and coupled the results to thorough experimental validation . 
 hereby , we made the first systematic analysis of spatio - temporal protein networks driving many stages of a developing organ identifying several novel signaling modules . 
 our results show that organ development relies on surprisingly few , extensively recycled , protein modules that integrate into complex higher - order networks . 
 this design allows the formation of a complicated organ using simple building blocks , and suggests how mutations in the same genes can lead to diverse phenotypes . 
 we observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis . 
 our analysis elucidates the organization and composition of spatio - temporal protein networks that drive the formation of organs , which in the future may lay the foundation of novel approaches in treatments , diagnostics , and regenerative medicine .