Abstract
We previously identified a deletion on chromosome 16p12.1 that is mostly inherited and associated with multiple neurodevelopmental outcomes, where severely affected probands carried an excess of rare pathogenic variants compared to mildly affected carrier parents. We hypothesized that the 16p12.1 deletion sensitizes the genome for disease, while “second-hits” in the genetic background modulate the phenotypic trajectory. To test this model, we examined how neurodevelopmental defects conferred by knockdown of individual 16p12.1 homologs are modulated by simultaneous knockdown of homologs of “second-hit” genes in Drosophila melanogaster and Xenopus laevis. We observed that knockdown of 16p12.1 homologs affect multiple phenotypic domains, leading to delayed developmental timing, seizure susceptibility, brain alterations, abnormal dendrite and axonal morphology, and cellular proliferation defects. Compared to genes within the 16p11.2 deletion, which has higher de novo occurrence, 16p12.1 homologs were less likely to interact with each other in Drosophila models or a human brain-specific interaction network, suggesting that interactions with “second-hit” genes may confer higher impact towards neurodevelopmental phenotypes. Assessment of 212 pairwise interactions in Drosophila between 16p12.1 homologs and 76 homologs of patient-specific “second-hit” genes (such as ARID1B and CACNA1A), genes within neurodevelopmental pathways (such as PTEN and UBE3A), and transcriptomic targets (such as DSCAM and TRRAP) identified genetic interactions in 63% of the tested pairs. In 11 out of 15 families, patient-specific “second-hits” enhanced or suppressed the phenotypic effects of one or many 16p12.1 homologs in 32/96 pairwise combinations tested. In fact, homologs of SETD5 synergistically interacted with homologs of MOSMO in both Drosophila and X. laevis, leading to modified cellular and brain phenotypes, as well as axon outgrowth defects that were not observed with knockdown of either individual homolog. Our results suggest that several 16p12.1 genes sensitize the genome towards neurodevelopmental defects, and complex interactions with “second-hit” genes determine the ultimate phenotypic manifestation.
Author summary
Copy-number variants, or deletions and duplications in the genome, are associated with multiple neurodevelopmental disorders. The developmental delay-associated 16p12.1 deletion is mostly inherited, and severely affected children carry an excess of “second-hits” variants compared to mildly affected carrier parents, suggesting that additional variants modulate the clinical manifestation. We studied this “two-hit” model using Drosophila and Xenopus laevis, and systematically tested how homologs of “second-hit” genes modulate neurodevelopmental defects observed for 16p12.1 homologs. We observed that 16p12.1 homologs independently led to multiple neurodevelopmental features and weakly interacted with each other, suggesting that interactions with “second-hit” homologs potentially have a higher impact towards neurodevelopmental defects than interactions between 16p12.1 homologs. We tested 212 pairwise interactions of 16p12.1 homologs with “second-hit” homologs and genes within conserved neurodevelopmental pathways, and observed modulation of neurodevelopmental defects caused by 16p12.1 homologs in 11 out of 15 families, and 16/32 of these changes could be attributed to genetic interactions. Interestingly, we observed that SETD5 homologs interacted with homologs of MOSMO, which conferred additional neuronal phenotypes not observed with knockdown of individual homologs. We propose that the 16p12.1 deletion sensitizes the genome to multiple neurodevelopmental defects, and complex interactions with “second-hit” genes determine the clinical trajectory of the disorder.
Introduction
Rare recurrent copy-number variants (CNVs) account for about 15% of individuals with neurodevelopmental disorders, such as autism, intellectual disability, and schizophrenia [1,2]. While certain CNVs were initially associated with specific neuropsychiatric diagnoses, such as the 16p11.2 deletion and autism [3,4], 3q29 deletion and schizophrenia [5], and 15q13.3 deletion and epilepsy [6], variable expressivity of phenotypes has been the norm rather than the exception for these CNVs [7]. A notable example of this is the 520-kbp deletion encompassing seven genes on chromosome 16p12.1, which is associated with multiple neuropsychiatric disorders, including intellectual disability/developmental delay (ID/DD), schizophrenia, and epilepsy [8,9]. Furthermore, a large-scale study on a control population reported cognitive defects in seemingly unaffected individuals with the 16p12.1 deletion [10], suggesting that the deletion is sufficient to cause neuropsychiatric features. In contrast to other pathogenic CNVs that occur mostly de novo, the 16p12.1 deletion is inherited in more than 95% of individuals from a mildly affected or unaffected carrier parent [8,9,11]. In fact, affected children with the deletion were more likely to carry another large CNV or deleterious mutation elsewhere in the genome (“second-hit”) compared to their carrier parents [8,9], providing evidence that additional rare variants modulate the effect of the deletion. These results suggest that the 16p12.1 deletion confers significant risk for disease and sensitizes the genome for a range of neuropsychiatric outcomes, while additional rare variants in the genetic background determine the ultimate phenotypic trajectory.
The extensive phenotypic variability and lack of chromosomal events, such as translocations and atypical deletions, have made causal gene discovery for variably-expressive CNVs such as the 16p12.1 deletion challenging. In particular, the developmental and neuronal phenotypes associated with each individual 16p12.1 gene and the interaction models that explain how “second-hit” genes modulate the associated phenotypes have not been assessed. Therefore, a systematic evaluation of developmental, neuronal, and cellular defects caused by reduced expression of individual 16p12.1 genes, as well as their interactions with each other and with “second-hit” genes from patients with the deletion, would allow us to understand the functional basis of the variable phenotypes associated with the deletion. Drosophila melanogaster and Xenopus laevis serve as excellent models for systematic evaluation of developmental and tissue-specific effects of multiple genes and their genetic interactions, as they are amenable for rapid genetic manipulation and high-throughput evaluation. In fact, Drosophila have been classically used to study the roles of genes and genetic interactions towards developmental and neurological phenotypes [12–14]. For example, Grossman and colleagues overexpressed human transgenes from chromosome 21 in flies and identified synergistic interactions between DSCAM and COL6A2, which potentially contribute to the heart defects observed in individuals with Down syndrome [15]. Furthermore, functional assays using X. laevis have uncovered developmental defects, behaviors, and molecular mechanisms for several homologs of genes associated with neurodevelopmental disorders, such as NLGN1 [16], CACNA1C [17], GRIK2 [18], and PTEN [19].
Using Drosophila and X. laevis models, we recently found that multiple genes within the variably expressive 16p11.2 and 3q29 deletion regions individually contribute to neurodevelopmental defects [20,21], suggesting that no single gene could be solely causative for the wide range of defects observed with deletion of an entire region. Moreover, we identified complex genetic interactions within conserved biological pathways among homologs of genes affected by these CNVs. For example, fly and X. laevis homologs of NCBP2 enhanced the neuronal and cellular phenotypes of each of the other homologs of 3q29 genes [21], while fly homologs of 16p11.2 genes interacted in cellular proliferation pathways in an epistatic manner to enhance or suppress phenotypes of individual homologs [20]. In fact, several aspects of the interactions observed in our studies were also functionally or thematically validated in vertebrate model systems, providing further evidence for the utility of these models to study complex genetic interactions [22,23]. While our previous work showed pervasive interactions of homologs within regions associated with neurodevelopmental disease, the deletions within these regions occur primarily de novo [11], indicating a strong phenotypic impact associated with these CNVs. In contrast, the 16p12.1 deletion is mostly inherited and more frequently co-occurs with “second-hit” variants in affected individuals than other pathogenic CNVs [11], suggesting that interactions involving “second-hit” genes may confer a higher impact towards the variable neurodevelopmental phenotypes compared to those caused by interactions between genes within the CNV region.
Here, using Drosophila melanogaster and X. laevis as two complementary model systems of development, we present the first systematic assessment of conserved genes within the 16p12.1 deletion towards developmental, neuronal, and cellular phenotypes in functional models. We found that knockdown of each individual 16p12.1 homolog affects multiple phenotypic domains of neurodevelopment, leading to developmental delay and seizure susceptibility, brain size alterations, neuronal morphology abnormalities, and cellular proliferation defects. These defects were modulated by simultaneous knockdown of homologs of genes in established neurodevelopmental pathways and transcriptome targets, as well as homologs of genes that carried “second-hits” in affected children with the deletion, through genetic interactions and “additive” effects. Our results suggest a model where reduced expression of each individual gene within 16p12.1 is sufficient to sensitize the genome towards distinct neurodevelopmental defects, which are then modulated by complex interactions with “second-hit” genes.
Results
Multiple homologs of 16p12.1 genes contribute to Drosophila and X. laevis development
We identified four conserved fly homologs out of the seven human protein coding 16p12.1 genes using reciprocal BLAST and orthology prediction tools (S1 Table) [24]. Using RNA interference (RNAi) and the UAS-GAL4 system [25], we reduced the expression of the four fly homologs in a tissue-specific manner, and studied their individual contributions towards developmental, neuronal, and cellular defects (Fig 1). A complete list of the fly lines used in this study and full genotypes for all experiments are provided in S1 File. We authenticated the RNAi lines by confirming 40–60% expression of the four homologs using RT-qPCR (S1 Fig). We note that the genes are represented with fly gene names along with human counterparts at first mention in the text, and as fly genes with allele names in the figures.
We first assessed the global role of 16p12.1 homologs during development by decreasing their expression ubiquitously using the da-GAL4 driver, and detected larval lethality with knockdown of Sin (POLR3E) and larval and pupal lethality with knockdown of UQCR-C2 (UQCRC2) (Figs 2A and S2). Wing-specific bxMS1096-GAL4 mediated knockdown led to severe phenotypes for Sin and severe defects and lethality for UQCR-C2 fly models, recapitulating the observations made with ubiquitous knockdown (Figs 2A and S2) and suggesting a role for these homologs in signaling pathways required for early development [26–28]. Next, we evaluated whether decreased expression of the homologs leads to neuronal phenotypes frequently observed in animal models of neurodevelopmental disease, including altered lifespan, susceptibility to seizures, delayed developmental timing, changes in brain size, and dendritic arbor defects [29–34]. We observed early lethality in adult flies with nervous system-specific Elav-GAL4-mediated knockdown of Sin and CG14182 (MOSMO) (Fig 2B), while extended lifespan was observed with knockdown of UQCR-C2, as previously reported for Hsp26, Hsp27 [35], and SOD [36]. While altered mitochondrial activity has been shown to increase lifespan in Drosophila [37,38], further studies are necessary to understand the mechanism underlying this phenotype observed with knockdown of UQCR-C2. UQCR-C2 knockdown in the nervous system also led to significantly greater recovery time when subjected to mechanical stress during bang sensitivity assays, suggesting a higher susceptibility to developing seizures [32] (S2 Fig). Furthermore, evaluation of developmental transitions revealed delayed pupariation and larval lethality with knockdown of Sin, indicating a possible role for this gene in developmental timing, as well as partial larval lethality for CG14182 (Fig 2C). We also analyzed neuronal morphology in Drosophila class IV sensory neurons using the ppk-Gal4 driver [31,39,40], and identified reduced complexity of dendritic arbors during development for CG14182 (Fig 2D). Measurements of total area of the developing third instar larval brain led to reduced brain sizes with pan-neuronal knockdown of CG14182 and Sin (Figs 2E and S3), which corresponded with a decreased number of cells in the brain lobe stained with anti-phosphorylated-Histone 3 (pH3), a marker for proliferating cells (Fig 2F). Interestingly, Sin knockdown also led to a reduction in the number of apoptotic cells, as indicated by staining with anti-Death-caspase-1 (Dcp-1) (S3 Fig), likely reflecting its role in both proliferation and apoptotic processes [41,42].
We then performed RNA-sequencing of fly heads with pan-neuronal knockdown of the 16p12.1 homologs. Gene Ontology (GO) enrichment analysis of differentially expressed genes identified enrichments for multiple cellular, developmental, and neuronal processes (S4 Fig and S2 File). We found that each 16p12.1 homolog disrupted unique sets of genes and biological functions, as 1,386/1,870 (74%) differentially expressed genes and 28/52 (53.8%) enriched GO biological process terms were uniquely disrupted by one homolog (S4 Fig). Notably, we also observed this trend among the human homologs of differentially-expressed genes, with 654/994 (65.8%) uniquely differentially expressed genes and 353/428 (82.5%) GO terms uniquely disrupted by the 16p12.1 homologs, suggesting that they may act within independent pathways (S4 Fig). For example, knockdown of CG14182 altered the expression of fly homologs of human genes involved in synapse assembly and transmission (NLGN1, CEL) as well as histone methyltransferase binding (NOP56, CBX1). Similarly, human homologs of genes differentially expressed with knockdown of Sin were involved in neuronal projection, neurotransmitter release (such as CHRNA7, KCNAB2, and multiple solute carrier transport family genes, including SLC6A1), and GABA pathways (such as ADCY2, ADCY4, and ADCY7), as well as in the development of several non-neuronal organ systems, including cardiac, kidney, lung, and muscle, further indicating the importance of Sin towards global development.
Next, we examined developmental phenotypes associated with decreased dosage of homologs of 16p12.1 genes in X. laevis, a complementary vertebrate model system (Figs 1 and 2G). We injected homolog-specific morpholinos at two- or four-cell stage embryos to reduce the expression of each homolog to approximately 50% (partial knockdown), and further reduced expression with higher morpholino concentrations (stronger knockdown) to increase our sensitivity to detect more specific phenotypes (S1 Fig, see Materials and Methods). Reduced expression of mosmo and polr3e led to severe craniofacial defects in stage 42 tadpoles, as measured by specific facial landmarks, while milder defects were observed for cdr2 (Figs 2H and S5). This suggests a role for these homologs in key developmental processes involved in craniofacial morphogenesis, such as neural crest cell formation and migration [43–48], and could potentially explain the craniofacial changes observed in more than 50% of individuals with the 16p12.1 deletion [9]. We next examined axon outgrowth phenotypes in neural tube explants from stage 20–22 injected X. laevis embryos, and found that stronger knockdown of mosmo (20 ng morpholino) led to a significant reduction in axon length (Figs 2I and S5), suggesting a potential role for the homolog in cytoskeletal signaling processes involved in axon outgrowth [49]. Furthermore, stronger knockdown of mosmo (20 ng morpholino) and polr3e (20 ng morpholino) resulted in decreased forebrain and midbrain area (Figs 2J and S5), in concordance with the brain size defects we observed in Drosophila models. Interestingly, partial knockdown of mosmo (12 ng morpholino) also led to a severe reduction in forebrain and midbrain area (S5 Fig). Western blot analysis for whole embryo lysates using anti-pH3 antibody as a marker for cellular proliferation showed decreased proliferation with knockdown of polr3e, while knockdown of mosmo did not lead to any overt changes (S6 Fig). Overall, these results suggest that homologs of 16p12.1 genes individually contribute to multiple developmental defects and affect distinct developmental, neuronal, and cellular processes in Drosophila and X. laevis.
Weak genetic interactions and combined independent effects of 16p12.1 homologs mediate neurodevelopmental defects
Our previous studies identified several potential models for how genes within CNVs combinatorially influence neurodevelopmental phenotypes [20,21,50]. As multiple homologs of 16p12.1 genes contribute towards developmental, neuronal, and cellular phenotypes, we assessed the effect of simultaneous knockdown of pairs of 16p12.1 fly homologs. The Drosophila eye has been widely used to identify genetic interactions that disrupt ommatidial organization during development [51], and modifier genes for homologs of several human diseases, including Spinocerebellar ataxia type 1 [52], Huntington’s disease [52], and Fragile X syndrome [53], have been studied in flies. We assessed whether eye-specific GMR-GAL4 mediated knockdown of individual homologs led to phenotypes, and evaluated the severity of eye roughness using Flynotyper, a tool that quantifies the levels of ommatidial disorderliness in the adult fly eye [54]. We observed that knockdown of Sin led to a subtle disruption of ommatidial organization compared with controls, while no such phenotypes were observed with knockdown of other homologs (S7 Fig). Further reduction in expression of the 16p12.1 homologs using GMR-GAL4 and overexpression of Dicer2 led to more severe eye phenotypes for CG14182 and Sin (S7 Fig). As GMR-GAL4-mediated knockdown of the 16p12.1 homologs only exhibited modest eye phenotypes, we used Flynotyper scores as a sensitive quantitative trait with a wide dynamic range to assess for combinatorial effects of 16p12.1 homologs. We therefore generated GMR-GAL4 eye-specific recombinant lines for each homolog and crossed them with multiple RNAi lines for other 16p12.1 homologs (see Materials and Methods, S1 File), to test a total of 30 two-hit crosses for 12 pairwise knockdowns (Figs 1, 3A and S8).
We performed two independent analyses to interpret the combinatorial effect of 16p12.1 homologs on eye phenotypes. First, we assessed whether the phenotypic severity observed with knockdown of a 16p12.1 homolog is enhanced or suppressed with simultaneous knockdown of a second homolog. We observed significant changes in eye severity for four pairwise knockdowns compared with single hit recombinant lines crossed with controls, which were further validated with multiple RNAi lines (S3 File). For example, we observed that simultaneous knockdown of UQCR-C2 with Sin or CG14182 led to an increase in eye phenotype compared to knockdown of UQCR-C2 crossed with control (Fig 3B and 3C). Similarly, decreased expression of Sin led to an enhancement of the CG14182 eye phenotype. Second, to quantitatively assess whether the change in phenotypic severity due to pairwise knockdowns could be attributed to genetic interactions, we applied a “multiplicative” model to the Flynotyper scores (S9 Fig). The multiplicative model estimates the expected combined effect (i.e., no interaction) of two gene mutations as the product of the phenotypes observed with individual gene mutations (Figs 3D and S9), and identifies any deviation of the observed phenotypes from the expected values as positive (ameliorating the phenotype) or negative/synergistic (aggravating the phenotype) interactions. This strategy has been widely applied to identify fitness-based genetic interactions [55,56], and more recently, to assess for interactions contributing to non-fitness-related quantitative phenotypes, such as cell count, nuclear area [57], and protein folding in the endoplasmic reticulum [58]. After applying the multiplicative model to our pairwise interaction data, we identified five pairwise combinations of 16p12.1 homologs that were validated using multiple RNAi lines (S2 Table). Two pairwise combinations corresponded with no interactions, while the remaining three were positive genetic interactions, with an observed phenotype milder than expected (S3 File). Only one out of the four pairwise knockdowns that resulted in significant changes in eye severity compared with single hit recombinant lines crossed with control corresponded with a genetic interaction, while the rest were not validated across multiple fly lines tested (S3 File). To contextualize these observations, we compared the strength of genetic interactions among the 16p12.1 homologs to those of homologs of genes affected by the autism-associated 16p11.2 deletion, a region with reported pervasive genetic interactions [20]. We quantified the magnitude of genetic interactions using “interaction scores”, defined as the log2 ratio between the observed and expected phenotypic values from the multiplicative model (see Materials and Methods), and found significantly lower interaction scores for the 16p12.1 homologs compared to the 16p11.2 homologs (S4 File).
We further investigated the effects of the combined knockdown of homologs of MOSMO and POLR3E, genes that individually contributed to multiple defects in both fly and X. laevis models, towards X. laevis development (Figs 1 and 3E). Pairwise interactions in X. laevis models were tested using partial knockdown of the homologs to avoid potential lethality with stronger knockdown. Partial pairwise knockdown of polr3e (10 ng morpholino) and mosmo (12 ng morpholino) showed significantly reduced forebrain and midbrain area when compared to knockdown of polr3e alone (Fig 3F), but not when compared to knockdown of mosmo alone. Similarly, we assessed whether mosmo and polr3e interact to modulate cellular proliferation processes during X. laevis development and did not observe any changes in anti-pH3 signals with combined knockdown of polr3e and mosmo compared with knockdown of polr3e alone (Figs 3G and S6). Overall, our analysis in Drosophila and X. laevis suggest that 16p12.1 homologs contribute towards neurodevelopmental phenotypes through both weak genetic interactions and combined independent effects.
Homologs of 16p12.1 genes interact with genes in conserved neurodevelopmental pathways
We recently identified genetic interactions between fly homologs of CNV genes and conserved genes in neurodevelopmental pathways, providing functional evidence that phenotypes of CNV genes are modulated by key neurodevelopmental genes [20,21]. As our functional analyses showed that knockdown of each 16p12.1 homolog resulted in multiple neuronal and developmental phenotypes, we hypothesized that genes involved in conserved neurodevelopmental pathways could modulate phenotypes due to knockdown of 16p12.1 homologs through genetic interactions. We therefore performed 255 crosses to test 116 pairwise gene combinations between eye-specific recombinant lines for each of the four 16p12.1 homologs and 13 homologs of known neurodevelopmental genes and 39 homologs of transcriptional targets (Figs 4A and S10, S2 and S3 Tables). As validation, we used multiple RNAi, mutant or overexpression lines when available (Fig 1). Details of the number of homologs, fly lines, and crosses used for all interaction experiments are provided in S2 Table. First, we screened for 55 combinations between homologs of 16p12.1 genes and 13 homologs of human genes in established developmental pathways, such as synapse function (Prosap/SHANK3), cell division (Pten/PTEN), and chromatin modulation (kis/CHD8), as well as genes functionally related to 16p12.1 homologs [54,59–61]. Using Flynotyper to quantify adult eye defects and the multiplicative model to identify genetic interactions, we identified interactions specific to an individual 16p12.1 homolog or those involving multiple homologs (S11–S16 Figs and S3 File). For example, CG10465 (KCTD13) negatively interacted with UQCR-C2 and CG14182, leading to significantly more severe phenotypes than expected using the multiplicative model (Fig 4B). Similarly, simultaneous knockdown of Sin with kis led to an exaggerated eye phenotype, suggesting negative interactions between the genes (Fig 4B). Overall, we confirmed 22 interactions out of the 55 pairwise combinations (40%) tested, including both positive (12/55) and negative (10/55) effects (Figs 4C, 4D and S17 and S2 Table). Next, to identify interactors of 16p12.1 homologs towards developmental functions and pathways (S10 Fig and S3 Table), we screened for interactions of the homologs with 25 dysregulated fly genes selected from our transcriptome studies as well as 14 genes within enriched Gene Ontology categories, such as nervous system development and function (Dscam1, Asp, mGluR, NaCP60E), protein folding (Hsp23, Hsp26, Hsp70Ab), and muscle contraction (Actn, ck). We identified interactions for 42 out of 61 tested pairs (68.8%, S2 Table), validated using additional lines when available (S3 File). For example, knockdown of Gat (SLC6A1), Dscam4 (DSCAM), Nipped-A (TRRAP), and aurB (AURKB) each modified the eye phenotype due to knockdown of Sin through positive or negative genetic interactions (Figs 4C, S13, S16 and S3 File). Furthermore, the protein-folding gene Hsp26 (CRYAA) was differentially expressed with knockdown of Cen, and its overexpression enhanced the phenotype of Cen through a negative interaction (Figs 4C and S12 and S3 File). Overall, we identified 64 pairwise interactions between the 16p12.1 homologs and genes from established neuronal functions and transcriptome targets (Fig 4C and 4D and S2 Table), suggesting that phenotypes of 16p12.1 homologs can be modulated by genes within multiple neurodevelopmental pathways through genetic interactions.
Homologs of patient-specific “second-hit” genes modulate phenotypes of 16p12.1 homologs
We recently found that an increased burden of rare variants (or “second-hits”) outside of disease-associated CNVs, such as 16p11.2 deletion, 15q13.3 deletion, and 16p12.1 deletion, contributed to variability of cognitive and developmental phenotypes among affected children with these CNVs [8,9,11]. In fact, we found that severely affected children with the 16p12.1 deletion had additional loss-of-function or severe missense variants within functionally intolerant genes compared to their mildly affected carrier parents [8,9,11]. We hypothesized that homologs of genes carrying patient-specific “second-hits” modulate the effects of individual 16p12.1 homologs not only “additively” but also through genetic interactions (S10 Fig and S3 Table). To test this, we performed 227 crosses to study 96 pairwise interactions between eye-specific recombinant lines for each of the four 16p12.1 homologs and 46 RNAi or mutant lines for 24 homologs of patient-specific “second-hit” genes identified in 15 families with the 16p12.1 deletion (Figs 1 and S18 and S2–S4 Tables) [9]. Out of the 96 combinations tested, we identified 32 pairwise knockdowns that modulated the phenotype of a 16p12.1 homolog, confirmed with additional lines when available, for 11 out of 15 families carrying “second-hit” genes (Fig 5A–5C and S2–S4 Tables). In fact, the phenotypic effects of 16 out of 32 combinations were attributed to genetic interactions (Fig 4D and S3 File). Interestingly, we observed that different “second-hit” homologs showed distinct patterns of interactions with homologs of 16p12.1 genes (Fig 5B and S3 File). For example, the affected child in family GL_11 carried “second-hit” pathogenic mutations in NRXN1 and CEP135 (Fig 5A). Knockdown of the fly homolog Nrx-1 enhanced the eye phenotype caused by knockdown of Sin and UQCR-C2, while simultaneous knockdown of Cep135 with UQCR-C2 led to lower phenotypic score compared to knockdown of UQCR-C2 alone (Fig 5B and 5C). While the two-hit phenotypes were not significantly different from the expected combined effects of the individual genes in the above cases (S3 File), we observed genetic interactions between Nrx-1 and CG14182, and Cep135 and Sin or Cen, suggesting potential functional connections between these genes (Fig 5D). Interestingly, for 11/96 combinations tested with the multiplicative model, we found that the phenotype of the pairwise knockdown was more severe compared to the phenotype observed with the knockdown of an individual 16p12.1 homolog, but significantly less severe than the expected effects, suggesting potential buffering against deleterious combined independent effects of the genes [62,63] (Figs 4C and 5D and S3 File). In another example, the affected child in family GL_01 carried inherited “second-hit” variants in LAMC3 and DMD, as well as a de novo loss-of-function mutation in the intellectual disability-associated and chromatin regulator gene SETD5 [64] (S18 Fig). Knockdown of Lanb2, homolog of LAMC3, enhanced the phenotype caused by knockdown of UQCR-C2, although they positively interacted towards a milder phenotype than expected (Fig 4D and S3 File). Furthermore, upSET, homolog of SETD5, led to enhancements of the phenotypes caused by knockdown of Sin and CG14182 (S3 File). Interestingly, while the phenotype caused by simultaneous knockdown of Sin and upSET was not different from expected using the multiplicative model, upSET synergistically interacted with CG14182, leading to an enhanced eye phenotype with pairwise knockdown (Fig 6A). To assess the cellular changes affected by this interaction during development, we tested for alterations in apoptosis and proliferation in the third instar larval eye discs, and found that simultaneous knockdown of CG14182 and upSET led to an increased number of cells undergoing proliferation and apoptosis compared to knockdown of CG14182 alone (Fig 6B). Interestingly, we also identified interactions between CG14182 and other chromatin modifier genes, including Nipped-A, a transcriptional target of Sin, and Osa, homolog of the “second-hit” gene ARID1B, identified in family GL_13 (S16 Fig and S3 File). These interactions also modulated cellular proliferation and apoptosis processes in the developing eye discs observed with knockdown of CG14182 (S19 Fig).
We further evaluated whether interactions between the fly homologs of POLR3E and MOSMO with SETD5 were also conserved during vertebrate development, and studied brain and axon outgrowth phenotypes of homologs of these genes in X. laevis (Fig 1). We observed that simultaneous knockdown of polr3e and setd5 led to smaller forebrain and midbrain areas compared with polr3e knockdown alone (S20 Fig). Similarly, simultaneous knockdown of mosmo and setd5 led to a further reduction in midbrain area than that observed with knockdown of mosmo alone (Fig 6C). Furthermore, analysis of axon outgrowth in developing X. laevis embryos showed that simultaneous knockdown of mosmo and setd5 led to significantly reduced axon length compared to the individual knockdowns of either mosmo or setd5, while no changes were observed with simultaneous knockdown of polr3e and setd5 (Figs 6D and S20). In fact, the axon outgrowth defect observed with simultaneous knockdown of mosmo and setd5 was not observed with partial knockdown of either individual homolog. This result suggests a potential interaction between mosmo and setd5 during vertebrate nervous system development. Overall, our results show that interactions with “second-hit” genes can modulate neurodevelopmental and cellular phenotypes associated with homologs of 16p12.1 genes.
Discussion
We previously described multiple models for how genes within CNVs contribute towards neurodevelopmental phenotypes [20,21,50]. Here, we analyzed neurodevelopmental defects and cellular and molecular mechanisms due to individual and pairwise knockdown of conserved 16p12.1 homologs in Drosophila and X. laevis, and evaluated how these defects are modulated by homologs of “second-hit” genes. Our results provide multiple hypotheses for how genes within the deletion contribute to neurodevelopmental phenotypes. First, in line with our previous findings for homologs of genes within CNV regions [20,21], our results show that no single homolog within the 16p12.1 region is solely responsible for the observed neurodevelopmental phenotypes. In fact, we observed a global developmental role for multiple 16p12.1 homologs, as well as specific roles of each homolog towards craniofacial and brain development (S5 Table). This was further confirmed by interactions of 16p12.1 homologs with genes in conserved neurodevelopmental pathways. Our findings are in accordance with the core biological functions described for some of these genes. For example, POLR3E encodes a cofactor of the RNA polymerase III, which is involved in the transcription of small RNA, 5S ribosomal RNA, and tRNA [65], while MOSMO is a negative regulator of the hedgehog signaling pathway [66]. Second, knockdown of individual homologs sensitized both model organisms towards specific phenotypes. For example, knockdown of homologs of MOSMO led to neuronal morphology defects and knockdown of homologs of POLR3E led to brain size phenotypes that correlated with cellular proliferation defects in both model systems, while knockdown of UQCR-C2 led to seizure susceptibility in flies. Third, we found that the 16p12.1 homologs were less likely to interact with each other (3 interactions out of 12 pairs tested) compared to their interactions with downstream transcriptome targets (42 interactions out of 61 pairs tested, Fisher’s exact test, p = 0.0077). These results suggest reduced functional overlap among the 16p12.1 homologs, an observation supported by the distinct sets of biological functions enriched among the differentially expressed genes obtained with knockdown of each individual homolog (S4 Fig). Beyond the four conserved homologs evaluated in this study, little functional information is available on the other genes in the region, including VWA3A and PDZD9 as well as non-protein coding genes. Results from mouse models of EEF2K, which encodes a kinase associated with protein synthesis elongation, have postulated associations of this gene with synaptic plasticity [67], learning and memory [68], atherosclerosis-mediated cardiovascular disease [69], and depression [70]. Although EEF2K could function in concert with the tested 16p12.1 genes to contribute towards neurodevelopmental features, it showed low connectivity (29th percentile) to other 16p12.1 genes in a human brain-specific interaction network compared to the pairwise connectivity of all genes in the network [71,72] (S5 File). VWA3A showed even lower connectivity (5th percentile) to other 16p12.1 genes compared to all gene pairs. Further functional analyses that include all protein-coding and non-coding genes are necessary for a comprehensive understanding of the consequences of the entire deleted region, as these genes may also contribute towards the pathogenicity of 16p12.1 deletion.
We recently showed that additional variants or “second-hits” modulate the manifestation of developmental and cognitive phenotypes associated with disease-causing variants, including intelligence quotient and head circumference phenotypes [8,9,11]. Using the 16p12.1 deletion as a paradigm for a complex disorder, we examined how homologs of genes carrying “second-hit” variants modulate the phenotypes caused by decreased expression of individual CNV homologs. For example, homologs of ARID1B, CEP135 and CACNA1A suppressed the eye phenotypes and interacted with one or more 16p12.1 homologs. Furthermore, we identified a negative interaction between homologs of MOSMO and SETD5, which led to novel neurodevelopmental phenotypes in both Drosophila and X. laevis compared with knockdown of either individual homolog. Interestingly, mouse embryonic stem cells lacking Setd5 exhibited dysregulation of genes involved in hedgehog signaling [73], a key pathway recently associated with MOSMO function [66]. Moreover, we observed that MOSMO and SETD5 are highly connected to each other in a human brain-specific interaction network compared to all genes in the genome (top 84th percentile compared to all genetic interactions with MOSMO), suggesting that the human genes may also be functionally related [71,72]. We further observed interactions between CG14182 and other genes with chromatin regulating function, such as Nipped-A (TRRAP) and osa (ARID1B) (S16 Fig). Based on these observations, we propose that while genes carrying “second-hit” variants in combination with the deletion may “additively” contribute towards more severe phenotypes, they may also interact towards developmental phenotypes, conferring high impact towards variable defects associated with the 16p12.1 deletion (S21 Fig). The ultimate nature of the interactions will depend on the role of the individual CNV genes towards specific phenotypes, the identity of genes carrying “second-hits”, as well as the molecular complexity associated with each phenotypic domain [50].
The high inheritance rate of the 16p12.1 deletion [8,9] suggests that while it confers risk for several phenotypes, the CNV can be transmitted through multiple generations until additional variants accumulate and cumulatively surpass the threshold for severe disease [7]. In contrast, other CNVs associated with neurodevelopmental disease, such as the autism-associated 16p11.2 deletion and the 17p11.2 deletion that causes Smith-Magenis syndrome, occur mostly de novo and are less likely to co-occur with another “second-hit”, suggesting a higher pathogenicity on their own [11,74,75]. For example, the 16p11.2 deletion occurs de novo in approximately 66% of the cases, and only 8% of the affected children carry another rare large CNV, in contrast to 25% of severely affected children with 16p12.1 deletion that carry a “second-hit” large CNV [11]. When we compared experimental results from 16p12.1 homologs with those from fly homologs of 16p11.2 genes [20], we found evidence that the varying pathogenicity of the CNVs could be explained by differential connectivity and combinatorial effects of genes within each region (Fig 7A) [76]. For example, we previously found that 24 out of the 52 tested pairwise knockdowns of 16p11.2 homologs led to enhancement or suppression of phenotypes, significantly modifying the effect of the individual genes [20]. In contrast, only four out of twelve tested combinations between 16p12.1 homologs led to a slight change in phenotypic severity, which in aggregate showed lower phenotypic scores than those observed for pairwise knockdown of 16p11.2 homologs (Figs 7B and S22). In fact, using a multiplicative model, we found that the magnitude of interactions between homologs of 16p11.2 genes was stronger than that observed between 16p12.1 homologs (Fig 7C). Moreover, transcriptome analyses showed a higher overlap of differentially expressed genes among 16p11.2 homologs compared to 16p12.1 homologs, further suggesting a higher functional relatedness among the 16p11.2 genes (Fig 7D). We similarly compared the connectivity of genes within both CNV regions in a human brain-specific interaction network [71,72], and found that 16p11.2 genes were more strongly connected to each other than were 16p12.1 genes, and were also more strongly connected to each other than with other genes in the genome (Figs 7E, 7F and S22). Furthermore, the connectivity of 16p12.1 genes was lower than 99.6% of connectivity values of simulated sets of six 16p11.2 genes (0.4th percentile). In fact, the connectivity values of genes within 16p12.1 and 16p11.2 were in the lower (~6th) and higher (~79th) percentiles of connectivity values from simulated sets of contiguous genes in the genome, respectively (S23 Fig). Interestingly, genes connecting pairs of 16p11.2 genes were enriched for genes intolerant to functional variation (Fig 7E and 7G), such as ASH1L, a histone methyltransferase activator and autism candidate gene [77], and CAMK2B, a protein kinase gene causative for intellectual disability [78]. In contrast, connector genes unique to 16p12.1 genes were not associated with neurodevelopmental disease or enriched for genes intolerant to variation (S5 File). This suggests that the 16p11.2 deletion disrupts a tight network of key genes in the brain, including other neurodevelopmental genes and genes with disease relevance [79,80]. Overall, we propose that 16p12.1 genes contribute towards multiple neurodevelopmental phenotypes through weak genetic interactions and “additive” effects and exhibit less functional connectivity compared with 16p11.2 genes, leading to a high transmissibility of the deletion and allowing for “second-hit” variants to modulate neurodevelopmental phenotypes.
Our study provides the first systematic analysis of individual and pair-wise contributions of 16p12.1 homologs towards neurodevelopmental phenotypes and associated cellular and molecular mechanisms, and identifies a key role of genetic interactions with “second-hit” homologs towards variability of phenotypes. Our work does not intend to recapitulate human disease, but rather highlights the basic cellular roles of individual conserved genes and their interactions towards neurodevelopmental phenotypes. As such, these findings should be further examined in higher-order model systems, including mouse and human cellular models. Our functional analyses suggest a model where 16p12.1 genes sensitize an individual towards defects in different domains of neurodevelopment, but the ultimate phenotypic manifestation may depend on complex interactions with “second-hits” in the genetic background.
Materials and methods
Ethics statement
All X. laevis experiments were approved by the Boston College Institutional Animal Care and Use Committee (Protocol #2016–012), and were performed according to national regulatory standards.
Drosophila stocks and genetics
Using Ensembl database [81], NCBI Protein-Protein BLAST tool [82], and DRSC Integrative Ortholog Prediction Tool (DIOPT) [24], we identified four homologs out of the seven genes within the 16p12.1 deletion region in Drosophila melanogaster (S1 Table). No fly homologs were present for three genes, including VWA3A, PDZD9 and EEF2K. Similar strategies were used to identify fly homologs of conserved neurodevelopmental genes and genes carrying “second-hits” in children with the 16p12.1 deletion. Fly Atlas Anatomy microarray expression data from FlyBase confirmed the expression of each 16p12.1 homolog in the nervous system during Drosophila development (S1 Table) [83], and expression data from Xenbase [84] confirmed the expression of the homologs in X. laevis brain.
Multiple RNAi lines were used to test neurodevelopmental defects of 16p12.1 homologs (S1 File). RNAi, mutant, or overexpression lines for fly homologs were obtained from the Vienna Drosophila Resource Center (VDRC), Bloomington Drosophila Stock Center (BDSC) (NIH P40OD018537), or Kyoto Stock Center (S1 File). The following lines used were generated in various research labs: Drice17_1 and Drice17_2 from Bergmann lab [85], GluRIIB Overexp EGFP from Sigrist lab [86], Hsp26Overexp Hsp26 from Benzer lab [35], and Hsp70AbOverexp Hsp70-9.1 and Hsp70AbOverexp Hsp70-4.3 from Robertson lab [87]. Tissue-specific knockdown of homologs of 16p12.1 genes was achieved using the UAS-GAL4 system [25], with specific GAL4 lines including w1118;dCad-GFP, GMR-GAL4/CyO (Zhi-Chun Lai, Penn State University), w1118;GMR-GAL4; UAS-Dicer2 (Claire Thomas, Penn State University), w1118,mcd8-GFP, Elav-GAL4/Fm7c;; UAS-Dicer2 (Scott Selleck, Penn State University), w1118,Elav-GAL4 (Mike Groteweil, VCU), w1118;;Elav-GAL4,UAS-Dicer2 (Scott Selleck, Penn State University), w1118;da- GAL4 (Scott Selleck, Penn State University), w1118,bxMS1096-GAL4;; UAS-Dicer2 (Zhi-Chun Lai, Penn State University), and UAS-Dicer2; ppk-GAL4, UAS-mCD8-GFP (Melissa Rolls, Penn State University). A list of full genotypes for all fly lines and crosses tested in this study is provided in S1 File. Fly crosses were reared on a cornmeal-sucrose-dextrose-yeast medium at room temperature (RT), 25°C or 30°C. For all experiments, RNAi lines were compared to a control with the same genetic background to account for background-specific effects (S1 File). Three different controls were used: w1118 from VDRC (GD stock # 60000), in which inverted repeats are inserted by P-element insertion; y,w1118 from VDRC (KK stock # 60100), where inverted repeats are inserted by site-specific recombination; and {y[1] v[1]; P{y[+t7.7] = CaryP}attP2 from BDSC (TRiP stock # 36303).
RT-quantitative PCR for Drosophila RNAi knockdown of 16p12.1 homologs
Decreased expression of homologs of 16p12.1 genes in the nervous system was confirmed using reverse transcription quantitative PCR (RT-qPCR) for individual Drosophila RNAi lines. Decreased expression of the genes was achieved using Elav-GAL4;;UAS-Dicer2 lines, reared at 25°C. As nervous system-specific knockdown of Sin with Elav-GAL4;;UAS-Dicer2 caused developmental lethality in all three RNAi lines tested (SinGD7027, SinKK101936, SinHMC03807), we confirmed knockdown of Sin using Elav-GAL4 without overexpression of Dicer2 and reared at RT. We note that all experiments with nervous system-specific knockdown of Sin were performed under these conditions. Briefly, three biological replicates, each containing 35–40 female heads, were collected after being separated by repeated freezing in liquid nitrogen and vortex cycles. Total RNA was extracted from Drosophila heads using TRIzol (Invitrogen, Carlsbad, CA, USA), and cDNA was generated using qScript cDNA synthesis kit (Quantabio, Beverly, MA, USA). Quantitative RT-PCR was performed in an Applied Biosystems Fast 7500 system using SYBR Green PCR master mix (Quantabio), with rp49 as the reference gene. Primers were designed using NCBI Primer-BLAST [88], with primer pairs separated by an intron in the corresponding genomic DNA, if possible. S6 Table details the primers used to quantify the level of expression of 16p12.1 homologs. The delta-delta Ct method was used to calculate the percentage of expression compared to the control [89], and statistical significance compared to the control was determined using t-tests.
Eye and wing imaging
Eye-specific knockdown of the 16p12.1 homologs was achieved using GMR-GAL4 driver at 30°C. Female progeny were collected on day 2–3 and imaged using an Olympus BX53 compound microscope with LMPLan N 20X air objective and a DP73 c-mount camera at 0.5X magnification, with a z-step size of 12.1μm (Olympus Corporation, Tokyo, Japan). Individual image slices were captured using the CellSens Dimension software (Olympus Corporation, Tokyo, Japan), and were stacked into their maximum projection using Zerene Stacker software (Zerene Systems, Richland, WA, USA). Wing phenotypes were assessed in day 2–5 female progeny from bxMS1096-GAL4 lines crossed to the RNAi lines at 25°C. Adult wings were imaged using a Zeiss Discovery V20 stereoscope (Zeiss, Thornwood, NY, USA) and a ProgRes Speed XT Core 3 camera (Jenoptik AG, Jena, Germany) with a 40X objective. Adult wing images were captured using ProgRes CapturePro v.2.8.8 software. We characterized qualitative phenotypes for between 10–20 wing images, including curly, wrinkled, shriveled, dusky or vein defects, and 10–30 eye images were assessed for rough, glazed, eye size, and necrotic patches defects. Quantitative assessment of rough adult eye phenotypes was performed using a software called Flynotyper [20,54], which calculates a phenotypic score for each eye image by integrating the distances and angles between neighboring ommatidia. The phenotypic scores generated by Flynotyper were compared between RNAi lines and their respective controls using one-tailed Mann-Whitney tests, with Benjamini-Hochberg correction for multiple tests.
Lifespan measurement
Lifespan assessment of homologs of 16p12.1 genes was performed as previously reported [90]. Briefly, fly crosses were set up at 25°C with Elav-GAL4;;UAS-Dicer2 for each of the fly homologs, or Elav-GAL4 at RT for SinGD7027. In all cases, the newly emerged progeny were collected every day for five consecutive days, and the birth date was recorded. F1 flies were allowed to mate for 24 hours, and were separated under CO2 into at least four vials, each containing 20 females. Vials were transferred every 2–3 days, and the age and number of living flies were registered. One-way repeated measures ANOVA with post-hoc pairwise t-tests were performed to identify changes in lifespan for the individual 16p12.1 homologs.
Bang-sensitive assay
Sensitivity to mechanical stress was assessed in females with decreased expression of 16p12.1 homologs in the nervous system, using Elav-GAL4;;UAS-Dicer2 and reared at 25°C. Sin was excluded from the analysis, as adult flies with Elav-GAL4 knockdown of the gene exhibited severe motor defects. Ten female flies from the progeny were collected on day 0–1 for ten consecutive days, and experiments were performed on day 2–3. Flies were individually separated under CO2 24 hours before the experiments, collected in culture vials containing food, and transferred to another empty culture vial the day of the experiment. Identification of bang-sensitive phenotypes was performed as previously reported [91]. Each vial was vortexed at maximum speed (Fischer Scientific) for 15 seconds, and the time for each fly to recover from paralysis was registered. Differences in bang-sensitivity compared with controls were identified using two-tailed Mann-Whitney tests.
Assessment of delay in developmental timing
Pupariation time was assessed in third instar larvae obtained from crosses between RNAi lines and w1118;;Elav-GAL4,UAS-Dicer2 or w1118,Elav-GAL4 flies. Developmentally-synced larvae were obtained from apple juice plates with yeast paste, and were reared for 24 hours. Thirty newly emerged first instar larvae were transferred to culture vials, for a total of four to ten vials per RNAi line tested. The number of larvae transitioning to pupae were counted every 24 hours. Significant differences in pupariation timing compared with the control across the duration of the experiment were identified with one-way repeated measures ANOVA and post-hoc pairwise t-tests.
Dendritic arborization experiments
Class IV sensory neuron-specific knockdown was achieved by crossing the RNAi lines to UAS-Dicer2; ppk-GAL4 driver at 25°C in apple juice plates. First instar larvae were collected and transferred to cornmeal-based food plates for 48 hours. Z-stack images of the dorsal side of third instar larvae were obtained using a Zeiss LSM 800 (Zeiss, Thornwood, NY, USA) confocal microscope. To perform Sholl analyses, we assessed the number of intersections of dendrite branches with four concentric circles starting from the cell body and separated by 25 μm. The total number of intersections was normalized to the width of the larval hemi-segment, and significant changes compared with control were assessed using two-tailed Mann-Whitney tests.
Measurement of larval brain area
Larval brain area was assessed in third instar larvae obtained from crosses between the RNAi lines with Elav-GAL4. Crosses were set up in apple plates containing yeast paste to control for size effects generated by food availability. Fifteen first instar larvae were transferred to culture vials containing a fixed volume (8–10 mL) of cornmeal-based food. Brains were dissected from third instar larva in PBS (13mM NaCl, 0.7mM Na2HPO4, and 0.3mM NaH2PO4), fixed in 4% paraformaldehyde in PBS for 20 minutes, washed three times in PBS, and mounted in Prolong Gold antifade reagent with DAPI (Thermo Fisher Scientific, P36930). Z-stacks of Drosophila brains were acquired every 10μm with a 10X air objective with 1.2X magnification using an Olympus Fluoview FV1000 laser scanning confocal microscope (Olympus America, Lake Success, NY). The area of the maximum projection of the Z-stack was measured using Fiji software [92]. Differences in brain area were assessed using two-tailed Mann-Whitney tests.
RNA sequencing and differential expression analysis in Drosophila melanogaster
RNA sequencing was performed for three biological replicates of RNA isolated from 35–40 Drosophila heads with Elav-GAL4 mediated nervous system-specific knockdown of 16p12.1 homologs as well as controls with matching drivers and rearing temperatures. cDNA libraries were prepared with TruSeq Stranded mRNA LT Sample Prep Kit (Illumina, San Diego, CA). Single-end 100bp sequencing of the cDNA libraries was performed using Illumina HiSeq 2000 at the Pennsylvania State University Genomics Core Facility, at an average coverage of 35.1 million reads/sample. Quality control was performed using Trimmomatic [93], and raw sequencing data was aligned to the fly reference genome and transcriptome build 6.08 using TopHat2 v.2.1.1 [94]. Total read counts per gene were calculated using HTSeq-Count v.0.6.1 [95]. Differences in gene expression were identified using a generalized linear model method in edgeR v.3.20.1 [96], with genes showing a log2-fold change >1 or < -1 and with a Benjamini-Hochberg corrected FDR<0.05 defined as differentially expressed. Human homologs of differentially-expressed genes in flies were identified using DIOPT v7.0. Biological pathways and processes affected by downregulation of homologs of 16p12.1 genes, defined as significant enrichments of Gene Ontology (GO) terms (p<0.05, Fisher’s exact test with Benjamini-Hochberg multiple testing correction), were identified using PantherDB [97].
Pairwise knockdowns in the fly eye
To study genetic interactions in the fly eye, we generated recombinant stock lines for each 16p12.1 homolog by crossing RNAi lines with eye-specific GMR-GAL4, as detailed in S1 File. Various factors including presence of balancers, chromosomal insertion of the shRNA, lethality with Elav-GAL4, and severity of eye phenotypes with GMR-GAL4 were considered to select RNAi lines for generating recombinant lines. For example, for CG14182, we used the GD RNAi line CG14182GD2738, which showed milder eye phenotypes, in order to test a wider range of potential interactions. We assessed genetic interactions between homologs of 16p12.1 genes with each other as well as with homologs of “second-hits” identified in children with the 16p12.1 deletion, conserved neurodevelopmental genes, and select transcriptional targets. A total of 24 homologs of genes carrying “second-hits” were selected as disease-associated genes carrying rare (ExAC frequency ≤1%) copy-number variants, loss-of-function (frameshift, stopgain or splicing) mutations, or de novo or likely-pathogenic (Phred-like CADD ≥25) missense mutations previously identified from exome sequencing and SNP microarrays in 15 affected children with the 16p12.1 deletion and their family members [9,98,99]. We also selected seven conserved genes strongly associated with neurodevelopmental disorders [20,54] and six genes with previously described functional associations with individual 16p12.1 genes, such as mitochondrial genes for UQCRC2 [59] and Myc for POLR3E and CDR2 [60,61]. We also tested interactions of the 16p12.1 homologs with 25 differentially-expressed genes (or “transcriptome targets”) and 14 genes selected from enriched Gene Ontology groups identified from RNA sequencing experiments (S3 File). Overall, we tested 212 pairwise gene interactions including 96 interactions with homologs of “second-hit” genes, 55 with neurodevelopmental genes, and 61 with transcriptome targets, using multiple RNAi, mutant or overexpression lines per gene when available (S2 Table).
GMR-GAL4 recombinant lines for the homologs of 16p12.1 genes were crossed with RNAi or mutant lines for the interacting genes to achieve simultaneous knockdown of two genes in the eye. We also tested overexpression lines for specific genes that are functionally related to 16p12.1 homologs, including Myc, Hsp23, and Hsp26. Our previous assessment showed no changes in phenotypic scores for recombinant lines crossed with UAS-GFP compared to crosses with controls, demonstrating that the lines have adequate GAL4 to bind to two independent UAS-RNAi constructs [20].
To evaluate how simultaneous knockdown of interacting genes modulated the phenotype of 16p12.1 homologs, Flynotyper scores from flies with double knockdowns were compared to the scores from flies obtained from crosses between 16p12.1 recombinant lines and controls carrying the same genetic background as the interacting gene. Significant enhancements or suppressions of phenotypes of 16p12.1 homologs were identified using two-tailed Mann-Whitney tests and Benjamini-Hochberg multiple testing correction (S3 File).
Analysis of genetic interactions using the multiplicative model
The nature of genetic interactions between pairs of gene knockdowns was determined using a multiplicative model, which has been widely used for evaluating genetic interactions for quantitative phenotypes in yeast, Drosophila, and E. coli models [55–58,100]. This model tests whether the observed phenotypic effect of simultaneously knocking down two genes is different from the expected product of effects due to knockdown of individual genes. We first normalized Flynotyper scores for each individual line and pairwise knockdown to the Flynotyper scores from the background-specific controls to obtain normalized phenotypic scores as “percentage of control.” We then calculated the expected effects as the product of the averages of normalized scores for the two individual gene knockdowns, and compared the expected scores to the normalized scores from pairwise knockdowns using a two-tailed one-sample Wilcoxon signed ranked test with Benjamini-Hochberg correction. The distributions of the expected and observed values for all individual pairs of genes and pairwise knockdowns are shown in S9 Fig. Pairwise knockdowns where the observed effects were significantly higher than expected were categorized as negative, aggravating or synergistic genetic interactions, while those with observed values significantly lower than expected were considered as positive or alleviating interactions. Pairwise knockdowns where the observed effects were not significantly different from the expected effects were considered as not interacting. The magnitude of a genetic interaction was measured using “interaction scores”, calculated as the log2 ratio between the observed and expected values (S4 File). Positive interaction scores indicated negative or aggravating genetic interactions, while negative interaction scores indicated positive or alleviating genetic interactions. An interaction was considered to be validated when the observed trend was reproduced by multiple fly lines when available. Interactions assessed with only one fly line were considered as “potential negative”, “potential positive” or “potential no interaction” (S3 File). To compare interactions of 16p12.1 homologs to 16p11.2 homologs, we obtained Flynotyper phenotypic scores from single and pairwise GMR-GAL4-mediated knockdown of 16p11.2 homologs, previously described in Iyer et al. [20].
Immunohistochemistry of the developing brain and eye discs in Drosophila melanogaster
Third instar larvae brain or eye discs were dissected in PBS and fixed in 4% paraformaldehyde in PBT (0.3% Triton X-100 in PBS), followed by three washes with PBT. Preparations were blocked for one hour in blocking buffer (5% FBS or 1% BSA in 0.3% PBT), followed by incubation overnight at 4°C with the primary antibody. We assessed for markers of proliferation using mouse anti-pH3 (S10) (1:100; 9706, Cell Signaling Technology, Danvers, MA, USA) and apoptosis using rabbit anti-Dcp-1 (Asp216) (1:100, 9578, Cell Signaling). Secondary antibody incubation was performed using Alexa fluor 647 goat anti-mouse (1:100, Invitrogen, Carlsbad, CA, USA) and Alexa fluor 568 goat anti-rabbit (1:100, Invitrogen) for 2 hours at 25°C, followed by three washes with PBT. Tissues were mounted in Prolong Gold antifade reagent with DAPI (Thermo Fisher Scientific, P36930) prior to imaging. Z-stacks of brain lobe or eye discs were acquired every 4μm with a 40X air objective with 1.2X magnification using an Olympus Fluoview FV1000 laser scanning confocal microscope (Olympus America, Lake Success, NY). Image analysis was performed using Fiji [92]. The number of cells undergoing proliferation or apoptosis were quantified throughout the brain lobe, or posterior to the morphogenetic furrow in the developing eye discs. The total number of Dcp-1 positive cells in larval brain and eye discs, as well as pH3 cells in the eye discs, were manually counted from the maximum projections. The total number of pH3 positive cells in the larval brain were quantified using the MaxEntropy automated thresholding algorithm per slice, followed by counting the number of particles larger than 1.5 μm. Differences in the number of positive pH3 or Dcp-1 cells were compared with appropriate controls using two-tailed Mann-Whitney tests.
Xenopus laevis embryos
Eggs collected from female X. laevis frogs were fertilized in vitro, dejellied, and cultured following standard methods [16,101]. Embryos received injections of exogenous mRNAs or antisense oligonucleotide strategies at the two- or four-cell stage, using four total injections performed in 0.1X MMR media containing 5% Ficoll. Embryos were staged according to Nieuwkoop and Faber [102].
X. laevis gene knockdown and rescue
Morpholinos (MOs) were targeted to early splice sites of X. laevis mosmo, polr3e, uqcrc2, cdr2, and setd5, or standard control MO (S7 Table), purchased from Gene Tools (Philomath, OR). In knockdown experiments, all MOs were injected at either the 2-cell or 4-cell stage, with embryos receiving injections two or four times total. mosmo and control MOs were injected at 12 ng/embryo for partial and 20 ng/embryo for stronger knockdown; polr3e and control MOs were injected at 10 ng/embryo for partial and 20 ng/embryo for stronger; uqcrc2 and control MOs were injected at 35 ng/embryo for partial and 50 ng/embryo for stronger; cdr2 and control MOs were injected at 10 ng/embryo for partial and 20ng for stronger knockdown; and setd5 and control MOs were injected at 10 ng/embryo for partial knockdown. All double knockdown experiments were performed with partial knockdown to avoid potential lethality.
Splice site MOs were validated using RT-PCR. Total RNA was extracted using Trizol reagent, followed by chloroform extraction and ethanol precipitation from 2-day old embryos injected with increasing concentrations of MO targeted to each 16p12.1 homolog, respectively. cDNA was synthesized using SuperScript II Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA). PCR was performed in a Mastercycler using HotStarTaq DNA Polymerase (Qiagen, Germantown, MD, USA) following manufacturer instructions. PCR was performed using primers with sequences detailed in S6 Table. RT-PCR was performed in triplicate, and band intensity was measured using the densitometry function in ImageJ [103] and normalized to the uninjected control mean relative to the housekeeping control odc1. Phenotypes were rescued with exogenous mRNAs co-injected with their corresponding MO strategies. X. laevis ORF for mosmo was purchased from the European Xenopus Resource Center (EXRC, Portsmouth, UK) and gateway-cloned into pCSF107mT-GATEWAY-3’GFP destination vector. Constructs used were mosmo-GFP, and GFP in pCS2+. In rescue experiments, MOs of the same amount used as for the knockdown of each homolog were co-injected along with mRNA (1000pg/embryo for mosmo-GFP) in the same injection solution.
Quantifying craniofacial shape and size of X. laevis embryos
The protocol for quantifying craniofacial shape and size was adapted from Kennedy and Dickinson [104]. Embryos at stage 42 were fixed overnight in 4% paraformaldehyde in PBS. A razor blade was used to make a cut bisecting the gut to isolate the head. Isolated heads were mounted in small holes in a clay-lined dish containing PBS. Frontal and lateral view images were taken using a Zeiss AxioCam MRc attached to a Zeiss SteREO Discovery.V8 light microscope (Zeiss, Thornwood, NY, USA). ImageJ software [103] was used to perform craniofacial measurements, including: 1) facial width, which is the distance between the eyes; 2) face height, which is the distance between the top of the eyes and the top of the cement gland at the midline; 3) dorsal mouth angle, which is the angle created by drawing lines from the center of one eye, to the dorsal midline of the mouth, to the center of the opposite eye; and 4) midface area, which is the area measured from the top of the eyes to the cement gland encircling the edges of both eyes. For all facial measurements, two-tailed student’s t-tests were performed between knockdown embryos and control MO-injected embryos with the same amount of morpholino.
Neural tube explants, imaging, and analysis
Embryos were injected with either control MO or 16p12.1 homolog-specific MO at the 2–4 cell stage, and culturing of Xenopus embryonic neural tube explants from stage 20–22 embryos were performed as previously described [101]. For axon outgrowth analysis, phase contrast images of axons were collected on a Zeiss Axio Observer inverted motorized microscope with a Zeiss 20X/0.5 Plan Apo phase objective (Zeiss, Thornwood, NY, USA). Raw images were analyzed by manually tracing the length of individual axons using the NeuronJ plug-in in ImageJ [105]. All experiments were performed on multiple independent occasions to ensure reproducibility. Axon outgrowth data were normalized to controls from the same experiment to account for day-to-day fluctuations. Statistical differences were identified between knockdown embryos and control MO-injected embryos with same amounts of morpholino using two-tailed student’s t-tests.
Immunostaining for brain morphology, imaging, and analysis
For brain morphology analysis, half embryo KDs were performed at the two-cell stage. X. laevis embryos were unilaterally injected two times with either control MO or 16p12.1 homolog-specific MO and a GFP mRNA construct (300pg/embryo). The other blastomere was left uninjected. Embryos were raised in 0.1X MMR through neurulation, and then sorted based on left/right fluorescence. Stage 47 embryos were fixed in 4% paraformaldehyde diluted in PBS for one hour, rinsed in PBS, and gutted to reduce autofluorescence. Embryos were processed for immunoreactivity by incubating in 3% bovine serum albumin and 1% Triton-X 100 in PBS for two hours, and then incubated in anti-acetylated tubulin (1:700, T7451SigmaAldrich, St. Louis MO, USA) and goat anti-mouse Alexa Fluor 488 conjugate secondary antibody (1:1000, Invitrogen, Carlsbad, CA, USA). Embryos were rinsed in 1% Tween-20 in PBS and imaged in PBS. Removal of the skin dorsal to the brain was performed if the brain was not clearly visible due to pigment.
Images were taken at 3.2X magnification using a Zeiss AxioCam MRc attached to a Zeiss SteREO Discovery.V8 light microscope (Zeiss, Thornwood, NY, USA). Images were processed in ImageJ [103]. The areas of the forebrain and midbrain were determined from raw images using the polygon area function in ImageJ. Brain sizes were quantified by taking the ratio of forebrain and midbrain areas between the injected side versus the uninjected side for each sample. All experiments were performed on at least three independent occasions to ensure reproducibility, and data shown represent findings from multiple replicates. Statistical differences were identified between knockdown embryos and control MO injected embryos with the same amount of morpholino using two-tailed student’s t-tests.
Western blot for cell proliferation
Embryos at stage 20 to 22 were lysed in buffer (50mM Tris pH 7.5, 1% NP40, 150mM NaCl, 1mM PMSF, 0.5 mM EDTA), supplemented with cOmplete™ Mini EDTA-free Protease Inhibitor Cocktail (Sigma-Aldrich) and PhosSTOP Phosphatase Inhibitor Cocktail (Sigma-Aldrich). Blotting was carried out using rabbit polyclonal antibody to Phospho-Histone H3 (Ser10) (1:500, PA5-17869, Invitrogen), with mouse anti-beta actin (1:2500, ab8224, Abcam, Cambridge, MA, USA) as a loading control. Bands were detected by chemiluminescence using Amersham ECL Western blot reagent (GE Healthcare Bio-Sciences, Pittsburgh, PA). Band intensities were quantified by densitometry in ImageJ and normalized to the control mean relative to β-actin.
Connectivity of 16p12.1 and 16p11.2 deletion genes in a human brain-specific interaction network
We examined the connectivity of human 16p12.1 and 16p11.2 deletion genes in the context of a human brain-specific gene interaction network that was previously built using a Bayesian classifier trained on gene co-expression datasets [71,72]. As the classifier assigned weighted probabilities for interactions between all possible pairs of genes in the genome, we first built a network that only contained the top 0.5% of all pairwise interactions (predicted weights >2.0). Within this network, we identified the shortest paths between 25/27 genes in the 16p11.2 deletion or 6/7 genes in the 16p12.1 region that were present in the network and all other protein-coding genes in the genome, using the inverse of the probabilities as weights for each interaction. For each shortest path, we calculated the overall length as a measure of connectivity between the two genes, and also identified the connector genes located within the shortest path (S5 File). All network analyses were performed using the NetworkX v.2.4 Python package [106]. We compared the average connectivity of the six 16p12.1 genes to the 25 16p11.2 genes, as well as the predicted pathogenicity of connector genes for 16p11.2 and 16p12.1 interactions, using two-tailed Mann-Whitney tests. To account for a larger number of genes in the 16p11.2 deletion, we also compared the median connectivity of 16p12.1 genes to the distribution of median connectivity values for 1000 simulations of six random genes from the 16p11.2 region. We further compared the median connectivity of 16p12.1 genes to the connectivity of 1000 random sets of six genes in the network. Finally, to compare these values to random sets of contiguous genes in the genome, we calculated the median connectivity among 1000 randomly-selected contiguous blocks of six and 25 genes, excluding blocks containing genes within canonical CNV regions [11]. For each comparison with simulated gene sets, we calculated one-tailed z-scores and percentile values for the observed median connectivity values (S6 File).
Statistical analyses
All statistical analyses of functional data were performed using R v.3.4.2 (R Foundation for Statistical Computing, Vienna, Austria). Details for each statistical test, including sample size, p-values with and without multiple testing correction, confidence intervals, test statistics, and ANOVA degrees of freedom, are provided in S6 File.
Supporting information
Data Availability
Gene expression data for the Drosophila RNAi knockdown of homologs of 16p12.1 genes and controls have been submitted to the NCBI Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE151330, and the raw RNA Sequencing files are deposited in the SRA (Sequence Read Archive) with BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/) accession number PRJNA635495. Source code for the RNA-Sequencing and network analysis is available on the Girirajan lab GitHub page at https://github.com/girirajanlab/16p12_fly_project.
Funding Statement
This work was supported by the National Institutes of Health (NIH) R01GM121907 (https://www.nih.gov) and resources from the Huck Institutes of the Life Sciences (https://www.huck.psu.edu) to S.G, Fulbright Commission Uruguay-Agencia Nacional de Investigacion e Innovacion (https://fulbright.org.uy/en/) to L.P, NIH T32-GM102057 to M.J., and NIH R01GM085115 to M.M.R. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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