KIRREL3 localizes to the Golgi complex.

<p>Rat PNCs overexpressing the GFP-tagged KIRREL3 were immunostained with GFP antibody (green signal) (A) and the Golgi marker GS28 antibody (red signal, solid arrow) (B). Nuclei were stained with DAPI (blue signal, arrow head) (C). A distinct localized yellow signal (thin arrow) in the merged image (D) suggested the colocalization of KIRREL3 with the Golgi apparatus. Enlarged overlay images and individual red and green channels for a region of interest (ROI) are shown (E). The degree of overlap between the green and red signals was statistically analyzed (E) and expressed with Pearson’s correlation coefficient (PC) and Mander’s colocalization coefficients (M1 and M2). Bar, 20μm.</p

Schematic representation of the KIRREL3 domains.

<p>Five immunoglobulin domains (IgD), a signal peptide (SP) region, a transmembrane domain (TMD), and a PDZ- domain binding motif (PDZ-BD) are shown. ECD, extracellular domain; ICD, intracellular domain. The blue arrow indicates a potential cleavage site.</p

Individual yeast clones identified as potential interacting partners of KIRREL3-ECD and KIRREL3-ICD.

<p>(A) Positive control: yeast mating of [pGBKT7-p53] in AH109 and [pGADT7-T] in Y187. (B) Negative control: yeast mating of [pGBKT7- KIRREL3- ECD] in AH109 and [pGADT7-T] in Y187. (C) Yeast mating of [pGBKT7-KIRREL3-ECD] in AH109 and [pGADT7-MAP1BLC1] in Y187. (D) Yeast mating of [pGBKT7-KIRREL3 ECD] in AH109 and [pGADT7-MYO16] in Y187. (E) Negative control: yeast mating of [pGBKT7- KIRREL3-ICD] in AH109 and [pGADT7-T] in Y187. (F) Yeast mating of [pGBKT7-KIRREL3-ICD] in AH109 and [pGADT7-ATP1B1] in Y187. (G) Yeast mating of [pGBKT7-KIRREL3-ICD] in AH109 and [pGADT7-UFC1] in Y187. (H) Yeast mating of [pGBKT7-KIRREL3-ICD] in AH109 and [pGADT7-SHMT2] in Y187. Yeast mating was performed and cells were grown on—AHLT X-α-gal plates. Only clones with interacting proteins grow on—AHLT X-α-gal media and turn blue.</p

Western blot analysis of the Co-IP of KIRREL3-V5 with MAP1BLC1-FLAG (A1) and endogenous MAP1BLC1 (A2); KIRREL3-V5 with GFP-MYO16 (B), ATP1B1-FLAG (C), UFC1-FLAG (D), and GFP-KIRREL3 with SHMT2-FLAG (E).

<p>Lysates from HEK293H cells overexpressing the indicated expression constructs were incubated with anti-FLAG antibody (A1), anti-V5 antibody (A2, C, and D), and anti-GFP antibody (B, E), and precipitated with magnetic beads. Lysates from N2a cells overexpressing KIRREL3-V5 expression construct was incubated with anti-V5 antibody, and precipitated with magnetic beads (A2). Immunoprecipitates (lane IP, Co-IP) were analyzed by western blotting as indicated with anti-V5, anti-MAP1BLC1, anti-FLAG, and anti-GFP antibodies. Expression of all proteins was also analyzed in total lysates (lane L). MAP1BLC1-FLAG (green arrow) immobilizes KIRREL3-V5 (A1, lane IP, red arrow), but not LacZ-V5 (black arrow). KIRREL3-V5 (green arrow) and KIRREL3-ECD-V5 (brown arrow), but not LacZ-V5 (black arrow) immobilize endogenous MAP1BLC1 (A2, lane IP, red arrow). GFP-MYO16 (green arrow) immobilizes KIRREL3-V5 (B, lane IP, red arrow), KIRREL3-ECD-V5 (B, lane IP, brown arrow) but not LacZ-V5 (B, lane IP, black arrow). (C) KIRREL3-V5 (green arrow) but not LacZ-V5 (black arrow) immobilizes ATP1B1-FLAG (red arrow). (D) KIRREL3-V5 (green arrow) but not LacZ-V5 (black arrow) immobilizes UFC1-FLAG (red arrow). (E) GFP-KIRREL3 (green arrow) immobilizes SHMT2-FLAG (red arrow) but not BAP-FLAG (black arrow).</p

Autism and Intellectual Disability-Associated KIRREL3 Interacts with Neuronal Proteins MAP1B and MYO16 with Potential Roles in Neurodevelopment - Fig 4

<p>(A) KIRREL3-V5 (red, i) and MAP1BLC1-FLAG (green, ii) co-overexpressed in rat PNCs. (B) KIRREL3-V5 (red, i) and GFP-MYO16 (green, ii) co-overexpressed in rat PNCs. The overlapping signals of the two proteins appear as yellow/orange (Aiii, Biii) within the region of cytoplasm and in neurite processes (arrows). Enlarged overlay images and individual red and green channels for each ROIs (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123106#sec009" target="_blank">Materials and Methods</a>) are shown (A-B, iv and v). The degree of colocalization between the red and green signals was statistically analyzed and expressed with Pearson’s correlation coefficient (PC) and Mander’s colocalization coefficients M1 and M2 (A-B, iv and v). M1 represents the fraction of KIRREL3-V5 (red signal) overlapped with MAP1BLC1-FLAG or GFP-MYO16 (green signal). M2 represents the fraction of MAP1BLC1-FLAG or GFP-MYO16 (green signal) overlapped with the KIRREL3-V5 (red signal). All calculations for Pearson’s and Mander’s coefficients were performed by the ImageJ version 1.45s visualization software with JACoP plugin. Bar, 20μm.</p

The Subjectivity Behind the Numbers

Comparison of brain size in WT and dyrk1aa KO fish. (A) Relative size of brain compartments in KO fish brain was shown as a ratio, compared to those in WT fish brain. Also, body length (cm) of WT and KO fish used for this analysis was constant. Tel, Telencephalon; TeO, Tectum Opticum; CCe, Corpus Cerebelli. Number of dissected brains: n = 13 for WT fish and n = 13 for KO fish. (B) Percent of TeV space in the total brain. Mean value for the TeV sizes was measured in relative sections of multiple brain samples. Number of fish used for this assay: n = 6 for WT fish and n = 5 for KO fish. Data are presented as mean ± SEM. * p < 0.05, ** p < 0.01 by Student’s t test. (PDF 1033 kb

Additional file 10: Figure S8. of Zebrafish knockout of Down syndrome gene, DYRK1A, shows social impairments relevant to autism

Social cohesion in different group sizes and water depths in the shoaling assay. (A) Schematic illustrations of the method to measure the distances between individual fish in the shoaling assay. Different numbers of fish were used as a group, ranging from 3 to 7. Social cohesion was represented as a mean distance of individual fish in the group. (B, C) Mean distance between individuals (cm) in a fish group represents the degree of social cohesion. The mean distance for social cohesion was analyzed in 2 different conditions; 1) different group sizes (B) and 2) water depths and volume (C). Number of trials for each experiment: n = 7. Data are presented as mean ± SEM. (PDF 1086 kb

Table_1_A rigorous in silico genomic interrogation at 1p13.3 reveals 16 autosomal dominant candidate genes in syndromic neurodevelopmental disorders.docx

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases.</p

Table_3_A rigorous in silico genomic interrogation at 1p13.3 reveals 16 autosomal dominant candidate genes in syndromic neurodevelopmental disorders.docx

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases.</p

Image_1_A rigorous in silico genomic interrogation at 1p13.3 reveals 16 autosomal dominant candidate genes in syndromic neurodevelopmental disorders.JPEG

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases.</p