Open Access

Identification of candidate intergenic risk loci in autism spectrum disorder

BMC Genomics201314:499

DOI: 10.1186/1471-2164-14-499

Received: 22 January 2013

Accepted: 20 July 2013

Published: 24 July 2013

Abstract

Background

Copy number variations (CNVs) and DNA sequence alterations affecting specific neuronal genes are established risk factors for Autism Spectrum Disorder (ASD). In what is largely considered a genetic condition, so far, these mutations account for ~20% of individuals having an ASD diagnosis. However, non-coding genomic sequence also contains functional elements introducing additional disease risk loci for investigation.

Results

We have performed genome-wide analyses and identified rare inherited CNVs affecting non-genic intervals in 41 of 1491 (3%) of ASD cases examined. Examples of such intergenic CNV regions include 16q21 and 2p16.3 near known ASD risk genes CDH8 and NRXN1 respectively, as well as novel loci contiguous with ZHX2, MOCS1, LRRC4C, SEMA3C, and other genes.

Conclusions

Rare variants in intergenic regions may implicate new risk loci and genes in ASD and also present useful data for comparison with coming whole genome sequence datasets.

Keywords

Autism spectrum disorder Copy number variation Non-coding DNA

Background

Newer genomic technologies like high-resolution microarrays and next generation exome sequencing have enabled the identification of many clinically relevant genetic variants for both Mendelian and complex disorders. Yet for many conditions the identified genes account for only a proportion of heritability. This observation coupled with the recognition of the functional relevance of non-genic regions [1] target these genomic segments as candidates for investigation for a role in disease.

ASD encompasses a range of neurodevelopmental disorders characterised by social impairment, communication difficulties and restricted, repetitive behavioural patterns. ASD, which is clinically and genetically heterogeneous, demonstrates high heritability, familial clustering and ~4:1 male to female bias. While there has been progress identifying risk genes, most are still unknown [2]. Analyses of rare (<1% population frequency) CNVs, insertions and deletions (indels) and point mutations have most convincingly identified synaptic genes such as members of the Neuroligin (NLGN3, NLGN4)[3], Neurexin (NRXN1[4], NRXN2[5], NRXN3[6]), SHANK (SHANK1[7], SHANK2[8], SHANK3[9]) families and Gephyrin [10] as highly-penetrant risk loci [2]. ASD subjects with multiple genetic risk factors for ASD and associated medical conditions are also known [11]. In addition, there are a few examples of mutations in ASD cases identified in non-genic segments of DNA [12] and non-coding RNAs [13]. Similar findings are even better documented in studies of intellectual disability [14, 15], which is observed in ~40% of cases of ASD. Focusing on the intergenic intervals of the genome, we performed a systematic genome-wide investigation to identify rare CNVs enriched in cases compared with controls [16] to identify known and novel ASD susceptibility loci.

Methods

A collection of 1491 unrelated ASD cases were genotyped using either the Illumina 1M (993) or the Affymetrix SNP 6.0 platforms (498). The ASD subjects, all diagnosed using gold-standard instruments including Autism Diagnostic Interview and Autism Diagnostic Observation Schedule, are described elsewhere [16, 17]. Informed written consent was obtained from all participants, as approved by the Research Ethics Boards at The Hospital for Sick Children and McMaster University. For controls, 1287 samples from the SAGE cohort were genotyped on with the Illumina 1M and 1234 samples from the Ottawa Heart Institute (OHI) and 1123 from the POPGEN collections were genotyped on the Affymetrix SNP 6.0. CNV discovery was performed using previously described pipelines [1618]. Three CNV detection tools were used for each platform (Birdsuite, iPattern and Genotyping Console for Affymetrix 6.0 and iPattern, QuantiSNP & PennCNV for Illumina 1 M). A subset of CNVs in both cases and controls were considered rare if they were present in <1% of the overall dataset and these were further analysed if they failed to intersect or fall within a known gene (according to the NCBI Reference Sequence (RefSeq), August 2011). Rare genic CNVs identified from these data have been reported previously and from these data approximately 10% of cases carry a de novo or rare inherited CNV thought to contribute to ASD in that individual [16, 17, 19, 20]. All CNVs discussed were validated where DNA was available using independent laboratory methods such as long range or quantitative PCR and the mode of inheritance determined (Additional files 1 and 2).

Results and discussion

Microarray data from a cohort of 1491 unrelated ASD probands were analysed for rare copy number variants as described previously [16, 17] and CNVs falling outside of known coding sequence were identified. A total of 212 non-coding genomic regions were determined as harboring overlapping CNVs in two or more unrelated ASD cases that were absent in control samples. Each region was examined for plausible biological function by comparison with multiple databases. Data was collated for evidence of expressed sequences from mRNA or EST data at GenBank or evolutionary conservation as well as functional predictions from the VISTA enhancer browser (http://​enhancer.​lbl.​gov/​) and Rfam (http://​rfam.​sanger.​ac.​uk/​). The Database of Genomic Variants (http://​dgvbeta.​tcag.​ca/​dgv/​app/​home) was used to eliminate additional regions as non-ASD specific CNVs and regions with >80% masked as repetitive sequences were removed. Loci were also prioritised as being of potential clinical significance in ASD due to proximity to genes considered known or candidate ASD risk genes [17].

Fifteen intergenic regions emerged as plausible candidate ASD risk loci and in all instances the defining CNV events were inherited. In one of these regions, an additional case (SK0167-003) was found with an overlapping CNV described by Marshall et al. (2008) [19] (Table 1, Figure 1 and Additional files 1 and 2). In 14 of 15, the intergenic interval identified has not been described before and in three regions the CNV neighboured a known ASD gene, namely, CDH8 [21], C3orf58 [22] and NRXN1 [4]. In the case of the NRXN1 gene, upstream CNVs found in five individuals impact the same mRNA (AK127244) reported elsewhere with a CNV in a family with ASD (Table 1, Figure 1A) [23]. Examples of other intergenic CNVs identified highlight regions at 8q24.12 upstream of ZHX2, 6p21.2 upstream of MOCS1, 11p12 upstream of LRRC4C (Figure 1B) and 7q21.11 upstream of SEMA3C, as putative novel ASD rearrangements. In one case (8-14208-3350), deletions were identified at three separate loci; 4q13.1 upstream of EPHA5, 11p14.3 upstream of LUZP2 and 11p12 upstream of LRRC4C and another case (3-0496-003) carried a 46, XXY sex chromosome imbalance. Other CNVs found in these 41 cases are shown in Additional file 3 and any or all of these may be contributing to the genetic load for ASD [11, 17]. Interestingly, all the CNVs identified through our analysis are inherited events. The significance of this observation is still to be determined but suggests incomplete and/or variable penetrance of phenotype, which is something often observed in ASD [6, 7, 17].
Table 1

ASD specific CNVs in intergenic regions

Locus

Gene

Sample

CNV

Start

End

Size

Furthest distance from gene

Bin

2p16.3

NRXN1 AK127244 mRNA

1-0045-004

loss

51405882

51524684

118802

1124

ii

8-3394-003

loss

51439897

51479683

39786

8-3394-003

loss

51157414

51189362

31948

8-14144-2420

loss

51157414

51225851

68437

1-0496-003

gain

52220120

52238172

18052

1-0449-003

loss

52237072

52253660

16588

3p22.3

ARPP21

2-1213-003

loss

34984049

35102773

118724

563

ii

3-0100-000

gain

35086691

35094736

8045

3q24

C3orf58 ZIC1, ZIC4

1-0007-003

loss

146168760

146934953

766193

1383 1955, 1979

i

8-3093-004

loss

146575437

146631141

55704

4q13.1

EPHA5

8-14208-3350

loss

66505324

66633530

128206

840

i

8-14186-3050

loss

66515708

66633530

117822

1-0138-004

loss

66515708

66633530

117822

2-0082-004

loss

67045815

67134170

88355

1-0455-003

loss

67058506

67075558

17052

6p21.2

MOCS1

3-0139-000

gain

40021898

40078515

56617

168

i or ii

2-0139-003

gain

40023327

40062155

38828

1-0381-003

loss

40174188

40209324

35136

2-1368-003

loss

40174188

40210694

36506

7q21.11

SEMA3C

8-6258-03

loss

80431202

80512022

80820

96

i

1-0345-005

loss

80482597

80517630

35033

8p12

UNC5D NRG1

8-14243-3670

loss

34923482

34956067

32585

256 2183

i

3-0044-000

loss

34923482

34956067

32585

3-0300-000

loss

34925149

34957854

32705

8-14181-2940

loss

34923482

34956067

32585

8q24.13

ZHX2

8-3317-003

gain

123572785

123625681

52896

237

i or ii

3-0186-000

loss

123583028

123639417

56389

9q33.1

ASTN2

8-3055-004

loss

119254497

119374796

120299

98

i

3-0115-000

loss

119314967

119319559

4592

9q34.2

OLFM1 RXRA

2-1272-003

gain

136479329

136604233

124904

508 8

i

2-1189-003

gain

136480334

136598491

118157

11p14.3

LUZP2

8-14175-2820

loss

24177612

24316053

138441

160

i or ii

8-14059-1020

loss

24262511

24303132

40621

8-14208-3350

loss

24262511

24303132

40621

11p12

LRRC4C

8-14208-3350

gain

40304880

40703298

398418

196

iii

2-0272-003

loss

40379668

40550356

170688

SK0167-003

loss

40417554

40610400

192846

3-0208-000

loss

40468058

40492541

24483

11p12

LRRC4C

8-14032-600

loss

41990280

42021250

30970

1738

i or ii

8-3276-003

loss

42243624

42279094

35470

2-0286-003

loss

42243624

42279094

35470

11q13.2

MRGPRD

4-0023-003

loss

68486121

68493638

7517

10

i

2-1075-003

loss

68486121

68500238

14117

16q21

CDH8

8-14251-3750

loss

61650435

61787984

137549

1030

i or ii

  

2-1175-003

loss

61658675

61755232

96557

  

Location and size of all CNVs discovered are listed with the proposed associated candidate gene. Bin denotes possible mechanism of action by i) altering sequence elements required for regulating expression of neighboring genes ii) affecting undiscovered genes or non-coding RNAs iii) disrupting uncharacterised isoforms of adjacent genes. Genome browser views of all loci are shown in Figure 1 and Additional file 1. All pedigrees are shown in Additional file 2. Additional sample SK0167-003 identified in reference [19].

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-14-499/MediaObjects/12864_2013_Article_5225_Fig1_HTML.jpg
Figure 1

Genome browser views of ASD specific CNVs at A) 2p16.3 B) 11p12 C) 8p12 and D) 4q13.1. In each case, representative isoforms of known RefSeq genes, mRNA and/or Expressed Sequence Tags are shown. Deletions and duplications are represented by red and blue bars, respectively. In Figure 1A) a dashed line indicates a diploid region located between two adjacent deletions in the same individual. Additional browser views from other loci shown in Table 1 are included in Additional file 1 A-J. In all cases where parental DNA was available, the CNVs shown were found to be inherited. Additional case SK0167-003 found in Marshall et al.[19].

The mechanism of action of these rare CNVs in the pathogenesis of ASD could be (i) through altering the necessary copy number or positional context of key DNA sequence elements required for regulating the proper expression of nearby genes [1], (ii) affecting still undiscovered genes or non-coding RNAs residing in the CNV regions and (iii) disrupting uncharacterized isoforms of the adjacent annotated genes. In the first scenario, we find CNVs both upstream (e.g. UNC5D (Figure 1C), MOCS1, ASTN2, SEMA3C, ZHX2, LUZP2, CDH8) and down-stream (C3orf58, RXRA, MRGPRD) of known ASD risk genes and putative novel loci. For at least three regions (4q13.1, 6p21.2 and 11p12 (shown in Figure 1D, Additional file 1C and Figure 1B respectively)), our CNV mapping data in fact identify two distinct clusters of CNVs at the same locus, all overlapping spliced ESTs and thus with a possible regulatory role. Secondly, three independent CNV deletions interrupting a collection of spliced expressed sequenced tags approximately 330 kb proximal to EPHA5 highlight a potentially newly discovered ASD risk gene (Figure 1D). Finally, longer isoforms of LRRC4C likely exist given the discovery of mRNAs DQ084201 and DQ084202. There are, of course, other functional DNA elements or modifications that need to be considered [24] as the mapping resolution increases.

Conclusions

Given the challenges faced in interpreting the clinical significance of multitudes of genetic variants found in for example, whole genome sequencing [25], accruing evidence across multiple studies will advocate loci outside of known genes or other regulatory elements for further study, particularly for rare variants. In this light, these data provide a useful resource for comparison as new data sets of both CNVs and nucleotide-level variants become available to help fine-map additional discover new ASD risk loci. This general research strategy can also be applied to other disease gene studies.

Declarations

Acknowledgements

Supported by NeuroDevNet, Genome Canada, the Ontario Genomics Institute, The Government of Ontario, the Canadian Institute of Health Research (CIHR), the Canadian Institute for Advanced Research, The McLaughin Centre, the Canadian Foundation for Innovation and the Ontario Ministry of Research and Innovation. SW holds a joint CIHR Autism Research Training and NeuroDevNet post-doctoral Fellowship. SWS holds the GlaxoSmithKline-CIHR Chair in Genome Sciences at the University of Toronto and The Hospital for Sick Children. We thank The Centre for Applied Genomics for technical contributions. We also acknowledge the assistance of Ines Sousa, Astrid Vicente, Alistair Pagnamenta, Richard Holt, Anthony Monaco, Catalina Betancur and Sylvia Lamoureux for assistance with CNV validation experiments.

Authors’ Affiliations

(1)
Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children
(2)
McLaughlin Centre, University of Toronto

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