Behavioral Phenotypes Are Heterogeneous, Requiring Careful Characterization Prior to Genetic Analysis.

Even in simple model organisms, complex behavioral phenotypes exhibit continuous variation that is not amenable to dichotomous categorization. Phenotypes associated with individuals on the ASD spectrum are also continuously distributed. However, most studies, whether based on genetics, neurobiology, or behavior, compare an ASD group to a typically developing group of individuals. Categorizing the behavioral heterogeneity of individuals within a population as typical or atypical does not take into account the heterogeneity of ASD. Despite the large overlap of continuously distributed data points between groups, group mean differences are still used to represent all individuals within a group. This approach does not lend itself to predictions of individual susceptibility or precision medicine. McDiarmid et al. (2) successfully use a more dimensional fractionable approach to develop their phenomic data and embrace the heterogeneity of the phenotypes emerging from the behavioral phenotyping of worms carrying ASD-associated gene alterations. This approach recognizes the heterogeneity of the data and the variability within and between phenomic clusters.

There is Natural Genetic Variation for Most, If Not All, Individual Differences in Behavioral Traits in Animals.

This statement is borne out through various methodologies, including pedigree analyses of families, artificial selection, quantitative genetics, candidate gene analysis, and, more recently, whole-genome sequencing technologies (GWAS). ASD has a strong genetic component, which includes monozygotic concordance estimates of ∼70 to 90% and the identification of several distinct highly penetrant genetic syndromes (7).

Many Genes with Small Effects Influence Individual Differences in Behavior.

Hundreds to thousands of genes can affect individual differences in behavior. One of the challenges is to identify which of these genes are core to the development and functioning of individual differences in a behavior (8). There are >100 ASD-associated genes, all of which have small effects on ASD, accounting for a very small percentage of the total number of ASD cases (e.g., most frequently mutated genes account for <1% of the total cases) (7). These rare de novo genetic variants associate with neuronal signaling and development, chromatin regulation, and synaptic function (9). In GWAS, a candidate single-nucleotide polymorphism (SNP) that passes the significance threshold is commonly associated with the nearest gene along the DNA sequence; however, it cannot be assumed that a SNP affects the functioning of the nearest gene. Some SNPs are positioned within the coding region of a gene, resulting, for example, in a stop codon or missense mutation. In this case, if the SNP has a functional effect on the phenotype it will act through the gene that it has disrupted. However, it is not uncommon for genes to be embedded within other genes or for genes to be transcribed from the opposite DNA strand, so without functional validation it is not known whether or not the gene identified by the SNP found by association from the GWAS is in fact involved in the trait of interest. More challenging still is assigning a function to a SNP that does not reside within the coding region of a gene. A SNP may reside in a number of locations that are suggestive of regulatory functions such as the putative promoter region(s) or the 5′ or 3′ untranslated region of a gene. SNPs can also be in introns embedded within or outside of a gene or act over very long distances to affect a gene (e.g., in transregulatory elements). The extent to which genetic variants residing outside the coding regions of genes (e.g., in regulatory regions) play an important role in ASD remains to be determined.

Most Genes That Influence Behavior Have Multiple Functions; They Are Pleiotropic.

It is a challenging task to dissect the multiple functions of a gene. For example, the foraging gene in the fruit fly Drosophila produces at least 21 transcripts expressed through 4 transcription start sites whose expression is temporally and spatially regulated. The modular structure of genes can provide a way forward to interrogate behavioral pleiotropy experimentally (10). When GWAS associates with more than one genetic variant (e.g., SNP) in a gene, the extent of pleiotropy combined with the complexities of gene structure make it necessary to validate the effect of each individual genetic variant. SNPs that associate with and map within the same gene may not have the same effect on function. Results from McDiarmid et al. (2) support this notion.

Genetic Background Strongly Affects Behavior.

Genetic background is defined as the genotypes of all genes in the genome that may interact and influence the focal gene under study (6). In animal research, it is prudent to control for variation in genetic background. McDiarmid et al. (2) tested the functions of C. elegans ASD-associated mutant genes in a common genetic background. Notably, even with extensive control of genetic background and the rearing and testing environment, they did not find evidence for separate phenotypic classes of the ASD-associated genes. In contrast, at the molecular level of investigation they found functionally distinct groupings of ASD-associated genes. When genes were clustered according to phenomics certain genes were closer to each other than other genes, reflecting molecular interactions. In humans, genetic background most likely influences core ASD genes to affect individual differences in ASD; however, little is currently known about how this occurs.

Gene–Environment Interactions on Behavioral Phenotypes Are Pervasive.

Genetic variation predisposes individuals to behave in a certain way, and the environment (which itself is multidimensional) can modify this predisposition (11, 12). In model organisms, the modification of gene expression through experience can readily be seen at the molecular level acting through gene regulatory networks that act within circuits (13). Large-scale studies of the genetic contributions to ASD rarely consider environmental factors (14). Rutter’s (14) reflection on gene–environment interplay in ASD states, “Whether or not such non-genetic factors will turn out to be measured environmental influences or, rather, stochastic (chance) effects remains to be seen, but both possibilities must be considered.” ASD runs in families (9). If a family has one child with ASD, the full sibling of that child has a 10-fold increase in the risk of ASD. Much of this arises from genetic contributions, but unknown shared environments may also play a role. Future human research should investigate the interaction between allelic variation and gene expression and how the same ASD genetic risk factor can result in different outcomes. It is important to adopt a developmental approach using longitudinal studies of families that begin prior to pregnancy and cross the lifespan where detailed data about the environment/experience, genetics, epigenetics, imaging of brain development, and state-of-the-art measures of behavior are collected throughout development and adulthood (15).

When paired with human studies, model organisms such as C. elegans are well-positioned to contribute further knowledge about the molecular basis of gene function and the mechanisms underlying ASD (2).