The future of genomics for developmentalists

Abstract

The momentum of genomic science will carry it far into the future and into the heart of research on typical and atypical behavioral development. The purpose of this paper is to focus on a few implications and applications of these advances for understanding behavioral development. Quantitative genetics is genomic and will chart the course for molecular genomic research now that these two worlds of genetics are merging in the search for many genes of small effect. Although current attempts to identify specific genes have had limited success, known as the missing heritability problem, whole-genome sequencing will improve this situation by identifying all DNA sequence variations, including rare variants. Because the heritability of complex traits is caused by many DNA variants of small effect in the population, polygenic scores that are composites of hundreds or thousands of DNA variants will be used by developmentalists to predict children's genetic risk and resilience. The most far-reaching advance will be the widespread availability of whole-genome sequence for children, which means that developmentalists would no longer need to obtain DNA or to genotype children in order to use genomic information in research or in the clinic.

Figure 1. All the ‘-omic’ pathways between the genome and behavior are important for understanding individual differences.

However, DNA sequence variation in the genome is ultimately responsible for hereditary influences on behavior. Correlations between DNA sequence variation and behavior are causal, as indicated by the single-headed arrow from the genome to behavior. Although behavior is often referred to as the observable ‘phenome’, all levels between the genome and behavior can be considered as phenotypes, which we show as connected by double-headed arrows signifying possible two-way directions of effect. The genetic and environmental origins of individual differences in these phenotypes need to be assessed rather than assumed.

Figure 2. The starting point for Genome-wide Complex Trait Analysis (GCTA) is a matrix of chance genetic similarity across hundreds of thousands of SNPs pair by pair for large samples of unrelated individuals.

(Adapted from Plomin, Haworth, et al., 2013.)

Figure 3. Missing heritability: The relation between effect size and allele frequency.

(Adapted from McCarthy et al., 2008.)

Figure 4. A polygenic score based on 32 SNPs associated with weight corrected for height (body mass index, BMI) correlates 0.12 with BMI.

Although the polygenic score only accounts for 1.5 percent of the total variance of BMI, individuals with the lowest and highest 2 percent polygenic scores differ by 8 kg, suggesting the possibility of reasonably sized research samples selected solely on the basis of polygenic scores (genotypic selection). Figure used with permission from Speliotes et al. (, Figure 2.1, p.940).