The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders.

Nursery grounds provide conditions favorable for growth and survival of juvenile fish and crustaceans through abundant food resources and refugia, and enhance secondary production of populations. While small-scale studies remain important tools to assess nursery value of structured habitats and environmental factors, targeted applications that unify survey data over large spatial and temporal scales are vital to generalize inference of nursery function, identify highly productive regions, and inform management strategies. Using 21 years of spatio-temporally indexed survey data (i.e., water chemistry, turbidity, blue crab, and predator abundance) and GIS information on potential nursery habitats (i.e., seagrass, salt marsh, and unvegetated shallow bottom), we constructed five Bayesian hierarchical models with varying spatial and temporal dependence structures to infer variation in nursery habitat value for young juveniles (20–40 mm carapace width) of the blue crab Callinectes sapidus within three tributaries (James, York and Rappahannock Rivers) in lower Chesapeake Bay. Out-of-sample predictions of juvenile blue crab counts from a model considering fully nonseparable spatiotemporal dependence outperformed predictions from simpler models. Salt marsh surface area and turbidity were the strongest determinants of crab abundance (positive association in both cases). Highest crab abundances occurred near the turbidity maximum where relative salt marsh area was greatest. Relative seagrass area, which has been emphasized as the most valuable nursery in studies conducted at small spatial scales, was not associated with high crab abundance within the three tributaries. Hence, salt marshes should be considered a key nursery habitat for the blue crab, even where extensive seagrass beds occur. The patterns between juvenile blue crab abundance and environmental variables also indicated that identification of nurseries should be based on investigations at broad spatial and temporal scales incorporating multiple potential nursery habitats, and based on statistical analyses that address spatial and temporal statistical dependence.

Ecological studies indicate that structurally complex habitats support elevated biodiversity, stability and resilience. The long-term persistence of structured habitats and their importance in maintaining biodiverse hotspots remain underexplored. We combined geohistorical data (dead mollusc assemblages, ‘DA’) and contemporary surveys (live mollusc assemblages, ‘LA’) to assess the persistence of local seagrass habitats over multi-centennial timescales and to evaluate whether they acted as long-term drivers of biodiversity, stability and resilience of associated fauna. We sampled structured seagrass meadows and open sandy bottoms along Florida's Gulf Coast. Results indicated that: (i) LA composition differed significantly between the two habitat types, (ii) LA from seagrass sites were characterized by significantly elevated local biodiversity and significantly higher spatial stability, (iii) DA composition differed significantly between the two habitat types, and (iv) fidelity between LA and DA was significantly greater for seagrass habitats. Contemporary results support the hypotheses that local biodiversity and spatial stability of marine benthos are both elevated in structured seagrass habitats. Geohistorical results suggest that structured habitats persist as local hotspots of elevated biodiversity and faunal stability over centennial-to-millennial timescales; indicating that habitat degradation and concomitant loss within structurally complex marine systems is a key driver of declining biodiversity and resilience.