RESUMEN
Differences in local habitat conditions are often implicated as drivers for morphological and genetic divergence in natural populations. However, there are still relatively few studies regarding how divergent habitats influence patterns for morphotypes and genetic lineages in aquatic invertebrates. In this study, we explored the morphological patterns, genetic divergence, and distributions of a bivalve, Corbicula fluminea, in a lotic-lentic system. Sampling locations included lotic, ecotone, and lentic habitats. First, we found two lineages (Lineages A and B) with significant genetic divergence that primarily corresponded to two morphotypes (Morphs D and C) of C. fluminea. Lineage A consisted of 88.68% Morph D (shell sculpture: 8-14 ridges/cmsh) and 11.32% Morph C (shell sculpture: 15 ridges/cmsh) individuals and had genetic similarity to invasive populations. Lineage B consisted of only Morph C (shell sculpture: 15-23 ridges/cmsh). Second, we revealed clear effects of habitat on the spatial distribution patterns for the two lineages of C. fluminea. Lineage A was dominant in lotic habitats, with a significantly higher density than that of Lineage B in these locations. Lineage B was dominant in lentic habitats. However, both lineages had their highest densities in the ecotone habitat, without clear dominance and no significant difference in density between groups. Individuals of Lineages A and B are different in shell morphology, which may be related to a benefit trade-off between shell shapes that allow for rapid burrowing and holding position in different flow conditions. The distribution patterns indicate that Lineages A and B may not prefer uniquely lotic and lentic habitats, but each lineage is more tolerant to one habitat type, respectively. Generally, our study established a correlation among morphotypes, lineages, and different habitats for C. fluminea along a lotic-lentic gradient system, which has important implementations for fisheries management units and for understanding the role of habitat preference for this species in monitoring for pioneer dispersal in invasive species management.
RESUMEN
Background: Autism is a severe neurodevelopmental disorder characterized by social interaction deficits, impairments in communication, and restricted and repetitive stereotyped behavior and activities. Family and twin studies suggested an essential role of genetic factors in the etiology of autism spectrum disorder (ASD). Also, other studies found SORCS3 and GSDME (DFNA5) might be involved in brain development and susceptible to ASD. Methods: In this study, 17 genome-wide significant SNPs reported in previous ASD genome-wide association studies (GWAS) and 7 SNPs in strong linkage disequilibrium with known ASD GWAS hits were selected to investigate the association between these SNPs and autism in the Han Chinese population. Then, 10 tagSNPs in SORCS3 and 11 tagSNPs in GSDME were selected to analyze the association between these SNPs and autism. The selected 24 SNPs and tagSNPs were genotyped using the Agena MassARRAY SNP genotyping assay in 757 Han Chinese autism trios. Results: Rs1484144 in NAA11 was significantly associated with autism; significance remained after the Bonferroni correction (P < 0.0022). Also, rs79879286, rs12154597, and rs12540919 near GSDME, as well as rs9787523 and rs3750261 in SORCS3, were nominally associated with autism. Conclusion: Our study suggests that rs1484144 in NAA11 is a significant SNP for autism in the Han Chinese population, while SORCS3 and GSDME might be the susceptibility genes for autism in this population.
RESUMEN
Background: Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level. Objective: This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children. Methods: A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets. Results: Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets. Conclusions: Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.