Biology subjects

Klassmann, A.

Publications and source records attributed to Klassmann, A..

3 recordsLinked to original sources

bioRxiv2025

Disentangling multivariate relationships between cognition, language and social traits: structures of G, E, and rGE

BackgroundCognitive, language, and social abilities are complex, heritable and intertwined traits shaping childrens development and later mental health. To better understand cross-trait interrelationships, we model here the structures of shared genomic and shared non-genomic/residual (i.e. broadly environmental) influences, and their correlation (rGE), investigating cognitive, language, and social behavioural/communication measures. MethodsData were obtained for unrelated children (8-13 years) from two population-based cohorts: the UK Avon Longitudinal Study of Parents and Children (ALSPAC, N[≤]6,543) and the US Adolescent Brain Cognitive DevelopmentSM (ABCD) Study (N[≤]4,412), and analyses were carried out implementing an extended data-driven genetic-relationship-matrix structural equation modelling (GRM-SEM) approach. ResultsIn ALSPAC, we identified two independent phenotypic domains, each captured by a structurally matching pair consisting of a genomic (A) and a non-genomic/residual (E) factor. The first domain reflected cognitive/language difficulties, with the largest genomic and residual factor loadings ({lambda}A and {lambda}E, respectively) for verbal IQ ({lambda}A=0.73(SE=0.05); {lambda}E=0.57(SE=0.07)). The second domain captured social difficulties, with the largest {lambda}A and {lambda}E for social communication measures ({lambda}A=0.39(SE=0.10); {lambda}E=0.82(SE=0.10)). We identified trait-specific rGE between pairs of A and E factors with different directions of effect (cognition/language rGE=0.89(SE=0.18), social rGE=-0.62(SE=0.17)). rGE patterns were linked to increased measurable A and E contributions for cognition/language difficulties, but decreased contributions for social problems. Analyses in ABCD confirmed the two domains for E and phenotypic structures, although genomic contributions were low. ConclusionsIn childhood, cognitive/language abilities versus social abilities are influenced by distinct genomic and/or environmental factors, potentially interlinked through trait-specific rGE, suggesting differences in developmental processes.

genomics↗

bioRxiv2017

The third moments of the site frequency spectrum

The analysis of patterns of segregating (i.e. polymorphic) sites in aligned sequences is routine in population genetics. Quantities of interest include the total number of segregating sites and the number of sites with mutations of different frequencies, the so-called site frequency spectrum. For neutrally evolving sequences, some classical results are available, including the expected value and variance of the spectrum in the Kingman coalescent model without recombination as calculated by FO_SCPLOWUC_SCPLOW (1995).\n\nIn this work, we use similar techniques to compute the third moments of the site frequency spectrum without recombination. We also account for the linkage pattern of mutations, yielding the full haplotype spectrum of three polymorphic sites. Based on these results, we derive analytical results for the bias of Tajimas D and other neutrality tests.\n\nAs an application, we obtain the second moments of the spectrum of linked sites, which is related to the neutral spectrum of chromosomal inversions and other structural variants. These moments can be used for the normalisation of new neutrality tests relying on these spectra.

genetics↗

bioRxiv2017

The expected neutral frequency spectrum of linked sites

We introduce the conditional Site Frequency Spectrum (SFS) for a genomic region linked to a focal mutation of known frequency. An exact expression for its expected value is provided for the neutral model without recombination. Its relation with the expected SFS for two sites, 2-SFS, is discussed. These spectra derive from the coalescent approach of Fu (1995) for finite samples, which is reviewed. Remarkably simple expressions are obtained for the linked SFS of a large population, which are also solutions of the multiallelic Kolmogorov equations. These formulae are the immediate extensions of the well known single site{theta} /f neutral SFS. Besides the general interest in these spectra, they relate to relevant biological cases, such as structural variants and introgressions. As an application, a recipe to adapt Tajimas D and other SFS-based neutrality tests to a non-recombining region containing a neutral marker is presented.

genetics↗