Carol Becker Lynch (1942–2019),

The 2020 International Workshop on Statistical Genetic Methods for Human Complex Traits (Formerly the `Methodology of Twin and Family Studies Introductory Workshop’)

Awards Presented at the 49th Annual Meeting of the BEHAVIOR GENETICS ASSOCIATION

Announcement of the Fulker Award for a Paper Published in Behavior Genetics, Volume 48, 2018

Referees for Volume 49

Minutes of the Annual Business Meeting of the Members of the Behavior Genetics Association

Behavior Genetics Association 49th Annual Meeting Abstracts

Construct Validity and Cross Validity of a Test Battery Modeling Autism Spectrum Disorder (ASD) in Mice Abstract Modeling in other organism species is one of the crucial stages in ascertaining the association between gene and psychiatric disorder. Testing Autism Spectrum Disorder (ASD) in mice is very popular but construct validity of the batteries is not available. We presented here the first factor analysis of a behavioral model of ASD-like in mice coupled with empirical validation. We defined fourteen measures aligning mouse-behavior measures with the criteria defined by DSM-5 for the diagnostic of ASD. Sixty-five mice belonging to a heterogeneous pool of genotypes were tested. Reliability coefficients vary from .68 to .81. The factor analysis resulted in a three- factor solution in line with DSM criteria: social behavior, stereotypy and narrowness of the field of interest. The empirical validation with mice sharing a haplo-insufficiency of the zinc-finger transcription factor TSHZ3/Tshz3 associated with ASD shows the discriminant power of the highly loaded items.

A Novel Model to Explain Extreme Feather Pecking Behavior in Laying Hens Abstract Feather pecking (FP) is a serious economic and welfare problem in the domestic fowl. It has recently been shown that the distribution of FP bouts within groups is heterogeneous and contains a sub-population of extreme feather peckers (EFP). The present study proposed a novel model to detect EFP hens. A mixture of two negative binomial distributions was fitted to FP data of a F2 cross of about 960 hens, and, based on the results, a calculation of the posterior probability for each hen belonging to the EFP subgroup (pEFP) was done. The fit of the mixture distribution revealed that the EFP subgroup made up a proportion of one third of the F2 cross. The EFP birds came more frequently into pecking mood and showed higher pecking intensities compared to the remaining birds. Tonic immobility and emerge box tests were conducted at juvenile and adult age of the hens to relate fearfulness to EFP. After dichotomization, all traits were analyzed in a multivariate threshold model and a genomewide association study was performed. The new trait pEFP has a medium heritability of 0.35 and is positively correlated with the fear traits. Breeding for this new trait could be an interesting option to reduce the proportion of extreme feather peckers. An index of fear related traits might serve as a proxy to breed indirectly for pEFP. GWAS revealed that all traits are typical quantitative traits with many genes and small effects contributing to the genetic variance.

Introducing M-GCTA a Software Package to Estimate Maternal (or Paternal) Genetic Effects on Offspring Phenotypes Abstract There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.