This note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].

Mapping genetic risk factors for endometriosis continues from early studies on women’s health initiated by Nick Martin and Susan Treloar. Their initial recruitment of endometriosis cases and family members received a major boost and became a flagship project within the Cooperative Research Centre (CRC) for the Discovery of Common Human Disease. We extended the study through a formal collaboration with Professor Stephen Kennedy and his group in Oxford. Our first joint scientific meeting was held in Brisbane and was sadly memorable as the day the planes were flown into the Twin Towers in New York. Our initial collaboration expanded into the International Endometriosis Genetics Consortium (IEGC). The IEGC now has 15 groups around the world, and the most recent meta-analysis will be published this year.

There have been incredible advances made in human genetics over the past 40 years. I have set out in the next few pages to describe just some of these changes and to illustrate how they unfolded through my own experiences.

A quantitative trait locus (QTL) analysis of female reproductive data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six F1 boars and 23 F1 sows, progeny of six LW boars and six MS sows, produced 573 F2 females and 530 F2 males. Six traits, i.e. teat number (TN), age at puberty (AP), ovulation rate (OR), weight at mating (WTM), number of viable embryos (NVE) and embryo survival (ES) at 30 days of gestation were analysed. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross (LC) regression and a half–full sib (HFS) maximum likelihood test. Genome-wide (GW) highly significant (P < 0.001) QTL were detected for WTM on SSC 7 and for AP on SSC 13. They explained, respectively, 14.5% and 8.9% of the trait phenotypic variance. Other GW significant (P < 0.05) QTL were detected for TN on SSC 3, 7, 8, 16 and 17, for OR on SSC 4 and 5, and for ES on SSC 9. Two additional chromosome-wide significant (P < 0.05) QTL were detected for TN, three for WTM, four for AP, three for OR, three for NVE and two for ES. With the exception of the two above-mentioned loci, the QTL explained from 1.2% to 4.6% of trait phenotypic variance. QTL alleles were in most cases not fixed in the grand-parental populations and Meishan alleles were not systematically associated with higher reproductive performance.

The Jackson Laboratory, having the world's largest collection of mouse mutant stocks and genetically diverse inbred strains, is an ideal place to discover genetically determined eye variations and disorders. In this paper, we list and describe mouse models for ocular research available from Mouse Eye Mutant Resource at The Jackson Laboratory. While screening mouse strains and stocks at The Jackson Laboratory (TJL) for genetic mouse models of human ocular disorders, we have identified numerous spontaneous or naturally occurring mutants. We characterized these mutants using serial indirect ophthalmoscopy, fundus photography, electroretinography (ERG) and histology, and performed genetic analysis including linkage studies and gene identification. Utilizing ophthalmoscopy, electroretinography, and histology, to date we have discovered 109 new disorders affecting all aspects of the eye including the lid, cornea, iris, lens, and retina, resulting in corneal disorders, glaucoma, cataracts, and retinal degenerations. The number of known serious or disabling eye diseases in humans is large and affects millions of people each year. Yet research on these diseases frequently is limited by the obvious restrictions on studying pathophysiologic processes in the human eye. Likewise, many human ocular diseases are genetic in origin, but appropriate families often are not readily available for genetic studies. Mouse models of inherited ocular disease provide powerful tools for rapid genetic analysis, characterization, and gene identification. Because of the great similarity among mammalian genomes, these findings in mice have direct relevance to the homologous human conditions.

The indica rice Xieqingzao eB1 (XQZ eB1), a mutant with an elongated uppermost internode, was produced by mutagenesis from elite maintainer line Xieqingzao B (XQZ B) using γ-radiation. Compared with the wild-type XQZ B, plant height and the length of the rice panicle neck, second internode and third internode from the panicle were elongated significantly in XQZ eB1. Genetic analysis indicated that the trait for uppermost internode elongation of XQZ eB1 is controlled by a single recessive gene eui1, which is allelic to that of IR50eui (derived from 76:4512). Further studies were carried out using the bulk segregated analysis approach. An F3 population, derived from the cross XQZ eB1×Aijiaonante, was used to map the mutant gene eui1. Two SSR makers, RM164 and AC9, were identified to link to eui1, their genetic distances to eui1 being 18.4 and 7.9 cM, respectively. The eui1 gene was also mapped to the long arm of chromosome 5 in this research.

The relationships between phenotype and genotype were first described by Mendelian genetics in the case of genes with a major phenotypic effect. The remarkable improvement of biochemical and molecular tools has now made it possible to identify the molecular nature of major genes, and to understand better their mode of action. From a functional point of view, mutations of a given gene can be classified into three groups: loss of function, interference and dominant negative action, and gain of function. From a structural point of view, a large diversity of molecular polymorphisms can be found, the consequences of which depend rather on their position than on their nature. Genetic abnormalities or mutations with obvious morphological effects provide the most didactic examples to understand the genotype-phenotype relationships. The example of sex-linked dwarfism in chicken is described in detail and the present state of knowledge on the molecular identification of major genes in the chicken is reviewed. Finally, a general discussion, based upon examples taken from human genetics and mouse genetics, draws lessons from the study of major genes in order to approach the study of complex phenotypes or genotype x environment interactions.

One method of linkage analysis in humans is based on identity-by-descent of pairs of relatives who share a phenotype of interest (for example, a particular disease). We replace the convenient assumption of continuous specification of regions of identity by descent by the more realistic, although still artificially simple, assumption of data from a discrete set of equally spaced infinitely polymorphic markers. We generalize the continuous time Markov chain analysis of Feingold (1993b) and compare the accuracy of the new approximation with that of the simpler Gaussian approximation of Feingold, Brown and Siegmund (1993) under a variety of assumptions about the composition of the pedigrees to be studied. We also suggest a perturbation of the Gaussian approximation as a compromise to achieve reasonable accuracy with minimal computational effort.

A statistical analysis strategy for the detection of quantitative trait loci (QTLs) in half-sib populations is outlined. The initial exploratory analysis is a multiple regression of the trait score on a subset of markers to allow a rapid identification of possible chromosomal regions of interest. This is followed by multiple marker interval mapping with regression methods within and across families fitting one or two QTLs. Empirical thresholds are determined by experiment-wise permutation tests for different significance levels and empirical confidence intervals for the QTLs' positions are obtained by bootstrapping methods. For traits with evidence for a significant single-QTL effect, an approximate maximum likelihood analysis is performed to obtain estimates of QTL effect and the probability of the QTL genotype for each parent of a group of half-sibs. The strategy is demonstrated in an analysis of previously published data on chromosome 6 and five production traits from a granddaughter design in dairy cattle. The results confirm and extend evidence for QTLs affecting protein percentage. Informativeness of markers limited the possibility of mapping more than one QTL on the same linkage group.

Amplified fragment length polymorphisms (AFLPs) offer a reproducible, multiplex DNA assay by which to genotype mapping populations. We have evaluated physiological traits in barley seedlings grown in an hydroponic system and given a salt treatment. Multiple regression was used to show associations between AFLPs and quantitative traits. Effects at different loci were detected in stress treatments in comparison to the control implying that either novel gene action was induced by salt stress or that normal activity was reduced to a low level where alternate gene action is revealed. The QTLs occurred on all chromosomes but there appeared to be clusters of loci on chromosomes 1 (7H), 4 (4H), 5 (1H) and 6 (6H). The significance of our results is discussed in the context of studies to explore the barley genome and the application of the results of these genetical analyses to barley breeding.