1. The fixation index, FIS has been a staple measure to detect selection or departures from random mating in populations. However, current Next Generation Sequencing (NGS) cannot easily estimate Fis, in multi-locus gene families, which contain multiple loci having similar or identical arrays of variant sequences of ≥1 kilobase, which differ at multiple positions. In these families, high-quality short-read NGS data typically identify variants, but not the genomic location, which is required to calculate Fis (based on locus-specific observed and expected heterozygosity). Thus, to assess assortative mating, or selection on heterozygotes, from NGS of multi-locus gene families, we need a method that does not require knowledge of which variants are allelic at which locus in the genome. 2. We developed such a method. Like Fis, our novel measure, 1His, is based on the principle that positive assortative mating, or selection against heterozygotes, reduces within-individual variability relative to the population. 3. We demonstrate high accuracy of 1His on a wide-range of simulated scenarios, and two datasets from natural populations of penguins and dolphins. 4. 1His is important because multi-locus gene families are often involved in assortative mating, or selection on heterozygotes. 1His is particularly useful for multi-locus gene families such as toll-like receptors, the major-histocompatibility-complex in animals, homeobox genes in fungi and self-incompatibility genes in plants.
Potential subdivision events in populations can have a wide range of causes: from natural disasters like bushfires that isolate communities, to anthropogenic disturbances like infrastructure projects cutting through a population’s habitat. Due to the unpredictability inherent in events like bushfires, or even for predictable events such as property development, populations affected by these potential subdivisions are often not studied until after the event, making it extremely hard to assess negative conservation impacts without the benefit of prior data. This paper aims to apply population genetics methods to assess whether it is possible to accurately assess the impact a potential subdivision event can have on the genetic makeup of a population, especially when one has no data prior to such an event. Differentiation measures, such as Fst, might be used for detecting whether a population has been subdivided. However, these measures often take dozens of generations to show a significant change from zero (i.e., no differentiation), especially in larger populations. In this paper we present a more sensitive method, which is suitable for detecting subdivision effects within a few generations of the event and which can be applied without prior data. We test this method using both simulated data, and genetic data from a population of koalas impacted by a railroad infrastructure development.
New sequencing technologies have opened the door to many new research opportunities, but these advances in data collection are not always compatible with some important methods for data analysis. Fis has been a staple calculation in the field of population genetics. Fis can be used to measure either a departure from random mating, or measure underlying selective pressures for or against heterozygote genotypes. However, when using Next Generation Sequencing (NGS) technology on multi-locus gene families it is often impossible to discern which allelic variants are present at each locus. Some important multi-locus gene families are: the major histocompatibility complex (MHC) in animals; homeobox genes in fungi; or the self-incompatibility genes in plants. This in turn makes it impossible to calculate either locus-specific expected heterozygosity, or observed heterozygosity, both of which are required to calculate Fis. Without the ability to calculate Fis from NGS of multi-locus gene families, we need a new multi-locus measure that will allow us to detect the underlining mating, and selective patterns present in such multi-locus genes. This paper provides such a novel multi-locus measure, called 1His. We demonstrate the accuracy of the 1His equation using simulated data, and two datasets taken from natural populations of dolphins and penguins. The introduction of this new measure is particularly important because of the great interest in mating patterns and selection of multi-locus gene families, such as MHC.