GENETIC MANAGEMENT TOOLS

A tool for managing group-living species in the wild.  Case study: can we help the helmeted honeyeater make better mating choices?

Robledo-Ruiz DA, Pavlova A, Clarke RH, Magrath MJL, Quin B, Harrisson KA, Gan HM, Low GW, Sunnucks P. (2022) A novel framework for evaluating in-situ breeding management strategies in endangered populations. Molecular Ecology Resources, 22, 239-253.  Video abstract

A 'swiss army knife' for genetic management: a set of R tools to streamline the application of genetics in conservation

Robledo-Ruiz DA, Austin L, Amos JN, Castrejón-Figueroa J, Harley DKP, Magrath MJL, Sunnucks P, Pavlova A, 2023. Easy-to-use R functions to separate reduced-representation genomic datasets into sex-linked and autosomal loci, and conduct sex-assignment. Molecular Ecology Resources, published online 2/08/2023 http://doi.org/10.1111/1755-0998.13844.Code available at https://github.com/drobledoruiz/conservation_genomics, data available at https://doi.org/10.26180/21608028.v6.

We work with SNP datasets produced by Reduced-representation sequencing (RRS). The datasets are imported to R environment as genlight objects. We developed and tested a suite of R functions for filtering and manipulating genlight object. 

Our paper presents the following four functions (explained by Diana in this video): 

1. Detecting and filtering sex-linked loci. Many population genetic analyses (such as parentage assignment, genetic diversity and genetic differentiation analyses) assume that loci in the data are located on autosomes. Sex-linked loci not filtered from SNP datasets add noise and can hinder detection of important biological processes. We developed an R function filter.sex.linked which detects loci with different heterozygosities between known males and females, and removes them from the data (it also outputs sex-linked loci for you to look at, and nice graphs of sex-specific heterozygosities before and after filtering). 

2. Using sex-linked loci to determine sex of individuals. If some but not all genotyped individuals are assigned to sexes, and sex-linked loci are present in the genotyping dataset, the R function infer.sex will assigns sex to all individuals based on sex-linked markers. The output allows testing whether initial sex-assignments are correct.

3. Filtering out extremely heterozygous loci. Biallelic loci with unexpectedly high heterozygosity may represent duplicated loci erroneously scored as one (i.e. merged when genotyping). The R script filter.excess.het checks whether each locus with heterozygosity > 0.5 is excessively heterozygous and outputs a genlight object without excessively heterozygous loci, along with a table with tests for loci with heterozygosity > 0.5.

4. Preparing Colony2 input file from genlight object. Colony2 is a software for conducting parentage and sibship analyses. The R function gl2colony helps to create an input file in R environment.