By: Isaac Miller-Crews, PhD Candidate, University of Texas at Austin
My job would be much easier if CVS sold paternity testing kits for fish instead of humans! I am interested in the evolution of the neural regulation of reproduction, which requires knowing whether an animal reproduced. Genetic testing, such as parentage analysis, allows us to figure out relationships among individuals without direct historical knowledge. This testing has generally relied on looking in the DNA for microsatellites but we’re discovering new, more powerful, and cheaper ways to conduct these tests in the ‘Age of Big Data’ (Flanagan, 2018; Hodel, 2016). This is especially true if your fish population stubbornly refuse to have variable microsatellites!
Yet, common standards or guidelines for dealing with next-generation sequencing data still need to be figured out (Flanagan, 2018). Importantly, few bioinformatic tools exist that can differentiate well between closely related individuals or deal with DNA mixtures. Looking at single nucleotide polymorphisms (SNPs) across thousands of genomic sites allows researchers significantly more information on variability among samples than standard microsatellite approaches (Hodel, 2016). A new technique called restriction site-associated DNA sequencing (RAD-seq) helps us narrow down which places to look at on the DNA, because it only sequences certain fragments, and which fragments you get depends on which endonucleases you use to cut up the DNA. 2bRAD sequencing uses an endonuclease (type-2b) that give you consistent fragments across your sample, not to mention it’s very cost-effective (Wang, 2012).
The simplest form of paternity testing is exclusion, in which paternity is ruled out if a single site disagrees between the alleged father and the offspring-mother pair (Marshall, 1998), is prone to errors. (Wang, 2010). Parental and sibship reconstruction can generate full sets of possible parental genotype profiles but cannot be used with pooled offspring samples (Wang, 2004). The most common paternity testing technique uses a likelihood model to categorically assign paternity between individuals (Meagher, 1986). Not only does this approach require setting a threshold to call genotypes, but it also limits paternity to the comparison of only two alleged fathers (Marshall, 1998). Furthermore, this type of technique cannot deal with cases of mixed or pooled samples, since it can only categorically assign paternity to one putative father.
Luckily, there is always a Bayesian approach! Partial paternity testing assigns fractions of the offspring to candidate parents based on the highest Bayesian posterior probability (Hadfield, 2006) and outperforms categorical likelihood models, especially in being able to circumvent systematic biases, such as over-assigning paternity to males with a relatively higher number of homozygous loci (Devlin, 1988). Assigning partial paternity is thus perfect if you want to assess an entire brood or clutch or litter at once!
Most parentage testing techniques assume that parents are unrelated, and the pool of putative parents contain no close relatives, which can lead to troubling situations where full-siblings are assigned parentage over actual parents (Thompson, 1976). Populations with a lot of closely related individuals pose a problem to both microsatellite and SNP assays due to the lower variation amongst samples. In these cases, only 100 SNPs are required to outperform microsatellites (Flanagan, 2018). If close relatives are suspected to be in the sample, broader pedigree analysis is often required, such as done with identity-by-state (IBS) matrix clustering. Yet, to date, only one study has attempted to combine IBS clustering with any paternity testing method, categorical assignment, or to a genotyping-by-sequencing with RAD-seq data (Gutierrez, 2017). If only someone could combine the awesome power of IBS matrix clustering with the staggering potential of partial paternity testing!
The African cichlid fish Burton’s mouthbrooder, Astatotilapia burtoni, is a model system in social neuroscience, which forms highly complex and dynamic social communities. Adult male A. burtoni are considered either territorial or non-territorial (Fernald, 1977). Males position within the social dominance hierarchy is dynamic as possession of territories is transient (Hofmann, 1999). A. burtoni reproduce within territorial bowers prior to female mouth-brooding for around two weeks, during which fry can be directly removed from the mother’s buccal cavity. Current estimates of male reproductive success usually integrate some combination of female behavior (proximity, duration/frequency in shelter, or number of eggs laid in a territory), with variation in female preference assumed from this proxy of male reproductive success (Kidd, 2006). Although a female may associate with a male this does not directly equate to mating outcomes, meaning behavioral scoring is not enough to assign paternity (Theis, 2012).
My research aims to do just that by developing a NGS-based parentage analysis bioinformatics pipeline that integrates partial paternity assignment and IBS matrix clustering. The powerful pairing of these two parentage assignment methods allows detection of biases that might arise from closely related individuals in the alleged parent population and will handle pooled samples of multiple offspring. Which is great since our laboratory population of A. burtoni is quite inbred and produces fairly large broods (imagine mouth-brooding anywhere from 10-60 fry). Implementation of paternity testing to measure reproduction outcomes can help us understand the interaction between dynamic systems such as female reproductive cycle and male social dynamics (Fig. 1).
The integration of a bioinformatics pipeline and the unique advantages of 2bRAD sequencing will allow for relatively easy expansion both into alternative DNA sequencing approaches and any species, regardless of available genomic resources. I plan to integrate paternity testing, as a measure of Darwinian fitness, into analysis on mate preferences and reproductive success in naturalistic communities of A. burtoni. While we use a lot of behavioral proxies of reproduction, such as social interactions or association time, nothing let’s you know that the deed was done like genetically testing everyone. Layered on top of these models of reproductive success within a social hierarchy I want to integrate neuromolecular techniques, from both the spatial resolution of single genes up to transcriptomic networks. This means I will know information about an individual’s behavior, reproductive success, and neural profile all within the context of an actual social community. Talk about truly integrative!