Detectability of runs of homozygosity is influenced by analysis parameters and population-specific demographic history

Wild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness. Detecting and characterizing runs of homozygosity (ROHs) is a popular strategy for assessing the extent of individual inbreeding present in a population and can also shed light on the genetic mechanisms contributing to inbreeding depression. Here, we analyze simulated and empirical datasets to demonstrate the downstream effects of program selection and long-term demographic history on ROH inference, leading to context-dependent biases in the results. Through a sensitivity analysis we evaluate how various parameter values impact ROH-calling results, highlighting its utility as a tool for parameter exploration. Our results indicate that ROH inferences are sensitive to factors such as sequencing depth and ROH length distribution, with bias direction and magnitude varying with demographic history and the programs used. Estimation biases are particularly pronounced at lower sequencing depths, potentially leading to either underestimation or overestimation of inbreeding. These results are particularly important for the management of endangered species, as underestimating inbreeding signals in the genome can substantially undermine conservation initiatives. We also found that small true ROHs can be incorrectly lumped together and called as longer ROHs, leading to erroneous inference of recent inbreeding. To address these challenges, we suggest using a combination of ROH detection tools and ROH length-specific inferences, along with sensitivity analysis, to generate robust and context-appropriate population inferences regarding inbreeding history. We outline these recommendations for ROH estimation at multiple levels of sequencing effort, which are typical of conservation genomics studies.Author summary: In this study, we explored how various factors affect the accuracy of detecting runs of homozygosity (ROHs). ROHs are long sections of the genome where both inherited DNA strands are identical due to shared ancestry in the maternal and paternal lines. Because these sections reflect shared ancestry, ROHs are useful for measuring inbreeding in populations, which can negatively impact individual fitness and species survival. We analyzed simulated and empirical data to examine how factors such as demographic history and sequencing depth influence ROH detection. Our results show that these estimates of inbreeding are highly sensitive to the analysis software and data quality. Misidentifying ROHs can lead to significant overestimates or underestimates of inbreeding, potentially complicating conservation efforts. To improve accuracy, we recommend using multiple analysis methods and conducting sensitivity analyses to account for data variability. These findings are particularly relevant for managing endangered species, where precise genetic information is critical for effective conservation planning.