CoalQC - Quality control while inferring demographic histories from genomic data: Application to forest tree genomes

Abstract

Estimating demographic histories using genomic datasets has proven to be useful in addressing diverse evolutionary questions. Despite improvements in inference methods and availability of large genomic datasets, quality control steps to be performed prior to the use of sequentially Markovian coalescent (SMC) based methods remains understudied. While various filtering and masking steps have been used by previous studies, the rationale for such filtering and its consequences have not been assessed systematically. In this study, we have developed a reusable pipeline called “CoalQC”, to investigate potential sources of bias (such as repeat regions, heterogeneous coverage, and callability). First, we demonstrate that genome assembly quality can affect the estimation of demographic history using the genomes of several species. We then use the CoalQC pipeline to evaluate how different repeat classes affect the inference of demographic history in the plant species Populus trichocarpa. Next, we assemble a draft genome by generating whole-genome sequencing data for Mesua ferrea (sampled from Western Ghats, India), a multipurpose forest plant distributed across tropical south-east Asia and use it as an example to evaluate several technical (sequencing technology, PSMC parameter settings) and biological aspects that need to be considered while comparing demographic histories. Finally, we collate the genomic datasets of 14 additional forest tree species to compare the temporal dynamics of Ne and find evidence of a strong bottleneck in all tropical forest plants during Mid-Pleistocene glaciations. Our findings suggest that quality control prior to the use of SMC based methods is important and needs to be standardised.

Reference genome and demographic history of the most endangered marine mammal, the vaquita

“…The remaining parameters were left as the default values used for humans (Li & Durbin, 2011), and we performed 100 bootstrap resamplings on all PSMC analyses to assess variance of the model. We also conducted PSMC after masking of repeat regions to control for potential bias due to variation in collapsed repeats (Patil et al., 2020), but because the removal of repeat regions resulted in significantly less data, the PSMC parameters could not be optimized for sufficient resolution in older time periods, resulting in higher variance for those intervals. The effects of collapsed repeats (expected to be less pronounced in a very complete genome like this one, where most repeats have been resolved) are expected to only change the Ne estimates in the most recent and oldest time periods (Patil et al., 2020).…”

“…We also conducted PSMC after masking of repeat regions to control for potential bias due to variation in collapsed repeats (Patil et al., 2020), but because the removal of repeat regions resulted in significantly less data, the PSMC parameters could not be optimized for sufficient resolution in older time periods, resulting in higher variance for those intervals. The effects of collapsed repeats (expected to be less pronounced in a very complete genome like this one, where most repeats have been resolved) are expected to only change the Ne estimates in the most recent and oldest time periods (Patil et al., 2020). Our repeat‐masked plot looks nearly identical to the full‐genome plot in the most recent and middle time periods, and similar (but higher variance) in the oldest time periods (Figure S1).…”

The endangered White Sands pupfish (Cyprinodon tularosa) genome reveals low diversity and heterogenous patterns of differentiation

“…tularosa was reconstructed using the cleaned Illumina paired‐end reads. To help prevent the inadvertent incorporation of nuclear translocations (NUMTs) into the mtDNA assembly, we first used coalqc (v.0.1; Patil et al 2020) and samtools (v.1.17; Li et al, 2009) to extract Illumina reads that aligned to the Devils Hole pupfish ( C . diabolis ) mtDNA assembly (NC_030345.1; Lema et al, 2016).…”

“…The complete mtDNA sequence of C. tularosa was reconstructed using the cleaned Illumina paired-end reads. To help prevent the inadvertent incorporation of nuclear translocations (NUMTs) into the mtDNA assembly, we first used coalqc (v.0.1; Patil et al 2020) and samtools (v.1.17; to extract Illumina reads that aligned to the Devils Hole pupfish (C. diabolis) mtDNA assembly (NC_030345.1; Lema et al, 2016). The resulting bam file was then converted back to fastq file format with bedtools (v.2.29.0; Quinlan & Hall, 2010) and used alongside the C. diabolis full mitogenome as a backbone for the C. tularosa mtDNA genome assembly with mitobim (v.1.8; Hahn et al, 2013).…”