S2 Appendix. Effects of sample size and sequencing depth on diversity and population structure analysis of Bromus auleticus with pool-seq dataset.

Bromus auleticus, a valuable forage grass native to the Pampa biome, is currently suffering genetic erosion. Therefore, it is central to assess the appropriate methodologies for developing population genomic studies and contributing to the conservation of this plant genetic resource. This study evaluated five accessions using two genotyping strategies: individual sequencing (ind-seq) and pooled sequencing (pool-seq). To compare their efficacy, was investigated the correlation between allele frequencies calculated using each approach. Geneticdiversity and population structure were also analyzed using both methods. These comparisons explicitly accounted for the potential effects of one or more of the following parameters: sample size, missing data, sequencing depth, and minor allele frequencies. Notably, the highest concordance and percentage of common SNPs between ind-seq and pool-seq was achieved using 30 to 60 plants per accession, with a maximum missing data threshold of 10% and a more tolerant minimum allele frequency threshold for pool-seq (0.01) compared to ind-seq (0.05). Reaching maximum similarity in allele frequencies also required a higher sequencing depth for pool-seq (4.8 million reads-Mr) than for ind-seq (0.9 Mr). Pools of 50 individuals yielded the highest number of polymorphic sites, averaging over 9,000 across all accessions at a sequencing depth of 4.8 Mr. Under these conditions, pool-seq consistently yielded a means across all accessions of 0.09 higher expected heterozygosity and 0.24 lower allelic richness compared to ind-seq across all accessions. The population structure detected with both methodologies showed agreement, aligning with the outcrossing nature of B. auleticus and the geographical origin of each accession. The average inbreeding coefficient of 0.2 indicates signs of inbreeding, highlighting the importance of conservation efforts of this valuable plant genetic resource. Based on these findings, two workflows were proposed to carry out population genomics studies of Bromus auleticus.