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Microarrays can be a cost-effective alternative to high-throughput sequencing for discovering novel single-nucleotide polymorphisms (SNPs). Illumina’s iScan platform dominates the market, but their commercial microarray products are designed for model organisms. Further, the platform outputs data in a proprietary format. This cannot be easily converted to human-readable genotypes or be merged with pre-existing data. To address this, we present and validate a novel pipeline to facilitate data analysis from cross-species application of Illumina microarrays. This facilitates the generation of a compatible VCF from iScan data and the merging of this with a second VCF comprising genotypes derived from other samples and sources. Our pipeline includes a custom script, iScanVCFMerge (presented as a Python package), which we validate using iScan data from three great ape genera. We conclude that cross-species application of microarrays can be a rapid, cost-effective approach for SNP discovery in non-model organisms. Our pipeline surmounts the common challenges of integrating iScan genotypes with pre-existing data.

We monitored the reproductive parameters of South China Tigers (SCT) in captivity from 1983 to 2018. Tigers gave birth in all but 3 months of the year, with a peak in May, June, and July (goodness of fit test, χ2 = 49.928, p = 0.000, n = 270 litters from 65 mothers). The minimum age at 1st reproduction was 4.96 ± 2.43 (standard deviation, SD) years. The mean interval between litters was 410.2 ± 290.2 (SD) days (n = 38 pairs with consecutive reproduction). Mean litter size was 2.1 ± 0.9 (SD) (n = 270 litters from 65 tigers). The average survival rate of newborn cubs was 55.7% (SD = 17.7). There was significant maternal age variation among the litters studied. Reproduction mainly occurs in females in their prime (3–14 years old), with little in young and old females (one-way analysis of variance, ANOVA, F = 8.314, p = 0.005). Reproductive parameters of SCTs could be the basis of analysis on the population dynamics and management, and genetic considerations are necessary to plan future breeding programs and to assist in the selection of individuals for reintroduction to the wild.