Single-nucleotide polymorphism (SNP) analyses are a powerful tool for population genetics, pedigree reconstruction and phenotypic trait mapping. SNPs could also be useful for sexing individuals in species with reduced sexual dimorphism, yet this possibility remains poorly explored. Here, we develop a novel protocol for molecular sexing of birds based on the detection of unique Z- and W-linked SNP markers. Our method is based on the identification of two unique loci, one in each sexual chromosome. Individuals are considered males when they are heterozygotic for the Z-linked SNP and females when they are homozygote for the Z-linked SNP and have the W-linked SNP. We validated the method in the Jackdaw (Corvus monedula), a species whose reduced sexual dimorphism makes it difficult to sex individuals in the wild. We assessed the reliability of the method with 36 individuals of known sex, and found that their sex was correctly assigned in 100% of cases. The sex-linked markers also proved to be widely applicable to discriminate males and females from a sample of 927 genotyped individuals of different maturity stages with an accuracy of 99.5%. Given that SNP markers are increasingly used in quantitative genetic analyses of wild populations, the approach we propose has a great potential to be integrated into broader genetic research programmes without the need of additional sexing techniques.

Analysis of intra- and inter-population diversity has become important for defining the genetic status and distribution patterns of a species and a powerful tool for conservation programs, since high levels of inbreeding could lead into a whole population extinction in few generations. Microsatellites (SSR) are commonly used in population studies, but discovering highly variable regions across species’ genomes requires demanding computation and laboratorial optimization. In this work, we combine next generation sequencing (NGS) with automatic computing to develop a genomic-oriented tool for characterizing SSRs at the population level. Herein, we describe a new Python pipeline, named Micro-Primers, designed to identify and design PCR primers for amplification of SSR loci from a multi-individual enriched microsatellite library. The pipeline takes as input a fastq file containing sequences from NGS and returns a text file with information regarding the microsatellite markers, including number of alleles in the population, the melting temperature and the respective product of primer sets to easily guide the selection of optimal markers for the species. Experimental results show that Micro-Primers is able to reduce significantly a manual analysis that takes about 24 hours to 2 minutes, while keeping the same quality of the results.