Next-generation DNA sequencing (NGS) offers a promising way to obtain massive numbers of orthologous loci to understand phylogenetic relationships among organisms. Of particular interest are old museum specimens and other samples with degraded DNA, where traditional sequencing methods have proven to be challenging. Low coverage shotgun sequencing and sequence capture are two widely used NGS approaches for degraded DNA. Sequence capture can yield sequence data for large numbers of orthologous loci, but it can only be used to sequence genomic regions near conserved sequences that can be used as probes. Low coverage shotgun sequencing has the potential to yield different data types throughout the genome. However, many studies using this method have often generated mitochondrial sequences, and few nuclear sequences, suggesting orthologous nuclear sequences are likely harder to recover. To determine the phylogenetic position of the galliform genus Tropicoperdix, whose phylogenetic position is currently uncertain, we explored two strategies to maximize data extraction from low coverage shotgun sequencing from approximately 100-year-old museum specimens from two species of Tropicoperdix. One approach, a simple read mapping strategy, outperformed the other (a reduced complexity assembly approach), and allowed us to obtain a large number of ultraconserved element (UCE) loci, relatively conserved exons, more variable introns, as well as mitochondrial genomes. Additionally, we demonstrated some simple approaches to explore possible artifacts that may result from the use of degraded DNA. Our data placed Tropicoperdix within a clade that includes many taxa characterized with ornamental eyespots (peafowl, argus pheasants, and peacock pheasants), and established relationships among species within the genus. Therefore, our study demonstrated that low coverage shotgun sequencing can easily be leveraged to yield substantial amounts and varying types of data, which opens the door for many research questions that might require information from different data types from museum specimens.