**3. Anchoring marsupial and monotreme genome assemblies**

Genome sequence data on its own is an extremely valuable resource but it is also equally as important to know how the genome fits together. BACs have played an essential role in anchoring marsupial and monotreme sequence to chromosomes. Different approaches have been taken that have utilized BACs to improve genome assemblies, with the strategy employed dependent the quality of the genome assembly.

The opossum and platypus genome projects employed BACs in a similar fashion. BAC-end sequencing was used to assist in connecting sequence contigs into scaffolds (Mikkelsen et al., 2007; Warren et al., 2008). Scaffolds were anchored and oriented on chromosomes by FISH-mapping BACs from ends of sequence scaffolds (Duke et al., 2007; Warren et al., 2008). For the opossum genome, the mapping of 381 BACs resulted in 97% of the genome being assigned to chromosomes (Duke et al., 2007). The more fragmented nature of the platypus genome assembly made it more difficult to anchor each scaffold but FISH-mapping of BACs assigned 198 scaffolds, corresponding to approximately 20% of the genome, to chromosomes (Warren et al., 2008).

Anchoring of the even more fragmented wallaby and devil genome assemblies required a different approach. A novel approach was developed to anchor the low-coverage wallaby genome sequence to chromosomes. A cytogenetic map of the genome was constructed by mapping BACs containing genes from the ends of human-opossum conserved gene blocks. This strategy was first trialed on tammar wallaby chromosome 5 (Deakin et al., 2008b) and later applied to the entire genome (Renfree et al., 2011). A virtual map of the wallaby genome was made by extrapolating from the content of these mapped conserved blocks from the opossum genome assembly, thereby allowing the location of each gene on tammar wallaby chromosomes to be predicted (Wang et al., 2011a). A similar approach is being used to construct a map of the devil genome, which has been sequenced entirely by next generation sequencing (Miller et al., 2011).
