|Hammond, John - Pirbright Laboratory|
|Schwartz, John - Pirbright Laboratory|
|Heimeier, Dorothea - Pirbright Laboratory|
|Smith, Timothy - Tim|
Submitted to: International Society for Animal Genetics (ISAG)
Publication Type: Abstract Only
Publication Acceptance Date: 4/11/2016
Publication Date: 7/23/2016
Citation: Bickhart, D.M., Hammond, J.A., Schwartz, J.C., Heimeier, D., Smith, T.P. 2016. Resolving misassembled cattle immune gene clusters with hierarchical, long read sequencing. International Society for Animal Genetics (ISAG). Salt Lake City, UT, July 23-27. p. 105–106 (P4054).
Technical Abstract: Animal health is a critical component of productivity; however, current genomic selection genotyping tools have a paucity of genetic markers within key immune gene clusters (IGC) involved in the cattle innate and adaptive immune systems. With diseases such as Bovine Tuberculosis and Johne’s disease costing the UK and US industries an annual £50 million and $200 million, respectively, identifying genetic markers associated with disease resistance will greatly assist producers. The high genetic diversity and highly repetitive nature of IGCs also means that the cattle reference genome assembly contains many mistakes or greatly underrepresents the true diversity of alleles in these clusters. To properly identify and annotate the breadth of IGC alleles, we use a hierarchical assembly approach that sequences bacterial artificial chromosome (BAC) library clones that span target sites with long read sequencing. The sequencing of 46 such BACs has already identified an alternative allele for the natural killer cell (NKC) cluster that is currently not represented on the cattle reference genome. In total, replacement NKC sequence fills 10 existing sequence gaps on the genome and removes an improperly assigned contig containing olfactory receptor genes. Further assembly polishing using this approach will finally enable the interrogation of functional variants within IGC regions, thereby enabling future genomic selection of animal health traits.