Using milk MIR spectra to identify candidate genes associated with climate-smart traits in cattle

Enhancing the resilience to extreme climate events and reducing greenhouse gases (mitigation), while improving productivity are of large importance in future breeding objectives. However, gaps to get large-scale phenotyping as well as limited knowledge about the biological basis are still challenges. This study tried to exploit the milk MIR spectra jointly with genomics to identify potential candidate genes affecting mitigation and resilience abilities. For mitigation, methane emissions (CH4) and phosphorus (P) could be viewed as major sources of environmental pollution. Biomarkers reflecting the equilibrium between mobilisation and intake and body ketones associated with energy status are potential indicator traits for resilience to thermal stress. Predicted phenotypes form MIR data, CH4 and P (mitigation), and C18:1cis-9, Acetone, BHB in addition to milk yield (resilience) were used in this study. The proportion of variance explained by SNPs was evaluated for all studied traits. The putative genes located within or close to outliers SNPs were further identified. Concerning CH4 and P, 31; 28 and 7% of the what we called outliers SNPs were located at BTA14; BTA1 and BTA15, respectively. The markers in the most informative windows on BTA1 were close or within several genes such as RIPK4, PRDM15, ABCG1, SLC37A1, UBASH3A and FAM3B. On BTA14, the top outlier SNPs were located in LD block containing 3 genes (DGAT1, CYHR1, and PLEC). For resilience traits, the two outlier markers associated with acetone slope were located on BTA7 at approximately 45.5-45.7 Mb. Possible candidate genes located within this interval are UQC411 and ATP5F1D. The SNPs ARSBFGL- NGS-4939 and ARS-BFGL-NGS-34135, located on BTA14 were top SNPs and were also detected to affect milk, C18:1cis9, acetone, and BHB slopes. Interesting candidate genes such as DGAT1, HSP1 and SLC52A2 were identified surrounding those two markers. In conclusion, markers identified for resilience and mitigation traits could prove useful in genomic selection for climate-smart breeding programs.