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To satisfy an increasing demand for dietary protein, the poultry industry ha employed genetic selection to increase the growth rate of broilers by over 400% in the past 50 years. Although modern broilers reach a marketable weight of ~ 2 kg in a short span of 35 days, a speed twice as fast as a broiler 50 years ago, the expedited growth has been associated with several negative detrimental consequences. Our objective for this study was to perform a comprehensive genomic analysis of domestic chicken breeds, focusing on broilers that underwent intensive selective breeding in the last 50 years to offer snapshots of genetic changes introduced during the breeding program, as well as insight into the underlying genetics of accelerated growth and changes in immune function. We aim to identify genes and pathways involved in metabolism and innate immune responses that have been altered by artificial selection, with some pathways showing potential in modifying modern broiler responses to foreign pathogens that represent novel avenues for future investigations focusing on improving poultry health.
The genomes of two female chickens from each of the University of Alberta Meat Control strains unselected since 1957 and 1978, respectively, and a commercial Ross 308 broiler were generated. CNV related genes were defined on the basis of their sequence overlapping by at least 50% with a CNV. Phylogenetic tree construction Phylogenetic trees were generated using SNPs detected from all breeds. First, reads that mapped to multiple genomic regions were filtered. Based on SNP analyses, we defined five prioritization strategies to define transcripts of interest: Strategy 1. Transcripts that have accumulated most SNPs in the last 50 years. Nonsynonymous SNP density increase between the 1957 and the 1978 broiler was compared to the nonsynonymous SNP density increase between the 1978 and Ross 308 broiler. For a transcript to be prioritized by this strategy, the difference in SNP density between the 1957 and 1978 broiler OR between the 1978 broiler and Ross 308 must be in the 95th percentile. Additionally, all SNP density changes between 1957 and 1978 and 1978 and Ross 308 must be positive (i.e. more SNPs in more recently bred lines). Strategy 2. Transcripts with the most SNPs unique to fast-growing broilers. This strategy selected for transcripts with the highest number of variants (90th percentile after normalizing by transcript length) that belonged exclusively Zou et al. BMC Genetics (2020) 21:5 Page 11 of 14 to the 1978 and/or Ross 308 subset OR the subset of SNPs exclusive only to Ross 308. The former subset (transcripts with high number of unique variants in 1978 and Ross 308 combined) includes transcripts that have not gained unique variants between 1978 and Ross 308 but have accumulated unique variants since the 1950s. Strategy 3. Transcripts containing high impact variants (i.e. frameshift, start loss, and stop gain variants) only in Ross 308 or the 1978 broiler. Strategy 4. Transcripts with decreasing SIFT score. For every transcript, the mean SIFT score is calculated, only transcripts that show a decrease in SIFT score when comparing the 1957, 1978, and Ross 308 broilers and are also in the bottom 50th percentile for either the 1978 or Ross 308 broiler are selected. Strategy 5. Transcripts that have accumulated deleterious SNPs. Transcripts that show an increase in number of deleterious variants (SNPs with SIFT scores less than 0.05) when comparing the 1957, 1978, and Ross 308 broilers and possess the highest number of deleterious variants (99th percentile) after normalizing by transcript length.
Given that identifying the underlying genetic basis responsible for a less sensitive innate immune response would be economically beneficial for poultry breeding, we decided to compare the genomes of two unselected meat control strains that are representative of broilers from 1957 and 1978, and a current commercial broiler line. Through analysis of genetic variants, we developed a custom prioritization strategy to identify genes and pathways that have accumulated genetic changes and are biologically relevant to immune response and growth performance. Our results highlight two genes, TLR3 and PLIN3, with genetic variants that are predicted to enhance growth performance at the expense of immune function.
This study illustrates how comparisons of the genome sequences derived from temporally related lines can help reveal the genes and biological processes that help drive livestock breeding programs.