Methylome Patterns of Cattle Adaptation to Heat Stress.

Heat stress has a detrimental impact on cattle health, welfare and productivity by affecting gene expression, metabolism and immune response, but little is known on the epigenetic mechanisms mediating the effect of temperature at the cellular and organism level. In this study, we investigated genome-wide DNA methylation in blood samples collected from 5 bulls of the heat stress resilient Nellore breed and 5 bulls of the Angus that are more heat stress susceptible, exposed to the sun and high temperature-high humidity during the summer season of the Brazilian South-East region. The methylomes were analyzed during and after the exposure by Reduced Representation Bisulfite Sequencing, which provided genome-wide single-base resolution methylation profiles. Significant methylation changes between stressful and recovery periods were observed in 819 genes. Among these, 351 were only seen in Angus, 366 were specific to Nellore, and 102 showed significant changes in methylation patterns in both breeds. KEGG and Gene Ontology (GO) enrichment analyses showed that responses were breed-specific. Interestingly, in Nellore significant genes and pathways were mainly involved in stress responses and cellular defense and were under methylated during heat stress, whereas in Angus the response was less focused. These preliminary results suggest that heat challenge induces changes in methylation patterns in specific loci, which should be further scrutinized to assess their role in heat tolerance.

Growth Rate and Acceleration Analysis of the COVID-19 Pandemic Reveals the Effect of Public Health Measures in Real Time.

Background: Ending the COVID-19 pandemic is arguably one of the most prominent challenges in recent human history. Following closely the growth dynamics of the disease is one of the pillars toward achieving that goal. Objective: We aimed at developing a simple framework to facilitate the analysis of the growth rate (cases/day) and growth acceleration (cases/day2) of COVID-19 cases in real-time. Methods: The framework was built using the Moving Regression (MR) technique and a Hidden Markov Model (HMM). The dynamics of the pandemic was initially modeled via combinations of four different growth stages: lagging (beginning of the outbreak), exponential (rapid growth), deceleration (growth decay), and stationary (near zero growth). A fifth growth behavior, namely linear growth (constant growth above zero), was further introduced to add more flexibility to the framework. An R Shiny application was developed, which can be accessed at https://theguarani.com.br/ or downloaded from https://github.com/adamtaiti/SARS-CoV-2. The framework was applied to data from the European Center for Disease Prevention and Control (ECDC), which comprised 3,722,128 cases reported worldwide as of May 8th 2020. Results: We found that the impact of public health measures on the prevalence of COVID-19 could be perceived in seemingly real-time by monitoring growth acceleration curves. Restriction to human mobility produced detectable decline in growth acceleration within 1 week, deceleration within ~2 weeks and near-stationary growth within ~6 weeks. Countries exhibiting different permutations of the five growth stages indicated that the evolution of COVID-19 prevalence is more complex and dynamic than previously appreciated. Conclusions: These results corroborate that mass social isolation is a highly effective measure against the dissemination of SARS-CoV-2, as previously suggested. Apart from the analysis of prevalence partitioned by country, the proposed framework is easily applicable to city, state, region and arbitrary territory data, serving as an asset to monitor the local behavior of COVID-19 cases.

Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus.

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9-48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding.

Genome-wide association study using haplotype alleles for the evaluation of reproductive traits in Nelore cattle.

Zebu cattle (Bos taurus indicus) are highly adapted to tropical regions. However, females reach puberty after taurine heifers, which affects the economic efficiency of beef cattle breeding in the tropical regions. The aims of this study were to establish associations between the haplotype alleles of the bovine genome and age at first calving (AFC) in the Nelore cattle, and to identify the genes and quantitative trait loci (QTL) related to this phenotype. A total of 2,273 Nelore cattle (995 males and 1,278 females) genotyped using the Illumina BovineHD BeadChip were used in the current study. The association analysis included females with valid first calving records as well as open heifers. Linkage disequilibrium (LD) analysis among the markers was performed using blocks of 5, 10, and 15 markers, which were determined by sliding windows shifting one marker at a time. Then, the haplotype block size to be used in the association study was chosen based on the highest r2 average among the SNPs in the block. The five HapAlleles most strongly associated with the trait (top five) were considered as significant associations. The results of the analysis revealed four genomic regions related to AFC, which overlapped with 20 QTL of the reproductive traits reported previously. Furthermore, there were 19 genes related to reproduction in those regions. In conclusion, the use of haplotypes allowed the detection of chromosomal regions associated with AFC in Nelore cattle, and provided the basis for elucidating the mechanisms underlying this trait.

A PLAG1 mutation contributed to stature recovery in modern cattle.

The recent evolution of cattle is marked by fluctuations in body size. Height in the Bos taurus lineage was reduced by a factor of ~1.5 from the Neolithic to the Middle Ages, and increased again only during the Early Modern Ages. Using haplotype analysis, we found evidence that the bovine PLAG1 mutation (Q) with major effects on body size, weight and reproduction is a >1,000 years old derived allele that increased rapidly in frequency in Northwestern European B. taurus between the 16th and 18th centuries. Towards the 19th and 20th centuries, Q was introgressed into non-European B. taurus and Bos indicus breeds. These data implicate a major role of Q in recent changes in body size in modern cattle, and represent one of the first examples of a genomic sweep in livestock that was driven by selection on a complex trait.