Widespread cis-regulation of RNA editing in a large mammal

Comparison of genomic prediction accuracies in dairy cattle lactation traits using five classes of functional variants versus generic SNP

BACKGROUND

Genomic selection, typically employing genetic markers from SNP chips, is routine in modern dairy cattle breeding. This study assessed the impact of functional sequence variants on genomic prediction accuracy relative to 50 k SNP chip markers for fat percent, protein percent, milk volume, fat yield, and protein yield in lactating dairy cattle. The functional variants were identified through GWAS, RNA-seq, Histone modification ChIP-seq, ATAC-seq, or were coding variants. The genomic prediction accuracy obtained using each class of functional variants was compared with matched numbers of SNPs randomly selected from the Illumina 50 k SNP chip.

RESULTS

The investigation revealed that variants identified by GWAS or RNA-seq, significantly improved the prediction accuracy across all five traits. Contributions from ChIP-seq, ATAC-seq, and coding variants varied. Some variants identified using ChIP-seq showed marked improvements, while others reduced accuracy in protein yield predictions. Relative to a matched number of 32,595 SNPs from the SNP chip, pooling all the functional variants demonstrated prediction accuracy increases of 1.76% for fat percent, 2.97% for protein percent, 0.51% for milk volume, and 0.26% for fat yield, but with a slight decrease of 0.43% in protein yield.

CONCLUSION

The study demonstrates that functional variants can improve prediction accuracy relative to equivalent numbers of variants from a generic SNP panel, with percent traits showing more significant gains than yield traits. The main advantage of using functional variants for genomic prediction was achievement of comparable accuracy using a smaller, more selective set of loci. This is particularly evident in trait-specific scenarios. Our findings indicate that specific combinations of functional variants comprising 16 k variants can achieve genomic prediction accuracy comparable to employing a standard panel of twice the size (32.6 k), especially for percent traits. This highlights the potential for the development of more efficient, trait-focused SNP panels utilizing functional variants.

A stochastic RNA editing process targets a limited number of sites in individual Drosophila glutamatergic motoneurons

RNA editing is a post-transcriptional source of protein diversity and occurs across the animal kingdom. Given the complete profile of mRNA targets and their editing rate in individual cells is unclear, we analyzed single cell RNA transcriptomes from Drosophila larval tonic and phasic glutamatergic motoneuron subtypes to determine the most highly edited targets and identify cell-type specific editing. From ∼15,000 genes encoded in the genome, 316 high confidence A-to-I canonical RNA edit sites were identified, with 102 causing missense amino acid changes in proteins regulating membrane excitability, synaptic transmission, and cellular function. Some sites showed 100% editing in single neurons as observed with mRNAs encoding mammalian AMPA receptors. However, most sites were edited at lower levels and generated variable expression of edited and unedited mRNAs within individual neurons. Together, these data provide insights into how the RNA editing landscape alters protein function to modulate the properties of two well-characterized neuronal populations in Drosophila .

A Comprehensive Evolutionary Study of Chloroplast RNA Editing in Gymnosperms: A Novel Type of G-to-A RNA Editing Is Common in Gymnosperms

Although more than 9100 plant plastomes have been sequenced, RNA editing sites of the whole plastome have been experimentally verified in only approximately 21 species, which seriously hampers the comprehensive evolutionary study of chloroplast RNA editing. We investigated the evolutionary pattern of chloroplast RNA editing sites in 19 species from all 13 families of gymnosperms based on a combination of genomic and transcriptomic data. We found that the chloroplast C-to-U RNA editing sites of gymnosperms shared many common characteristics with those of other land plants, but also exhibited many unique characteristics. In contrast to that noted in angiosperms, the density of RNA editing sites in ndh genes was not the highest in the sampled gymnosperms, and both loss and gain events at editing sites occurred frequently during the evolution of gymnosperms. In addition, GC content and plastomic size were positively correlated with the number of chloroplast RNA editing sites in gymnosperms, suggesting that the increase in GC content could provide more materials for RNA editing and facilitate the evolution of RNA editing in land plants or vice versa. Interestingly, novel G-to-A RNA editing events were commonly found in all sampled gymnosperm species, and G-to-A RNA editing exhibits many different characteristics from C-to-U RNA editing in gymnosperms. This study revealed a comprehensive evolutionary scenario for chloroplast RNA editing sites in gymnosperms, and reported that a novel type of G-to-A RNA editing is prevalent in gymnosperms.

Pan-RNA editing analysis of the bovine genome

RNA editing is an essential process for modifying nucleotides at specific RNA sites during post-transcription in many species. However, its genomic landscape and characters have not been systematically explored in the bovine genome. In the present study, we characterized global RNA editing profiles from 50 samples of cattle and revealed a range of RNA editing profiles in different tissues. Most editing sites were significantly enriched in specific BovB-derived SINEs, especially the dispersed Bov-tAs, which likely forms dsRNA structures similar to the primate-specific Alu elements. Interestingly, ADARB1 (ADAR2) was observed to be predominant in determining global editing in the bovine genome. Common RNA editing sites among similar tissues were associated with tissue-specific biological functions. Taken together, the wide distribution of RNA editing sites and their tissue-specific characters implied the bovine RNA editome should be further explored.

The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle

Over the last 100 years, significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs. Technological progress has enabled a shift from labour intensive, on-farm collection and processing of samples that assess yield and fat levels in milk, to large-scale processing of samples through centralised laboratories, with the scope extended to include quantification of other traits. Fourier-transform mid-infrared (FT-MIR) spectroscopy has had a significant role in the transformation of milk composition phenotyping, with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally. Increasingly, there is interest in analysing the individual FT-MIR wavenumbers, and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs. This includes traits related to the nutritional value of milk, the processability of milk into products such as cheese, and traits relevant to animal health and the environment. The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits, and the genetic correlations between the FT-MIR predicted and actual trait values. Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis. The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes. Additionally, there are other molecular phenotypes such as those related to the metabolome, chromatin accessibility, and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest. Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets, and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

Multiple QTL underlie milk phenotypes at the CSF2RB locus

Background

Over many years, artificial selection has substantially improved milk production by cows. However, the genes that underlie milk production quantitative trait loci (QTL) remain relatively poorly characterised. Here, we investigate a previously reported QTL located at the CSF2RB locus on chromosome 5, for several milk production phenotypes, to better understand its underlying genetic and molecular causes.

Results

Using a population of 29,350 taurine dairy cows, we conducted association analyses for milk yield and composition traits, and identified highly significant QTL for milk yield, milk fat concentration, and milk protein concentration. Strikingly, protein concentration and milk yield appear to show co-located yet genetically distinct QTL. To attempt to understand the molecular mechanisms that might be mediating these effects, gene expression data were used to investigate eQTL for 11 genes in the broader interval. This analysis highlighted genetic impacts on CSF2RB and NCF4 expression that share similar association signatures to those observed for lactation QTL, strongly implicating one or both of these genes as responsible for these effects. Using the same gene expression dataset representing 357 lactating cows, we also identified 38 novel RNA editing sites in the 3′ UTR of CSF2RB transcripts. The extent to which two of these sites were edited also appears to be genetically co-regulated with lactation QTL, highlighting a further layer of regulatory complexity that involves the CSF2RB gene.

Conclusions

This locus presents a diversity of molecular and lactation QTL, likely representing multiple overlapping effects that, at a minimum, highlight the CSF2RB gene as having a causal role in these processes.

Electronic supplementary material

The online version of this article (10.1186/s12711-019-0446-x) contains supplementary material, which is available to authorized users.