Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes

Reynolds, Edwardo; Neeley, Catherine; Lopdell, Thomas; Keehan, Michael; Dittmer, Keren E.; Harland, Chad; Couldrey, Christine; Johnson, Thomas; Tiplady, Kathryn; Worth, G.M.; Walker, Mark; Davis, Stephen R.; Sherlock, Richard G.; Carnie, Katie; Harris, B. L.; Charlier, Carole; Georges, Michel; Spelman, Richard; Garrick, Dorian J.; Littlejohn, Mathew D

doi:10.1038/s41588-021-00872-5

Cited by 42 publications

(61 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other wavenumber QTL where a co-localized eQTL was identified within FT-MIR wavenumbers, but not the predicted milk composition traits, included effects that highlighted a number of genes that appear novel to the present study: CLDN8 , CSTB , TA B2 , LAPTM4A , CAPN5 , PMP22 , HID1 and THRB ; and a number of genes previously reported as having an effect on bovine milk composition: SLC37A1 [ 66 , 86 ], NCF4 [ 66 , 69 ], SLC34A2 [ 87 ], TENT5A [ 40 ], RNF217 [ 67 ], MPC1 [ 85 ], XDH [ 88 , 89 ], PAEP [ 60 ], DGAT1 [ 56 ], RGL1 [ 90 ], LTF [ 91 , 92 ] and MUS81 [ 93 ]. These results underscore the gain in power that is available when using individual FT-MIR wavenumber phenotypes, compared to using predicted milk composition phenotypes which are linear functions of FT-MIR absorbance values.…”

Section: Discussionmentioning

confidence: 99%

“…Second, our approach could be extended to account for non-additive QTL. Recently, we conducted non-additive association mapping of growth and development traits in cattle, which highlighted a number of major-effect mutations that had not been identified through application of standard additive models [ 93 ]. Although the low MAF variants identified in that study would require larger samples than those explored here, future analyses based on larger populations might be expected to identify similar non-additive effects for FT-MIR wavenumber and predicted milk composition traits.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk. Results Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk. Conclusions This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…We applied a non-additive GWAS approach that is similar to that described in Reynolds et al . [ 12 ] to identify non-additive QTL for milk traits. This approach is a two-step method that leaves-one-segment-out (LOSO) and fits all other genomic SNP effects among the 31,451 SNPs to adjust for population structure, and then applies a Markov chain Monte Carlo (MCMC) method to test the effects of all imputed-to-sequence variants in the segment that had been left out, one at a time.…”

Section: Methodsmentioning

confidence: 99%

“…Genome-wide association studies (GWAS) have been used to investigate non-additive effects in quantitative traits, but the number of findings remains limited in comparison to additive effects, where most such analyses fit an additive model only. Recent studies of non-additive effects include the investigation of complex traits in both humans [ 7 ] and cattle [ 8 – 12 ]. In cattle, Reynolds et al .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci

et al. 2022

Self Cite

View full text Add to dashboard Cite

Background Deleterious recessive conditions have been primarily studied in the context of Mendelian diseases. Recently, several deleterious recessive mutations with large effects were discovered via non-additive genome-wide association studies (GWAS) of quantitative growth and developmental traits in cattle, which showed that quantitative traits can be used as proxies of genetic disorders when such traits are indicative of whole-animal health status. We reasoned that lactation traits in cattle might also reflect genetic disorders, given the increased energy demands of lactation and the substantial stresses imposed on the animal. In this study, we screened more than 124,000 cows for recessive effects based on lactation traits. Results We discovered five novel quantitative trait loci (QTL) that are associated with large recessive impacts on three milk yield traits, with these loci presenting missense variants in the DOCK8, IL4R, KIAA0556, and SLC25A4 genes or premature stop variants in the ITGAL, LRCH4, and RBM34 genes, as candidate causal mutations. For two milk composition traits, we identified several previously reported additive QTL that display small dominance effects. By contrasting results from milk yield and milk composition phenotypes, we note differing genetic architectures. Compared to milk composition phenotypes, milk yield phenotypes had lower heritabilities and were associated with fewer additive QTL but had a higher non-additive genetic variance and were associated with a higher proportion of loci exhibiting dominance. Conclusions We identified large-effect recessive QTL which are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits, with yield phenotypes acting as a better proxy of underlying biological disorders through presentation of a larger number of major recessive impacts.

show abstract

A Mutation Losing an RBP‐Binding Site in the LncRNA NORSF Transcript Influences Granulosa Cell Apoptosis and Sow Fertility

Wang,

Sheng,

Zhang

et al. 2024

Advanced Science

View full text Add to dashboard Cite

Sow fertility is an economically important quantitative trait. Hundreds of quantitative trait loci (QTLs) containing tens of thousands of potential candidate genes are excavated. However, among these genes, non‐coding RNAs including long non‐coding RNAs (lncRNAs) are often overlooked. Here, it is reported that NORSF is a novel causal lncRNA for sow fertility traits in QTLs. QTLs are characterized for sow fertility traits at the genome‐wide level and identified 4,630 potential candidate lncRNAs, with 13 differentially expressed during sow follicular atresia. NORSF, a lncRNA that involved in sow granulosa cell (sGC) function, is identified as a candidate gene for sow fertility traits as a G to A transversion at 128 nt in its transcript is shown to be markedly associated with sow fertility traits. Mechanistically, after forming the RNA:dsDNA triplexes with the promoter of Caspase8, NORSF transcript with allele G binds to an RNA‐binding protein (RBP) NR2C1 and recruits it to the promoter of Caspase8, to induce Caspase8 transcription in sGCs. Functionally, this leads to a loss of inducing effect of NORSF on sGC apoptosis by inactivating the death receptor‐mediated apoptotic pathway. This study identified a novel causal lncRNA that can be used for the genetic improvement of sow fertility traits.

show abstract

Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes

Cited by 42 publications

References 40 publications

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci

A Mutation Losing an RBP‐Binding Site in the LncRNA NORSF Transcript Influences Granulosa Cell Apoptosis and Sow Fertility

Contact Info

Product

Resources

About