Publications by authors named "Mike Keehan"

5 Publications

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NGS-based reverse genetic screen for common embryonic lethal mutations compromising fertility in livestock.

Genome Res 2016 10 19;26(10):1333-1341. Epub 2016 Sep 19.

Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège (B34), 4000-Liège, Belgium.

We herein report the result of a large-scale, next generation sequencing (NGS)-based screen for embryonic lethal (EL) mutations in Belgian beef and New Zealand dairy cattle. We estimated by simulation that cattle might carry, on average, ∼0.5 recessive EL mutations. We mined exome sequence data from >600 animals, and identified 1377 stop-gain, 3139 frame-shift, 1341 splice-site, 22,939 disruptive missense, 62,399 benign missense, and 92,163 synonymous variants. We show that cattle have a comparable load of loss-of-function (LoF) variants (defined as stop-gain, frame-shift, or splice-site variants) as humans despite having a more variable exome. We genotyped >40,000 animals for up to 296 LoF and 3483 disruptive missense, breed-specific variants. We identified candidate EL mutations based on the observation of a significant depletion in homozygotes. We estimated the proportion of EL mutations at 15% of tested LoF and 6% of tested disruptive missense variants. We confirmed the EL nature of nine candidate variants by genotyping 200 carrier × carrier trios, and demonstrating the absence of homozygous offspring. The nine identified EL mutations segregate at frequencies ranging from 1.2% to 6.6% in the studied populations and collectively account for the mortality of ∼0.6% of conceptuses. We show that EL mutations preferentially affect gene products fulfilling basic cellular functions. The resulting information will be useful to avoid at-risk matings, thereby improving fertility.
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http://dx.doi.org/10.1101/gr.207076.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5052051PMC
October 2016

Sequence-based Association Analysis Reveals an MGST1 eQTL with Pleiotropic Effects on Bovine Milk Composition.

Sci Rep 2016 05 5;6:25376. Epub 2016 May 5.

Livestock Improvement Corporation, Hamilton, New Zealand.

The mammary gland is a prolific lipogenic organ, synthesising copious amounts of triglycerides for secretion into milk. The fat content of milk varies widely both between and within species, and recent independent genome-wide association studies have highlighted a milk fat percentage quantitative trait locus (QTL) of large effect on bovine chromosome 5. Although both EPS8 and MGST1 have been proposed to underlie these signals, the causative status of these genes has not been functionally confirmed. To investigate this QTL in detail, we report genome sequence-based imputation and association mapping in a population of 64,244 taurine cattle. This analysis reveals a cluster of 17 non-coding variants spanning MGST1 that are highly associated with milk fat percentage, and a range of other milk composition traits. Further, we exploit a high-depth mammary RNA sequence dataset to conduct expression QTL (eQTL) mapping in 375 lactating cows, revealing a strong MGST1 eQTL underpinning these effects. These data demonstrate the utility of DNA and RNA sequence-based association mapping, and implicate MGST1, a gene with no obvious mechanistic relationship to milk composition regulation, as causally involved in these processes.
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http://dx.doi.org/10.1038/srep25376DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857175PMC
May 2016

Variants modulating the expression of a chromosome domain encompassing PLAG1 influence bovine stature.

Nat Genet 2011 May 24;43(5):405-13. Epub 2011 Apr 24.

Unit of Animal Genomics, Interdisciplinary Institute of Applied Genomics (GIGA-R) and Faculty of Veterinary Medicine, University of Liège (B34), Liège, Belgium.

We report mapping of a quantitative trait locus (QTL) with a major effect on bovine stature to a ∼780-kb interval using a Hidden Markov Model-based approach that simultaneously exploits linkage and linkage disequilibrium. We re-sequenced the interval in six sires with known QTL genotype and identified 13 clustered candidate quantitative trait nucleotides (QTNs) out of >9,572 discovered variants. We eliminated five candidate QTNs by studying the phenotypic effect of a recombinant haplotype identified in a breed diversity panel. We show that the QTL influences fetal expression of seven of the nine genes mapping to the ∼780-kb interval. We further show that two of the eight candidate QTNs, mapping to the PLAG1-CHCHD7 intergenic region, influence bidirectional promoter strength and affect binding of nuclear factors. By performing expression QTL analyses, we identified a splice site variant in CHCHD7 and exploited this naturally occurring null allele to exclude CHCHD7 as single causative gene.
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http://dx.doi.org/10.1038/ng.814DOI Listing
May 2011

Genome scan of pigmentation traits in Friesian-Jersey crossbred cattle.

J Genet Genomics 2009 Nov;36(11):661-6

Livestock Improvement Corporation, Priv. Bag 3016, Hamilton 3240, New Zealand.

Pigmentation traits expressed in animals are visual characteristics that allow us to distinguish between breeds and between strains within breed. The objective of this study was to map quantitative trait loci (QTLs) affecting the pigmentation traits in approximately 800 F(2) grand daughter dairy cattle from a Holstein-Friesian and Jersey cross breed cattle. Traits analyzed included pigmentation phenotypes on the body, teat and hoop. The phenoypes were collected from digital photos or visual inspection of live animals. QTL mapping was implemented using half-sib and line-of-descent inheritance models. Our analysis initially detected a number of significant QTLs on chromosomes: 2, 6, 13, 15, 18 and 22. The significant QTLs were divided into two groups: one group influencing the pigmentation color and the other group affecting the absence or level of pigmentation. The most significant QTL peaks were observed on Bovine taurus autosome 18 (BTA18) close to melanocortin 1 receptor (MC1R) for the color traits, on BTA6 close to the receptor tyrosine kinase (KIT) and BTA22 close to microphthalmia-associated transcription factor (MITF) gene for the spotting traits. Association studies were conducted for candidate regions or genes known to affect pigmentation in dairy cattle.
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http://dx.doi.org/10.1016/S1673-8527(08)60158-7DOI Listing
November 2009

A high density linkage map of the bovine genome.

BMC Genet 2009 Apr 24;10:18. Epub 2009 Apr 24.

Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand.

Background: Recent technological advances have made it possible to efficiently genotype large numbers of single nucleotide polymorphisms (SNPs) in livestock species, allowing the production of high-density linkage maps. Such maps can be used for quality control of other SNPs and for fine mapping of quantitative trait loci (QTL) via linkage disequilibrium (LD).

Results: A high-density bovine linkage map was constructed using three types of markers. The genotypic information was obtained from 294 microsatellites, three milk protein haplotypes and 6769 SNPs. The map was constructed by combining genetic (linkage) and physical information in an iterative mapping process. Markers were mapped to 3,155 unique positions; the 6,924 autosomal markers were mapped to 3,078 unique positions and the 123 non-pseudoautosomal and 19 pseudoautosomal sex chromosome markers were mapped to 62 and 15 unique positions, respectively. The linkage map had a total length of 3,249 cM. For the autosomes the average genetic distance between adjacent markers was 0.449 cM, the genetic distance between unique map positions was 1.01 cM and the average genetic distance (cM) per Mb was 1.25.

Conclusion: There is a high concordance between the order of the SNPs in our linkage map and their physical positions on the most recent bovine genome sequence assembly (Btau 4.0). The linkage maps provide support for fine mapping projects and LD studies in bovine populations. Additionally, the linkage map may help to resolve positions of unassigned portions of the bovine genome.
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http://dx.doi.org/10.1186/1471-2156-10-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680908PMC
April 2009