Donagh Berry

Dr. Donagh Berry

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Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2009 in Journal of Dairy Science
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Journal Article
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JRJohn R. Roche
John R. Roche
NFN.C. Friggens
N.C. Friggens
JKJ.K. Kay
J.K. Kay
MFM.W. Fisher
M.W. Fisher
KSK.J. Stafford
K.J. Stafford
DBDonagh Berry
Donagh Berry
The body condition score (BCS) of a dairy cow is an assessment of the proportion of body fat that it possesses, and it is recognized by animal scientists and producers as being an important factor in dairy cattle management. The scale used to measure BCS differs between countries, but low values always reflect emaciation and high values equate to obesity. The intercalving profile of BCS is a mirror image of the milk lactation profile. Cows lose condition for 50 to 100 d postcalving, because of homeorhetic changes that occur in the somatotropic axis and the sensitivity of peripheral tissues to insulin, and the upregulation of lipolytic pathways in adipose tissue. Management and feeding have little effect on early postcalving BCS loss (wk 1 to 4 postcalving) until the natural period of insulin resistance has passed and the somatotropic axis has recoupled. There is evidence, however, that management and diet can influence the timing of recoupling of the somatotropic axis and the sensitivity of peripheral tissues to insulin, and gene expression differences in adipose tissue 30 d in milk confirm an effect of energy intake on lipogenic enzymes. The BCS in which a cow calves, nadir BCS, and the amount of BCS she loses postcalving are associated with milk production, reproduction, and health. Body condition score may also be a valid indicator of animal welfare, but further research is required to determine the effect of BCS and BCS change on how a cow "feels." Although the actual strength of the association may vary, there is relative consistency in the associations among calving and nadir BCS, and BCS change on milk production, postpartum anestrous, the likelihood of a successful pregnancy and days open, the risk of uterine infection, and the risk of metabolic disorders. For many production and health variables, the association with BCS is nonlinear, with an optimum calving BCS of 3.0 to 3.25 (5-point scale); lower calving BCS is associated with reduced production and reproduction, whereas calving BCS >/=3.5 (5-point scale) is associated with a reduction in early lactation dry matter intake and milk production and an increased risk of metabolic disorders. Ongoing research into the automation of body condition scoring suggests that it is a likely candidate to be incorporated into decision support systems in the near future to aid producers in making operational and tactical decisions.

14 August 2012 in BMC Genetics
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Journal Article
Open access
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DPDeirdre C Purfield
Deirdre C Purfield
DBDonagh Berry
Donagh Berry
SMSinéad McParland
Sinéad McParland
DBDaniel G Bradley
Daniel G Bradley
Background: Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that are present in an individual due to parents transmitting identical haplotypes to their offspring. The extent and frequency of ROHs may inform on the ancestry of an individual and its population. Here we use high density (n = 777,962) bi-allelic SNPs in a range of cattle breed samples to correlate ROH with the pedigree-based inbreeding coefficients and to validate subsequent analyses using 54,001 SNP genotypes. This study provides a first testing of the inference drawn from ROH through comparison with estimates of inbreeding from calculations based on the detailed pedigree data available for several breeds. Results: All animals genotyped on the HD panel displayed at least one ROH that was between 1–5 Mb in length with certain regions of the genome more likely to be involved in a ROH than others. Strong correlations (r = 0.75, p < 0.0001) existed between the pedigree-based inbreeding coefficient and a statistic based on sum of ROH of length > 0.5 KB and suggests that in the absence of an animal’s pedigree data, the extent of a genome under ROH may be used to infer aspects of recent population history even from relatively few samples. Conclusions: Our findings suggest that ROH are frequent across all breeds but differing patterns of ROH length and burden illustrate variations in breed origins and recent management.

1 January 2014 in Animal
Verified
Journal Article
Open access
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DBDonagh Berry
Donagh Berry
EWE. Wall
E. Wall
JPJ. E. Pryce
J. E. Pryce
Excellent reproductive performance in both males and females is fundamental to profitable dairy and beef production systems. In this review we undertook a meta-analysis of genetic parameters for female reproductive performance across 55 dairy studies or populations and 12 beef studies or populations as well as across 28 different studies or populations for male reproductive performance. A plethora of reproductive phenotypes exist in dairy and beef cattle and a meta-analysis of the literature suggests that most of the female reproductive traits in dairy and beef cattle tend to be lowly heritable (0.02 to 0.04). Reproductive-related phenotypes in male animals (e.g. semen quality) tend to be more heritable than female reproductive phenotypes with mean heritability estimates of between 0.05 and 0.22 for semen-related traits with the exception of scrotal circumference (0.42) and field non-return rate (0.001). The low heritability of reproductive traits, in females in particular, does not however imply that genetic selection cannot alter phenotypic performance as evidenced by the decline until recently in dairy cow reproductive performance attributable in part to aggressive selection for increased milk production. Moreover, the antagonistic genetic correlations among reproductive traits and both milk (dairy cattle) and meat (beef cattle) yield is not unity thereby implying that simultaneous genetic selection for both increased (milk and meat) yield and reproductive performance is indeed possible. The required emphasis on reproductive traits within a breeding goal to halt deterioration will vary based on the underlying assumptions and is discussed using examples for Ireland, the United Kingdom and Australia as well as quantifying the impact on genetic gain for milk production. Advancements in genomic technologies can aid in increasing the accuracy of selection for especially reproductive traits and thus genetic gain. Elucidation of the underlying genomic mechanisms for reproduction could also aid in resolving genetic antagonisms. Past breeding programmes have contributed to the deterioration in reproductive performance of dairy and beef cattle. The tools now exist, however, to reverse the genetic trends in reproductive performance underlying the observed phenotypic trends.

19 February 2018 in Nature Genetics
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Journal Article
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ABAniek C. Bouwman
Aniek C. Bouwman
HDHans Daetwyler
Hans Daetwyler
ACAmanda J. Chamberlain
Amanda J. Chamberlain
CPCarla Hurtado Ponce
Carla Hurtado Ponce
MSMehdi Sargolzaei
Mehdi Sargolzaei
BHBen Hayes
Ben Hayes
Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

1 August 2017 in Applied and Environmental Microbiology
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Journal Article
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UMUrsula M. McCormack
Ursula M. McCormack
TCTânia Curião
Tânia Curião
SBStefan G. Buzoianu
Stefan G. Buzoianu
MPMaria L. Prieto
Maria L. Prieto
TRTomas Ryan
Tomas Ryan
PLPeadar G. Lawlor
Peadar G. Lawlor
Feed efficiency (FE) is critical in pig production for both economic and environmental reasons. As the intestinal microbiota plays an important role in energy harvest, it is likely to influence FE. Therefore, our aim was to characterize the intestinal microbiota of pigs ranked as low, medium, and high residual feed intake ([RFI] a metric for FE), where genetic, nutritional, and management effects were minimized, to explore a possible link between the intestinal microbiota and FE. Eighty-one pigs were ranked according to RFI between weaning and day 126 postweaning, and 32 were selected as the extremes in RFI (12 low, 10 medium, and 10 high). Intestinal microbiota diversity, composition, and predicted functionality were assessed by 16S rRNA gene sequencing. Although no differences in microbial diversity were found, some RFI-associated compositional differences were revealed, principally among members of Firmicutes , predominantly in feces at slaughter (albeit mainly for low-abundance taxa). In particular, microbes associated with a leaner and healthier host (e.g., Christensenellaceae , Oscillibacter , and Cellulosilyticum ) were enriched in low RFI (more feed-efficient) pigs. Differences were also observed in the ileum of low RFI pigs; most notably, Nocardiaceae ( Rhodococcus ) were less abundant. Predictive functional analysis suggested improved metabolic capabilities in these animals, especially within the ileal microbiota. Higher ileal isobutyric acid concentrations were also found in low RFI pigs. Overall, the differences observed within the intestinal microbiota of low RFI pigs compared with that of their high RFI counterparts, albeit relatively subtle, suggest a possible link between the intestinal microbiota and FE in pigs. IMPORTANCE This study is one of the first to show that differences in intestinal microbiota composition, albeit subtle, may partly explain improved feed efficiency (FE) in low residual feed intake (RFI) pigs. One of the main findings is that, although microbial diversity did not differ among animals of varying FE, specific intestinal microbes could potentially be linked with porcine FE. However, as the factors impacting FE are still not fully understood, intestinal microbiota composition may not be a major factor determining differences in FE. Nonetheless, this work has provided a potential set of microbial biomarkers for FE in pigs. Although culturability could be a limiting factor and intervention studies are required, these taxa could potentially be targeted in the future to manipulate the intestinal microbiome so as to improve FE in pigs. If successful, this has the potential to reduce both production costs and the environmental impact of pig production.

1 April 2013 in Journal of Animal Science
Verified
Journal Article
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PDF file
DBDonagh Berry
Donagh Berry
JCJ. J. Crowley
J. J. Crowley
Increasing food production for the growing human population off a constraining land base will require greater efficiency of production. Genetic improvement of feed efficiency in cattle, which is cumulative and permanent, is one likely vehicle to achieving efficiency gains. The objective of this review is to summarize genetic parameters for feed efficiency traits in dairy and beef cattle and also to address some of the misconceptions associated with feed efficiency in these sectors, as well as discuss the potential use of feed efficiency in breeding programs. A meta-analysis of up to 39 scientific publications in growing cattle clearly showed that genetic variation in feed efficiency exists with a pooled heritability for residual feed intake (RFI) and feed conversion efficiency of 0.33 ± 0.01 (range of 0.07 to 0.62) and 0.23 ± 0.01 (range of 0.06 to 0.46), respectively. Heritability estimates for feed efficiency in cows were lower; a meta-analysis of up to 11 estimates revealed heritability estimates for gross feed efficiency and RFI of 0.06 ± 0.010 and 0.04 ± 0.008, respectively. Meta-analysis of genetic correlations between feed intake, feed efficiency and other performance traits are presented, and selection index theory is used to calculate the proportion of genetic variation in feed intake that can be explained by easy to measure, and often already collected, data. A large proportion of the genetic variation in feed intake could be explained in both growing animals and lactating animals using up to 5 predictor traits, including BW, growth rate, milk yield, body composition, and linear type traits reflecting body size and muscularity. Knowledge of genetic merit for feed intake can be used, along with estimates of genetic merit for energy sinks, to calculate genetic merit for feed efficiency. Therefore, the marginal benefit of collecting actual feed intake data, using the genetic parameters used in this study, appears to be low. There is now sufficient information available to develop a road map on how best to direct research to ensure long-term food security for a growing human population. Gaps in knowledge are identified here, and possibilities to address these gaps are discussed.