Invited review: Bioinformatic methods to discover the likely causal variant of a new autosomal recessive genetic condition using genome-wide data

In animals, new autosomal recessive genetic diseases (ARGD) arise all the time due to the regular, random mutations that occur during meiosis. In order to reduce the effect of any damaging new variant, it is necessary to find its cause. To evaluate the best way of doing this, 34 papers which found the exact location of a new genetic disease in livestock were reviewed and found to require at least two stages. In the initial stage the commonly used χ2 method, applied in a case-control association analysis with single nucleotide polymorphism (SNP)-chip data, was found to have limitations and was almost always used in conjunction with a second method to locate the target region on the genome containing the variant. The commonly used methods had their drawbacks; so a new method was devised based on long runs of homozygosity, a common feature of new ARGD. This ‘autozygosity by difference’ method was found to be as good as, or better than, all the reviewed methods tested based on its ability to unambiguously find the shortest known target region in an already analysed data set. Mean target region length was found to be 4.6 megabases in the published reports. Success did not depend on the size of commercial SNP-chip used, and studies with as few as three cases and four controls were large enough to find the target region. The final stage relied on either sequencing the candidate genes found in the target region or using whole genome sequencing (WGS) on a small number of cases. Sometimes this latter method was used in conjunction with WGS on a number of control animals or resources such as the 1000 bull genomes data. Calculations showed that, in cattle, less than 15 animals would be needed in order to locate the new variant when using WGS data. This could be any combination of cases plus parents or other unrelated animals in the breed. Using WGS data, it would be necessary to search the three billion bases of the cattle genome for base positions which were homozygous for the same allele in all cases and heterozygous for that allele in parents, or not containing that homozygote in unrelated controls. This site could be confirmed on other healthy animals using much cheaper methods, and then a genetic test could be devised for that variant in order to screen the whole population and to devise a breeding programme to eliminate the disorder from the population

Genetic factors controlling wool shedding in a composite Easycare sheep flock

Historically, sheep have been selectively bred for desirable traits including wool characteristics. However, recent moves towards extensive farming and reduced farm labour have seen a renewed interest in Easycare breeds. The aim of this study was to quantify the underlying genetic architecture of wool shedding in an Easycare flock. Wool shedding scores were collected from 565 pedigreed commercial Easycare sheep from 2002 to 2010. The wool scoring system was based on a 10-point (0-9) scale, with score 0 for animals retaining full fleece and 9 for those completely shedding. DNA was sampled from 200 animals of which 48 with extreme phenotypes were genotyped using a 50-k SNP chip. Three genetic analyses were performed: heritability analysis, complex segregation analysis to test for a major gene hypothesis and a genome-wide association study to map regions in the genome affecting the trait. Phenotypes were treated as a continuous or binary variable and categories. High estimates of heritability (0.80 when treated as a continuous, 0.65-0.75 as binary and 0.75 as categories) for shedding were obtained from linear mixed model analyses. Complex segregation analysis gave similar estimates (0.80 ± 0.06) to those above with additional evidence for a major gene with dominance effects. Mixed model association analyses identified four significant (P <0.05) SNPs. Further analyses of these four SNPs in all 200 animals revealed that one of the SNPs displayed dominance effects similar to those obtained from the complex segregation analyses. In summary, we found strong genetic control for wool shedding, demonstrated the possibility of a single putative dominant gene controlling this trait and identified four SNPs that may be in partial linkage disequilibrium with gene(s) controlling shedding

Dairy cattle in a temperate climate: the effects of weather on milk yield and composition depend on management

A better understanding of how livestock respond to weather is essential to enable farming to adapt to a changing climate. Climate change is mainly expected to impact dairy cattle through heat stress and an increase in the frequency of extreme weather events. We investigated the effects of weather on milk yield and composition (fat and protein content) in an experimental dairy herd in Scotland over 21 years. Holstein Friesian cows were either housed indoors in winter and grazed over the summer or were continuously housed. Milk yield was measured daily, resulting in 762 786 test day records from 1369 individuals, and fat and protein percentage were sampled once a week, giving 89 331 records from 1220 cows/trait. The relative influence of 11 weather elements, measured from local outdoor weather stations, and two indices of temperature and humidity (THI), indicators of heat stress, were compared using separate maximum likelihood models for each element or index. Models containing a direct measure of temperature (dry bulb, wet bulb, grass or soil temperature) or a THI provided the best fits to milk yield and fat data; wind speed and the number of hours of sunshine were most important in explaining protein content. Weather elements summarised across a week's timescale from the test day usually explained milk yield and fat content better than shorter-scale (3 day, test day, test day -1) metrics. Then, examining a subset of key weather variables using restricted maximum likelihood, we found that THI, wind speed and the number of hours of sunshine influenced milk yield and composition. The shape and magnitude of these effects depended on whether animals were inside or outside on the test day. The milk yield of cows outdoors was lower at the extremes of THI than at average values, and the highest yields were obtained when THI, recorded at 0900 h, was 55 units. Cows indoors decreased milk yield as THI increased. Fat content was lower at higher THIs than at intermediate THIs in both environments. Protein content decreased as THI increased in animals kept indoors and outdoors, and the rate of decrease was greater when animals were outside than when they were inside. Moderate wind speeds appeared to alleviate heat stress. These results show that milk yield and composition are impacted at the upper extreme of THI under conditions currently experienced in Scotland, where animals have so far experienced little pressure to adapt to heat stress

Age at First Viral Infection Determines the Pattern of T Cell–mediated Disease during Reinfection in Adulthood

Infants experiencing severe respiratory syncytial virus (RSV) bronchiolitis have an increased frequency of wheeze and asthma in later childhood. Since most severe RSV infections occur between the 8th and 24th postnatal week, we examined whether age at first infection determines the balance of cytokine production and lung pathology during subsequent rechallenge. Primary RSV infection in newborn mice followed the same viral kinetics as in adults but was associated with reduced and delayed IFN-γ responses. To study rechallenge, mice were infected at 1 day or 1, 4, or 8 weeks of age and reinfected at 12 weeks. Neonatal priming produced more severe weight loss and increased inflammatory cell recruitment (including T helper 2 cells and eosinophils) during reinfection, whereas delayed priming led to enhanced interferon γ production and less severe disease during reinfection. These results show the crucial importance of age at first infection in determining the outcome of reinfection and suggest that the environment of the neonatal lung is a major determinant of cytokine production and disease patterns in later life. Thus, simply delaying RSV infection beyond infancy might reduce subsequent respiratory morbidity in later childhood

Association between Single Nucleotide Polymorphism in RelA with Somatic Cell Count and Longevity Supports Importance of NF-¦ÊB Signalling in Cattle Health

Mastitis reduces milk production and causes culling. The NF-κB transcription factor RelA plays a central regulatory role in innate immunity. This study used a candidate gene approach to investigate associations between the synonymous C/G SNP rs48035703 in RELA with somatic cell count (SCC) and survival time. Blood samples were collected from 337 Holstein-Friesian heifers on 19 farms and genotyped by PCR-restriction fragment length polymorphism. Animals were monitored from 6 months until 2340 d of age. Pedigree, milk production and disease records were obtained. Genotype frequencies were CC 0.63, CG 0.30 and GG 0.06. The C allele had a favourable additive effect on survival: average longevities from birth were CC, 1872 d; CG, 1745 d and GG 1596 d (P < 0.003). Log transformed first lactation somatic cell count (SCC)data showed a significant association with this SNP using an allele substitution model (mean residuals ± SD: GG 0.30 ± 1.263; CG 0.22 ± 0.994, CC −0.04 ± 0.803, P < 0.05). More CC cows than expected were classified as intermediate and fewer as mastitic (30.4% v 45.9%) with respect to SCC class when categorised as 0 (unaffected), 1 (intermediate) and 2 (mastitic), whereas for CG heterozygotes fewer were intermediate and more were mastitic (12.1% v 60.3%) (p = 0.05). RELA rs48035703 CC genotype cows were therefore less likely to experience a high SCC and survived longer. These results support a role for RelA in combating mammary gland infection and warrant further studies in additional populations

A Nonsynonymous Change in Adhesion G Protein–Coupled Receptor L3 Associated With Risk for Equine Degenerative Myeloencephalopathy in the Caspian Horse

Equine degenerative myeloencephalopathy (EDM), a neurological disease of young horses, causes progressive development of symmetric ataxia predominantly in the pelvic limbs. Equine degenerative myeloencephalopathy is likely inherited and with no known treatment affected horses frequently need euthanasia. Alpha-tocopherol deficiency during early life appears to contribute to the phenotype. This study sought to identify any genetic variants correlated with EDM in Caspian foals. Two half-sibling EDM-diagnosed cases were genotyped at 52,063 loci and evaluated by the Autozygosity by Difference statistic. Additional horses not affected by EDM were used for genetic comparison to identify regions unique to the case phenotype. The associated region on chromosome 3 contains only one gene encoding adhesion G protein–coupled receptor L3 (ADGRL3). Adhesion G protein–coupled receptor L3 is a member of the latrophilin subfamily of G protein–coupled receptors and may contribute to attention deficit/hyperactivity disorder in humans and hyperactive motor function in mice and zebrafish. Analysis of the predicted coding regions for Equine ADGRL3 in affected horses revealed a nonsynonymous single nucleotide polymorphism at Chr3:71,917,591 bp. Caspian and Caspian cross-relatives (n = 81) of the two initial cases and unrelated horses from similar breeds (n = 130, including Arabians, American Miniatures, and Shetlands) possessed this allele at 5% frequency, with no homozygotes observed within the non-Caspian breeds. This study suggests that a polymorphism in ADGRL3 could contribute to a genetic predisposition to Caspian horse EDM

Locating a novel autosomal recessive genetic condition using only WGS data from three cases and six controls; a case study of a new variant in the cattle glucokinase gene

New Mendelian genetic conditions, which adversely affect livestock, arise all the time. To manage them effectively, some methods need to be devised that are quick and accurate. Until recently, finding the causal genomic site of a new autosomal recessive genetic disease has required a two-stage approach using single-nucleotide polymorphism (SNP) chip genotyping to locate the region containing the new variant. This region is then explored using fine-mapping methods to locate the actual site of the new variant. This study explores bioinformatic methods that can be used to identify the causative variants of recessive genetic disorders with full penetrance with just nine whole genome-sequenced animals to simplify and expedite the process to a one-step procedure. Using whole genome sequencing of only three cases and six carriers, the site of a novel variant causing perinatal mortality in Irish moiled calves was located. Four methods were used to interrogate the variant call format (VCF) data file of these nine animals, they are genotype criteria (GCR), autozygosity-by-difference (ABD), variant prediction scoring, and registered SNP information. From more than nine million variants in the VCF file, only one site was identified by all four methods (Chr4: g.77173487A>T (ARS-UCD1.2 (GCF_002263795.1)). This site was a splice acceptor variant located in the glucokinase gene (GCK). It was verified on an independent sample of animals from the breed using genotyping by polymerase chain reaction at the candidate site and autozygosity-by-difference using SNP-chips. Both methods confirmed the candidate site. Investigation of the GCR method found that sites meeting the GCR were not evenly spread across the genome but concentrated in regions of long runs of homozygosity. Locating GCR sites was best performed using two carriers to every case, and the carriers should be distantly related to the cases, within the breed concerned. Fewer than 20 animals need to be sequenced when using the GCR and ABD methods together. The genomic site of novel autosomal recessive Mendelian genetic diseases can be located using fewer than 20 animals combined with two bioinformatic methods, autozygosity-by-difference, and genotype criteria. In many instances it may also be confirmed with variant prediction scoring. This should speed-up and simplify the management of new genetic diseases to a single-step process

Environmental factors affecting lactation curve parameters in the United Kingdom’s commercial dairy herds

Environmental factors affecting lactation curve parameters in the United Kingdom&apos;s commercial dairy herds Factores ambientales que determinan los parámetros de la curva de lactación usando un modelo biológico en rebaños lecheros comerciales en el Reino Unido RESUMEN El objetivo del trabajo fue determinar los factores ambientales que determinan los parámetros de la curva de lactación utilizando un modelo biológico de ajuste de curva. El modelo propuesto ajusta dos curvas logísticas que simulan el incremento inicial en el número de células secretoras de leche en la lactación temprana, y la progresión de la apoptosis en la lactación tardía. Se analizaron lactaciones de 182.987 vacas Holstein-Friesian. Los factores vaca, rebaño y número de lactación explican el 74% de la suma total de cuadrados (P &lt; 0,001). La edad promedio a primer parto fue de 28 meses, teniendo un efecto significativo sobre la mayoría de los parámetros de la curva. Incrementos en la edad a primer de parto (20-40 meses) fueron asociados con incrementos lineales en los rendimientos totales de leche. Los parámetros tasa máxima de secreción y máximo de lactación estuvieron altamente correlacionados entre sí, indicando que son virtualmente los mismos. Adicionalmente, altos valores de estos dos parámetros indican altos rendimientos totales de leche. El día del máximo de lactación se correlacionó negativamente (0,64) con persistencia de la lactación. Los factores vaca, rebaño número de lactación y edad a primer parto fueron los factores más determinantes sobre los parámetros de la curva de lactación de vacas de primera lactancia así como de lactaciones múltiples

The application of a mechanistic model to analyze the factors that affect the lactation curve parameters of dairy sheep in Mexico

Pollott́s mechanistic model has been designed to describe lactation curve parameters based on the known biology of milk production and can be useful for analyzing the factors that affect this process. A total of 553 lactations (9956 weekly test-day records) of crossbred dairy sheep from four commercial farms located in Mexico, were analyzed to investigate environmental factors that influenced lactation curve parameters, using Pollott’s 5-parameter additive model. This model was fitted to each lactation using an iterative nonlinear procedure. The estimated parameters were maximum milk secretion potential (MSmax), relative rate of increase in cell differentiation (GR), maximum secretion loss (MSLmax), relative rate of decline in cell numbers (DR) and the proportion of parenchyma cells dead at parturition. A general linear model procedure was used to determine the effect of type of lambing, lambing number, flock and lambing season on total lactation milk yield (TMY), lactation length and estimated parameters of the Pollott model. Ewes had an average milk yield of 74.4 L with an average lactation length of 140 days. Flock had a significant (P < 0.05) effect on most of the analyzed traits, which can be explained by the different farmś management practices. The TMY were significantly (P = 0.005) higher for twin-lambing than single-lambing lactations. Sheep in their first lambing had lower TMY than those in their fourth lambing (P = 0.01), possibly explained by the lower values of MSmax (2.85 vs. 5.3 L) and the decrease in DR throughout life (P = 0.03). However, the relative GR was greatest (P = 0.04) during first lambing and then decreased as lambing number increased. Both lambing number and type of lambing also affected milk yield. The parameters of the Pollott model can be useful to explain, with a biological approximation, the dynamics of differentiation, secretion and death of mammary cells in dairy sheep