Evaluation of single nucleotide polymorphisms identified through the use of SNP assay in Romanian and Chinese Holstein and Simmental cattle breeds

Ilie, Daniela Elena; Gao, Yahui; Nicolae, Ioana; Sun, Dongxiao; Li, Junya; Gavojdian, Dinu

doi:10.18388/abp.2020_5080

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…The basic genetic diversity indices (H o , H e , and MAF) pointed to the increase of overall genomic homozygosity in each analysed population consistent with Matukumalli et al [75], which developed and characterised the high-density bovine SNP microarray. Similarly, various other genomic studies reported the decrease of overall heterozygosity in European cattle breeds [6,70,76,77]. Heterozygosity can range from 0 (no heterozygosity) to 1 (populations with a large number of alleles with approximately the same frequency).…”

Section: Discussionmentioning

confidence: 71%

Food Resources Biodiversity: The Case of Local Cattle in Slovakia

et al. 2021

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This study aimed to assess the level of biodiversity in selected local cattle populations as important food resources in Slovakia. The biodiversity level was derived from the genome-wide data collected for dairy (Jersey), dual-purpose (Slovak Pinzgau, Slovak Spotted), and beef breeds (Charolais, Limousine). The commonly used indices, genomic inbreeding (FROH, FGRM, FHOM, FUNI) and effective population size (NeLD), were used to quantify the impact of relatives mating on the genome of analysed populations. Even if the low NeLD estimates signalise significant loss of genetic variability within populations, the genomic inbreeding under 1% (except Jersey) showed that the intensity of diversity loss is not so rapid and can be managed by the re-arrangement of long-term breeding strategies. The analysis of genetic differentiation degree across populations assumed that the specialisation of breeds during their grading-up led to the specific nucleotide changes, especially in genes responsible for preferred phenotypic traits. The breed-specific differences observed mainly in the genome of Charolais (carcass traits) and Jersey (milk production traits) populations resulted from the polymorphisms in CAPN1 (μ-calpain) and CSN1S2 (casein alpha s2) genes, respectively. Obtained results confirmed that the specific haplotypes are strongly associated with the genetic nature of breed depending on production type.

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Section: Discussionmentioning

confidence: 71%

Food Resources Biodiversity: The Case of Local Cattle in Slovakia

et al. 2021

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“…In total, 20 lactating adult multiparous cows of the Romanian Holstein breed were tested between August and September 2022. The Romanian Holstein breed (RH, national name Bălțată cu Negru Românească) belongs to the dairy Holstein-Friesian strain, with a current census of 264,000 cows, representing 22% of the breed structure in Romania ( 36 ). The RH originates in the 19th century, being the result of systematic crossbreeding between Friesian bulls imported from Denmark and Germany and local cattle, such as Romanian Spotted and Dobruja Red.…”

Section: Methodsmentioning

confidence: 99%

BovineTalk: machine learning for vocalization analysis of dairy cattle under the negative affective state of isolation

Gavojdian,

Mincu,

Lazebnik

et al. 2024

Front. Vet. Sci.

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There is a critical need to develop and validate non-invasive animal-based indicators of affective states in livestock species, in order to integrate them into on-farm assessment protocols, potentially via the use of precision livestock farming (PLF) tools. One such promising approach is the use of vocal indicators. The acoustic structure of vocalizations and their functions were extensively studied in important livestock species, such as pigs, horses, poultry, and goats, yet cattle remain understudied in this context to date. Cows were shown to produce two types of vocalizations: low-frequency calls (LF), produced with the mouth closed, or partially closed, for close distance contacts, and open mouth emitted high-frequency calls (HF), produced for long-distance communication, with the latter considered to be largely associated with negative affective states. Moreover, cattle vocalizations were shown to contain information on individuality across a wide range of contexts, both negative and positive. Nowadays, dairy cows are facing a series of negative challenges and stressors in a typical production cycle, making vocalizations during negative affective states of special interest for research. One contribution of this study is providing the largest to date pre-processed (clean from noises) dataset of lactating adult multiparous dairy cows during negative affective states induced by visual isolation challenges. Here, we present two computational frameworks—deep learning based and explainable machine learning based, to classify high and low-frequency cattle calls and individual cow voice recognition. Our models in these two frameworks reached 87.2 and 89.4% accuracy for LF and HF classification, with 68.9 and 72.5% accuracy rates for the cow individual identification, respectively.

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“…The α value was not fixed for each phenotype or even different functional regions of the genome [ 11 ]. A value of α = 0 or −1 is usually used to estimate the functional enrichment in livestock population [ 12 ], but the consequences of different α values on heritability enrichment have not been systematically compared and studied.…”

Section: Introductionmentioning

confidence: 99%

Model Comparison of Heritability Enrichment Analysis in Livestock Population

Cai

Teng

Ren

et al. 2022

Genes

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Heritability enrichment analysis is an important means of exploring the genetic architecture of complex traits in human genetics. Heritability enrichment is typically defined as the proportion of an SNP subset explained heritability, divided by the proportion of SNPs. Heritability enrichment enables better study of underlying complex traits, such as functional variant/gene subsets, biological networks and metabolic pathways detected through integrating explosively increased omics data. This would be beneficial for genomic prediction of disease risk in humans and genetic values estimation of important economical traits in livestock and plant species. However, in livestock, factors affecting the heritability enrichment estimation of complex traits have not been examined. Previous studies on humans reported that the frequencies, effect sizes, and levels of linkage disequilibrium (LD) of underlying causal variants (CVs) would affect the heritability enrichment estimation. Therefore, the distribution of heritability across the genome should be fully considered to obtain the unbiased estimation of heritability enrichment. To explore the performance of different heritability enrichment models in livestock populations, we used the VanRaden, GCTA and α models, assuming different α values, and the LDAK model, considering LD weight. We simulated three types of phenotypes, with CVs from various minor allele frequency (MAF) ranges: genome-wide (0.005 ≤ MAF ≤ 0.5), common (0.05 ≤ MAF ≤ 0.5), and uncommon (0.01 ≤ MAF < 0.05). The performances of the models with two different subsets (one of which contained known CVs and the other consisting of randomly selected markers) were compared to verify the accuracy of heritability enrichment estimation of functional variant sets. Our results showed that models with known CV subsets provided more robust enrichment estimation. Models with different α values tended to provide stable and accurate estimates for common and genome-wide CVs (relative deviation 0.5–2.2%), while tending to underestimate the enrichment of uncommon CVs. As the α value increased, enrichments from 15.73% higher than true value (i.e., 3.00) to 48.93% lower than true value for uncommon CVs were observed. In addition, the long-range LD windows (e.g., 5000 kb) led to large bias of the enrichment estimations for both common and uncommon CVs. Overall, heritability enrichment estimations were sensitive for the α value assumption and LD weight consideration of different models. Accuracy would be greatly improved by using a suitable model. This study would be helpful in understanding the genetic architecture of complex traits and provides a reference for genetic analysis in the livestock population.

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Evaluation of single nucleotide polymorphisms identified through the use of SNP assay in Romanian and Chinese Holstein and Simmental cattle breeds

Cited by 5 publications

References 32 publications

Food Resources Biodiversity: The Case of Local Cattle in Slovakia

Food Resources Biodiversity: The Case of Local Cattle in Slovakia

BovineTalk: machine learning for vocalization analysis of dairy cattle under the negative affective state of isolation

Model Comparison of Heritability Enrichment Analysis in Livestock Population

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