Evidence map›Paper›PMID 33996959›Full record

ReviewFrontiers in veterinary science2021

Climate-Resilient Dairy Cattle Production: Applications of Genomic Tools and Statistical Models.

Mullakkalparambil Velayudhan Silpa, Sven König, Veerasamy Sejian, Pradeep Kumar Malik, Mini Ravi Reshma Nair, Vinicius F C Fonseca, Alex Sandro Campos Maia, Raghavendra Bhatta

Abstract readReview
In one paragraph

Review in Frontiers in veterinary science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mullakkalparambil Velayudhan SilpaInstitute of Animal Breeding and Genetics, Justus-Liebig-Universität Gießen, Gießen, Germany.
Sven KönigInstitute of Animal Breeding and Genetics, Justus-Liebig-Universität Gießen, Gießen, Germany.
Veerasamy SejianCenter for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India.
Pradeep Kumar MalikCenter for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India.
Mini Ravi Reshma NairCenter for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India.
Vinicius F C FonsecaInnovation Group of Thermal Comfort and Animal Welfare (INOBIO-MANERA), Animal Science Department, Universidade Federal da Paraíba, Areia, Brazil.
Alex Sandro Campos MaiaInnovation Group of Thermal Comfort and Animal Welfare (INOBIO-MANERA), Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), São Paulo, Brazil.
Raghavendra BhattaCenter for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current changing climate trend poses a threat to the productive efficacy and welfare of livestock across the globe. This review is an attempt to synthesize information pertaining to the applications of various genomic tools and statistical models that are available to identify climate-resilient dairy cows. The different functional and economical traits which govern milk production play a significant role in determining the cost of milk production. Thus, identification of these traits may revolutionize the breeding programs to develop climate-resilient dairy cattle. Moreover, the genotype-environment interaction also influences the performance of dairy cattle especially during a challenging situation. The recent advancement in molecular biology has led to the development of a few biotechnological tools and statistical models like next-generation sequencing (NGS), microarray technology, whole transcriptome analysis, and genome-wide association studies (GWAS) which can be used to quantify the molecular mechanisms which govern the climate resilience capacity of dairy cows. Among these, the most preferred option for researchers around the globe was GWAS as this approach jointly takes into account all the genotype, phenotype, and pedigree information of farm animals. Furthermore, selection signatures can also help to demarcate functionally important regions in the genome which can be used to detect potential loci and candidate genes that have undergone positive selection in complex milk production traits of dairy cattle. These identified biomarkers can be incorporated in the existing breeding policies using genomic selection to develop climate-resilient dairy cattle.

Indexed as

dairy (cows)genome-wide association studyheat stressmolecular markersthermoregulation

Identifiers

PMID33996959
PMCPMC8117237

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.