Research on Genetics and Genomics of Cattle
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Animal Genetics and Genomics".
Deadline for manuscript submissions: 20 May 2024 | Viewed by 7346
Special Issue Editor
Special Issue Information
Dear Colleagues,
Cattle are the most widespread species of large ruminants. They have incredibly high economic value and provide us with meat (such as Japanese beef, Angus, and Simmental), milk (Holstein and Jersey), leather, and other useful products. With the development of biotechnology, molecular biology, genetics, and bioinformatics, multi-omics approaches are commonly used to reveal the mechanisms underlying bovine milk performance, reproductive traits, beef quality, growth traits, disease resistance, and other important traits from the DNA level (such as polymorphisms and chromosome modification), RNA level (ncRNA, alternative splicing, and RNA modification), and protein level (protein phosphorylation and acetylation). However, much of their detailed regulatory mechanism is unknown. Genes is now inviting submissions for a Special Issue on the topic of “Genetics and Genomics of Cattle”. Research articles, reviews, short communications, brief reports, and other forms of original articles on this topic are all welcome. Your contribution will open new avenues to discover the theoretical and practical aspects of cattle phenotype traits and provide valuable information for cattle breeding projects.
Dr. Hanfang Cai
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- cattle
- regulatory mechanisms
- epigenetics
- transcriptome
- proteome
- sequencing
- gene
- polymorphisms
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
1. Title: KBeagle: An Adaptive Strategy and Tool for Improving Imputation Accuracy and Computing Time
Abstract: Deep sequencing is now the primary way to uncover genetic variation and genomic. However, the complexity of entire genomes means that large segments remain missing even after sequencing. This issue has led to the development of computing intensive and efficient imputation software. In particular, the imputation software Beagle has been widely preferred for its low memory consumption and fast running speed. Here, we combined K-Means clustering algorithm with Beagle to improve the program’s imputation matching rate and shorten its computing time. We named this strategy as “KBeagle” (code freely available on Github: https://github.com/QinJieqq/KBeagle). The datasets used in the genomic selection test with imputed, unimputed, and real genotype show similar prediction accuracy under five-fold cross validation. However, estimated heritability using the KBeagle-imputed genotype dataset was closer to the estimations using the dataset containing real genotype. We envisage a major application of KBeagle will be focus on livestock sequencing studies under strong genetic structure. In conclusion, wimputation matching rate and computing time.