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      Short communication: Time-dependent genetic parameters and single-step genome-wide association analyses for predicted milk fatty acid composition in Ayrshire and Jersey dairy cattle.

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          Abstract

          Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS, FGF10, and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle.

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          Most cited references51

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          KEGG: kyoto encyclopedia of genes and genomes.

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          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

              Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

                Author and article information

                Journal
                J Dairy Sci
                Journal of dairy science
                American Dairy Science Association
                1525-3198
                0022-0302
                Jun 2020
                : 103
                : 6
                Affiliations
                [1 ] Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Department of Animal Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil.
                [2 ] Department of Animal Sciences, Purdue University, West Lafayette, IN 47907.
                [3 ] Department of Animal Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil.
                [4 ] Lactanet Canada, Guelph, Ontario, N1K 1E5, Canada.
                [5 ] Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.
                [6 ] Department of Animal Sciences, Purdue University, West Lafayette, IN 47907. Electronic address: britol@purdue.edu.
                Article
                S0022-0302(20)30285-X
                10.3168/jds.2019-17820
                32307163
                c32c731c-ece0-4739-9c31-a03707adcc5c
                Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
                History

                genome-wide association studies,longitudinal trait,mid-infrared spectroscopy,random regression,saturated fatty acid

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