4 Heritability Estimations for Intramuscular Fat in Hereford Cattle Using Random Regressions.

遗传力 统计 随机效应模型 线性回归 数学 回归 回归分析 限制最大似然 协变量 多项式回归 逻辑回归 生物 最大似然 遗传学 医学 内科学 荟萃分析
作者
Jose S Delgadillo Liberona,J M Langdon,David G. Riley,Harvey D. Blackburn,Scott E Speidel,Bethany Krehbiel,Stacy Sanders,A. D. Herring
出处
期刊:Journal of Animal Science [Oxford University Press]
卷期号:96 (suppl_1): 2-3
标识
DOI:10.1093/jas/sky027.004
摘要

Random regressions make genetic predictions and parameter estimates possible across environmental gradients, which might possibly allow more accurate identification and beneficial use of breeding animals in specific environments. The objective of this study was to use random regression models for the estimation of heritability of intramuscular fat (IMF) in Hereford cattle, across a longitudinal gradient in the United States. Records were obtained from the American Hereford Association (n = 169,440) that included pedigree information from 227,902 animals. Three models were evaluated using ASReml: a quadratic random regression, a linear random regression, and a model without random regression. For all models, the fixed component involved the effects of contemporary group and ecoregion, where ecoregions were defined based on temperature and humidity designations across the United States. The random component considered the random effect of the animal itself, or as interacting with a linear or quadratic regression, using the longitude coordinates where the animal was reared as the regressor variable. The fit of the models was evaluated through likelihood-ratio tests, where the quadratic regression model proved to have significant advantages in comparison to the rest (P < 0.01). Heritability estimates using the quadratic model ranged from 0.31 to 0.54, having maximum value at the western coordinate evaluated (124.09 degrees west). Then, advancing from west to east the IMF heritability decreased reaching its minimum value at 99 degrees west. Furthermore, the heritability began to increase again, reaching values around 0.47 at the eastern coordinate evaluated (71.47 degrees west). These results indicate that quadratic random regressions may make improved parameter estimations and therefore improved genetic predictions for IMF in American Hereford cattle. This information may help to generate more precise selection indexes across different sectors of the United States. It may be possible that estimate differences could also occur for other economically relevant traits and other breeds, and further research is needed for this phenomenon.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
青衫完成签到 ,获得积分10
1秒前
按时毕业完成签到,获得积分10
4秒前
psycho完成签到,获得积分10
4秒前
龘勠完成签到 ,获得积分10
5秒前
lcjynwe完成签到,获得积分10
6秒前
勤奋花瓣完成签到 ,获得积分10
6秒前
lzl008完成签到 ,获得积分10
6秒前
7秒前
范六六发布了新的文献求助30
7秒前
BingyuLi完成签到,获得积分10
7秒前
8秒前
9秒前
小小灯笼完成签到 ,获得积分10
9秒前
慈祥的巧曼完成签到,获得积分10
11秒前
xin完成签到,获得积分10
11秒前
俭朴的觅松完成签到 ,获得积分10
11秒前
hhh完成签到,获得积分10
12秒前
Li818发布了新的文献求助10
13秒前
要减肥的翠萱完成签到 ,获得积分10
13秒前
菠萝蜜完成签到,获得积分10
14秒前
xuxu213发布了新的文献求助10
14秒前
大胖完成签到,获得积分10
14秒前
lanrete完成签到,获得积分10
15秒前
15秒前
ding应助张zz采纳,获得10
15秒前
小米完成签到,获得积分0
16秒前
英俊的铭应助WZH采纳,获得10
16秒前
orixero应助秀丽笑容采纳,获得10
16秒前
Tough发布了新的文献求助10
17秒前
17秒前
livra1058发布了新的文献求助10
17秒前
保持理智完成签到,获得积分10
19秒前
lzl007完成签到 ,获得积分10
20秒前
luxkex完成签到,获得积分10
21秒前
叮叮当当完成签到,获得积分10
23秒前
23秒前
脑洞疼应助科研通管家采纳,获得10
23秒前
23秒前
Xie应助科研通管家采纳,获得10
23秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359087
求助须知:如何正确求助?哪些是违规求助? 8173088
关于积分的说明 17212429
捐赠科研通 5414114
什么是DOI,文献DOI怎么找? 2865393
邀请新用户注册赠送积分活动 1842747
关于科研通互助平台的介绍 1690901