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利用日本气象数据对纯种长白猪活产仔数的高原线性反应规范模型分析。

Plateau-linear reaction norm model analysis of number born alive in purebred Landrace pigs using meteorological data in Japan.

机构信息

Division of Meat Animal and Poultry Research, Institute of Livestock and Grassland Science, NARO, Tsukuba, Ibaraki, Japan.

Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan.

出版信息

J Anim Breed Genet. 2024 Nov;141(6):656-667. doi: 10.1111/jbg.12871. Epub 2024 May 13.

Abstract

We performed a plateau-linear reaction norm model (RNM) analysis of number born alive (NBA) in purebred Landrace pigs, where breeding value changes according to maximum temperature at mating day, using public meteorological observation data in Japan. We analysed 52,668 NBA records obtained from 10,320 Landrace sows. Pedigree data contained 99,201 animals. Off-farm daily temperature data at the nearest weather station from each of the farms were downloaded from the Japan Meteorological Agency website. A plateau-linear RNM analysis based on daily maximum temperature on mating day (threshold temperature of 16.6°C) was performed. The percentage of the records with daily maximum temperatures at mating days of ≤16.6, ≥25.0, ≥30.0 and ≥35.0°C were 34.3%, 33.6%, 14.0% and 0.8%, respectively. The value of Akaike's information criterion for the plateau-linear RNM was lower than that for a simple repeatability model (RM). With the plateau-linear RNM, estimated value of heritability ranged from 0.14 to 0.15, while that from the RM analysis was 0.15. Additive genetic correlation between intercept and slope terms was estimated to be -0.52 from the plateau-linear RNM analysis. Estimated additive genetic correlations were >0.9 between NBA at different temperatures ranging from 16.6 to 37.6°C. For the 10,320 sows, average values of prediction reliability of the intercept and slope terms for breeding values in the plateau-linear RNM were 0.47 and 0.16, respectively. Increasing weight for slope term in linear selection index could bring positive genetic gain in the slope part, but prediction accuracy would decrease. Our results imply that genetically improving heat tolerance in sows reared in Japan focusing on NBA using RNM is possible, while RNM is more complex to implement and interpret. Therefore, further study should be encouraged to make genetic improvement for heat tolerance in sows more efficient.

摘要

我们对纯种长白猪的活产仔数(NBA)进行了平台线性反应规范模型(RNM)分析,其中根据配种日的最高温度来改变繁殖值,使用了日本的公共气象观测数据。我们分析了从 10320 头长白母猪获得的 52668 个 NBA 记录。系谱数据包含 99201 头动物。从每个农场最近的气象站下载了场外每日温度数据。从日本气象厅网站下载了场外每日温度数据。根据配种日的每日最高温度(16.6°C 的阈值温度)进行了平台线性 RNM 分析。配种日每日最高温度为≤16.6°C、≥25.0°C、≥30.0°C 和≥35.0°C 的记录百分比分别为 34.3%、33.6%、14.0%和 0.8%。平台线性 RNM 的 Akaike 信息准则值低于简单重复性模型(RM)的值。使用平台线性 RNM,估计的遗传力值范围在 0.14 到 0.15 之间,而 RM 分析的遗传力值为 0.15。平台线性 RNM 分析估计截距和斜率项之间的加性遗传相关性为-0.52。从平台线性 RNM 分析中估计,NBA 在 16.6°C 至 37.6°C 之间不同温度下的加性遗传相关性大于 0.9。对于 10320 头母猪,平台线性 RNM 中用于繁殖值的截距和斜率项的预测可靠性平均值分别为 0.47 和 0.16。线性选择指数中斜率项的权重增加会给斜率部分带来正向遗传增益,但预测准确性会降低。我们的结果表明,使用 RNM 从提高日本母猪的 NBA 方面来提高母猪的耐热性是可能的,尽管 RNM 更复杂,实施和解释起来也更困难。因此,应该鼓励进一步的研究,以使母猪的耐热性遗传改良更加高效。

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