REHE: Fast Variance Components Estimation for Linear Mixed Models

Linear mixed models are widely used in ecological and biological applications, especially in genetic studies. Reliable estimation of variance components is crucial for using linear mixed models. However, standard methods, such as the restricted maximum likelihood (REML), are computationally inefficient and may be unstable with small samples. Other commonly used methods, such as the Haseman-Elston (HE) regression, may yield negative estimates of variances. Utilizing regularized estimation strategies, we propose the restricted Haseman-Elston (REHE) regression and REHE with resampling (reREHE) estimators, along with an inference framework for REHE, as fast and robust alternatives that provide non-negative estimates with comparable accuracy to REML. The merits of REHE are illustrated using real data and benchmark simulation studies.

17 Investigating pig survival in different productive stages using genomic models

Pig survival is an economically important trait with animal welfare implications. Although survival is highly affected by the environment, previous studies reported genetic variability of this trait, indicating the opportunity for improvement through selection. Genomic information is currently included in the major commercial pig breeding programs, which can be incorporated by single-step genomic BLUP (ssGBLUP). The objectives of this study were to: 1) estimate (co)variance components for farrowing, lactation, nursery, and finishing survival; and 2) compare the individual breeding value accuracies obtained using traditional pedigree-based BLUP (BLUP) and ssGBLUP methods. Individual survival records were collected for a crossbred pig population, and two-trait threshold models, which included maternal effects, were used for (co)variance components estimation. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods, and individual accuracies were obtained based on posterior standard deviation. Heritabilities for the four survival phases were low, ranging from 0.04 to 0.12. Pre-weaning survival was controlled by dam and piglet additive gene effects. The additive direct and maternal components were equally important at farrowing, whereas the piglet’s own genetic merit was the most expressive during lactation. Common environment estimates were higher than maternal genetic effects, indicating early life experiences related to the sow, but independent of the maternal genetic component. Nursery and finishing survival showed the same or higher heritabilities compared to pre-weaning stages. The genetic correlation between the pre-weaning phases was high (0.68), whereas the correlation between the post-weaning measurements was moderate (0.42). The incorporation of genomic information through ssGBLUP increased the individual accuracy, on average, from 0.36 to 0.41 for direct and from 0.29 to 0.37 for maternal effects compared to BLUP. Although the heritabilities for survival in different productive stages are low, genetic gains can be obtained, given that breeding values benefit from the inclusion of genomic information.

PENDUGAAN PARAMETER GENETIK PERFORMA PRASAPIH DOMBA GARUT DI UPTD-BPPTDK MARGAWATI GARUT

Pengembangan sumber daya genetik ternak lokal penting dilakukan untuk memenuhi permintaan dagingdomba yang tinggi di Indonesia khususnya Jawa Barat melalui kegiatan seleksi bibit unggul Domba garut.Penelitian ini bertujuan untuk mengetahui nilai parameter genetik sifat-sifat prasapih Domba garut. Sifat-sifat yang dianalisis pada penelitian ini yaitu bobot lahir (B0), bobot 30, 60, 90 hari (B30, B60, B90), dan bobot sapih pada 100 hari (B100) Domba garut di UPTD-BPPTDK Margawati Garut yang berasal dari 104 ekor pejantan, 1.809 ekor induk, 2.921 ekor anak domba jantan, dan 2.632 ekor anak domba betina. Total catatan yang dianalisis yaitu 27.019 catatan bobot badan yang terdiri atas 6.559 catatan B0, 5.702 catatan B30, 5.248 catatan B60, 4.843 catatan B90 hari, dan 4.667 catatan B100 Tahun 2012-2019. Analisis data menggunakan Restricted Maximum Likelihood (REML) untuk menduga heritabilitas dengan software Variance Components Estimation (VCE) 6.0, menggunakan model maternal genetic effect (m2) dan lingkungan bersama (c2). Efek tetap yang dimasukkan ke dalam analisis yaitu jenis kelamin dan tipe kelahiran. Hasil penelitian menunjukkan bahwa nilai heritabilitas B0, B30, B60, B90, dan B100 menggunakan model maternal genetic effect dan lingkungan bersama yaitu sebesar 0,133±0,04, 0,108±0,03, 0,099±0,03, 0,122±0,03, 0,123±0,03, artinya nilai-nilai heritabilitas tersebut masuk dalam kategori rendah. Nilai maternal genetic effect dan lingkungan bersama B0, B30, B60, B90, dan B100 Domba garut 0,095±0,03, 0,163±0,03, 0,137±0,03, 0,113± 0,02, 0,115±0,02 dan 0,455±0,16, 0,268±0,13, 0,274±0,13 0,269±0,13 0,278±0,12. Hal ini menunjukkan bahwa pendugaan parameter genetik lebih akurat jika melibatkan maternal genetic effect dan lingkungan bersama.