Genetic Gain and Inbreeding in Different Simulated Genomic Selection Schemes for Grain Yield and Oil Content in Safflower.

Safflower ( L.) is a multipurpose minor crop consumed by developed and developing nations around the world with limited research funding and genetic resources. Genomic selection (GS) is an effective modern breeding tool that can help to fast-track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development.

Genetic parameters and evaluation of mortality and slaughter rate in Holstein and Jersey cows.

The longevity of dairy cattle has economic, animal welfare, and health implications and is influenced by the frequency of mortality on the farm and sale for slaughter. In this study cows removed from the herd due to death or slaughter during the lactation were coded 1 and cows that were not terminated were coded 0. Genetic parameters for mortality rates (MR) and slaughter rates (SR) were estimated for Holstein (H) and Jersey (J) breeds by applying both linear (LM) and threshold (TM) sire models using about 1.

Genomic prediction and selection response for grain yield in safflower.

In plant breeding programs, multiple traits are recorded in each trial, and the traits are often correlated. Correlated traits can be incorporated into genomic selection models, especially for traits with low heritability, to improve prediction accuracy. In this study, we investigated the genetic correlation between important agronomic traits in safflower.

Meta-analysis of genetic parameters for growth traits in meat, wool and dual-purpose sheep breeds in the world using a random-effects model.

Background: There is large variation in genetic parameters in literature for growth traits in sheep. Reliable estimation of genetic parameters is required for developing breeding programmes.

Objectives: The aim of this study was to aggregate results of different studies by meta-analysis to improve reliability of estimated parameters.

Erratum to "Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle" (JDS Commun. 3:114-119).

[This corrects the article DOI: 10.3168/jdsc.2021-0150.

Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle.

Although selection for increased milk production traits has led to a genetic increase in body weight (BW), the genetic gain in milk production has exceeded the gain in BW, so gross feed efficiency has improved. Nonetheless, greater gains may be possible by directly selecting for a measure of feed efficiency. Australia first introduced Feed Saved (FS) estimated breeding value (EBV) in 2015.

Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency.

Background: Sharing individual phenotype and genotype data between countries is complex and fraught with potential errors, while sharing summary statistics of genome-wide association studies (GWAS) is relatively straightforward, and thus would be especially useful for traits that are expensive or difficult-to-measure, such as feed efficiency. Here we examined: (1) the sharing of individual cow data from international partners; and (2) the use of sequence variants selected from GWAS of international cow data to evaluate the accuracy of genomic estimated breeding values (GEBV) for residual feed intake (RFI) in Australian cows.

Results: GEBV for RFI were estimated using genomic best linear unbiased prediction (GBLUP) with 50k or high-density single nucleotide polymorphisms (SNPs), from a training population of 3797 individuals in univariate to trivariate analyses where the three traits were RFI phenotypes calculated using 584 Australian lactating cows (AUSc), 824 growing heifers (AUSh), and 2526 international lactating cows (OVE).

Combining NDVI and Bacterial Blight Score to Predict Grain Yield in Field Pea.

Field pea is the most commonly grown temperate pulse crop, with close to 15 million tons produced globally in 2020. Varieties improved through breeding are important to ensure ongoing improvements in yield and disease resistance. Genomic selection (GS) is a modern breeding approach that could substantially improve the rate of genetic gain for grain yield, and its deployment depends on the prediction accuracy (PA) that can be achieved.

Machine learning approaches for the prediction of lameness in dairy cows.

Lameness is one of the costliest health problems, as well as a welfare concern in dairy cows. However, it is difficult to detect cows with possible lameness, or the ones that are at risk of becoming lame e.g.

Identification of sequence variation in the oocyte-derived bone morphogenetic protein 15 (BMP15) gene (BMP15) associated with litter size in New Zealand sheep (Ovis aries) breeds.

Advances in the study of reproductive traits indicate that functional variation in fertility genes may be useful for improving sheep fertility. The aim of this study was to search for variation in the bone morphogenetic protein 15 gene (BMP15) and ascertain any association with litter size in purebred Finnish Landrace sheep (n = 148), Finnish Landrace × Texel-cross sheep (n = 45), and composite sheep (of varying breed background; n = 58) from New Zealand (NZ). A 482 bp and 312 bp fragment of exon 1 and 2, respectively, of BMP15 were analysed using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP).

Including milk production, conformation, and functional traits in multivariate models for genetic evaluation of lameness.

Lameness is a serious health and welfare issue that can negatively affect the economic performance of cows, especially on pasture-based dairy farms. However, most genetic predictions (GP) of lameness have low accuracy because lameness data are often incomplete as data are collected voluntarily by farmers in countries such as Australia. The objective of this study was to find routinely measured traits that are correlated with lameness and use them in multivariate evaluation models to improve the accuracy of GP for lameness.

A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits.

Background: Imputation to whole-genome sequence is now possible in large sheep populations. It is therefore of interest to use this data in genome-wide association studies (GWAS) to investigate putative causal variants and genes that underpin economically important traits. Merino wool is globally sought after for luxury fabrics, but some key wool quality attributes are unfavourably correlated with the characteristic skin wrinkle of Merinos.

Improving Genomic Prediction of Crossbred and Purebred Dairy Cattle.

This study assessed the accuracy and bias of genomic prediction (GP) in purebred Holstein (H) and Jersey (J) as well as crossbred (H and J) validation cows using different reference sets and prediction strategies. The reference sets were made up of different combinations of 36,695 H and J purebreds and crossbreds. Additionally, the effect of using different sets of marker genotypes on GP was studied (conventional panel: 50k, custom panel enriched with, or close to, causal mutations: XT_50k, and conventional high-density with a limited custom set: pruned HDnGBS).

Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data.

Background: Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle.

Results: Based on the significant-association threshold (p < 5 × 10), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17).

Mitochondrial protein gene expression and the oxidative phosphorylation pathway associated with feed efficiency and energy balance in dairy cattle.

Feed efficiency and energy balance are important traits underpinning profitability and environmental sustainability in animal production. They are complex traits, and our understanding of their underlying biology is currently limited. One measure of feed efficiency is residual feed intake (RFI), which is the difference between actual and predicted intake.

Identification of polymorphisms in the oocyte-derived growth differentiation growth factor 9 (GDF9) gene associated with litter size in New Zealand sheep (Ovis aries) breeds.

Having the ability to control litter size is important for sheep farmers and breeders worldwide. However, making genetic gain in key livestock traits like reproductive performance needs typically a lot of time, and both the fecundity and fertility traits have a great economic importance. Attention has therefore turned to better understanding the genes that control reproductive performance.

Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations.

Background: Whole-genome sequence (WGS) data could contain information on genetic variants at or in high linkage disequilibrium with causative mutations that underlie the genetic variation of polygenic traits. Thus far, genomic prediction accuracy has shown limited increase when using such information in dairy cattle studies, in which one or few breeds with limited diversity predominate. The objective of our study was to evaluate the accuracy of genomic prediction in a multi-breed Australian sheep population of relatively less related target individuals, when using information on imputed WGS genotypes.

Accuracy of imputation to whole-genome sequence in sheep.

Background: The use of whole-genome sequence (WGS) data for genomic prediction and association studies is highly desirable because the causal mutations should be present in the data. The sequencing of 935 sheep from a range of breeds provides the opportunity to impute sheep genotyped with single nucleotide polymorphism (SNP) arrays to WGS. This study evaluated the accuracy of imputation from SNP genotypes to WGS using this reference population of 935 sequenced sheep.