Pre-weaning dairy calf and replacement heifer mortality represents significant economic loss, limits genetic improvement and growth of the herd, and indicates poor management and animal welfare status on the farm.
Currently, the rates and causes of the dairy calf and replacement heifer mortality in Jordan are not known. Therefore, the objective of this study was to determine the incidence rates and causes of mortality of pre-weaning calves and replacement heifers in Jordan. In addition, the age and seasonal distribution of mortality are determined in the study.
Data extracted from the farm management record software over 3 years (January 2016-December 2018) were used in this study. Calf-specific data included the day and month of birth and sex. Health-related data included age at death, necropsy findings, laboratory findings if available, and the presumptive diagnosis. Descriptive analysis was performed to determine the 3-year overall mortality rate as well as the yearly mortality rate in pre-weaning calves and replacement heifers using excel spreadsheets of Microsoft Word 10.
Only female calves (n = 724) born alive during the study period were used in the analysis. The overall calf mortality rate was 8.9% with a yearly rate ranging between 5.9% and 12%. The majority of deaths occurred in calves less than 50 days of age with an average age of 17 days. There was a seasonal pattern for calf mortality with the majority of deaths occurring during the colder months of the year (December, January, February, and March). The highest number of pre-weaning calves died because of enterotoxemia (39%) and pneumonia (30%). Other causes of calf mortality were abomasal ulcer (8%), enteritis (6%), septicemic salmonellosis (5%), meningitis (4%), rumen drinkers (3%), aspiration pneumonia (3%), septic arthritis (1%), and omphalitis (1%). The overall 3-year heifer mortality rate was 4%. The average age of dead heifers was 8 months (range 3-23 months). The highest number of heifers died because of neurologic disease (37%) and enterotoxemia (33%). Other causes of heifer mortality were abomasal ulcer (11%), enteric salmonellosis (7%), chronic rumen tympany (7%), and chronic pneumonia (4%).
Data presented in this study are essential to construct and implement effective preventative health programs and improve farm management practices to reduce calf and heifer losses.

Bread wheat (Triticum aestivum L.) is a major crop that feeds 40% of the world\'s population. Over the past several decades, advances in genomics have led to tremendous achievements in understanding the origin and domestication of wheat, and the genetic basis of agronomically important traits, which promote the breeding of elite varieties. In this review, we focus on progress that has been made in genomic research and genetic improvement of traits such as grain yield, end-use traits, flowering regulation, nutrient use efficiency, and biotic and abiotic stress responses, and various breeding strategies that contributed mainly by Chinese scientists. Functional genomic research in wheat is entering a new era with the availability of multiple reference wheat genome assemblies and the development of cutting-edge technologies such as precise genome editing tools, high-throughput phenotyping platforms, sequencing-based cloning strategies, high-efficiency genetic transformation systems, and speed-breeding facilities. These insights will further extend our understanding of the molecular mechanisms and regulatory networks underlying agronomic traits and facilitate the breeding process, ultimately contributing to more sustainable agriculture in China and throughout the world.

Current organic pig-breeding programs use pigs from conventional breeding populations. However, there are considerable differences between conventional and organic production systems. This simulation study aims to evaluate how the organic pig sector could benefit from having an independent breeding program. Two organic pig-breeding programs were simulated: one used sires from a conventional breeding population (conventional sires), and the other used sires from an organic breeding population (organic sires). For maintaining the breeding population, the conventional population used a conventional breeding goal, whereas the organic population used an organic breeding goal. Four breeding goals were simulated: one conventional breeding goal, and three organic breeding goals. When conventional sires were used, genetic gain in the organic population followed the conventional breeding goal, even when an organic breeding goal was used to select conventional sires. When organic sires were used, genetic gain followed the organic breeding goal. From an economic point of view, using conventional sires for breeding organic pigs is best, but only if there are no genotype-by-environment interactions. However, these results show that from a biological standpoint, using conventional sires biologically adapts organic pigs for a conventional production system.

The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Large yellow croaker (Larimichthys crocea) is one of the most important cultured marine fish on the southeast coast of China. Its body shape is important for the aquaculture industry since it affects the behavior such as swimming, ingesting, and evading, as well as customer preference. Due to the greater consumer demand of small head, slender body large yellow croaker, selecting and breeding of slender individuals with the assistance of genetic markers will benefit the industry quickly. In this study, several traits were employed to represent body shape, including body depth/body length (BD/BL), body thickness/body length (BT/BL), caudal peduncle depth/caudal peduncle length (CPDLR), tail length/body length (TL/BL), and body area/head area (BA/HA). Genome-wide association study was conducted with a panmictic population of 280 individuals to identify SNP and genes potentially associated with body shape. A set of 20 SNPs on 12 chromosomes were identified to be significantly associated with body shape-related traits. Besides, 5 SNPs were identified to be suggestive associated with CPDLR and BT/BL. Surrounding these SNPs, we found some body shape-related candidate genes, including fabp1, acrv1, bcor, mstn, bambi, and neo1, which involved in lipid metabolism, TGF-β signaling, and BMP pathway and other important regulatory pathways. These results will be useful for the understanding of the genetic basis of body shape formation and helpful for body shape controlling of large yellow croaker by using marker-assisted selection.

BACKGROUND: As a photoperiod-sensitive and self-pollinated species, the growth periods traits play important roles in the adaptability and yield of soybean. To examine the genetic architecture of soybean growth periods, we performed a genome-wide association study (GWAS) using a panel of 278 soybean accessions and 34,710 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) higher than 0.04 detected by the specific-locus amplified fragment sequencing (SLAF-seq) with a 6.14-fold average sequencing depth. GWAS was conducted by a compressed mixed linear model (CMLM) involving in both relative kinship and population structure.
RESULTS: GWAS revealed that 37 significant SNP peaks associated with soybean flowering time or other growth periods related traits including full bloom, beginning pod, full pod, beginning seed, and full seed in two or more environments at -log10(P) > 3.75 or -log10(P) > 4.44 were distributed on 14 chromosomes, including chromosome 1, 2, 3, 5, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19. Fourteen SNPs were novel loci and 23 SNPs were located within known QTLs or 75 kb near the known SNPs. Five candidate genes (Glyma.05G101800, Glyma.11G140100, Glyma.11G142900, Glyma.19G099700, Glyma.19G100900) in a 90 kb genomic region of each side of four significant SNPs (Gm5_27111367, Gm11_10629613, Gm11_10950924, Gm19_34768458) based on the average LD decay were homologs of Arabidopsis flowering time genes of AT5G48385.1, AT3G46510.1, AT5G59780.3, AT1G28050.1, and AT3G26790.1. These genes encoding FRI (FRIGIDA), PUB13 (plant U-box 13), MYB59, CONSTANS, and FUS3 proteins respectively might play important roles in controlling soybean growth periods.
CONCLUSIONS: This study identified putative SNP markers associated with soybean growth period traits, which could be used for the marker-assisted selection of soybean growth period traits. Furthermore, the possible candidate genes involved in the control of soybean flowering time were predicted.

We performed a genome-wide association study to identify candidate genes for body measurement traits in 463 Wagyu beef cattle typed with the Illumina Bovine HD 770K SNP array. At the genome-wide level, we detected 18, five and one SNPs associated with hip height, body height and body length respectively. In total, these SNPs are within or near 11 genes, six of which (PENK, XKR4, IMPAD1, PLAG1, CCND2 and SNTG1) have been reported previously and five of which (CSMD3, LAP3, SYN3, FAM19A5 and TIMP3) are novel candidate genes that we found to be associated with body measurement traits. Further exploration of these candidate genes will facilitate genetic improvement in Chinese Wagyu beef cattle.

The search landscape is a common metaphor to describe the structure of computational search spaces. Different landscape metrics can be computed and used to predict search difficulty. Yet, the metaphor falls short in visualisation terms because it is hard to represent complex landscapes, both in terms of size and dimensionality. This paper combines local optima networks, as a compact representation of the global structure of a search space, and dimensionality reduction, using the t-distributed stochastic neighbour embedding algorithm, in order to both bring the metaphor to life and convey new insight into the search process. As a case study, two benchmark programs, under a genetic improvement bug-fixing scenario, are analysed and visualised using the proposed method. Local optima networks for both iterated local search and a hybrid genetic algorithm, across different neighbourhoods, are compared, highlighting the differences in how the landscape is explored.

Interest in genetic improvement of carcass and tenderness traits of beef cattle using genome-based selection (GS) and marker-assisted management programs is increasing. The success of such a program depends on the presence of linkage disequilibrium between the observed markers and the underlying QTL as well as on the relationship between the discovery, validation, and target populations. For molecular breeding values (MBV) predicted for a target population using SNP markers, reliabilities of these MBV can be obtained from validation analyses conducted in an independent population distinct from the discovery set. The objective of this study was to test MBV predicted for carcass and tenderness traits of beef cattle in a Canadian-based validation population that is largely independent of a United States-based discovery set. The discovery data set comprised of genotypes and phenotypes from >2,900 multibreed beef cattle while the validation population consisted of 802 crossbred feeder heifers and steers. A bivariate animal model that fitted actual phenotype and MBV was used for validation analyses. The reliability of MBV was defined as square of the genetic correlation (R(2) g) that represents the proportion of the additive genetic variance explained by the SNP markers. Several scenarios involving different starting marker panels (384, 3K, 7K, and 50K) and different sets of SNP selected to compute MBV (50, 100, 200, 375, 400, 600, and 800) were investigated. Validation results showed that the most reliable MBV (R(2) g) were 0.34 for HCW, 0.36 for back fat thickness, 0.28 for rib eye area, 0.30 for marbling score, 0.25 for yield grade, and 0.38 for Warner-Bratzler shear force across the different scenarios explored. The results indicate that smaller SNP panels can be developed for use in genetic improvement of beef carcass and tenderness traits to exploit GS benefits.