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The Fusarium species is an important plant pathogen that can cause plant diseases in grassland, leading to the degradation of grassland quality. However, the morphology of Fusarium is greatly affected by environmental factors, which makes it difficult to identify its species. In addition, the pathogenic ability of different Fusarium species in plants has not been fully studied. In this study, Fusarium isolates were obtained from grassland herbaceous plants via tissue separation. Through morphological means and based on ITS, RPB2, and TEF-1 gene sequences, we compared and constructed polygenic phylogenetic trees to classify and identify the Fusarium species. In addition, the pathogenicity of different Fusarium species was also analyzed. The results showed that a total of 24 Fusarium strains were successfully isolated from grassland, from which ten species were identified: F. flagelliforme, F. longifundum, F. clavum, F. scirpi, F. ipomoeae, F. oxysporum, etc. and were included in four complexes: Fusarium incarnatum-equiseti species complex (FIESC), Fusarium oxysporum species complex (FOSC), Fusarium tricinctum species complex (FTSC), and Fusarium sambucinum species complex (FSAMSC). Pathogenicity tests demonstrated that except for F. ipomoeae QJ5211, F. sambucinum QJ203, and F. acuminatum QJ1662, other Fusarium species had different degrees of pathogenic ability. This is the first study that discusses the effect of Fusarium on grassland disease control in this area. This study further provides clear pathogen information for the prevention and control of grassland diseases.

Polymorphism at the β-Lactoglobulin (β-LG) gene of three Nigerian goat breeds, namely: the West African Dwarf, Sahel and Red Sokoto goats, was investigated using the Polymerase Chain Reaction-Random Fragment Length Polymorphism (PCR-RFLP) method. The restriction endonucleases used in the study were Rsal and Mspl, respectively. The results revealed the existence of only one polymorphic variant (allele A) with a gene frequency of 1.0 in all the three goat breeds studied. The amplified products were observed at 120 bp and the restriction digestion with Rsal revealed just one genotype at the β-LG locus. It was concluded that there was the absence of polymorphism at the β-LG locus of the goats investigated.

The aim of this study was to investigate 96 single-nucleotide polymorphisms (SNPs) from 54 candidate genes, and test the associations of the polymorphic SNPs with milk yield, composition, milk urea nitrogen (MUN) content and somatic cell score (SCS) in individual milk samples from Italian Brown Swiss cows. Milk and blood samples were collected from 1271 cows sampled once from 85 herds. Milk production, quality traits (i.e. protein, casein, fat and lactose percentages), MUN and SCS were measured for each milk sample. Genotyping was performed using a custom Illumina VeraCode GoldenGate approach. A Bayesian linear animal model that considered the effects of herd, days in milk, parity, SNP genotype and additive polygenic effect was used for the association analysis. Our results showed that 14 of the 51 polymorphic SNPs had relevant additive effects on at least one of the aforementioned traits. Polymorphisms in the glucocorticoid receptor DNA-binding factor 1 (GRLF1), prolactin receptor (PRLR) and chemokine ligand 2 (CCL2) were associated with milk yield; an SNP in the stearoyl-CoA desaturase (SCD-1) was related to fat content; SNPs in the caspase recruitment domain 15 protein (CARD15) and lipin 1 (LPIN1) affected the protein and casein contents; SNPs in growth hormone 1 (GH1), lactotransferrin (LTF) and SCD-1 were relevant for casein number; variants in beta casein (CSN2), GH1, GRLF1 and LTF affected lactose content; SNPs in beta-2 adrenergic receptor (ADRB2), serpin peptidase inhibitor (PI) and SCD-1 were associated with MUN; and SNPs in acetyl-CoA carboxylase alpha (ACACA) and signal transducer and activator of transcription 5A (STAT5A) were relevant in explaining the variation of SCS. Although further research is needed to validate these SNPs in other populations and breeds, the association between these markers and milk yield, composition, MUN and SCS could be exploited in gene-assisted selection programs for genetic improvement purposes.