Association mapping is a powerful approach for exploring the molecular genetic basis of complex quantitative traits. An alfalfa (Medicago sativa) association panel comprised of 336 genotypes from 75 alfalfa accessions represented by four to eight genotypes for each accession. Each genotype was genotyped using 85 simple sequence repeat (SSR) markers and phenotyped for five fiber-related traits in four different environments. A model-based structure analysis was used to group all genotypes into two groups. Most of the genotypes have a low relative kinship (<0.3), suggesting population stratification not be an issue for association analysis. Generally, the Q + K model exhibited the best performance to eliminate the false associated positives. In total, 124 marker-trait associations were predicted (p < 0.005). Among these, eight associations were predicted in two environments repeatedly and 20 markers were predicted to be associated with multiple traits. These trait-associated markers will greatly help marker-assisted breeding programs to improve fiber-related quality traits in alfalfa.
Due to a boom in the dairy industry in Northeast China, the hay industry has been developing rapidly. Thus, it is very important to evaluate the hay quality with a rapid and accurate method. In this research, a novel technique that combines near infrared spectroscopy (NIRs) with three different statistical analyses (MLR, PCR and PLS) was used to predict the chemical quality of sheepgrass (Leymus chinensis) in Heilongjiang Province, China including the concentrations of crude protein (CP), acid detergent fiber (ADF), and neutral detergent fiber (NDF). Firstly, the linear partial least squares regression (PLS) was performed on the spectra and the predictions were compared to those with laboratory-based recorded spectra. Then, the MLR evaluation method for CP has a potential to be used for industry requirements, as it needs less sophisticated and cheaper instrumentation using only a few wavelengths. Results show that in terms of CP, ADF and NDF, (i) the prediction accuracy in terms of CP, ADF and NDF using PLS was obviously improved compared to the PCR algorithm, and comparable or even better than results generated using the MLR algorithm; (ii) the predictions were worse compared to laboratory-based spectra with the MLR algorithmin, and poor predictions were obtained (R2, 0.62, RPD, 0.9) using MLR in terms of NDF; (iii) a satisfactory accuracy with R2 and RPD by PLS method of 0.91, 3.2 for CP, 0.89, 3.1 for ADF and 0.88, 3.0 for NDF, respectively, was obtained. Our results highlight the use of the combined NIRs-PLS method could be applied as a valuable technique to rapidly and accurately evaluate the quality of sheepgrass hay.
Background
Crohn's disease (CD) is a chronic non-specific inflammatory bowel disease. Current CD therapeutics cannot fundamentally change the natural course of CD. Therefore, it is of great significance to find new treatment strategies for CD. Preclinical and clinical studies have shown that mesenchymal stromal cells (MSCs) are a promising therapeutic approach. However, the mechanism by which MSCs alleviate CD and how MSCs affect gut microbes are still unclear and need further elucidation.
Methods
We used 2,4,6-trinitrobenzenesulfonic acid (TNBS) to induce experimental colitis in mice and analysed the microbiota in faecal samples from the control group, the TNBS group and the TNBS + MSC group with faecal 16S rDNA sequencing. Subsequent analyses of alpha and beta diversity were all performed based on the rarified data. PICRUStII analysis was performed on the 16S rRNA gene sequences to infer the gut microbiome functions.
Results
MSC Treatment improved TNBS-induced colitis by increasing survival rates and relieving symptoms. A distinct bacterial signature was found in the TNBS group that differed from the TNBS + MSC group and controls. MSCs prevented gut microbiota dysbiosis, including increasing α-diversity and the amount of Bacteroidetes Firmicutes and Tenericutes at the phylum level and decreasing the amount of Proteobacteria at the phylum level. MSCs alleviated the increased activities of sulphur and riboflavin metabolism. Meanwhile some metabolic pathways such as biosynthesis of amino acids lysine biosynthesis sphingolipid metabolism and secondary bile acid biosynthesis were decreased in the TNBS group compared with the control group and the TNBS + MSC group
Conclusions
Overall, our findings preliminarily confirmed that colitis in mice is closely related to microbial and metabolic dysbiosis. MSC treatment could modulate the dysregulated metabolism pathways in mice with colitis, restoring the abnormal microbiota function to that of the normal control group. This study provides insight into specific intestinal microbiota and metabolism pathways linked with MSC treatment, suggesting a new approach to the treatment of CD.
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