Substantial evidence demonstrates that the genetic background of milk production traits changes during lactation. However, most GWAS for milk production traits assume that genetic effects are constant during lactation and therefore might miss those quantitative trait loci (QTL) whose effects change during lactation. The GWAS for genotype by lactation stage interaction are aimed at explicitly detecting the QTL whose effects change during lactation. The purpose of this study was to perform GWAS for genotype by lactation stage interaction for milk yield, lactose yield, lactose content, fat yield, fat content, protein yield, and somatic cell score to detect QTL with changing effects during lactation. For this study, 19,286 test-day records of 1,800 first-parity Dutch Holstein cows were available and cows were genotyped using a 50K SNP panel. A total of 7 genomic regions with effects that change during lactation were detected in the GWAS for genotype by lactation stage interaction. Two regions on Bos taurus autosome (BTA)14 and BTA19 were also significant based on a GWAS that assumed constant genetic effects during lactation. Five regions on BTA4, BTA10, BTA11, BTA16, and BTA23 were only significant in the GWAS for genotype by lactation stage interaction. The biological mechanisms that cause these changes in genetic effects are still unknown, but negative energy balance and effects of pregnancy may play a role. These findings increase our understanding of the genetic background of lactation and may contribute to the development of better management indicators based on milk composition.

Genetic effects on milk production traits in dairy cattle might change during lactation. However, most genome-wide association studies (GWAS) for milk production traits assume that genetic effects are constant during lactation. This assumption might lead to missing these quantitative trait loci (QTL) whose effects change during lactation. This study aimed to screen the whole genome specifically for QTL whose effects change during lactation. For this purpose, 4 different GWAS approaches were performed using testday milk protein content records: (1) separate GWAS for specific lactation stages, (2) GWAS for estimated Wilmink lactation curve parameters, (3) a GWAS using a repeatability model where SNP effects are assumed constant during lactation, and (4) a GWAS for genotype by lactation stage interaction using a repeatability model and accounting for changing genetic effects during lactation. Separate GWAS for specific lactation stages suggested that the detection power greatly differs between lactation stages and that genetic effects of some QTL change during lactation. The GWAS for estimated Wilmink lactation curve parameters detected many chromosomal regions for Wilmink parameter a (protein content level), whereas 2 regions for Wilmink parameter b (decrease in protein content toward nadir) and no regions for Wilmink parameter c (increase in protein content after nadir) were detected. Twenty chromosomal regions were detected with effects on milk protein content; however, there was no evidence that their effects changed during lactation. For 5 chromosomal regions located on chromosomes 3, 9, 10, 14, and 27, significant evidence was observed for a genotype by lactation stage interaction and thus their effects on milk protein content changed during lactation. Three of these 5 regions were only identified using a GWAS for genotype by lactation stage interaction. Our study demonstrated that GWAS for genotype by lactation stage interaction offers new possibilities to identify QTL involved in milk protein content. The performed approaches can be applied to other milk production traits. Identification of QTL whose genetic effects change during lactation will help elucidate the genetic and biological background of milk production.

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Flubendiamide, which belongs to the new chemical class of phthalic acid diamides, is widely used against lepidopteron pests in a variety of vegetable and rice pests. It provides superior plant protection against a broad range of economically important lepidopterous pests, including Spodoptera exigua and Plutella xylostella. A determination method of flubendiamide in the cabbage was established in this paper. Flubendiamide in the cabbage was extracted with acetonitrile and ultrasonic extraction, and was purified by QuEChERS and analyzed by LC-MS/MS (liquid chromatography-tandem mass spectrometry). The results indicated that the average recovery of flubendiamide in the cabbage was 81.27%-91.45%, the coefficient of variation was 1.79%-4.81%, and the lowest detection concentration was 0.3 μg/kg. The extraction of flubendiamide from the cabbage and its analysis was in accordance with the pesticide residue criterion, i.e., simple, rapid, accurate, reproducible, stable, separatory, and convenient. It identifies and quantifies trace-level flubendiamide residues in the cabbage extracts using LC-MS/MS in the ESI negative mode coupled with the QuEChERS method.

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Figure 1.2. Genetic correlations of milk yield at different lactation stages and fat content at different lactation stages. Data are adapted from Druet et al. (2005). Genetic correlations of milk yield and fat content during lactation is shown in Figure 1.2. It shows that genetic correlations between test-day milk yield measured between day 20 till day 150 in lactation are higher than 0.8. Genetic correlations between fat content measured from day 20 till day 230 in lactation are higher than 0.8. The genetic correlations decrease when the time interval between lactation stages increases, e.g., the correlation between milk yield at day 20 and day 320 is smaller than 0.2. Similar results were found in other studies (

Sucrose phosphate synthase (SPS) is a key enzyme catalyzing sucrose metabolism in plants. In this study, we isolated the SPS cDNA from Saccharum spontaneum and designated as SsSPS (GenBank accession no. MF398541). The full-length of SsSPS cDNA was 4153-bp with an opening reading frame (ORF) of 3132 nucleotides, which encoded a 1043-amino acid protein. The nucleotide sequences alignment showed that it had 98%, 97% and 87% homology with S. officinarum, Setaria italica and Lolium perenne, respectively. Moreover, the SsSPS was detected to express in leaf and stem tissues of S. spontaneum and exhibited a predominant expression in the stem tissue. However, there was no significant difference in the expression level of SsSPS between young leaves and mature ones. Additionally, we generated transgenic S. spontaneum using Agrobacterium-mediated transformation. Our data will provide a valuable foundation for further study of the potential role of SPS in plants.