本研究以东北农业大学肉鸡高、低腹脂双向选择品系1-7周龄鸡只和永生化鸡前脂肪细胞（ICP2细胞）为材料，利用RT-qPCR和Western blot方法分析HBP1在脂肪组织和前脂肪细胞分化过程中的表达模式；以稳定过表达HBP1的ICP2细胞、敲除HBP1的ICP2细胞以及各自的对照细胞为材料，利用油红O染色、RT-qPCR和Western blot检测过表达/敲除HBP1对鸡前脂肪细胞分化的影响；利用信号通路分析试剂盒筛选HBP1调控鸡前脂肪细胞分化的潜在信号通路；在稳定过表达HBP1的ICP2细胞中添加信号转导和转录激活因子3（STAT3）的化学抑制剂或转染siRNA进行功能拯救实验。结果：基因表达分析结果表明，HBP1的表达与鸡腹部脂肪沉积和前脂肪细胞分化有关。过表达HBP1抑制鸡前脂肪细胞分化（P<0.05），敲除HBP1促进鸡前脂肪细胞分化（P<0.05）。进一步研究发现，HBP1靶向激活Janus激酶2（JAK2）基因的转录来激活STAT3信号通路。功能拯救实验结果表明，STAT3信号介导了HBP1对鸡前脂肪细胞分化的调控作用。以上结果表明，HBP1通过直接上调JAK2的表达来激活STAT3信号通路，从而抑制鸡前脂肪细胞的分化。本研究阐明了HBP1在鸡前脂肪细胞分化中的基本功能，并揭示了其部分分子机制。这些发现为进一步解析鸡脂肪组织生长发育的分子遗传基础提供了新的见解。

 

Field studies were conducted in 2012 and 2013 to evaluate weed and insect control efficacy with glyphosate at 1 230 g ai (active ingredient) ha–1 and the insecticides acephate (728 g ai ha–1), carbosulfan (135 g ai ha–1), endosulfan (683 g ai ha–1), imidacloprid (32 g ai ha–1), or lambda-cyhalothrin (23 g ai ha–1), as well as glyphosate tank-mixed with these insecticides. Four of the most common weeds in cotton, common purslane, false daisy, goosegrass, and lambsquarters, were manually sown in the cotton field and treated with glyphosate alone or in combination with insecticides. Glyphosate efficacy, based on visual estimates of control and weed fresh weight at 21 d after treatment (DAT), was unaffected by the addition of insecticides. Four weeds were controlled by 93–97% and 86–100% (visual rating) and reduced weed fresh biomass by 98–99% and 96–100% with glyphosate alone and its combination with insecticides, respectively. Addition of glyphosate to acephate improved cotton aphid control compared with acephate alone. However, addition of glyphosate to carbosulfan, endosulfan, imidacloprid, or lambda-cyhalothrin did not affect the aphid control when compared with the insecticide alone treatments. These results indicate that cotton producers could potentially integrate weed and insect management strategies by choosing suitable insecticide mixing partners with glyphosate, thereby reducing the application costs without sacrificing the efficacy of the glyphosate or the insecticides.

The cultivated soybean (Glycine max (L.) Merr.) was distinguished from its wild progenitor Glycine soja Sieb. & Zucc. in growth period structure, by a shorter vegetative phase (V), a prolonged reproductive phase (R) and hence a larger R/V ratio. However, the genetic basis of the domestication of soybean from wild materials is unclear. Here, a panel of 123 cultivated and 97 wild accessions were genotyped using a set of 24 presence/absence variants (PAVs) while at the same time the materials were phenotyped with respect to flowering and maturity times at two trial sites located at very different latitudes. The major result of this study showed that variation at PAVs is informative for assessing patterns of genetic diversity in Glycine spp. The genotyping was largely consistent with the taxonomic status, although a few accessions were intermediate between the two major clades identified. Allelic diversity was much higher in the wild germplasm than in the cultivated materials. A significant domestication signal was detected at 11 of the PAVs at 0.01 level. In particular, this study has provided information for revealing the genetic basis of photoperiodism which was a prominent feature for the domestication of soybean. A significant marker-trait association with R/V ratio was detected at 14 of the PAVs, but stripping out population structure reduced this to three. These results will provide markers information for further finding of R/V related genes that can help to understand the domestication process and introgress novel genes in wild soybean to broaden the genetic base of modern soybean cultivars.

    Information on the center of genetic diversity of soybean (Glycine max) will be helpful not only for designing efficient strategies for breeding programs, but also for understanding the domestication and origin of this species. Here, we describe an analysis of genetic diversity based on simple-sequence repeat (SSR) variations within a core collection of 2 111 accessions of Chinese soybean landraces. Prior to the diversity assessment, the geographic origin of each accession was mapped. The map was then divided into grids each 2.5° in latitude and 5° in longitude. We found two regions that had higher number of alleles (NA) and greater polymorphic information content (PIC) values than the others. These regions are adjacently located within grid position of 30°–35°N×105°–110°E, which includes the valley of the middle and lower reaches of the Wei River, and the valley of the upper reaches of the Hanjiang River. It was also observed that in many regions, genetic diversity decreased with the increase in distance from the center. Another region, in northern Hebei Province (115°–120°E×40°–42.5°N), was observed having higher diversity than any surrounding regions, indicating that this is a sub-center of soybean diversity. Based on the presented results, the domestication and origin of soybean are also discussed.

Secreted frizzled-related protein 2 (SFRP2), a member of the SFRPs family, is associated with cell growth and differentiation in myogenesis. Our previous study suggested that SFRP2 was a potential target of microRNA (miRNA)-1/206, which was considered as myomiRs. To further explore the biological function and regulation mechanisms of the SFRP2 gene in porcine skeletal muscle development, we first analyzed the sequence structure of the porcine SFRP2 gene. Subsequently, we detected its tissue distribution in adult Tongcheng pigs (a Chinese indigenous breed) and investigated its dynamic expression in developmental skeletal muscle (13 prenatal and 7 postnatal time points) in Tongcheng pigs. An interaction analysis between SFRP2 and myomiRs was also performed. The results showed that the expression pattern of the SFRP2 varied greatly across diverse tissues. It exhibited abundant expression in prenatal skeletal muscle and peaked at 55 days post coitus (E55), and had a lower expression in postnatal skeletal muscle, indicating that the SFRP2 gene might affect porcine embryonic skeletal muscle development. Co-expression analysis revealed that the expression levels of SFRP2 correlated negatively with miRNA-1 (r=–0.570, P-value=0.009) and miRNA-206 (r=–0.546, P-value=0.013), but positively with SFRP1 (r=0.613, P-value=0.004). The bioinformatics analysis and dual luciferase assay verified that the SFRP2 was a putative target of miRNA-1/206 in pigs. Therefore, this study is helpful for understanding the biological function and molecular regulation of the SFRP2 gene during porcine skeletal muscle development.

Goosegrass is one of the worst agricultural weeds on a worldwide basis. Understanding of its interference impact in crop field will provide useful information for weed control programs. Field experiments were conducted during 2010–2012 to determine the influence of goosegrass density on cotton growth at the weed densities of 0, 0.125, 0.25, 0.5, 1, 2, and 4 plants m–1 of row. Seed cotton yield tended to decrease with the increase in weed density, and goosegrass at a density of 4 plants m–1 of row significantly reduced cotton yields by 20 to 27%. A density of 11.6–19.2 goosegrass plant m–1 of row would result in a 50% cotton yield loss from the maximum yield according to the hyperbolic decay regression model. Boll production was not affected in the early growing season. But boll numbers per plant were reduced about 25% at the density of 4 plants m–1 of row in the late growing season. Both cotton boll weight and seed numbers per boll were significantly reduced (8%) at 4 goosegrass plants m–1 of row. Cotton plant height, stem diameter and sympodial branch number were not affected as much as cotton yields by goosegrass competition. Seed index, lint percentage and lint fiber properties were unaffected by weed competition. Intraspecific competition resulted in density-dependent effects on weed biomass per plant, 142–387 g dry weight by harvest. Goosegrass biomass m–2 tended to increase with increasing weed density as indicated by a quadratic response. The adverse impact of goosegrass on cotton yield identified in this study has indicated the need of effective goosegrass management.