Transcriptomic analysis of ovarian follicles uncovers the crucial genes relevant to follicle selection and preovulatory hierarchy in hens.

Follicle selection and preovulatory hierarchy of hen ovaries were important stages of follicle development and crucially determining egg-laying performance. The selected follicles with a higher expression level of follicle-stimulating hormone receptor (FSHR) mRNA that facilitates response to FSH, and rapidly develops into preovulatory follicles with distinctive characteristics of granulosa cells (GCs) proliferation and differentiation. Identification of the key genes involved in these developmental events is helpful for elucidation of the molecular mechanism underlying egg-laying traits in chicken and other domestic fowl. Herein, the comparative transcriptomic analysis of ovarian prehierarchical follicles before selection (BSF), follicles at selection stage (ASF), and hierarchical follicles (HF) were implemented in the Jilin Black chicken (JB) and Lohmann Brown layer (LB) with the divergences in their egg-laying performance by RNA-sequencing. The results showed that nine deferentially expressed genes (DEGs), including STMN4, FABP3, ROBO2, RSPO4, and DMRT1 were revealed between follicles BSF and ASF; and seventeen DEGs, such as SLC6A15, SLITRK3, PRKG2 and TMC3 were mined between ASF and HF. These two group DEGs being co-expressed between BSF and ASF, and between ASF and HF were compared and substantiated in the JB and LB layers, respectively. Furthermore, 10 signaling pathways, such as cAMP signaling, PPAR signaling pathway, AMPK(Adenosine 5'-monophosphate (AMP)-activated protein kinase) pathway, and estrogen signaling pathway were also identified. Moreover, the roles of two representative candidates ROBO2 and PRKG2 genes presented as downregulated mRNA expression pattern in the transcriptomic profiles were further verified in vitro. The results demonstrated that downregulation of ROBO2 or PRKG2 significantly increased the expression levels of FSHR mRNA and protein with the boosted expression of CCND1, STAR, and BCL-2, whereas remarkably inhibited the expression of Caspase-3, consequently, brought about the decrease of GC apoptosis in the ovarian follicles, but increase of GC proliferation and differentiation serving as the hallmarks for follicle selection. It indicated that ROBO2 and PRKG2 may play indispensable roles in follicle selection and preovulatory hierarchy of hen ovaries separately. Our findings provided a comparative transcriptomic evidence for clarifying the molecular mechanism of the follicle development underlying egg-laying traits in chicken.

Chicken ovarian follicle development undergoes follicle recruitment, prehierarchy, follicle selection, preovulatory/hierarchy, and finally ovulation. The follicle selection and preovulatory hierarchy play a vital role in egg production of hens. However, underlying the mechanism of the key genes involved in these developmental events remains largely unknown. Herein, to explore the promising genes potentially involved in follicle selection and hierarchical development of hen ovary, a comparative transcriptome analysis of the ovarian follicles before and after selection was performed by using Jilin Black (JB) chicken, an indigenous Chinese breed with a low egg-laying rate and strong broodiness, and which was substantiated by using Lohmann Brown (LB) layer, a commercial egg-laying breed, being characterized by a high rate of egg production. As a result, a total of nine critical differentially expressed genes (DEGs) that co-expressed in the ovarian follicles before selection compared with follicles at selection stage (ASF), and 17 DEGs in the ASF follicles compared with hierarchical follicles that developed shortly after the time of follicle selection were identified in the JB hens as well as in the LB layers, respectively. Moreover, the exact roles of two representative candidates ROBO2 and PRKG2 of the DEGs were further verified in regulation of the follicular granulosa cell proliferation and differentiation which are the major characteristics of follicle selection. And 10 signaling pathways that implicated in follicle selection and hierarchy were also enriched. The objectives aim to provide molecular evidence for underlying the regulatory mechanism of follicle development and egg production in chicken.

Numerical investigation of the influence of banded sand ditches on water infiltration in fine-textured soil.

Enhancing rainwater infiltration is important to reduce the risk of urban waterlogging and improve the utilization rate of urban rainwater resources. Using the HYDRUS model, a mathematical model of soil water movement under a banded sand ditch pattern (the vertical excavation of a deep trench with heavy soil and filled with light soil) was created. Forty-six scenarios were designed to examine effects of sand ditch soil saturated hydraulic conductivity (Kss), original homogenous fine-textured soil saturated hydraulic conductivity (Kso), sand ditch width (W), spacing (S), and depth (D) on the soil infiltration rate (i). Results indicate that banded sand ditches cause increased permeation and have a significant turning point 't0' in the curve of 'i' for 't.' Taking 't0' as the boundary, 'i' can be divided into two stages (t ≤ t0 and t > t0), 'i' and 't,' for each stage according to the power function relationship; there is little change in power function indices, which can be fixed at 0.34 and 0.63, respectively. In addition, the coefficient has a linear relationship with Kss, Kso, W, S, and D. Thus, an estimation model of the soil infiltration rate under a banded sand ditch pattern was proposed and verified for reliability.

[Geochemical Characteristics and Genesis Analyses of High-arsenic Groundwater in the Pearl River Delta].

To determine the main factors affecting the migration, enrichment, and sources of arsenic in the shallow groundwater of the Pearl River Delta (PRD), clustering analysis was used to partition the study area and then analyze the abnormal distribution of arsenic and groundwater storage environment in each part area based on the data obtained from the investigation of groundwater pollution in the PRD region. The results showed, in the study area, arsenic was mainly represented by As(Ⅲ), and its concentration ranged from under the detection limit to 560 µg·L-1. High-arsenic groundwater was mainly distributed in the plain area covered by Quaternary loose sediment, with the Shunde District in Foshan City having the highest, followed by Zhongshan City and central Guangzhou. The hydrochemical type of groundwater in the study area was mainly HCO3-Ca type water. The high-arsenic groundwater had the characteristics of high pH value; high concentrations of NH4+, Fe, and Mn; and a high permanganate index, in addition to a low concentration of NO3-. Based on scatter plot and factor analysis of various indicators of arsenic in groundwater and the impact of human activities on the groundwater environment of the PRD, it was concluded in this study that under the common influence of natural sedimentary environment and pollution input, a neutral or weak-alkaline-reducing environment, which was conducive to the occurrence of high-arsenic groundwater, was formed in the plain area. The role of microorganisms and the input of organic pollutants in the shallow groundwater led to the reduction and dissolution of arsenic-containing Fe-Mn oxide, resulting in the release of arsenic. The source of arsenic contamination in the groundwater was mainly the industrial pollution in Shunde and other areas in southern Foshan City.

[Comparison of Identification Methods of Main Component Hydrochemical Anomalies in Groundwater: A Case Study of Liujiang Basin].

Identification of chemical composition anomalies in groundwater is an important basis for establishing groundwater background values and quantifying the degree of influence of human activities. The main component anomaly identification by five kinds of hydrochemical diagrams has achieved good results in the past. However, this method is too complex to be used widely. In order to simplify the five kinds of hydrochemical diagrams, the Durov diagram was used to replace the five kinds of hydrochemical diagrams to identify the main component anomalies of groundwater, with the Liujiang basin employed as a verification example. The effects of seven kinds of anomaly identification methods combined by hydrochemical diagrams and mathematical statistics methods were compared, and the reliability of these methods were tested in the study. The result indicated that the combination of mathematical statistics and hydrochemical diagrams method can identify the groundwater anomalies better than either used alone. The method of the Pauta criterion+five kinds of hydrography diagrams and the Pauta criterion+the Durov diagram were the best to identify the major component anomalies of groundwater. This shows that the Durov diagram can effectively replace the five kinds of hydrochemical diagrams for anomaly recognition of groundwater, which not only preserves the scientificity of hydrochemical anomaly identification, but also greatly simplifies the process of calculation.