Many different chicken breeds are found around the world,their features vary among them,and they are valuable resources.Currently,there is a huge lack of knowledge of the genetic determinants responsible for phenotypi...Many different chicken breeds are found around the world,their features vary among them,and they are valuable resources.Currently,there is a huge lack of knowledge of the genetic determinants responsible for phenotypic and biochemical properties of these breeds of chickens.Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved chicken breeds.The whole-genomes of 140 chickens from 7 Shandong native breeds and 20 introduced recessive white chickens from China were re-sequenced.Comparative population genomics based on autosomal single nucleotide polymorphisms(SNPs)revealed geographically based clusters among the chickens.Through genome-wide scans for selective sweeps,we identified thyroid stimulating hormone receptor(TSHR,reproductive traits,circadian rhythm),erythrocyte membrane protein band 4.1 like 1(EPB41L1,body size),and alkylglycerol monooxygenase(AGMO,aggressive behavior),as major candidate breed-specific determining genes in chickens.In addition,we used a machine learning classification model to predict chicken breeds based on the SNPs significantly associated with recourse characteristics,and the prediction accuracy was 92%,which can effectively achieve the breed identification of Laiwu Black chickens.We provide the first comprehensive genomic data of the Shandong indigenous chickens.Our analyses revealed phylogeographic patterns among the Shandong indigenous chickens and candidate genes that potentially contribute to breed-specific traits of the chickens.In addition,we developed a machine learning-based prediction model using SNP data to identify chicken breeds.The genetic basis of indigenous chicken breeds revealed in this study is useful to better understand the mechanisms underlying the resource characteristics of chicken.展开更多
A fast analytical method for the simultaneous determination of 9 mycotoxins, including alfatoxins （B1, B2, G1, and G2）, fumonisins （B1, B2 and B3）, zearalenone, and deoxynivalenol in corn using dispersive solid-ph...A fast analytical method for the simultaneous determination of 9 mycotoxins, including alfatoxins （B1, B2, G1, and G2）, fumonisins （B1, B2 and B3）, zearalenone, and deoxynivalenol in corn using dispersive solid-phase extraction method and ultra-performance liquid chromatography coupled to tandem quadrupole time-of-lfight mass spectrometry （UPLC-Q-TOF-MS） was developed and validated. Samples were extracted with acetonitrile-water （84：16, v：v, containing 1% acetic acid） using ultrasonic extraction. The extracts were puriifed with a dispersive SPE method using C18 as a cleaning agent. The ifnal clear extracts were dried by nitrogen blowing and subsequently redissolved in methanol-water （5：5, v：v）. The samples were then analyzed by UPLC-Q-TOF-MS with 0.1% formic acid in ammonium acetate-methanol as mobile phase. The mean recoveries were ranged from 68.0 to 120.0%, and the relative standard deviation （RSD） ranged from 0.18 to 6.29%. Limits of detections ranged from 0.05 to 50 μg kg？1, and limits of quantiifcation ranged from 0.1 to 200 μg kg？1, which were below the legal limits set by the European Union for the legislated mycotoxins. The developed method was applied to 130 corn samples. Among the mycotoxins studied, alfatoxins B1 and fumonisins B1, B2 and B3 were the most predominant mycotoxins, and their concentrations were 0–593.12, 0–2.01×104, 0–6.94×103 and 0–3.05×103 μg kg–1, respectively.展开更多
基金funded by the China Agriculture Research System of MOF and MARA(CARS-41)the Agricultural Breed Project of Shandong Province,China(2019LZGC019 and 2020LZGC013)+1 种基金the Shandong Provincial Natural Science Foundation,China(ZR2020MC169)the Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Sciences,China(CXGC2022C04 and CXGC2022E11).
文摘Many different chicken breeds are found around the world,their features vary among them,and they are valuable resources.Currently,there is a huge lack of knowledge of the genetic determinants responsible for phenotypic and biochemical properties of these breeds of chickens.Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved chicken breeds.The whole-genomes of 140 chickens from 7 Shandong native breeds and 20 introduced recessive white chickens from China were re-sequenced.Comparative population genomics based on autosomal single nucleotide polymorphisms(SNPs)revealed geographically based clusters among the chickens.Through genome-wide scans for selective sweeps,we identified thyroid stimulating hormone receptor(TSHR,reproductive traits,circadian rhythm),erythrocyte membrane protein band 4.1 like 1(EPB41L1,body size),and alkylglycerol monooxygenase(AGMO,aggressive behavior),as major candidate breed-specific determining genes in chickens.In addition,we used a machine learning classification model to predict chicken breeds based on the SNPs significantly associated with recourse characteristics,and the prediction accuracy was 92%,which can effectively achieve the breed identification of Laiwu Black chickens.We provide the first comprehensive genomic data of the Shandong indigenous chickens.Our analyses revealed phylogeographic patterns among the Shandong indigenous chickens and candidate genes that potentially contribute to breed-specific traits of the chickens.In addition,we developed a machine learning-based prediction model using SNP data to identify chicken breeds.The genetic basis of indigenous chicken breeds revealed in this study is useful to better understand the mechanisms underlying the resource characteristics of chicken.
基金supported by the Key Project of Science and Technology Development Program of Shandong Province,China(2013KF03)
文摘A fast analytical method for the simultaneous determination of 9 mycotoxins, including alfatoxins （B1, B2, G1, and G2）, fumonisins （B1, B2 and B3）, zearalenone, and deoxynivalenol in corn using dispersive solid-phase extraction method and ultra-performance liquid chromatography coupled to tandem quadrupole time-of-lfight mass spectrometry （UPLC-Q-TOF-MS） was developed and validated. Samples were extracted with acetonitrile-water （84：16, v：v, containing 1% acetic acid） using ultrasonic extraction. The extracts were puriifed with a dispersive SPE method using C18 as a cleaning agent. The ifnal clear extracts were dried by nitrogen blowing and subsequently redissolved in methanol-water （5：5, v：v）. The samples were then analyzed by UPLC-Q-TOF-MS with 0.1% formic acid in ammonium acetate-methanol as mobile phase. The mean recoveries were ranged from 68.0 to 120.0%, and the relative standard deviation （RSD） ranged from 0.18 to 6.29%. Limits of detections ranged from 0.05 to 50 μg kg？1, and limits of quantiifcation ranged from 0.1 to 200 μg kg？1, which were below the legal limits set by the European Union for the legislated mycotoxins. The developed method was applied to 130 corn samples. Among the mycotoxins studied, alfatoxins B1 and fumonisins B1, B2 and B3 were the most predominant mycotoxins, and their concentrations were 0–593.12, 0–2.01×104, 0–6.94×103 and 0–3.05×103 μg kg–1, respectively.
