Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs

Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it was limited by the purebred population.Compared to directly combining two uncorrelated purebred populations to extend the reference population size,it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction.In this study,we simulated purebred offspring(PAS and PBS)and crossbred offspring(CAB)base on real genotype data of two base purebred populations(PA and PB),to evaluate the performance of genomic selection on purebred while incorporating crossbred information.The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship(REL)was better than the other methods(individuals closet or farthest to the purebred population,CP/FP)in term of the prediction accuracy.Furthermore,the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA,which was similar to combine PA and PAS.Moreover,the rank correlation between the multiple of the increased relationship(MIR)and reliability improvement was 0.60-0.70.But for individuals with low correlation(Cor(Pi,PA or B),the reliability improvement was significantly lower than other individuals.Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only.The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals.

MiR-106a targets ATG7 to inhibit autophagy and angiogenesis after myocardial infarction

Background:Myocardial infarction(MI)is an acute condition in which the heart mus-cle dies due to the lack of blood supply.Previous research has suggested that au-tophagy and angiogenesis play vital roles in the prevention of heart failure after MI,and miR-106a is considered to be an important regulatory factor in MI.But the specific mechanism remains unknown.In this study,using cultured venous endothelial cells and a rat model of MI,we aimed to identify the potential target genes of miR-106a and discover the mechanisms of inhibiting autophagy and angiogenesis.Methods:We first explored the biological functions of miR-106a on autophagy and angiogenesis on endothelial cells.Then we identified ATG7,which was the down-stream target gene of miR-106a.The expression of miR-106a and ATG7 was investi-gated in the rat model of MI.Results:We found that miR-106a inhibits the proliferation,cell cycle,autophagy and angiogenesis,but promoted the apoptosis of vein endothelial cells.Moreover,ATG7 was identified as the target of miR-106a,and ATG7 rescued the inhibition of autophagy and angiogenesis by miR-106a.The expression of miR-106a in the rat model of MI was decreased but the expression of ATG7 was increased in the infarction areas.Conclusion:Our results indicate that miR-106a may inhibit autophagy and angiogenesis by targeting ATG7.This mechanism may be a potential therapeutic treatment for MI.

Imputation from SNP chip to sequence: a case study in a Chinese indigenous chicken population

Background: Genome-wide association studies and genomic predictions are thought to be optimized by using whole-genome sequence(WGS) data. However, sequencing thousands of individuals of interest is expensive.Imputation from SNP panels to WGS data is an attractive and less expensive approach to obtain WGS data. The aims of this study were to investigate the accuracy of imputation and to provide insight into the design and execution of genotype imputation.Results: We genotyped 450 chickens with a 600 K SNP array, and sequenced 24 key individuals by whole genome re-sequencing. Accuracy of imputation from putative 60 K and 600 K array data to WGS data was 0.620 and 0.812 for Beagle, and 0.810 and 0.914 for FImpute, respectively. By increasing the sequencing cost from 24 X to 144 X, the imputation accuracy increased from 0.525 to 0.698 for Beagle and from 0.654 to 0.823 for FImpute. With fixed sequence depth(12 X), increasing the number of sequenced animals from 1 to 24, improved accuracy from 0.421 to0.897 for FImpute and from 0.396 to 0.777 for Beagle. Using optimally selected key individuals resulted in a higher imputation accuracy compared with using randomly selected individuals as a reference population for resequencing. With fixed reference population size(24), imputation accuracy increased from 0.654 to 0.875 for FImpute and from 0.512 to 0.762 for Beagle as the sequencing depth increased from 1 X to 12 X. With a given total cost of genotyping, accuracy increased with the size of the reference population for FImpute, but the pattern was not valid for Beagle, which showed the highest accuracy at six fold coverage for the scenarios used in this study.Conclusions: In conclusion, we comprehensively investigated the impacts of several key factors on genotype imputation. Generally, increasing sequencing cost gave a higher imputation accuracy. But with a fixed sequencing cost, the optimal imputation enhance the performance of WGP and GWAS. An optimal imputation strategy should take size of reference population, imputation algorithms, marker density, and population structure of the target population and methods to select key individuals into consideration comprehensively. This work sheds additional light on how to design and execute genotype imputation for livestock populations.

Momentum filtering scheme of cooling atomic clouds for the Chinese Space Station

To obtain cold atom samples with temperatures lower than 100 pK in the cold atom physics rack experiment of the Chinese Space Station,we propose to use the momentum filtering method for deep cooling of atoms.This paper introduces the experimental results of the momentum filtering method verified by our ground testing system.In the experiment,we designed a specific experimental sequence of standing-wave light pulses to control the temperature,atomic number,and size of the atomic cloud.The results show that the momentum filter can effectively and conveniently reduce the temperature of the atomic cloud and the energy of Bose–Einstein condensation,and can be flexibly combined with other cooling methods to enhance the cooling effect.This work provides a method for the atomic cooling scheme of the ultra-cold atomic system on the ground and on the space station,and shows a way of deep cooling atoms.