Process of Analyzing Pig Inbreeding Coefficient Using SAS Program

The paternity index is one of the important parameters which paternity determination depends on.Inbreeding is an indispensable and effective means to improve herds and breeds and breed new strains and breeds.It can fix good traits and improve herd genetic uniformity.The INBREED module of SAS statistical analysis software can be used to calculate the inbreeding coefficients of the offspring and their parents in the pig herd pedigree.In this study,we used actual data as an example to compile and operate an SAS program for calculating the inbreeding coefficients of a pig herd.Compared with the dedicated software for calculating inbreeding coefficients developed in recent years,such as BASIC+database dBASE,Visual Basic+database SQ L Serve method,DFREMLI,MTDF EMLI,VCE,ASREML,DMU,GBS and Herdsman,calculating inbreeding coefficients with SAS programs has the advantages of low cost,simple programming language,and easy operation.For livestock breeders who are not provided with special computing software,the use of SAS to calculate the inbreeding coefficients of pigs is of great significance to planned breed selection and assortative mating.

An Iterative Calculating Method for Inbreeding and Relationship Coefficient

The iterative formulas of inbreeding and relationship coefficients were put forward by using numerator elationship. It is suitable for any none - generation - overlap pedigree. The inbreeding and relationship coeffi- ient of offsprings can be calculated by those of parents. The deducing process of numerator relationship is simple and clear comparing with path analysis. An example shows the usage of these formulas.

Estimation of inbreeding and identification of regions under heavy selection based on runs of homozygosity in a Large White pig population

Background: Runs of homozygosity(ROHs) are homozygous segments of the genome where the two haplotypes inherited from the parents are identical. The current availability of genotypes for a very large number of single nucleotide polymorphisms(SNPs) is leading to more accurate characterization of ROHs in the whole genome. Here,we investigated the occurrence and distribution of ROHs in 3,692 Large White pigs and compared estimates of inbreeding coefficients calculated based on ROHs(FROH), homozygosity(FHOM), genomic relationship matrix(FGRM)and pedigree(FPED). Furthermore, we identified genomic regions with high ROH frequencies and annotated their candidate genes.Results: In total, 176,182 ROHs were identified from 3,569 animals, and all individuals displayed at least one ROH longer than 1 Mb. The ROHs identified were unevenly distributed on the autosomes. The highest and lowest coverages of Sus scrofa chromosomes(SSC) by ROH were on SSC14 and SSC13, respectively. The highest pairwise correlation among the different inbreeding coefficient estimates was 0.95 between FROH_totaland FHOM, while the lowest was-0.083 between FGRMand FPED. The correlations between FPEDand FROHusing four classes of ROH lengths ranged from 0.18 to 0.37 and increased with increasing ROH length, except for ROH > 10 Mb. Twelve ROH islands were located on four chromosomes(SSC1, 4, 6 and 14). These ROH islands harboured genes associated with reproduction, muscular development, fat deposition and adaptation, such as SIRT1, MYPN, SETDB1 and PSMD4.Conclusion: FROHcan be used to accurately assess individual inbreeding levels compared to other inbreeding coefficient estimators. In the absence of pedigree records, FROHcan provide an alternative to inbreeding estimates.Our findings can be used not only to effectively increase the response to selection by appropriately managing the rate of inbreeding and minimizing the negative effects of inbreeding depression but also to help detect genomic regions with an effect on traits under selection.

Estimates of genomic inbreeding and identification of candidate regions that differ between Chinese indigenous sheep breeds

Background:A run of homozygosity(ROH)is a consecutive tract of homozygous genotypes in an individual that indicates it has inherited the same ancestral haplotype from both parents.Genomic inbreeding can be quantified based on ROH.Genomic regions enriched with ROH may be indicative of selection sweeps and are known as ROH islands.We carried out ROH analyses in five Chinese indigenous sheep breeds;Altay sheep(n=50 individuals),Large-tailed Han sheep(n=50),Hulun Buir sheep(n=150),Short-tailed grassland sheep(n=150),and Tibetan sheep(n=50),using genotypes from an Ovine Infinium HD SNP BeadChip.Results:A total of 18,288 ROH were identified.The average number of ROH per individual across the five sheep breeds ranged from 39(Hulun Buir sheep)to 78(Large-tailed Han sheep)and the average length of ROH ranged from 0.929 Mb(Hulun Buir sheep)to 2.544 Mb(Large-tailed Han sheep).The effective population size(Ne)of Altay sheep,Large-tailed Han sheep,Hulun Buir sheep,Short-tailed grassland sheep and Tibetan sheep were estimated to be 81,78,253,238 and 70 five generations ago.The highest ROH-based inbreeding estimate(FROH)was 0.0808 in Large-tailed Han sheep,whereas the lowest F_(ROH)was 0.0148 in Hulun Buir sheep.Furthermore,the highest proportion of long ROH fragments(>5 Mb)was observed in the Large-tailed Han sheep breed which indicated recent inbreeding.In total,49 ROH islands(the top 0.1% of the SNPs most commonly observed in ROH)were identified in the five sheep breeds.Three ROH islands were common to all the five sheep breeds,and were located on OAR2:12.2-12.3 Mb,OAR12:78.4-79.1 Mb and OAR13:53.0-53.6 Mb.Three breed-specific ROH islands were observed in Altay sheep(OAR15:3.4-3.8 Mb),Large-tailed Han sheep(ORA17:53.5-53.8 Mb)and Tibetan sheep(ORA5:19.8-20.2 Mb).Collectively,the ROH islands harbored 78 unique genes,including 19 genes that have been documented as having associations with tail types,adaptation,growth,body size,reproduction or immune response.Conclusion:Different ROH patterns were observed in five Chinese indigenous sheep breeds,which reflected their different population histories.Large-tailed Han sheep had the highest genomic inbreeding coefficients and the highest proportion of long ROH fragments indicating recent inbreeding.Candidate genes in ROH islands could be used to illustrate the genetic characteristics of these five sheep breeds.Our findings contribute to the understanding of genetic diversity and population demography,and help design and implement breeding and conservation strategies for Chinese sheep.

Using non-destructive sampling to evaluate the population genomic status of captive Brown Eared Pheasants

Evaluating the genetic status of threatened species is an essential task in conservation genetics.However,the genetic status of threatened species has been mostly evaluated through techniques that fail to estimate genetic diversity at the whole genomic level.Next generation sequencing can meet this demand,but high quality samples such as blood or muscle tissues are required.However,it is difficult to collect such samples from threatened species because sampling work may impact their health.Therefore,it is essential to design a workflow to evaluate the whole genomic status of threatened species using non-destructive sampling.Even though non-destructive sampling has been used in traditional barcoding technique,the barcoding technique cannot evaluate the whole genomic status.Brown Eared Pheasant(Crossoptilon mantchuricum)is an endangered species,with captive populations maintained in Taiyuan Zoo,China,and Europe.However,the genetic diversity,inbreeding pattern,and mutation load of these two populations are unclear.To uncover the genetic status of these two captive populations,we applied 2b-RAD technology to evaluate the genomic status of these populations using feathers as samples.The feathers could be collected by non-destructive sampling.The results indicate that the Taiyuan Zoo population has a lower genetic diversity and higher inbreeding coefficient than the European population.The Taiyuan Zoo population has lethal mutations when homozygous.The current project uses a non-destructive sampling technique to evaluate the whole genomic status of the two captive populations,providing a paradigm for conservation genetics,which will facilitate the development of conservation biology.

Genome-wide detection for runs of homozygosity analysis in three pig breeds from Chinese Taihu Basin and Landrace pigs by SLAF-seq data

Erhualian(E),Meishan(MS)and Mi(MI)pigs are excellent indigenous pig breeds in Chinese Taihu Basin,which have made great contributions to the genetic improvement of commercial pigs.Investigation of the genetic structure and inbreeding level of the 3 pig breeds is of great significance for the sustainable breeding of commercial pigs.The length and number of runs of homozygosity(ROH)as well as the frequency of genomes covered by ROH can be used as indicators to evaluate the level of inbreeding and the origin of the population.In this study,the ROH characteristics of E,MS,MI and Landrace(L)pigs were analyzed by SLAF-seq data,and the inbreeding coefficient based on ROH(F_(ROH))was calculated.In addition,we have identified candidate genes in the genomic regions associated with ROH.A total of10568 ROH were detected in 116 individuals of 4 pig breeds.The analysis showed that there were significant differences in genetic structure between 3 Taihu Basin pig breeds and L,and the genetic structure of E and MI was similar.The results of F_(ROH)showed that the inbreeding level of MS was the highest(0.25±0.07),while E and MI were lower than L.Compared with the other 3 pig populations,MS showed a higher frequency of long ROH(>5 Mb),indicating higher inbreeding in MS in recent generations.A large number of candidate genes related to reproductive traits are located in the genomic regions with a high frequency of ROH,and these genes are expected to be used as candidate genes in marker-assisted selection(MAS)breeding programs.Our findings can provide theoretical support for genetic conservation and genetic improvement of 3 pig breeds in Chinese Taihu Basin.

Effect of Genetic Connectedness on the Selection Results of Breeding Pigs

Two pig populations were simulated with Monte Carlo method; each consisted of 5 boars and 50 sows per generation. Genetic connectedness between herds was established by randomly selecting 1 or 2 boars from one population to mate sows of the other population. Breeding pigs were selected within populations according to animal model BLUP. The benefits of genetic connectedness between herds were examined. The results showed that, the average coefficients of inbreeding decreased, while the cumulative selection responses of populations increased, and the higher response occurred randomly in the two populations at generation 5 with the increase of the genetic connectedness between herds. Selection response was affected by genetic connectedness and trait heritability, the lower heritability and higher connectedness, the better selection results. When the number of exchanged litters between populations per generation was 6 litters, the selection results reached a reflection point; if the number of exchanged litters between populations increased further from this point, neither the increase of the cumulative selection responses nor the decrease of coefficients of inbreeding was significant.

Statistical measures of genetic differentiation of populations： Rationales, history and current states

Population differentiation is a fundamental process of evolution, and many evolutionary studies, such as population genetics, phylogeography and conservation biology, all require the inference of population differentiation. Recently, there has been a lot of debate over the validity of FST （and its analogue Gsr） as a measure for population genetic differentiation, notably since the proposal of the new index D in 2008. Although several papers reviewed or explored specific features of these statistical measures, a succinct account of this bewildering issue with an overall update appears to be desirable. This is the purpose of the present review. The available statistics generally fall into two categories, represented by Fsv and D, respectively. None of them is perfect in measuring population genetic differentiation. Nevertheless, they each have advantages and are valuable for current re- search. In practice, both indices should be calculated and a comparison of them can generate useful insights into the evolutionary processes that influence population differentiation. FsT （GsT） has some unique irreplaceable characteristics assuring its standing as the default measure for the foreseeable near future. Also, it will continue to serve as the standard for any alternative measures to contrast with. Instead of being anxious about making choice between these indices, one should pay due attention to the equili-brium status and the level of diversity （especially Hs） of the populations, since they largely sway the power of a given statistic to address a specific question. We provide a multi-faceted comparative summary of the various statistics, which can serve as a basic reference for readers to guide their applications [Current Zoology 61 （5）： 886-897, 2015].