Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated  Advances in next-generation sequencing have enabled the application of genomics for the improvement of agronomically important crop species. Genomic selection (GS) and genome-wide association studies (GWAS) have delivered considerable crop improvements and rely on high density markers spread throughout the genome . GenotypWhile such methods can be cost-effective, especially in species with large genomes, the modal genome size of plants is approx. 600 Mbp , such thArabidopsis thaliana  or high missing data. As such the importance of high quality genomic resources shared by crop communities becomes increasingly important and applicable.As skim WGR results in missing data in the form of absent markers and incomplete allele recovery, the above-mentioned studies have often employed some form of specialized SNP discovery and genotyping method. Many studies have been able to exploit the ability to make assumptions based on biparental population structure, and even in diverse sample sets, efforts have been made to improve SNP genotyping. Having sequenced 533 diverse rice varieties, Several studies, particularly those applying ultra-low sequencing coverage (<1x) have relied on imputation to achieve sufficient SNPs for linkage mapping and GWAS. The ability to impute from low marker density to high, whether from low to high density array based SNPs or some form of low-coverage GBS, has been widely investigated, particularly in human and livestock studies, which found benefits in sequencing a large number of individuals at low coverage for the application of GS and GWAS . Skim WGDespite successful application in numerous plant species, skim WGR has not yet been fully exploited in amenable crop species with relatively small genomes as a routine genotyping tool outside of biparental population studies. bzh reference genome  were used to produce skim WGR sequences in silico, for analysis of the method. The original fastq files had an average of 10x coverage of the Darmor-bzh reference genome  after conversion to genotype and depth matrices. To assess the effect of sequencing depth, a range of minimum read depths including a minimum read depth of 5, 4, 3 and 2 were applied to each of the skim levels, resulting in 28 list-based SNP sets . Each of the resulting skim DH genotype matrixes were compared to the original 2x DH sequencing data to determine genotype accuracy. If the skim DH set was filtered to a minimum read depth of 1 or 2, the comparison was made against the original 2x sequencing data filtered to a minimum depth of 2, and if the skim DH set was filtered to a minimum read depth of 3, the comparison was made against the original 2x sequencing data filtered to a minimum depth of 3, and so on for each filtering depth.in silico skim BAM files aiming for 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x were 0.19x, 0.38x, 0.77x, 1.54x, 2.31x, 3.08x, and 3.85x, respectively, with a varying range of depth around the mean , more representative of an actual pooled sequenced data set. Increasing sequence coverage resulted in an exponential increase (R2 = 0.9289–0.9998) in SNPs and relaxing the stringency of depth filtering also significantly increased the total number of SNPs for each of the skim levels , stringent depth filtering resulted in highly variable SNP density, with some chromosomes having one or no SNPs Figure . RelaxinAs low sequencing depth is expected to impact the accuracy of genotype calls, a comparison was made between the original 10x data set and the skim data in each of the 28 list-based high-confidence SNP sets: 0.25x, 0.5x, 1x–5x, each filtered to a depth of 2, 3, 4, and 5. This relies on the assumption that the genotypes are correct in the full 10x data.In all list-based SNP sets the majority of genotype calls were correct, with matching genotype calls ranging from 53.3–74.9%, while the number of false genotype calls was low (<8%), decreasing as sequencing coverage increases Figure . Most ofAs the acceptable amount of missing data within a genotype matrix will vary between studies depending on the intended application, the number of SNPs and corresponding accuracy of genotype calls has been examined in cumulative increments of 10% missing data , a moderate percentage were missing (26.3–32.9%) and a small proportion were incorrect genotype calls (2.6–5.8%) in the de novo skim sets. An overall increase in mean missing data and some degree of insufficient allele sampling caused by skim sequencing coverage seems to account for the inclusion of novel SNP loci in the 1x and 5x skim de novo SNP sets, with the vast majority removed from the original 10x data set during MAF filtering.The genotypes of SNPs identified in the 1x and 5x Actual average genome coverage was 0.93x with a coefficient of variation of 0.34. Due to the heterozygous nature of these samples, the more lenient SNP list (approx. 9.4M SNPs) applied in the global diversity panel could not be used, as resulting SNPs need to be further filtered on excess heterozygosity caused by misalignment. Instead, a list of over four million high-confidence SNPs which have been previously validated and filtered on excess heterozygosity was used. As the data set is large , the relatively high proportion of absent genotypes resulted in the need to remove a large proportion of SNPs due to excess missing data. A range of filtering depths was considered to balance the total number of markers and the ability to accurately call heterozygous loci. A minimum of 5 reads resulted in only 8,538 SNPs, too few for association studies, while a minimum of 4 reads resulted in 19,073 SNPs , is likely to be appropriate for most genomics-based studies in canola. Additionally, in an attempt to mitigate the effect of insufficient allele sampling, a range of minimum read depths were used in this study. Often this resulted in selecting SNPs with higher than expected coverage, particularly for ultra-low skim sets. Sequencing depth varies across the genome even with only uniquely aligned reads and has been attributed in part to reference collapse, presence/absence between individuals and minor GC bias but the primary cause of this variance has not been established  from 9 million to over 177 million. While the percentage of false genotype calls only increases from 2.1 to 3.7%, the total number of erroneous data points increases from 190K to 6.5 million  of erroneous genotype calls, which decreased with sequencing coverage and more stringent depth filtering. Although genotype errors were low, the total number of data points varied significantly between SNP sets. For example, relaxing depth filtering from 5 reads to 2 reads in the 2x data increases the total number of data points generated  in attempt to prevent insufficient allele sampling, while balancing the total number of informative markers . For association studies in heterozygous samples, avoiding insufficient allele sampling and providing sufficient markers is more important than the proportion of missing data , 2016. CThe use of skim WGR in DHs was expected to result in a significant improvement in overall genotype accuracy, due to the simpler genetic background. With the exception of the dp 1 skim sets, the majority of called genotypes were accurate (95.2–97.7%) across DH SNP sets, an improvement at ultra-low coverage compared to the global diversity panel skim SNP sets when missing data is ignored (87.4–98.1%). There were fewer false calls in the DHs (2.1–4.6%) compared to the global diversity panel skims (1.9–12.6%), suggesting an improvement of accuracy in a DH background at some coverage levels, and that ultra-low skim WGR may be feasible in DHs. However, a significant number of loci were heterozygous (3.8–5.1%), decreasing as more stringent depth filtering was applied but not significantly affected by sequencing coverage. This suggests consistent misalignment of short reads, which has been found to occur at a local level in canola , and empAlternatively, genotype accuracy can be improved in skim WGR through the application of more advanced bioinformatics techniques. A GBS-RAD study in barley using a range of coverage between 16 and 4 average reads per SNP and minimum read depth of 2, achieved genotype accuracies of 99, 97, and 95% at maximum missing data of 15, 50, and 80%, respectively , similarde novo SNP discovery can be performed provided a certain degree of error can be accepted. Importantly, the DHs demonstrated the difficulty of accurately genotyping canola due to homoeologous misalignment. In future, the cost-structure and accuracy of long-read sequencing may be such that it will be the preferred method for routine genotyping in highly duplicated genomes. Whole genome sequencing, whether based on short or long reads, is likely to become the GBS method that will predominate in all species due its stable, flexible and transferable nature.This study has demonstrated the applicability of skim WGR outside of biparental segregating populations, in a highly duplicated genome of 1.13 Gbp in size, across a range of genetic backgrounds. The inherent flexibility in marker density and the cost-effective, high-throughput nature of skim WGR provides substantial advantages, allowing more samples to be sequenced for the same cost as other traditional GBS methods, increasing the power of association studies. As a broad recommendation, a realized coverage between 1x and 2x with relatively stringent depth filtering is suggested for the application of skim WGR in canola. Crop species including soybean, safflower and tomato have genomes of a similar size to canola and so could use 1x coverage as a starting point for skim WGR under current sequencing cost structures, but this needs to be evaluated on a case-by-case basis taking into consideration sample diversity, expected heterozygosity and available resources. While skim WGR has been applied in some plant species with large genomes, for example pea, to achieve 1x coverage in this species requires 4.3 Gbp of sequencing per sample. As such there are still substantial challenges present for the implementation of skim WGR in large genomes, and ultra-low skim WGR (<1x coverage) will likely remain most suitable in biparental populations. However, as sequencing technology advances and costs continue to fall, more and more species will become amenable to the method. The presence of a reference genome, and a list of pre-validated SNPs eases the implementation of skim WGR in canola, although DB and MM prepared the plant materials. MM, MD, MS, PT, and YO performed the sequencing library preparation. MM performed the data analysis. MM, GS, HD, and NC conceptualized the project and assisted in drafting the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The number of animals born dead, which includes the number of mummified (NM) and stillborn (NS) animals, is the most important trait to directly quantify the reproductive loss in domestic pigs. In this study, 282 Landrace sows and 250 Large White sows were genotyped by sequencing (GBS). A total of 816 and 1068 litter records for NM and NS were collected from them. A genome-wide association study (GWAS) was conducted to reveal the genetic difference between NM and NS.A total of 248 and 10 genome-wide significant SNPs were detected for NM and NS across numerous parities in Landrace pigs. The corresponding numbers for Large White pigs were 175 and 6, respectively. All of the detected SNPs were parity specific for both NM and NS in two breeds. Based on significant SNPs, in total 242  and 10 significant chromosome regions  were found for NM and NS, respectively. Among them, 237  and 8 significant chromosome regions  for NM and NS were not reported in previous studies. A list of candidate genes at the identified loci was proposed, including HMGB1, SOX5, KCNJ8, ABCC9 and YY1 for NM, ASTN1 for NS.This is the first time when GBS data was used to identify genetic regions affecting NM and NS in Landrace and Large White pigs. Many identified informative SNPs and candidate genes advance our understanding of the genetic architecture of NM and NS in pigs. However, further studies are needed to validate using larger populations with more breeds.The online version of this article (10.1186/s12863-018-0692-x) contains supplementary material, which is available to authorized users. Sow reproductive performance is one of the most important production traits in the pig industry. The total number born (TNB) and the number born alive (NBA) are two important traits to measure sow reproductive performance. The difference between them is defined as the number of piglets born dead, which directly measures loss in litters from the foetal stage to farrowing. The number born dead includes the number mummified (died before farrowing) (NM) and stillborn (dies during or shortly before farrowing) (NS). NM and NS are the most important traits for quantifying the loss of reproduction. In a normal clean environment, mummified piglets usually coincide with large litters, an insufficient nutrient supply, delayed placental development  and geneThe basis of litter loss is multifactorial due to the quantitative characteristics of the traits, variation is determined by many genes with mostly small effects and an unknown number of non-genetic effects. Using molecular markers, many linkage studies have been conducted to find QTL and causal genes for NM and NS . In the In general, the parity of sows significantly affects the sow’s reproduction performance because it reflects the sow’s reproductive age and physiological status. At prime parity, the litter size is smallest partly due to physiological immaturity. Up to the parity 4, 5, and 6, the litter size rapidly increases and then tends to stabilize, but it begins to decrease around parity 8 . HoweverTwo pig breeds populations were used in this study: one Large White and one Landrace pig population. Two populations derived from the same commercial pig farm , and introduced from Canadian Hylife Company at 2008. A total of 282 Landrace and 250 Large White producing sows were sampled randomly, and the pedigree data include 520 Landrace and 758 Large White pigs in two generations. In total, 816 and 1068 litter records for NM and NS were collected from the database of pig farm in 2012–2015, respectively. These records were grouped according to sow parity. For the Landrace pigs, the litter numbers were 282, 234, 179 and 121 for parities 1, 2, 3 and 4, respectively. For Large White pigs, the litter numbers were 250, 249, 244, 208 and 117 for parities 1, 2, 3, 4 and 5, respectively. Details are listed in Table MseI. Next, P1 and P2 barcode adapters that recognize Mse1-compatible sequences were ligated to the digested DNA fragments. The restriction fragments were enriched by PCR amplification with adapter-specific primers. The quality evaluation was performed using Qubit2.0, Agilent 2100 and Q-PCR. The data sequence from the pair-end reads were generated with the Illumina HiSeq PE150. In the raw reads, N contents with > 10% of sequence length or with low quality bases (< 5) and a number > 50% of the sequence length were removed. Then, barcode sequences were eliminated. The clean data were aligned to the pig reference genome  using Burrows-Wheeler Aligner (BWA) with the parameters mem -t 4 -k 32 -M [− 5, and sites with a mean depth greater than or equal to 3 (dp3). After quality control, a total of 345,570 SNP markers met the quality requirements.A total of 250 Large White and 282 Landrace sows were genotyped using GBS technology (Novegene limited Inc.). Genomic DNA was extracted from ear tissue using a surfactant and the protease pyrolysis method. Genomic DNA samples were checked using agarose gel electrophoresis, Nanodrop and Qubit. Then, 0.1–1 μg genomic DNA was digested with the restriction endonuclease -k 32 -M . Initialx is the phenotype value. Then, the birth year and month are included as a fixed effect, and the DMU software [y is the vector of phenotypic observation; β is the SNP effect; a is the vector of the remaining polygene effect following the multi-normal distribution  and a suggestive (1/N) thresholds were used in this study, where N is the number of SNPs used for analyses. In Landrace, a total of 251,678, 247,225, 245,353 and 240,368 SNPs for parity 1–4 were used to analysis. In Large White pigs, a total of 277,080, 275,687, 274,867, 272,405 and 271,736 SNPs for parity 1–5 were used to analysis. The percentage of phenotypic variance explained by each top significant SNP was calculated by For GWAS, single-marker regression analysis was conducted using GEMMA software . Becausesoftware  was usedTo detect the linkage disequilibrium (LD) between significant SNPs, the 40Kb region centring on each top SNP (with the highest –log(P) value) was used to performed LD analysis by Haploview software .To identify candidate genes for genome-wide significant loci, a search for annotated genes within a 40Kb region centring on each top SNP (with the highest –log(P) value) of significant loci in the pig reference genome assembly (Build 11.1) was implemented using ANNOVAR software .In each parity, a mixed linear model was used to implement a single SNP association test. The association patterns of SNPs with NM in Landrace pigs are shown in Table P = 5.25E-14) was located in HMGB1 gene, which explained 1.36% of the phenotypic variance. In this region, a total of 99 SNPs were detected and 8 positional candidate genes was located  were located in this region.By carrying out associate test with GBS data, many significant SNPs were identified. This study suggested six important SNPs including SSC11: 2898066 bp, SSC11: 7114076 bp, SSC5: 51702429 bp, SSC5: 49763855 bp, SSC9: 118987531 bp and SSC7: 121138988 bp. The markers within these significant regions (40Kb region centring on each significant SNP) were used to conduct LD analysis. The LD block plots were shown in Fig. In this study, a GWAS based on GBS data was implemented using univariate mixed linear model for animals born dead trait including NM and NS in two commercial pig populations. To eliminate the population stratification, this GWAS was performed separately in Landrace pig and Large White pig population.To the best of our knowledge, although QTL on NM and NS have been reported in previous studies , this waNM = 2.99E-09, PNS = 4.70E-08; SSC3, position = 129,076,023, PNM = 3.96E-06, PNS = 2.27E-08; SSC4, position = 73,553,176, PNM = 1.30E-06, PNS = 8.16E-10) were found in common between NM and NS in Landrace pig population at parity 3  gene plays a role in several cellular processes, including inflammation, cell differentiation and tumor cell migration. Knockout mutations in the HMGB1 gene resulted in lethality in mice [At 1.28–7.13 Mb on SSC11, a significant chromosome region for NM was detected in Landrace pig population at parity 3  gene is expressed in the embryo mesenchyme and many important physiological system [Potassium Voltage-Gated Channel Subfamily J Member 8) and ABCC9 (ATP Binding Cassette Subfamily C Member 9) genes are related to Hypertrichotic Osteochondrodysplasia [At 49.74–53.88 Mb on SSC5, a significant chromosome region for NM was detected in Large White population at parity 4  gene. This gene is a protein-coding gene and associated with peri-implantation lethality [At 121.12–121.16 Mb on SSC7, a significant chromosome region for NM was detected in parity 5 Table . Its topethality . TherefoP = 8.89E-08) was located to the ASTN1 (Astrotactin 1) gene. This gene is a protein-coding gene, and related to Schimke Immunoosseous Dysplasia with clinical phenotypes of growth retardation, renal failure, recurrent infections, cerebral infarcts [At 118.97–119.18 Mb on SSC9, a significant chromosome region for NS was detected in parity 2 Table . Its topinfarcts .In this study, we performed a GWAS study to detect genomic regions associated with NM and NS in different parities in two pig populations. These findings advance our understanding of the genetic architecture of the number of animals born dead in domestic pigs. Most of SNP detected were different between NM and NS. All of significant SNPs for both NM and NS were parity-specific, and no candidate gene was in common between parities. GBS technology explores many new SNPs for NM and NS, however, these SNPs should be further validated using larger populations with more breeds.Additional file 1:Table S1. Summary of significant chromosome regions including genomic level (0.05/N) for NM in Landrace population, N is the number of SNPs used for analyses. Table S2. Summary of significant chromosome regions including genomic level (0.05/N) for NM in Large White population, N is the number of SNPs used for analyses. Table S3. Summary of significant chromosome regions including genomic level (0.05/N) for NS in Landrace population, N is the number of SNPs used for analyses. Table S4. Summary of significant chromosome regions including genomic level (0.05/N) for NS in Large White population, N is the number of SNPs used for analyses. (DOCX 40 kb)


Oreochromis niloticus) is one of the most cultivated and economically important species in world aquaculture. Intensive production promotes the use of monosex animals, due to an important dimorphism that favors male growth. Currently, the main mechanism to obtain all-male populations is the use of hormones in feeding during larval and fry phases. Identifying genomic regions associated with sex determination in Nile tilapia is a research topic of great interest. The objective of this study was to identify genomic variants associated with sex determination in three commercial populations of Nile tilapia. Whole-genome sequencing of 326 individuals was performed, and a total of 2.4 million high-quality bi-allelic single nucleotide polymorphisms (SNPs) were identified after quality control. A genome-wide association study (GWAS) was conducted to identify markers associated with the binary sex trait . A mixed logistic regression GWAS model was fitted and a genome-wide significant signal comprising 36 SNPs, spanning a genomic region of 536 kb in chromosome 23 was identified. Ten out of these 36 genetic variants intercept the anti-Müllerian (Amh) hormone gene. Other significant SNPs were located in the neighboring Amh gene region. This gene has been strongly associated with sex determination in several vertebrate species, playing an essential role in the differentiation of male and female reproductive tissue in early stages of development. This finding provides useful information to better understand the genetic mechanisms underlying sex determination in Nile tilapia.Nile tilapia ( In aquaculture, many fish species of commercial interest exhibit sexual dimorphism in a variety of economically important traits such as growth rate, age at sexual maturity and carcass quality traits (Oncorhynchus tshawytscha) (Oncorhynchus mykiss) (Pelteobagrus fulvidraco)   (Hsd17b1 gene in fishes of the genus Seriola (sdy - irf9 in rainbow trout (Oncorhynchus mykiss)  strict control of genetic factors, ii) control by environmental factors only, or iii) interactions between both genetic and environmental factors (Oreochromis niloticus) and Mozambique tilapia (Oreochromis mossambicus) have a heterogeneous XX/XY male system (Oreochromis aureus) have a heterogeneous ZZ/ZW female system (wt1b) and cytochrome P450 family 19 subfamilies A member 1 (cyp19a)  . The cypAmh) and the doublesex- and mab-3 related transcription factor 2 (Dmrt2) genes  mapping tebrates . In addispecific .The multiple sex-determining regions described for Nile tilapia support the evidence that sex determination is a complex trait, and it is not yet clear which specific putative causative variants are involved in regulating the trait in this species. Previous studies have reported that the strain factor may influence the detection of different genetic regions associated with sex determination in this species . In thisFor the present study we used individuals from three commercial breeding populations established in Latin America, which are directly or indirectly related to Genetically Improved Farmed Tilapia (GIFT); the most widely cultivated Nile tilapia strain in the world. The GIFT strain was initially established in the Philippines in 1980 by the World Fish Center to initiate the first breeding program in Nile tilapia. The strain was bred using crosses of four Asian cultured strains from Israel, Singapore, Taiwan and Thailand and four strains from wild populations captured across the natural distribution of this species in Africa  (We used 59 samples from the POP_A breeding population from AquaAmerica (Brazil), and 126 and 141 samples from POP_B and POP_C breeding populations, respectively, both from Acuacorporación Internacional . POP_A was formed from a Malaysian breeding population introduced to Brazil in 2005 for breeding and production purposes. POP_B was generated using individuals from Israel, Singapore, Taiwan and Thailand present in the Philippines in the late 1980s. POP_B strain was imported to Costa Rica by ACI in 2005 from the aquaculture station Carmen Aquafarm (Philippines). POP_C was established in the Philippines by breeding the best available stock from GIFT populations with two of the original African strains that founded GIFT. The detailed origin of these populations were previously described by Genomic DNA was extracted from a total of 326 fish samples, using the Wizard Genomic DNA purification kit (Promega) according to manufacturer’s specifications. DNA quality was evaluated by agarose gel electrophoresis and quantified by a Qubit fluorimeter . After normalization, the sequencing libraries were prepared and barcoded with the 200-cycle DNA PCR-free TruSeq kit in pair-end format and sequenced through 66 lanes of an Illumina HiSeq 2500 machine  by a commercial supplier.O. niloticus as reference genome (https://www.broadinstitute.org/gatk/)  SNP call rate < 0.90. Finally, samples with more than 80% of missing genotypes were also discarded. The genomic regions containing the filtered SNPs were remapped to the actual reference assembly (GenBank accession GCF_001858045.2), using the protocol provided in procedure described by Raw SNPs were filtered using Vcftools software v. 0.1.15 (ST (Weir & Cockerham’S FST) estimated using Vcftools software v. 0.1.15 . Second, a principal component analysis (PCA) was carried out using PLINK v1.9 (ST estimates throughout the genome and within the region involved in sex determination. The heterozygosity of each SNP in the sex-associated region was assessed using PLINK v1.9 (IS) for SNPs that were found to be significantly associated with sex determination using software Vcftools.The population genetic diversity and differentiation was investigated among the three populations. First, genetic differentiation between populations was measured with pairwise Fgkin function. The general formula used for the logistic regression model is as follows:GWAS was conducted using the GenAbel R package  is also available in Figshare https://doi.org/10.6084/m9.figshare.9178082.v2.Data of genotypes and phenotypes used for this study are available in the online digital repository Figshare The whole-genome sequencing (WGS) and posterior alignment of the 326 fish generated an average of 76.9 million raw reads (SD = 65.0 million reads) and 76.3 million mapped reads (SD = 64.6 million mapped reads). The average coverage for each individual was 8.7X (SD = 8.9 X), with a minimum and maximum of 2.1x and 65.7x coverage per fish, respectively. In the discovery phase a total of 38,454,943 genetic variants were identified in the 326 animals. After the quality control steps, which included discarding indels, low-quality variants, exclusion of SNPs other than biallelic and genotypes called below 50% across all individuals, a total of 4,762,199 SNPs were retained. After QC including MAF, HWE, SNPs and sample call rate filtering, a total of 2.3 million high-quality bi-allelic SNPs were retained in 302 samples . Samples that passed the quality control by population were 56 , 114  and 132  for POP_A, POP_B and POP_C respectively.ST among the three commercial populations was 0.049. The lowest genetic differentiation was observed between POP_B and POP_C (FST 0.044). The analysis of nucleotide diversity among the populations suggested that POP_A (average π = 7.93 × 10-4) is slightly less diverse than populations from Costa Rica  . The first two principal components represented 25% of the genetic variation. A clear differentiation is observed among the three populations analyzed in this study . PCA1 al × 10-4) .A genome-wide significant association signal was detected in a genomic region within chromosome 23 see . The genAmh), suggested to be linked to the differentiation process of male and female reproductive tissue in early stages of development of vertebrates and various fish species , which has been described as a selective co-regulator for steroid receptor functions , which inhibits the LRH-1 receptor (liver receptor homolog-1), a gene abundantly expressed in the ovary and shown to activate the transcription of steroid genes, including Cyp11a1 in granulose cells  two sex-specific alternative splicings have been reported for the Amh gene , two concurrent sex-specific alternative splicing forms were identified within the dmrt1 and cyp19a1 genes . These results suggest that there is a higher degree of genetic differentiation between male and female sub-populations in this genomic region compared to the average genetic differentiation across the whole genome. In the same genomic region across the 36 significant SNPs, the average of FIS for males was -0.08102, while for females was 0.5184, suggesting that there is heterozygote deficit for females in this genomic region compared to males. To search for highly heterozygote loci in males  compared to females , the average heterozygosity differences between males and females were locally calculated for each SNP in the associated region within linkage group 23. Interestingly, we found co-localization of highly heterozygote variants in males when compared to females in the region harboring the most significant SNPs within and near the Amh gene , which is concordant with the common geographical origin of these farmed populations (Costa Rica). However, the three populations clustered in clear groups in the PCA, indicating a patent genetic structure among the three populations.In this study we analyzed three different farmed Nile tilapia populations which show a low level of genetic differentiation based on the global FThe approach used in this study was based on whole-genome sequencing of males and females from three different farmed populations providing a highly dense distribution of markers and covering the whole genome. The GWAS revealed a single genomic region in linkage group 23 that is associated with sex determination in Nile tilapia. These results are consistent with those previously reported  (Amh on the Y chromosome (Amhy). The coding sequence was identical to Amh linked to the X, except for a missense SNP in exon II, which changes an amino acid in the N-terminal region. Also, Amhy lacks 5608 bp of promoter sequence that is found in the X-linked Amh homolog.Two previous reports have identified a duplicate of the male-specific Amh gene in different positions, similar to previous studies. For instance, three SNPs located in exon II were identified, while Amh. A missense SNP in exon II was also described to be associated with the temperature-dependant sex reversal in Nile tilapia  (Amh gene is a member of the beta-transforming growth factor family (TGFβ). In some species of teleost fish, members of the TGFβ family and steroidogenic genes encoding the enzyme 17β-hydroxysteroid dehydrogenase 1 (Hsd17b1) have been identified as sex determination factors, in contrast to other vertebrates where key sex determination switches are transcription factors . In puffer fish (Takifugu rubripes), it was determined that the change of an SNP in the anti-Müllerian hormone receptor was associated with sex differentiation , another member of the family TGFβ, is a sex determinant; demonstrating that the expression of Gsdf was only present in the male gonads during the gonadal differentiation  providing strong evidence of Amh being a major gene controlling sex differentiation in Nile tilapia farmed populations.This study provides further evidence to better understand the genetic architecture of sex determination in commercial Nile tilapia populations established in Latin America. Ten SNPs highly associated with sex determination intercept the anti-Müllerian hormone gene (


Despite the short period since importation, we detected differentiation (Fst = 0.049) between the French Charolaise (CHA) and CHCU. However, CHA breed was the closest breed to CHCU followed by other hybrids breed with a clear CHA origin. Linkage disequilibrium (r2) decay tends to be lower in CHCU compared to CHA probably due to a less intense artificial selection programs of CHCU. Signals of recent adaptation to tropical conditions between CHCU and CHA were identified. Genes mapping within those regions reflect different functions related to immunity, metabolic changes and heat tolerance (CHCU) and muscle development and meat quality (CHA) that may have had an important role in the phenotypic differentiation of these breeds. Further studies will expand our knowledge on the molecular basis of adaptation of cattle to tropical conditions and molecular process associated with meat quality traits.In this study, we used BovineSNP50 Genotyping BeadChip data to estimate the structure, putative ancestral origin as well as to identify regions with selective sweeps that may have had an important role in the adaptation to tropical conditions of the ‘Charolais de Cuba’ (CHCU) breed. According to a principal component analysis, CHCU samples cluster together with taurine breeds with an estimated 93% of  Bos taurus and Bos indicus) descend from the extinct wild ox or aurochs (Bos primigenius)1. Cattle domestication is estimated to have occurred in two separated locations: the Fertile Crescent between 6000 and 2500 BC (taurine cattle) and then in the Indus Valley about 2000 BC (zebu cattle)3. It is generally accepted that Bos taurus, spread into Europe via two routes: a Mediterranean route and a Danubian  route4. Cattles were among the first old-world livestock species that were introduced in the Americas, as early as during the second Columbus trip in 14935. The first settlement occurred in the Caribbean islands. Among them, Cuba is the larger island (110 000 km²), which harbors genetic resources that are not well studied. The subtropical climate of Cuba is characterized by high heat periods, low feed inputs, presence of parasites and tropical diseases that are not optimum for Bos taurus breed. The importation from France by Cuban farmers of Charolais cattle (CHA) occurred at the beginning of the twentieth century. More specifically, in 1900, “Marqués de la Real Proclamacion de Cienfuegos” was the first farmer importing CHA. Nevertheless, Ignacio Casas Saumells was documented as the most successful farmer in the first middle of the twentieth century, who imported CHA bulls to Caimanes (Santiago de Cuba province) and San José del Retiro farms (Granma province) from 1919 to 19386. Interestingly, since the importation, these animals have been maintained as a “pure” breed without mating with other local breeds, mainly at the “Manuel Fajardo” genetic center located in Jiguani (Granma province)6.Domestic cattle breeds  while most of the females in France are calving in autumn and winter (30% and 39% respectively) and very few in summer (9%). The CHCU females are calving more early and have a longer productive life than CHA females: 11% of the calving females are 2 year old in Cuba, but only 2% in France and cows calving at 7 years or older are 38% and 28% respectively in Cuba and France. Growth capacity of CHCU is significantly lower than CHA with weights of 34 vs 46 kg at birth and 290 vs 493 kg for heifer’s weight at 18 months. CHCU progeny are also less efficient during fattening and produce carcasses with poorer muscle shape and higher fat content8.Phenotypically, CHCU animals are white and unlike CHA animals, they are hairless. The production systems in France and Cuba differ largely. There is a single management system in Cuba with few large herds where breeding is 100% by artificial insemination (AI) and females are grazing all year long. During the drought period, they may be complemented with sugar cane residues. Comparatively, in France, there is a large variety of production systems in relation with geographical conditions. There are also great differences in the use of AI among herds, with only 14% of the females bred by AI on averageCharolais de Cuba” (CHCU) and their relationships to other breeds is unknown. A pioneer report was done using blood groups9 suggesting a high variability of CHCU, similar allele composition with CHA as well as differentiation to other cattle breeds found in Cuba such as Holstein, Santa Gertrudis, Creole and Zebu9. The authors also reported the presence of a low frequency allele (U’1) found only in Zebu, suggesting a putative Bos indicus introgression in the formation of the CHCU breed. The main goal of this study was to use BovineSNP50 Genotyping BeadChip data to estimate the population structure, the putative ancestral origin of CHCU as well as to identify regions with selective sweeps that may have had an important role in the adaptation to tropical conditions, in comparison to CHA breed.The genetic structure and variability of the tropical adapted “Bos taurus and Bos indicus samples was observed  with a small percentages (7%) of putative Bos indicus ancestry . Interestingly, our admixture analysis at K = 3 detects a putative introgression of African taurine alleles in CHA, and thus consequently in CHCU populations. This finding is in agreement with previously published results10. The unsupervised analysis considering the whole dataset proposed a K = 37 as an optimum partition number . In line with these observations9, using blood groups markers reported a similar allele composition between CHCU and CHA as well as a putative introgression of Zebu (indicus) alleles. We recognized the limitations of our study to trace Bos indicus origins (due the SNP ascertainment bias of the Illumina Bovine 50K BeadChip). However, based on the admixture analysis we cannot exclude a putative small introgression or contribution of Bos indicus in the establishment of CHCU breed as previously suggested9. Further analyses using a less biased source of information (i.e. whole-genome sequence data) will be needed to better estimate the putative Bos indicus introgression.A clear distinction between ved Fig. , in agretry Fig. . Neverthber Fig.  suggestiBos taurus, 120 Hybrids and 100 Bos indicus samples) the differentiation coefficient Fst13 was calculated. As expected the maximum Fst value was observed between Bos indicus and Bos taurus samples  differentiation between the CHCU and CHA was observed (Fst = 0.049). Actually, CHA breed was the closest breed to CHCU followed by Canchim , Piedmontese  and Limousine  breeds  for CHA and CHCU was 0.48 and 0.43, respectively. The lower LD observed in CHCU compared to CHA may suggest a stronger artificial selective pressure in CHA as a consequence of the breeding programs in France, compared to CHCU . In agreement with the taurine ancestry of CHCU, the LD decay is equivalent to the values reported in taurine15 and higher to either composite or indicine cattle breeds17.In agreement with previous studies an inverse relationship between LD and genetic distance was observedCHA Fig. . For ins18. As observed in Fig. To identify putative signals of adaptation to tropical conditions the Extended Haplotype Homozygosity (EHHS) was calculated and contrasted between the CHCU and the CHA. According to the chosen criterion (see methods), 409 SNPs corresponding to 104 different genomic intervals were identified in regions with extremely long haplotypes in relation to the expected pattern. 57% of those SNPs were intergenic variants, 32% were intronic variants, 9% were located upstream/downstream of genes and 1% were exonic synonymous variants . AQP5 is therefore a good candidate gene to explain the thermo-tolerance seen in CHCU. Another interesting gene is heat shock protein HSPB1  located within interval 95. HSPB1 which encodes a small heat shock protein that functions as a molecular chaperone24, have been found in numerous studies among genes differentially expressed in heat-stressed animals from different species, including cattle25, zebu26 or buffalo27. It is worth noticing that this interval contains ACHE, another candidate gene potentially involved in thermo-tolerance. Indeed, knockout of ACHE, the gene encoding acetylcholinesterase, is responsible for hypothermia in mice28, while ACHE showed higher expression after exposing layer-type chickens to acute heat stress29. Interval 66 contains UCP3 which encodes a mitochondrial uncoupling protein (UCP). UCPs are mitochondrial carrier proteins that catalyze a regulated proton leak across the inner mitochondrial membrane, diverting free energy from ATP synthesis by the mitochondrial F0F1-ATP synthase to the production of heat30. UCPs play therefore an important role in the regulation of cold acclimation, energy expenditure and diet-induced thermogenesis31. There were no significant differences in body temperature between wild type and Ucp3 −/− mice, at thermo-neutral or cold (4 °C) conditions32. As these knockout animals were not exposed at high temperature, there is no evidence for a direct involvement of UCP3 in heat acclimation. However, it has been shown that Ucp3 expression was reduced in the hypothalamus of meat-type chicken after heat stress33 and that heat-stressed C2C12 murine myocytes displayed also a significant reduction of Ucp3 mRNA expression compared to control34. UCP3 therefore remains an interesting candidate gene to explain thermo-tolerance in CHCU, despite further work being needed. Overall, our results suggest that several of the regions selected in CHCU contain genes that might confer thermo-tolerance.Since its introduction to Cuba, CHCU animals have well adapted to the tropical conditions and have developed a tolerance to the high temperatures encountered on the island. It is noteworthy to point out that several of the regions selected in CHCU  are within or very closed to genomic regions associated to thermo-tolerance. For example, we identified 5 regions  also found by Howard and collaborators37. The pathway analysis was done considering all the EHH intervals  map within intervals with slower EHH decay in CHCU breed than CHA, suggesting evidence of selection , as consequences of the intensive artificial selection through breeding program of CHA in France, over-representation of pathways relate to meat quality and muscle development such as β-alanine degradation, HIPPO signalingBos taurus origin and were mostly related to the CHA. Putative signals of recent selection between CHCU and CHA were identified and genes mapping within those regions reflect different selection emphasis/functions related to immunity, metabolic changes and heat tolerance (CHCU) and muscle development and meat quality (CHA) that may have had an important role in the process of adaptation to tropical Cuban conditions of CHA breed. Further studies on these pathways will expand our knowledge on the molecular basis of adaptation of cattle to tropical conditions and molecular processes associated with meat quality traits.We present here the first study describing the genetic diversity and structure of CHCU and their relationships to other breeds. CHCU samples reflect a clear A total of 40 CHCU were sampled by ear biopsy using a NextGen tissue sampling technology (Allflex). DNA of the 40 samples was extracted and genotyped using the Illumina Bovine 50K BeadChip  by LABOGENA . Raw data were checked and analyzed with the GenomeStudio software (Illumina). Animal care and procedures were performed according European regulations about the protection of animals used in experimentation, following institutional guidelines for the Good Experimental Practices and approved by the Ethical Committee of the Institut National de la Recherche Agronomique (INRA).et al. 2014), which provided genotype information of 43,043 autosomal single nucleotide polymorphisms (SNPs) scored in 1,543 animals distributed across 134 breeds. To avoid bias determined by unequal sample size, only those breeds having at least 20 samples were retained for further analysis (880 samples distributed across 43 breeds)  <1% and missing genotypes >1%.To estimate the worldwide structure, diversity patterns and putative ancestral origin of the CHCU, we analyzed the public dataset corresponding to the study of  analysis. The evolutionary distances were computed using the p-distance method54 and are in the units of the number of base differences per site.To visualize genetic distances between populations, principal component analyses (PCA) were performed with smartpca program from EIGENSOFT55 was employed. Initially, ADMIXTURE 1.2 was run in an unsupervised manner with a variable number of clusters K = 2–44. Following the authors recommendations the lowest 10-fold cross-validation values were used to choose an optimum K-value. Additionally, a partial supervised approach was employed where assuming known ancestry K for samples corresponding to well-known established pure breeds. Before the PCA and ADMIXTURE analysis, linkage disequilibrium between SNPs was pruned using the option ‘–indep-pairwise’ in PLINK v1.0750. A total of 24,061 markers were selected from these analyses. Afterwards, a genetic differentiation analysis was done considering only beef breeds  and 100 Bos indicus, Supplementary Table 13. The significance of the observed Fst between CHA and CHCU was validated by comparing the observed Fst value against the Fst distribution  after randomization of the dataset.To examine potential origins of CHCU, the Maximum Likelihood approach implemented in ADMIXTURE56. Following the author recommendations56, first the integrated EHHS (iES) was estimated for each SNP and independently per population. Then, the EHHS decay of a single site between two populations was compared by calculating the log ratio of iES in both populations (ln(Rsb)). The cut-off for selecting the significant SNPs was established by picking out those SNPs that represented the top 1% of the tail area of the empirical distribution. Then, the genomic intervals were defined considering only those regions with at least two consecutive SNPs with less than 1 Mb distance. Finally, the extent of linkage disequilibrium (LD) between each pair of SNPs, measured as r2, which is less susceptible to bias due to differences in allelic frequency was calculated using PLINK v1.0750. In both cases the whole set of 42,331 SNPs were employed without excluding markers (i.e. pruned by linkage disequilibrium between SNPs).In order to detect selection signals across the genome, the Extended Haplotype Homozygosity (EHHS) was calculated and contrasted between the CHCU and CHA as described inhttp://www.ingenuity.com/products/ipa) tool. The list of protein-coding genes was uploaded into the application. Then, each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base (IPKB). Fischer’s exact test was employed to calculate a p-value, which determines the probability that each biological functions and/or canonical pathway is due to chance alone. Only the enriched pathways with adjusted p-values < 0.05 after Benjamini & Hochberg57 multiple testing correction were retained.In order to describe the most over-represented pathways and biological processes affected by putative selective sweeps, the genes mapping within putative selective sweeps were used to perform a pathway enrichment analysis using the Ingenuity Pathway Analysis (Supplementary InformationSupplementary table 3


The date palm is one of the oldest cultivated fruit trees. The tree can withstand high temperatures and low water and the fruit can be stored dry offering nutrition across the year. The first region of cultivation is believed to be near modern day Iraq, however, where and if the date palm was domesticated is still a topic of debate. Recent studies of chloroplast and genomic DNA revealed two major subpopulations of cultivars centered in both the Eastern range of date palm cultivation including Arabian Peninsula, Iraq and parts of South Asia, and the Western range, including North Africa.To better understand the origins of date palm cultivation we sequenced and analyzed over 200 mitochondrial and chloroplast genomes from a geographically diverse set of date palms. Here we show that, based on mitochondrial and chloroplast genome-wide genotyping data, the most common cultivated date palms contain 4 haplotypes that appear associated with geographical region of cultivar origin.These data suggest at least 3 and possibly 4 original maternal contributions to the current date palm population and doubles the original number. One new haplotype was found mainly in Tunisia, Algeria and Egypt and the second in Iraq, Iran and Oman. We propose that earliest date palm cultivation occurred independently in at least 3 distinct locations. This discovery will further inform understanding of the history and origins of cultivated date palm.The online version of this article (10.1186/s12864-019-5834-7) contains supplementary material, which is available to authorized users. P. theophrasti during the spread of date palm cultivation in North Africa [The importance of date palm to early civilizations is well documented and it is among the earliest cultivated fruit trees . There ah Africa .Multiple studies, including our own, of Y chromosome or chloroplast markers and genome-wide SNP analysis has confirmed at least two major sub-populations in the date palm –9. The sWhile analysis of nuclear genomic markers is highly informative for understanding genetic admixture patterns, little work has been done to study variation in organellar genomes of date palm cultivars from multiple geographical regions. Organellar genomes in angiosperms offer the benefit that, as in animals, they are transmitted from the maternal lineage with evidence for bipaternal transmission only in rare cases . For theBrahea dulcis and 4 Phoenix species for comparison  identified 37 SNPs in the Chloroplast and 168 in the Mitochondria genomes for a total of 205 intra-date palm SNPs.SNP filters that required at least one high quality alternative allele in any of the samples studied resulted in 177 SNPs identified in the 158,462 bp Chloroplast genome and 841 in the 715,001 bp Mitochondria genomes for a total of 1018 SNPs . AG2 is certainly closer to the AG1 haplotype (96/205 SNP differences combining chloroplast and mitochondria) or AG1 related NA2 haplotype (96/205 SNP differences) than the NA1 haplotype (146/205 SNP differences). However, the divergence between AG2 and AG1 is high when compared to the divergence of NA2 and AG1 (10/205 SNP differences) Tables  and 4. TP. sylvestris is important to note and agrees with the findings of Flowers and colleagues in their analyses of the date palm chloroplast and mitochondrial genomes [P. theophrasti occurred in the cultivation of the North African date palm, this was likely through male contribution as the chloroplast and mitochondrial genomes retain their close relationship to P. sylvestris. P. sylvestris is native to South Asia [P. sylvestris but how this would occur geographically requires further investigation. Nuclear markers from cultivars in this region show distinction from Arabian Gulf cultivars and are at the base of the date palm phylogenetic tree closer to other Phoenix species [The similarity of the major North African haplotype to  genomes . Their futh Asia  and so c species .P. sylvestris will require further research.Whether the combination of nuclear and organellar information is indication of a highly distinct, ancient date palm in North Africa or simply introgression with trnL intron or trnL-trnF spacer. Likewise 5 haplotypes were found in 30 Emirati cultivars [While the use of nuclear DNA markers assists in understanding admixture of populations, organellar genome markers can assist in understanding more simple maternal contributions. We see concordance with previous results from across the date palm cultivating regions that genotyped specific chloroplast markers and found 2 major haplotypes in date palm . From thultivars  and 3 maultivars . These gBased on the observation that the NA2 haplotype is more similar to the AG1 than any other haplotype suggests two possibilities. A recent ancestor of the NA2 haplotype may have been a maternal contributor to the AG1 cultivars or vice-versa. We propose that it was likely the NA2 haplotype that derived from the AG1 as they are both closer to the other Arabian Gulf haplotype (AG2) than the major North African 1 haplotype. This would then suggest that there were 3 major centers of date palm cultivation, two in the Arabian Gulf and one in North Africa. A fourth that derived from one of the Arabian Gulf cultivars then spread and includes the famous North African “Deglet Noor” and Egyptian “Zaghlool” cultivars.The fact that we did not observe mixing of the haplotypes in all the cultivars studied here suggests that the haplotypes came into existence prior to the spread of cultivars and that transmission of the mitochondria and chloroplast is indeed tightly linked. Whether the centers of cultivation were initiated by transfer of male contributors from other regions, as was observed in the major North African cultivars or rather contribution occurred later in the cultivation process remains to be studied for the second Arabian Gulf haplotype. However, it is clear that the female contribution to each center was unique based on the haplotypes observed here.P. sylvestris requires further investigation and may explain some of the previously observed genetic structure in the overall date palm population. Altogether, these results inform our understanding of the earliest origins of date palm cultivation.The strong distinction between the haplotypes found here argues against a single center of date palm cultivation whose cultivars then spread to other regions with a bottleneck creating significant distinction. Rather, it suggests that there were likely 3 distinct centers of cultivation from which cultivars in those regions all derived from a single maternal contributor followed by a fourth that developed from the AG1 haplotype. These centers of cultivation were then responsible for hundreds of future cultivars that are now available with admixture of the nuclear genome occurring at the boundaries of these centers. The proximity of the most common North African haplotype to Phoenix species identified by and collected from the USDA palm collection and the outgroup palm Brahea dulcis identified by and collected from the Huntington library botanical garden palm collection . DNA from fruit for date palm, or leaves for other species, was extracted as described [Date fruit samples were from the Qatar date fruit biobank , a colleescribed . SequencPhoenix and outgroup palms. We excluded insertions or deletions and required an overall population SNP call quality of greater than 900.Sequences were aligned to the complete date palm chloroplast  and mitochondrial  reference genomes of the Eastern cultivar Khalas , 24 usinhttp://tree.bio.ed.ac.uk/software/figtree/).Polymorphic sites in the form of a VCF file were transformed into PHYLIP formatted sequence using VCF2PHYLIP . We condAdditional file 1:Cultivar Information. Table containing information on date palm cultivars analyzed in this study. (XLSX 17 kb)Additional file 2:Mitochondrial and Chloroplast Haplotype SNP Positions. Table containing genotypes for all intra-date palm SNP positions in the Mitochondrial and Chloroplast haplotypes identified in this study. (XLSX 18 kb)Additional file 3:Date Palm Genotypes. File containing all genotypes utilized in this analysis in vcf format. (VCF 3902 kb)


Leuconostoc lactis CCK940, which exhibits glycosyltransferase activity, produces oligosaccharides using sucrose and maltose as donor and receptor molecules, respectively. The oligosaccharides produced were purified by Bio-gel P2 chromatography and the purified oligosaccharides (CCK-oligosaccharides) consisted of only glucose. 1H-NMR analysis revealed that the CCK-oligosaccharides were composed of 77.6% α-1,6 and 22.4% α-1,4 glycosidic linkages, and the molecular weight of the CCK-oligosaccharides was found to be 9.42 × 102 Da. To determine the prebiotic effect of the CCK-oligosaccharides, various carbon sources were added in modified media. Growth of six probiotic strains, Lactobacillus casei, L. pentosus, L. plantarum, Weissella cibaria, Bifidobacterim animalis, and Saccharomyces cerevisiae, was better when the CCK-oligosaccharides were used as the sole carbon source compared to fructo-oligosaccharides, which are widely used as prebiotics. These results showed that the CCK-oligosaccharides produced from Leu. lactis CCK940 could serve as good candidates for novel prebiotics. The dextran polymer has α-1,6 glycosidic bonds, mutan polymer has α-1,3 glycosidic bonds, alternan polymer consists of alternate α-1,6 and α-1,3 glycosidic bonds, and reuteran polymer has α-1,4 glycosidic bonds [Lactic acid bacteria produce carbohydrates, glycosides, oligosaccharides, or polysaccharides through glycosyltransferase activity ,2. Glycoic bonds ,8. Prebiotics are typically defined as “selectively fermented, non-digestible food ingredients or substances that specifically support the growth and/or activity of health-promoting bacteria that colonize the gastrointestinal tract” . This deLeuconostoc lactis CCK940, which has high glucansucrase activity, was isolated from home-made kimchi  and the production of oligosaccharides from Leu. lactis CCK940 was optimized [Leu. lactis CCK940 showed immunostimulating effects on RAW264.7 macrophage cells [In our previous reports, ptimized ,16. The ge cells .Leu. lactis CCK940 would also have prebiotic effects. Since only limited studies examining the prebiotic effects of oligosaccharides produced by lactic acid bacteria have been conducted, in the present study, we investigated the prebiotic effects of the CCK-oligosaccharides produced by Leu. lactis CCK940 using 24 probiotic strains.Because oligosaccharides are well known prebiotics, it was predicted that the oligosaccharides produced by w/v) dextrose and hydrolysates were identical. The purified oligosaccharides were identified as gluco-oligosaccharides (CCK-oligosaccharides) consisting of only glucose. To analyze the sugar composition, the CCK-oligosaccharides were acid-hydrolyzed by trifluoroacetic acid (TFA) and their hydrolyzed products were identified using thin-layer chromatography (TLC) and high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). As shown in 2 Da. The molecular weight of the purified CCK-oligosaccharides was analyzed using size exclusion chromatography . Among td-glucanase. CCK-oligosaccharides were hydrolyzed by pullulanase M1 and produced oligosaccharides with a degree of polymerization (DP) of 11. To determine the types of glycosidic bonds in the CCK-oligosaccharides, the CCK-oligosaccharides were hydrolyzed with several carbohydrate hydrolysis enzymes and their products were analyzed by TLC . CCK-oli1H-NMR spectroscopy was used to analyze the linkage ratios of the CCK-oligosaccharides. Chemical shifts of CCK-oligosaccharides, maltose, nigerose, and waxy corn starch (WCS) were determined at 5–5.8 ppm  (m-MRS) with FOS at 24 and 48 h of incubation. Viable cell numbers of W. cibaria were 9.36 and 4.35 log CFU/mL in MRS at 12 and 48 h, respectively. Viable cell numbers of W. cibaria were 8.01 and 7.94 log CFU/mL in FOS and CCK media, respectively, at 48 h of incubation. B. animalis also exhibited results similar to W. cibaria; the viable cell number of B. animalis in the CCK medium was significantly higher than that in FOS media. B. animalis and S. cerevisiae grew better in media containing CCK-oligosaccharides than in FOS. To determine the prebiotic effects of the CCK-oligosaccharides, various carbon sources were added into modified media. Six of 24 strains,  control . Viable Leu. mesenteroides B-742 produces GOS and mannitol using maltose as an acceptor [Leu. mesenteroides NRRL B-23188 synthesizes gluco-oligosaccharides using calcium hydroxide–sucrose solution [Leu. mesenteroides have been conducted, no studies have been conducted to investigate the gluco-oligosaccharides synthesized by Leu. lactis.It has been reported that acceptor , and tha3 Da [3 Da [It has been reported that when pooled human milk oligosaccharides are fractionated, the molecular weight of the fractions is 2.094–3.626 × 103 Da , and dexDa [3 Da . The mold-glucanase (EC 3.2.1.6) cleaves β-1,3 linkages. CCK-oligosaccharides were not hydrolyzed by these three enzymes. Amyloglucosidase (EC 3.2.1.3) hydrolyzes α-1,4 and α-1,6 glycosidic bonds from the non-reducing end of starch oligomers and polymers through an exo-type mechanism, and this enzyme hydrolyzed CCK-oligosaccharides and released glucose. Pullulanase M1 is an endo-type enzyme similar to amyloglucosidase, which hydrolyzes α-1,6 bonds of pullulan, amylopectin, glycogen, and α- and β-limit dextrins of amylopectin and glycogen. CCK-oligosaccharides were hydrolyzed by pullulanase M1 and produced oligosaccharides with a degree of polymerization (DP) of 11. Based on these results, it was predicted that there are no β-1,3 or β-1,4 glycosidic linkages in the CCK-oligosaccharides.α-Amylase (EC 3.2.1.1) hydrolyzes the α-1,4 glucose linkages of starch through an endo-type mechanism and α-glucosidase (EC 3.2.1.20) cleaves a glucose unit from the non-reducing end of α-1,4 oligosaccharides and polysaccharide starch fragments through an exo-type mechanism. CCK-oligosaccharides were not hydrolyzed by α-amylase or α-glucosidase, which implies that these carbohydrates are non-digestible in the human intestinal tract because α-amylase and α-glucosidase are major carbohydrate-hydrolyzing enzymes in the human digestive system. β-Glucosidase (EC 3.2.1.21) releases a glucose unit from the non-reducing end of β-1,4 or β-1,3 glycosidic bonds of oligosaccharides or polysaccharide fragments, lichenase hydrolyzes β-1,4 glycosidic linkages in β-glucans containing β-1,3 and β-1,4 bonds, and β-1,3-1H-NMR spectra. Maltose and nigerose are disaccharides formed from two units of glucose joined with an α-1,4 bond and connected with an α-1,3 linkage, respectively. Waxy corn starch (WCS) consists of polysaccharides formed from glucose polymers joined with α-1,4 and α-1,6 bonds. The enzyme 4,6-α-glucanotransferase of L. reuteri 121 acts on malto-oligosaccharides (MOS); the MOS consist of α-1,4 and α-1,6 glycosidic linkages [Leu. mesenteroides NRRL B-512F; dextran contains approximately 95% α-1,6 linkages; however, alternan contains alternating α-1,3 and α-1,6 linkages [Nuclear magnetic resonance (NMR) is the most powerful tool available for evaluating oligosaccharide linkage ratios . Generallinkages . The strWhen the prebiotic effect of a sugar is examined, minimal medium without a carbon source can be used so that the supplemented sugar is the sole carbon source. However, because lactic acid bacteria are fastidious bacteria, there is no suitable minimal medium for the growth of lactic acid bacteria. MRS medium, which is usually used for the cultivation of lactic acid bacteria, is a complex medium, but the beef extract and yeast extract in MRS are utilized as nitrogen sources rather than carbon sources by lactic acid bacteria . TherefoW. cibaria showed the highest viable cell number at 12 h of incubation, following which the viable cell number decreased. This phenomenon was attributed to the production of acid. It has been reported that gentio-oilgosaccharide, which is synthesized by Leu. mesenteroides NRRL B-1426, exerts a prebiotic effect on B. infantis and L. acidophilus [Leu. mesenteroides NRRL B-21297, exhibit a good prebiotic effect [dophilus  and α- used in this study was isolated from home-made kimchi [The strain e kimchi . This stLeu. lactis CCK940 were produced in optimized fermentation conditions and purified as described in a previous report [The oligosaccharides from s report .n-propyl alcohol :water. The developed TLC plate was dipped in 0.3% (w/v) N-(1-naphtyl) ethylenediamine dihydrochloride (Sigma-Aldrich) and 5% (v/v) sulfuric acid  in methanol , and then baked at 121 °C for 5 min. Glucose polymers  purchased from Carbosynth Co.  were used as standard sugars.Samples were spotted onto silica gel 60 F254 , and the gel plates were developed twice using 2:5:1.5 nitromethane :Leu. lactis CCK940 were analyzed using a HPAEC-PAD  [Leu. lactis CCK940 culture was centrifuged at 27,237× g for 1 min and the supernatant was analyzed by HPAEC-PAD (Dionex) with a CarboPac PA-1 column  and a CarboPac PA-1 guard column . The flow rate was 1.0 mL/min, and the mobile phase used for oligosaccharide separation was 150 mM sodium hydroxide for the first 20 min; subsequently, 600 mM sodium acetate (in 150 mM sodium hydroxide) was applied with a gradient of 60:40 to 0:100 from 20 to 25 min, and 150 mM sodium hydroxide was used from 25 to 40 min . Ten microliters of each sample was injected for each analysis.The CCK-oligosaccharides produced by CA, USA) ). The LeLeu. lactis CCK940 was analyzed using size exclusion chromatography. The CCK-oligosaccharides  were dissolved in distilled water and the soluble CCK-oligosaccharides were analyzed by HPLC  equipped with an OHpak SB-802.5 column . The flow rate was 0.4 mL/min, column oven temperature was 35 °C, the mobile phase used for CCK-oligosaccharides separation was filtered and distilled water, and they were detected by RI . One hundred microliters of sample was injected for analysis. Glucose polymers (DP 1–7) purchased from Carbosynth Co.  were used as a standard sugar.The size of the CCK-oligosaccharides produced by 2 gas flow. The sugar components of the CCK-oligosaccharides were analyzed by HPAEC-PAD and TLC.The CCK-oligosaccharides were hydrolyzed with 4 M TFA at 121 °C for 2 h. TFA was then removed by evaporation under gentle Nw/v) were treated with the following enzymes and concentrations: 10 mU of α-amylase, 100 mU of α-glucosidase, 520 mU of amyloglucosidase (Sigma-Aldrich), 1.4 U of pullulanase M1, 10 mU of lichenase , 100 mU of β-glucosidase, and 10 mU of β-1,3-d-glucanase (Sigma-Aldrich). The CCK-oligosaccharides were reacted with enzymes at 37 °C for 1 h and the products were determined by TLC.CCK-oligosaccharides were treated with various carbohydrate-hydrolyzing enzymes to determine the composition of the glycosidic bonds. CCK-oligosaccharides  and Delta NMR Processing and Control Software version 5.3 . Freeze-dried samples (10 mg/mL) were first dissolved in deuterium oxide (D2O) and then freeze-dried again. Samples dissolved in D2O (10 mg/mL) were analyzed by 1H-NMR. 1H-NMR spectra were collected at 80 °C.The relative abundance of α-1,4 and α-1,6 linkages in the CCK-oligosaccharides was determined by 400 MHz B. adolescentis KCCM 11206, B. animalis KCCM 11209, B. bifidum KCCM 12096, B. breve KCCM 42255, B. longum KCCM 11953, Enterococcus faecium KCCM 12118, L. acidophilus KCCM 32820, L. casei KCCM 12452, L. fermentum KCCM 35469, L. helveticus KCCM 40989, L. johnsonii KCCM 41274, L. paracasei KCCM 40995, L. pentosus KCCM 40997, L. plantarum KCCM 12116, L. rhamnosus KCCM 32405, L. salivarius KCCM 40210, Lactococcus lactis KCCM 40104, Leuconostoc citreum KCCM 12030, Leu. mesenteroides KCCM 11325, Pediococcus pentosaceus KCCM 11902, Streptococcus thermophilus KCCM 35496, and W. cibaria KCCM 41287. These strains were cultured in MRS medium in the presence or absence of prebiotics at 37 °C for 48 h. S. cerevisiae KCCM 50549 and Zygosaccharomyces rouxii KCCM 12066 were cultured using YM medium at 30 °C.A total of 24 probiotic strains were obtained from the Korean Culture Center of Microorganisms ; Leu. lactis CCK940, selected probiotic strains were incubated with medium containing CCK-oligosaccharides as the sole carbon source. m-MRS and modified YM (m-YM) had no carbon sources (w/v) dextrose) was used as a positive control, MRS with 1% (w/v) FOS, MRS with 1% (w/v) CCK-oligosaccharides (CCK), m-MRS with 1% (w/v) FOS, and m-MRS with 1% (w/v) CCK media were used. For yeast strains, m-YM was used as a negative control, commercial YM (YM containing 1% (w/v) dextrose) was used as a positive control, and m-YM with 1% (w/v) FOS, and m-YM with 1% (w/v) CCK media were used.To determine the prebiotic effects of the CCK-oligosaccharides produced by  sources . For lacv/v) culture broth was inoculated in various media. Bifidobacterium sp., lactic acid bacteria, and yeast were incubated in anaerobic, facultative anaerobic, and aerobic conditions, respectively. Culture broth was sampled at 0, 12, 24, and 48 h. Bifidobacterium sp. and lactic acid bacteria were spread on MRS agar plates and yeast was spread on YM agar plates.A colony of lactic acid bacteria was seeded in MRS broth and incubated at 37 °C for 24 h. Additionally, one colony of yeast was seeded in YM broth and incubated at 30 °C for 24 h at 250 rpm. One percent (p < 0.05). Data are presented as mean ± standard deviation (SD) from triplicate experiments. Statistical analyses were performed using SPSS 23 . Statistical significance between groups was determined by one-way analysis of variance (ANOVA), followed by Duncan’s multiple range test (Leu. lactis strains, although several studies have been conducted to examine the gluco-oligosaccharides produced by other lactic acid bacteria. The CCK-oligosaccharides found were novel oligosaccharides based on their structure, and we found that the glycosidic linkages were composed of 77.6% α-1,6 and 22.4% α-1,4. The CCK-oligosaccharides significantly promoted the growth of L. casei, L. pentosus, L. plantarum, W. cibaria, B. animalis, and S. cerevisiae, the major probiotic strains used in the food industry. The prebiotic activity of the CCK-oligosaccharides was better than FOS, which is a major commercially available prebiotic, in some probiotic strains. The prebiotic activities of CCK-oligosaccharides and FOS were found to be strain-dependent. This showed the potential suitability of the use of CCK-oligosaccharides as prebiotics and their significance in the rapidly growing market for prebiotics.To the best of our knowledge, this is the first study to investigate the gluco-oligosaccharides produced from


Sleepiness affects normal social life, which attracts more and more attention. Circadian phenotypes contribute to obvious individual differences in susceptibility to sleepiness. We aimed to identify candidate single nucleotide polymorphisms (SNPs) which may cause circadian phenotypes, elucidate the potential mechanisms, and generate corresponding SNP-gene-pathways. A genome-wide association studies (GWAS) dataset of circadian phenotypes was utilized in the study. Then, the Identify Candidate Causal SNPs and Pathways analysis was employed to the GWAS dataset after quality control filters. Furthermore, genotype-phenotype association analysis was performed with HapMap database. Four SNPs in three different genes were determined to correlate with usual weekday bedtime, totally providing seven hypothetical mechanisms. Eleven SNPs in six genes were identified to correlate with usual weekday sleep duration, which provided six hypothetical pathways. Our results demonstrated that fifteen candidate SNPs in eight genes played vital roles in six hypothetical pathways implicated in usual weekday bedtime and six potential pathways involved in usual weekday sleep duration. While behavioral factors, circadian factors (time of day), duration of wakefulness and sleep disorders are closely linked to daytime sleepiness, there are great interindividual differences in susceptibility to sleepiness. Accumulating evidence shows that excessive sleepiness is heritable–5. In modern society, nearly one-fifth of employees are involved in long-term night shift. As a result, work performance and scheduling have a significant impact on individual variability in diurnal preference. Studies also indicate that diurnal preference  is heritable–9. In addition, usual weekday sleep duration plays a critical role in daytime sleepiness. It has been investigated whether short or long sleep duration has been related to coronary heart disease, diabetes mellitus–12, hypertension, and mortality. Likewise, usual day sleep duration is heritable.Sleepiness impairs social function, reduces quality of life and causes occupational and motor vehicle accidents–18, but the functions of these SNPs remain undefined, which is a challenge in interpreting GWAS results. Thus, pathway-based approaches were optimized gradually, and the Identify Candidate Causal SNPs and Pathways (ICSNPathway) was created to determine potential SNPs and hypothetical mechanisms through GWAS data, using linkage disequilibrium (LD) analysis, functional SNP annotation and pathway-based analysis (PBA). Herein, we used bioinformatics methods combining ICSNPathway analysis and HapMap database to identify candidate SNPs and relevant pathways, aiming to develop SNP-gene-pathway hypotheses regarding circadian phenotypes.To date, several single nucleotide polymorphisms (SNPs) associated with circadian phenotypes in some genes were detected from three genome-wide association studies (GWASs)P<0.001). During data extraction, discussion with a third author (YW) helped resolve the discrepancies, with consensus on each item reached in the end. After extracting data from the original papers and contacting the corresponding authors, we ruled out the studies without details as needed.We applied publicly available databases to identify eligible GWASs on circadian phenotypes, which are the National Human Genome Research Institute GWAS catalog (http://www.genome.gov/26525384), the National Center for Biotechnology Information (NCBI) dbGap (http://www.ncbi.nlm.nih.gov/gap/), and the GWAS central . In addition, both EMBASE and PUBMED databases were searched with the following key words: “GWAS” or “genome-wide association study” and “circadian”. All searches were completed up to April 20th, 2016 without language limitation. In order to reduce the effect of genotyping errors, two independent authors (DZ and JYuan) filtered the primary GWAS data set and removed individuals with a call rate<95%, minor allele frequency<0.01, and deviating from the Hardy-Weinberg equilibrium (HWE) test  and positioned in the flanking region (with up to 500 kb upstream and downstream) . The extended dataset including HapMap data (http://hapmap.ncbi.nlm.nih.gov) was utilized to obtain more possible candidate SNPs. Additionally, to gain LD structures, we used SNAP dataset (http://www.broadinstitute.org/mpg/snap/). The other method involves the functional annotation on the SNPs by searching the international SNP function annotation databases, including PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/), Ensembl database (http://www.ensembl.org), SNPs3D (http://www.snps3d.org), and SIFT (http://sift.jcvi.org).ICSNPathway analysis was conducted in two consecutive stages. In the first stage, the candidate SNPs were pre-selected by LD analysis and functional SNP annotation with . Besides, the data of corresponding mRNA expression was acquired from lymphoblastic cell lines of the 270 individuals mentioned above, which was extracted from SNPexp (http://app3.titan.uio.no/biotools/help.php?app=snpexp/).Genotypic frequencies of candidate SNPs was extracted from the International HapMap Project , consisting of 3.96 million SNP genotypes from 270 subjectsP-value and a FDR  were calculated.During the second stage, PBA algorithm was employed to annotate biological pathways of selected SNPs by integrating data from four databases, including BioCarta (http://www.biocarta.com), MsiDB (http://www.broadinstitute.org/gsea/msigdb), Kyoto Encyclopedia of Genes and Genomes  and gene ontology . Furthermore, SNP label normalization and permutation were adopted to correct gene variations and generate the distribution of significant proportion based enrichment score (SPES).According to the distributions of SPESs, a nominal t test. Furthermore, one way ANOVA was utilized to assess the difference of transcript expression levels in more than two genotypes. The statistical analysis was performed with SPSS version 21.0. P values<0.05 were considered statistically significant.The expression levels were shown as mean±SEM, and the difference between two genotypes was evaluated by two-side Student's  with publicly available summary data after a thorough search. In the GWAS on circadian phenotypes, totally 749 subjects were collected from the Framingham Offspring Study containing 2848 participants who accomplished sleep habit questionnaires between 1995 and 1998 (Offspring Examination Cycle 6) for the Sleep Heart Health Study. For usual weekday bedtime, 65,514 candidate causative SNPs were originally generated with an Affymetrix 100K SNP Gene Chip, and afterwards 47,285 SNPs passed the quality control filters which were employed for ultimate bioinformatics analysis. Besides, for usual weekday sleep duration, 65,514 SNPs were generated with the gene chip, while 47,301 SNPs met the quality control criterions and were then applied for subsequent analysis.One GWAS drawn from NCBI dbGap (study accession: phs000007) was finally adopted in our studyTable 1, totally four SNPs in three genes were determined to correlate with usual weekday bedtime, namely, MT-ND5 rs10517616, GRSF1 rs3775728, and ENAM rs7671281, rs3796704 polymorphisms. Moreover, eleven SNPs in six genes were identified to correlate with usual weekday sleep duration, namely, HSPD1 rs8539, APOBEC2 rs2076472, GRSF1 rs3775728, TTN rs9808377, rs1001238, rs2042995, rs3829746, rs2042996, CENPE rs2243682, rs2615542 and SLC17A1 rs13213957. Of note, GRSF1 rs3775728 was linked with both usual weekday bedtime and usual weekday sleep duration. SNP rs3775728 was in LD with rs2278134 (r2=1.0) ; rs7671281 and rs3796704 were in LD with rs2553319 ; rs9808377, rs1001238 and rs2042995 were in LD with rs3829746 ; rs2243682 and rs2615542 were in LD with rs2290943 ; SNP rs13213957 was in LD with rs3734523 (r2=0.828). Except for a repeated SNP, fourteen regional LD plots are shown in Fig. 1. As presented in Table 2. However, the SLC17A1 rs13213957 polymorphisms might tend to affect the mRNA expression levels of SLC17A1 , which is consistent with the functional class indicated in Table 1. In addition, the functions of the corresponding proteins were examined, which demonstrated that all SNPs could cause residue change except for HSPD1 rs8539, summarized in Table 3. In addition, MT-ND5 rs10517616 was not estimated here because no data was available publicly.Then, we examined the roles of different genotypes in mRNA expression levels via HapMap c-DNA expression database which was publicly available. No significant association between all SNPs with the mRNA expressions of corresponding genes was found in Caucasians as presented in Table 4. The first mechanism involved MT-ND5 rs10517616 polymorphism (nonsynonymous coding) in pathways such as NADH dehydrogenase activity , respiratory electron transport chain , oxidoreductase activity , and oxidative phosphorylation . The second was GRSF1 rs3775728 polymorphism (nonsynonymous coding) in mRNA binding pathway . The third one included ENAM rs7671281, rs3796704 polymorphisms (nonsynonymous coding) in pathway of biomineral formation .During the ICSNPathway analysis, six pathways about usual weekday bedtime were detected and are summarized in Table 4 similarly. The first was HSPD1 rs8539 polymorphism (nonsynonymous coding) in the unfolded protein binding pathway . The second one was APOBEC2 rs2076472 polymorphism (nonsynonymous coding) in pathway of mRNA processing . The third mechanism involved GRSF1 rs3775728 polymorphism (nonsynonymous coding) in pathways containing mRNA processing , RNA processing , and mRNA binding . The fourth pathway consisted of TTN rs9808377, rs1001238, rs2042995, rs3829746, rs2042996, and CENPE rs2243682, rs2615542 polymorphisms (nonsynonymous coding) in cell cycle . The last one was SLC17A1 rs13213957 polymorphism (regulatory region) in the anion transport pathway .In the ICSNPathway analysis of usual weekday sleep duration, six pathways were found and are presented in . GWASs are limited to detect single SNP associations and identify new loci, so we applied a pathway-based pattern to take the biological interplay between multiple genes into consideration, and propose novel views into how genes might help the development of circadian phenotypes.A compound molecular network may make a significant contribution to the development of circadian phenotypes, containing several cellular pathways. It was reported that NADH promoted the transcription of the lactate dehydrogenase (LDH) gene under redox state. This is based on the activation of E-box by binding heterodimer Bmal1/NPAS2, the master brain clock to regulate circadian rhythmicity[. The second candidate gene GRSF1 found in this study and previous studies has been implied in the pathway of mRNA binding through SNP rs3775728–35. The third biological mechanism involves the modulation of ENAM by rs7671281 and rs3796704 to affect its role in mineral formation–37. The forth one involves the influence of rs8539 on HSPD1 in unfolded protein binding. The fifth involves the modulation of APOBEC2 by rs2076472 to affect mRNA processing. The sixth involves the modulation of TTN by rs9808377, rs1001238, rs2042995, rs3829746, and rs2042996 as well as CENPE by rs2243682 and rs2615542 to influence its role in cell cycle. The seventh involves the modulation of SLC17A1 by rs13213957 to affect anion transport–41, which could influence the mRNA expression of SLC17A1.In this study, we applied ICSNPathway analysis to identify six potential regulating mechanisms, respectively, in usual weekday bedtime and sleep duration. The most significant SNP-to-gene-to-effect hypothesis was that rs10517616 changes the feature of MT-ND5 in NADH dehydrogenase activity. Thus, the results received in our study might help the development of novel hypotheses for the further investigations.As far as we know, these mechanisms of circadian phenotypes, including MT-ND5, GRSF1, ENAM, HSPD1, APOBEC2, TTN, CENPE and SLC17A1, have been firstly identified in our study. The ICSNPathway analysis has been conducted to identify candidate causal genes relevant to disease-related phenotypes such as rheumatoid arthritis, which may limit the application to the whole populations and weaken the authority to identify the candidate SNPs. Secondly, with no study supplying strong supports for these results, the candidate SNP-gene-pathways should be verified in more studies.Even though the abovementioned biological mechanisms may affect circadian phenotypes, several limitations should be acknowledged. Firstly, the data was obtained from only 749 subjectsIn short, our results demonstrated fifteen candidate SNPs in eight genes , which participate in six hypothetical pathways involved in usual weekday bedtime and six potential pathways implicated usual weekday sleep duration. However, further investigations are warranted to validate the identified genetic variations in the biological pathways related to circadian phenotypes.


MSTN, SOD2, MC5R and CD83, which are responsible for economic traits including lean muscle mass, fertility and immunization. Overall, this study found a series of candidate genes putatively associated with the breeding improvement of Duroc pigs and the polygenic basis of adaptive evolution, which can provide important references and fundamental information for future breeding programs.Identifying genetic basis of domestication and improvement in livestock contributes to our understanding of the role of artificial selection in shaping the genome. Here we used whole-genome sequencing and the genotyping by sequencing approach to detect artificial selection signatures and identify the associated SNPs of two economic traits in Duroc pigs. A total of 38 candidate selection regions were detected by combining the fixation index and the Composite Likelihood Ratio methods. Further genome-wide association study revealed seven associated SNPs that were related with intramuscular fat content and feed conversion ratio traits, respectively. Enrichment analysis suggested that the artificial selection regions harbored genes, such as  Duroc, an older breed of domestic pig, was developed in America and formed the basis for many mixed-breed commercial boars after a long period of artificial selection. It is predominantly used as the terminal sires in pig industry, and is well known for its superior performance in growth, feed conversion efficiency, carcass and meat quality traits . The artIn general, most of the economic traits in commercial animals are quantitative and controlled by many genes with small effects  content is one of the most important factors affecting pork quality. Based on marker-assisted selection, there is increasing interest in mapping some of the causal genes of IMF for its genetic improvement (ST), were applied to detect selection signatures. In addition, we also carried out GWAS to identify the key genes related with IMF and FCR that were changed during the breeding improvement of Durocs. We found strong signatures of selection left in Durocs during breed formation exemplified by several striking selective sweeps overlapping with some major QTLs. The results would provide useful information for those who are interested in further understanding the genetic basis of important commercial traits, and facilitate future breeding of Durocs to improve these traits through genomic selection.In this study, we used paired-end Illumina sequencing to resequence the genomes of four purebred Durocs and used the genotyping by sequencing approach to characterize the genomes of 282 individuals from the same population. To identify the signatures of artificial selection, sequences from 23 purebred Durocs, 21 Asian wild boars (AWB), and 25 European wild boars (EWB) were downloaded from the most advanced publically available database. Two different statisticses, the Composite of Likelihood Ratio (CLR) and the fixation index  approved by the Standing Committee of Hubei People’s Congress and the ethics committee of Huazhong Agricultural University in P. R. China. In addition, all experiments were performed in accordance with approved relevant guidelines and regulations.https://www.ebi.ac.uk/), including 23 Duroc pigs, 21 Asian wild boars and 25 European wild boars (Supplementary Table S1). Quality control of sequence data applied the following criteria: reads with (i) > 10 bp aligned to the adapter with up to 10% mismatches, (ii) up to 10% unidentified nucleotides (N), (iii) > 50% bases having a phred quality less than 5 were removed, and (iv) Duplicate reads generated by PCR amplification in the library construction process were also removed.In this study, genomic DNA was extracted from ear tissues of each of 286 purebred Duroc pigs using a standard phenol-chloroform method. Among them, four individuals were selected to sequence the whole genomes. Paired-end sequencing libraries with an insert size around 350-bp were constructed for each sample. 2×150-bp paired-end sequencing was performed on an Illumina HiSeq X-ten platform at the BGI-Huada Genomics Institute in Shenzhen. The rest of individuals were genotyped by sequencing (GBS) on an Illumina HiSeq 2000 platform in Buckler Lab for Maize Genetics and Diversity at Cornell University  using the Burrows-Wheeler Aligner (BWA) software . The refP < 10e–6). To decrease the influence from genotype imputation, only SNPs with the missing ratio of samples within each population < 20% were used to detect selection signatures. Beagle software was used to impute the missing genotypes and infer haplotypes with default settings  coverage depth ≥ 4, (ii) RMS mapping quality ≥ 20, (iii) the distance of adjacent SNPs ≥ 5 bp, (iv) the missing ratio of samples within each population < 50%, and (v) the minor allele frequency (MAF) ≥ 0.01 were kept for further analysis. The SNPs that were used for GWAS need further apply quality control of Hardy–Weinberg equilibrium  with the gene-based annotation modules of ANNOVAR (r2) for every pair of SNPs to measure the LD level in Duroc pigs and two wild boar populations using PLINK . To identify artificial selection signatures, AWB and EWB were defined as the reference population, respectively.ST statistic for pairwise sites between the observed populations and the reference population  to 1 (complete differentiation). To produce comparable CLR and FST test results, single site scores for FST were averaged in non-overlapping windows of 25 kb resulting in a total of 90,322 and 90,411 FST scores across the genome when AWB and EWB were defined as the reference population, respectively. The empirical P-values were generated by genome wide ranking of FST and CLR values  .=u+Ss+Xb+Wα+ey, where y is the phenotypes vector, u is the intercept, S is a design matrix of the fixed effects, s is the batches effect, b is the SNP effect, X is a design matrix for allele dosages for the imputed SNPs, W is an incidence matrix linking α to y, α is the additive genetic effect ∼ N , where б2a is the additive genetic variance and G is the realized genomic relationship matrix that was estimated using genotype information, and e is the random residual term. To avoid double fitting of SNP effects efficiently, the test SNP and the other SNPs in the same chromosome were removed in constructing the G matrix each time based on the standardized relatedness matrix in GEMMA  based on the SimpleM method was used to account for multiple tests in this analysis. A total of 4,853 independent tests were identified here that was in turn inferred by the number of principal components accounting for a 99% of the variance of the SNP matrix , and then an enrichment analysis, which included the terms cellular component (CC), molecular function (MF), biological process (BP), and pathway analysis was performed for the identified genes using DAVID 6.7 (http://david.abcc.ncifcrf.gov/) . Genes located in putatively selected regions were identified using the BioMart program (https://figshare.com/s/e45cc6d717cd498d5013). Supplemental material available at Figshare: https://doi.org/10.25387/g3.7077125.The Illumina sequence reads are available in the NCBI Sequence Read Archive under the accession SRP158574. Supplemental files, the GBS data and phenotype data can be downloaded from Figshare . Correspondingly, a total of 70 fragments, spanning lengths of 81.40 Mb and covering 3.3% of the genome, were identified as CRSs in Duroc pigs . Collectively, a total of 38 CASRs, spanning lengths of 40.48 Mb and covering 1.62% of the genome, were identified in Duroc pigs through compared with the wild populations . In addition, we further check genotype-class frequencies and phenotypic means for seven significant SNPs. As shown in Supplementary Table S7, we can clearly observe the trend of phenotypic changes with three genotypes. The results suggested that the SNPs passing the less conservative significance threshold are still promising in this study.https://www.animalgenome.org), we found that these four SNPs were also overlapping with ‘the drip loss’ and ‘the stearic acid content’, respectively . Among them, one possible positional candidate gene, insulin like growth factor 2 receptor (IGF2R), serves IGF2 turnover in IGF signal mediated process  .Among them, a set of genes overlapping artificial selection regions were enriched for the ability of immunity, which mainly included ‘GO:0042267∼natural killer cell mediated cytotoxicity’ (6 genes), ‘GO:0019882∼antigen processing and presentation’ (6 genes) and ‘hsa04650:Natural killer cell mediated cytotoxicity’ (6 genes) (Supplementary Table S9). Additionally, we also found one significant candidate artificial selection regions that overlapped with feration . Due to P-value coincide with a cluster of genes involved in meat quality, growth, fertility and so on (MSTN gene, which was associated with lean muscle mass and played an important role in the process of muscle development (WNT9A gene associated with chondrogenesis and CMYA5 gene associated with carcass length and meat quality were overlapping with the strong selection signatures. MC5R gene, an established sweep in previous studies, was found close to the 97.625-98.725 Mb regions on SSC6, which was not only associated with back fat thickness but also played an important role in proinflammatory activity (HOMER1 gene that is overlapped with the 86.55-92.75 Mb artificial selection regions on SSC2 is associated with muscle differentiation and calcium homeostasis (SOD2, JMY, NDC80 and CASP1, overlapping with artificial selection regions in this analysis were associated with the reproductive traits. In comparing with its wild ancestors, litter size, fetal weight and the other fertility traits would change for adapting human-driven selection. These results indicated that the improvement of fertility and other complex traits may due to the polygenic basis, rather than be caused by only a few critical loci.In addition to those significant Go and Pathway terms, a set of artificial selection signatures with extreme nd so on . An inteIn summary, this study detected signatures of artificial selection and identified a number of loci associated with some important economic traits, like IMF and FCR, which provided an important resource in future Durocs breeding programs. SNP annotation implied that there was no predictable distribution in where those artificial selection regions were located in genome. Enrichment analyses suggested that the polygenic basis may be a reasonable explanation for the phenomenon, that many different genes associated with the economic traits have often been selected during the improvement and breed formation. The application of combining sweep analysis and genome-wide association analysis are effective in mapping commercial important genes, especially to the data with small sample size caused by the expensive measurement traits.