Cashmere goats are a unique husbandry resource in China. These goats are well known for producing the highest cashmere yield and best fiber quality in the world. Although cashmere is highly valued and also known as “fiber gem” and “soft gold”, few studies have examined the genetic basis of cashmere traits in cashmere goats. Here, we identified selection signals by comparing Fst and XP-EHH (the cross population extend haplotype homozygosity test) of a non-cashmere breed (Huanghuai goat) with those of two cashmere breeds (Inner Mongolia and Liaoning cashmere goats). Two genes (WNT10A and CSN3) were potentially associated with cashmere traits. This information may be valuable for studying the genetic uniqueness of cashmere goats and elucidating the mechanisms underlying cashmere traits in cashmere goats.Fst and XP-EHH. The top 5% of SNPs had selection signatures. After gene annotation, 222 and 173 candidate genes were identified in Inner Mongolia and Liaoning cashmere goats, respectively. Several genes were related to hair follicle development, such as TRPS1, WDR74, LRRC14, SPTLC3, IGF1R, PADI2, FOXP1, WNT10A and CSN3. Gene enrichment analysis of these cashmere trait-associated genes related 67 enriched signaling pathways that mainly participate in hair follicle development and stem cell pluripotency regulation. Furthermore, we identified 20 overlapping genes that were selected in both cashmere goat breeds. Among these overlapping genes, WNT10A and CSN3, which are associated with hair follicle development, are potentially involved in cashmere production. These findings may improve molecular breeding of cashmere goats in the future.Inner Mongolia and Liaoning cashmere goats in China are well-known for their cashmere quality and yield. Thus, they are great models for identifying genomic regions associated with cashmere traits. Herein, 53 Inner Mongolia cashmere goats, Liaoning cashmere goats and Huanghuai goats were genotyped, and 53,347 single-nucleotide polymorphisms (SNPs) were produced using the Illumina Caprine 50K SNP chip. Additionally, we identified some positively selected SNPs by analyzing  Cashmere goats produce cashmere  from theLHX2, FGF9 and WNT2) were identified [FGF5) [FGF5, SGK3, IGFBP7, OXTR and ROCK1) [With the development of high-throughput technology, association studies between genetic diversity and phenotypes can be carried out at the genome level. Selection of a trait could be traced by detecting selection signatures in a genome, and the relevant genes can be identified by selection signal analysis . Recentlentified . Guan etd [FGF5) . Li et ad ROCK1) . Despited ROCK1) .Fst and Cross Population Extend Haplotype Homozygosity Test (XP-EHH) analyses, relevant genes correlated with Cashmere traits were identified based on selection signals. Fst, which is based on allele frequency difference, can identify candidate genes between populations, and it is widely used because of its simplicity [Fst to eliminate false positives and improve signal analysis accuracy [Fst and XP-EHH to detect genes and merged the genes to identify the strongest selection signature by Fst and XP-EHH. These finding will provide a further theoretical basis for research on the formation mechanism of Cashmere and protection of local goat resources. Additionally, some important genes related to Cashmere traits were identified that can be used to enrich the gene pool of candidate Cashmere goats. Here, we compared Inner Mongolia and Liaoning Cashmere goats with the Huanghuai goats. Based on mplicity . XP-EHH accuracy . TherefoCapra falconeri [All experimental procedures involving goats were approved by the Science Research Department  of the Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (IAS-CAAS) . Ethical approval on animal survival was given by the animal ethics committee of IAS-CAAS . In this study, 53 individuals of three goat breeds were collected from conservation farms or core areas of origin and including 17 Inner Mongolia Cashmere goats (MGR), 20 Liaoning Cashmere goats (LNR) and 16 Huanghuai goats (HHG) . The Casp < 10−6; (ii) SNP call rate > 90%, (iii) SNP minimum allele frequency (MAF) > 0.01 and (iv) presence of mapped autosomal loci.To increase the data processing accuracy, stringent quality control criteria were applied. SNPs were removed if they could not pass the following four criteria: (i) Hardy_Weinberg equilibrium https://www.rdocumentation.org/packages/ggplot2) [https://sourceforge.net/projects/tassel/) [https://itol.embl.de/upload.cgi) [Principal component analysis (PCA) was performed using PLINK1.90 to discern genetic relationships among breeds . The graggplot2) . A neightassel/) . The N-Joad.cgi) . In addioad.cgi) . The coroad.cgi) . Fst and XP-EHH values between the Cashmere and non-Cashmere goats detecting selection signals among genome-wide SNP genotypes [Fst and XP-EHH values. Two approaches were used to identify selection signatures in the domestic goat genomes. First, the genomic regions with strongly differing or differentially fixed variants in alleles frequency between different breeds were identified by the population differentiation index (Fst), which is the conventional measure of population genetic differentiation. We calculated Fst value for each SNP as Fst = MSP is the mean square error within the populations, MSG represents the mean square error between the two populations, and cn represents the average sample size of the entire population after correction [To detect the potential mechanisms underlying Cashmere traits, we searched for autosomal SNPs that showed evidence of specific selection by comparing enotypes ,25. We crrection ,27.an and An are the numbers of alleles a and A haplotypes, respectively; in is the number of the ith haplotype in a population, and hx represents the number of different haplotypes in a genomic region at locus X. The integral domain D  was selected, so that the EHH values of both populations were reduced to sufficiently small values [Furthermore, we also computed the XP-EHH values using haplotype information in the XP-EHH program  to deterl values .Fst and XP-EHH values (top 5% level). Based on the goat reference genome annotation, the 50-kb upstream and downstream regions of significant SNP loci were operationally defined as candidate regions under selection. Genes were identified by these different methods and annotated using the goat genome information database. Gene function was determined using the National Center for Biotechnology Information database (https://www.ncbi.nlm.nih.gov/) and by literature search. We selected some significant genes associated with Cashmere trait submitted to the DAVID database (http://david.abcc.ncifcrf.gov/) for Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis [Capra hircus. Significantly enriched pathway was indicated by Q-value < 0.05.We defined candidate selection SNPs as those that fell into the upper 95th percentile of the empirical distribution with extremely high analysis . The selAfter data quality control, 45,575 SNP markers were passed through filters and quality control. The individuals were representative of six native goat breeds in China: MGR, LNR, HHG, DYG, CDM and LLG (north to south) a. AccordFst revealed a high coefficient of genetic differentiation, and has been widely used to identify selection signals among whole-genome SNPs [Fst for each SNP and ultimately annotated 1907 (Fst > 0.2878) and 1821 genes (Fst > 0.3248) in MGR and LNR, respectively. XP-EHH was also calculated for each SNP [ome SNPs ,34. We cFst > 0.38 in MGR  Fst > 0.78 and 18COL5A2, WNT10A, CSN3, SPTLC3, LRRC14, TRPS1 and WDR74 were associated with Cashmere traits. PADI2 WNT10A, CSN3, IGF1R and FOXP1 were identified in LNR . The KEGG pathway analysis revealed that the genes associated with the significantly correlated SNPs were highly enriched in 67 pathways  and secondary WNTs (WNT0A and WNT10B) are essential for hair follicle initiation, morphogenesis and development. CSN3(casein kappa) represents one of the most important proteins that determine the manufacturing properties of milk [CSN3 has other plausible biological functions related to Cashmere traits, and may be involved in regular hair follicle development [STAT5 activation acts as a mesenchyme switch to trigger natural anagen entry in post-developmental hair follicle cycling. STAT5 deletion results in significantly upregulated expression of genes, such as CSN3, Dkk3 and Dlk1, which inhibit WNT and Notch signaling. Alternatively, WNT6, FGF7 and FGF10, known regulators of anagen induction/progression, were all significantly downregulated [CSN3 also has an important role in hair follicle development, although the precise function of CSN3 relative to Cashmere traits remains unknown and should be verified in future studies. Detection of selection signals associated with economic traits has been successfully implemented in several livestock species, such as cattle , pigs 3, sheep  and hors20 genes . The gene family ,40,41,42e family . WNT sige family ,45. Moreelopment . Thomas elopment  demonstr of milk . Howeverelopment ,50. STATegulated ,50. TherDiarrhoea, which is a major impediment to profitable hair goat production in many countries as it predisposes animals to blowfly strike and contaminates wool [Haemonchus contortus is a bloodsucking parasite that causes an extreme stress on animals that are already protein deficient owing to the requirements for hair growth, especially in hair goat. Ectoparasites also can inflict serious damage in the hair and pelts of goats, such as Bovicola  caprae, the biting louse of goats, which is the most serious external parasite in hair goats. Economic losses are realized by hair damage occurring when goats bite or rub themselves to relieve itching [PADI2 is predominantly in skeletal muscle and belongs to PAD, which is responsible for the formation of protein-bound citrulline, a major amino acid in the inner root sheath and hair follicle medulla [FOXP1 is crucial for maintaining quiescence of hair follicle stem cells. FOXP1 loss in skin epithelial cells leads to precocious stem cell activation, which results in a drastic shortening of the quiescent phase of the hair cycle [TRPS1 [WDR74 and WNT10A were related to hair follicle morphogenesis [LRRC14 regulates hair follicle induction [In mammals, coat hair protects against environmental changes . Mohair tes wool . Haemonc itching . In addi itching . Genetic itching . Candida medulla . FOXP1 iir cycle . In addiir cycle . A previe [TRPS1 , which iogenesis , and LRRnduction  and inhinduction ; therefonduction . IGF1R was identified in Liaoning Cashmere goats; this gene regulates the anagen phase by activating BMP4, which affects the stem cell bulge and hair follicle cycle [FGF18 can prevent the hair follicle stem cells of FOXP1 null mice from being prematurely activated. As FGF18 controls telogen phase length and is a key downstream target of FOXP1, FOXP1 regulates the telogen stem cell state in the hair follicle stem cell niche by controlling FGF18 expression [TRPS1 directly represses expression of the hair follicle stem cell regulator Sox9 to control follicle epithelium proliferation [In general, the secondary follicle cycle can be divided into three periods: anagen (April–November), regression (December–January the following year), and telogen (from February to March the following year) . In the le cycle . Moreovepression . TRPS1 dferation , and plaferation .KEGG pathway analysis revealed that some important pathways were remarkably enriched for Cashmere traits. The hair follicle is a unique mini organ that self-renews throughout its lifetime. Many stem cell populations reside within human hair follicles and enable their regeneration . Stem ceCSN3 may have a novel selection signal associated with goat Cashmere production. However, no clear main effect genes for Cashmere growth have been found. Our research enriches the candidate gene pool for elucidating the mechanisms underlying Cashmere traits and provides an important basis for protecting and sustainably using Cashmere goats. However, further study is needed to fully understand Cashmere production in Inner Mongolia and Liaoning Cashmere goats.We conducted a comprehensive study to identify selection signatures in Cashmere and non-Cashmere goats based on Illumina Caprine 50K SNP chip data. Our results showed that a high degree of genetic diversity was present in our goat samples, and many important genes and pathways related to Cashmere traits could be targeted for trait improvement. We found that


Drosophila melanogaster. Our approach combines an Illumina shotgun library, Oxford nanopore long reads, and chromosome conformation capture for long range scaffolding. This single fly genome assembly has a N50 of 26 Mb, a length that encompasses entire chromosome arms, contains 95% of expected single copy orthologs, and a nearly complete assembly of this individual's Wolbachia endosymbiont. The methods described here enable the accurate and complete assembly of genomes from small, field collected organisms as well as precious clinical samples.A high quality genome assembly is a vital first step for the study of an organism. Recent advances in technology have made the creation of high quality chromosome scale assemblies feasible and low cost. However, the amount of input DNA needed for an assembly project can be a limiting factor for small organisms or precious samples. Here we demonstrate the feasibility of creating a chromosome scale assembly using a hybrid method for a low input sample, a single outbred  The creation of high quality genome assemblies is a key step for the study of organisms on both the level of individuals and populations . ConventTwo recent advances in genomic technologies have dramatically raised the quality of genome assemblies . First, Genome projects can be complicated by the small size of many organisms, which yield corresponding low amounts of DNA from a single individual. Consequently it is not always feasible to obtain sufficient input material for the genomic approaches described above without pooling individuals . Nonetheet al. released a whole-genome assembly obtained from a single mosquito, Anopheles coluzzii, sequenced using three PacBio SMRT Cells  beads at 0.7 beads:1 sample ratio and eluted in 25 ul ultrapure water.End repair and A-tailing was performed using NEBNext Ultra II End Repair/dA-Tailing Module followed by ligation of Nextera adapters using NEB Blunt/TA Ligase Master Mix following the manufacturer's protocol. The adaptor ligated sample was purified by SPRI beads at a 1:1 ratio and eluted in 50 ul of ultrapure water. The sample was divided into six, 25 ul PCR reactions with Nextera primers and KAPA HiFi Readymix 2× . The PCR reactions were pooled and purified by SPRI beads at a 1:1 ratio and eluted in 60 ul of ultrapure water. Concentration was measured to be 110 ng/ul using the Qubit dsDNA HS assay. The entire sample was size selected by gel electrophoresis using a 1% low melting agarose gel. An area from 6–10 kb was cut out and digested using NEB Beta Agarase I following the manufacturer's protocol then purified using SPRI beads at a 1:1 ratio.One hundred nanograms of size selected DNA was mixed with 50 ng of a DNA splint and circularized by Gibson assembly using 2× NEBuilder HiFi DNA Assembly Master Mix incubated for 60 min at 50°C. Non circularized DNA was digested overnight at 37°C using Exonuclease I, Exonuclease III and Lambda Exonuclease . Circularized DNA was purified by SPRI beads at a 0.8:1 ratio and eluted in 40 ul of ultrapure water.The circularized DNA was split into 8 50 ul rolling circle amplification (RCA) reactions (5 ul 10× Phi29 buffer (NEB), 2.5 ul 10 mM dNTPs (NEB), 2.5 ul 10 uM exonuclease resistant random hexamer primers (Thermo), 5 ul DNA, 1 ul Phi29 polymerase (NEB), 34 ul ultrapure water). Reactions were incubated overnight at 30°C. All reactions were pooled and debranched using T7 Endonuclease (NEB) for 2 h at 37°C. To shear ultra-long RCA products the sample was run through a Zymo Research DNA Clean and Concentrator-5 column and eluted in 40 ul ultrapure water. A final size selection was performed by gel electrophoresis using a 1% low melting agarose gel. An area at approximately 10 kb was cut out and digested using NEB Beta Agarase I following the manufacturer's protocol then purified using SPRI beads at a 1:1 ratio.The cleaned and size selected RCA product was sequenced using the ONT 1D Genomic DNA by Ligation sample prep kit (SQK-LSK109) and a single MinION flow cell following the manufacturer's protocol. The raw data was basecalled using the Guppy basecaller. Consensus reads were generated by Concatemeric Consensus Caller with Partial Order alignments (C3POa).The anterior half of the fly was placed into a 1.5 ml tube with 1 ml of cold 1× PBS. 31.25 ul of 32% paraformaldehyde was added. The sample was briefly vortexed and incubated for 30 min at room temperature with rotation. After incubation the supernatant was removed and washed twice with 1 ml of cold 1× PBS. 50 ul of lysate wash buffer was added before grinding with pestle. 5 ul of 20% SDS was added then vortexed for 30 s and incubated at 37°C for 15 min with shaking. 100 ul of SPRI beads were added to bind chromatin. Bound sample was washed 3 times with SPRI wash buffer.Beads were resuspended in 50 ul of Dpn II digestion mix  and digested for 1 h at 37°C with shaking. Beads were washed twice with SPRI wash buffer and resuspended in 50 ul of end fill-in mix  then incubated for 30 min at room temperature while shaking. Beads were washed twice with SPRI wash buffer and resuspended in 200 ul of intra-aggragete mix  then incubated at 16°C overnight while shaking. Beads were placed on a magnet to remove supernatant then resuspended in 50 ul of crosslink reversal buffer  then incubated for 15 min at 55°C, followed by 45 min at 68°C while shaking. Beads were placed on a magnet and the supernatant was transferred to a clean 1.5 ml tube. 100 ul of SPRI beads were added to the supernatant and allowed to bind before washing twice with 80% ethanol and eluting sample with 50 ul of 1× TE buffer.The sample was then fragmented by sonication. Fragmented sample was end repaired and adapter ligated using the NEBNext Ultra II kit following the manufacturer's protocol. The sample was purified from ligation reaction by SPRI beads, washed twice with 80% ethanol, and eluted in 30 ul of 1× TE. Biotin tagged fragments were enriched using streptavidin C1 Dynabeads. Enriched fragments were indexed by PCR  and amplified for 11 cycles. Reaction was purified by SPRI beads and quantified using the Qubit dsDNA HS Assay Kit and the Agilent TapeStation.de Bruijn graph algorithm, Meraculous   to map tThe draft assembly went through a total of four iterative rounds of polishing using the automated software tool Pilon using default settings. For each round the short and long-read data was mapped to the draft assembly using minimap2. After each round, the assembly was evaluated for misassemblies, indels, mismatches, N50, and assembly size using QUAST  to deterTo evaluate the completeness of the H3 assembly we searched for conserved genes using Benchmarking Universal Single-Copy Orthologs v3, (BUSCO) with the metazoa odb9 lineage gene set . To compDrosophila melanogaster reference using Minimap2 with default parameters and sam output  processes these raw reads and generates two types of output reads: (i) consensus reads are generated if an ONT raw read is long enough to cover an insert sequence more than once which is evaluated by detecting a splint sequence in the raw read and (ii) regular ‘1D’ reads for which no splint could be detected in the raw read. In total, 277 305 consensus reads and 1 769 380 ‘1D’ reads were generated from a single ONT MinION flow cell. Both read types were included in the assembly. We additionally produced an Illumina sequencing library using a standard Tn5-based protocol  and from this we obtained 133 135 777 total paired-end reads  from which we obtained a scaffold N50 of 26 Mb. Our final scaffolded assembly contains all the major chromosome arms in the wolbachia contigs), which presumably reflects the success in our polishing and gap filling by incorporating additional sequences.Because we combined diverse data types, and in particular because our primary assembly relies on error-prone long reads, we sought to polish the contigs and fill gaps in the final highly contiguous assembly. In total we performed four rounds of iterative polishing with Pilon , see Mat. The finD. melanogaster ISO1 reference BUSCO score of 98.9%, but it is not dramatically different. We therefore conclude that the majority of the expected genic sequences are complete in our assembly.We assessed our final assembly quality using several metrics. First, we applied the Benchmarking Universal Single-Copy Orthologs, BUSCO, algorithm . BrieflyD. melanogaster strain, A4  of 0.00sensu , which hsensu ,31. The Although not a primary consideration in this work, we found that our assembly captures additional material that is potentially of interest and underscores the power of our approach. First, our selected individual was phenotypically female, nonetheless, we discovered a non-trivial rate of Y-chromosome mapping contigs. Importantly, we found a similar Y-mapping rate in all three raw sequencing datasets , and theWolbachia, as we used this as the female parent in the cross Wolbachia is present in our sample due to infected embryos. Despite the differences in read-depths relative to the nuclear genome, our assembly includes nearly full coverage of the Wolbachia genome with few apparent misassemblies , and age insect .Recent advances in technology have greatly increased the quality of genome assemblies but generally require a relatively large DNA input. This limitation reduces the applicability of these methods for many precious, rare, and/or field collected specimens. Here, from a single fly we were able to construct a chromosome scale genome assembly with an N50 of 26 Mb. The primary assemblies were made with less than 90 ng of total input DNA. Therefore, our approach demonstrates that high quality chromosome-scale assemblies can be obtained from limited sample inputs.Our method also compares favorably for total cost outlay. The DNA isolation and library preparation involves only basic molecular biology methods and equipment. We produced all necessary sequencing data on approximately one half of a HiSeq 4000 lane and a single MinION flow cell. We can therefore produce a contiguous, high quality genome for approximately $1,200 in total materials and reagent costs. For cost effectiveness, our approach compares quite favorably with available alternatives such as Pacbio SMRT cells at $2,000 each.There are many genome assembly approaches available, and ours may not be optimal for all applications. When input materials are severely limited, the approach we describe here provides an appealing set of trade-offs and may be the only option to produce highly contiguous genome assemblies. Indeed, we have been able to make R2C2 libraries with as little as 10 ng of input DNA. Nonetheless, if more DNA is available, recent advances in PacBio library preparations  might bePerhaps the most fundamental concern for the suitability of our approach is the researcher's specific questions and motivations for making a genome. Applications that require high contiguity in an assembly would be enhanced significantly using this approach. For example, association studies and quantitative trait locus mapping approaches generally require knowledge of large-scale linkage among sites to be successful . SimilarThis approach can serve as a guide point for genome projects of small organisms which make a large majority of the diversity of life. Approximately 80% of known species are insects, and ∼5 million total insect species are believed to exist on earth . Additiohttps://www.ncbi.nlm.nih.gov/bioproject/) under accession number PRJNA591165.The sequencing data and final assembly generated in this study has been submitted to the NCBI BioProject database (gkaa450_Supplemental_FileClick here for additional data file.


Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China.At present, there are few studies on polymorphism of The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed.p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots . Three genomic clusters, each with genomic distance ≤12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots.As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8%  of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area. Mycobacterium tuberculosis (Mtb) of different molecular types have different transmission capacities, pathogenicity and drug resistance rates [It is widely recognized that ce rates , 2. Therce rates , 4. Guance rates . Howeverce rates . Some en6110 restriction fragment length polymorphism (RFLP), spoligotyping, and variable-number tandem repeat (VNTR) typing [Whole genome sequencing (WGS) was employed in this study because it provided a powerful tool for phylogenetic analysis and epidemiological tracing than other conventional methods such as IS) typing –11. Sing) typing . HoweverBased on the above reasons, this study was conducted to 1) document the differences of Mtb polymorphisms (SNP) between hot and cold spot areas, 2) identify Mtb genotype with high level of local transmission and 3) analyse the relationship between different level of SNP variations and geographic distribution of the Mtb isolates.A case-only study in the TB notification hot and cold spot areas of Guangxi was performed from January to June 2018.Based on the spatial clustering analysis, three counties (C1-C3) with significantly high TB notification were identified as hot spots, and three counties C4-C6) with significantly low notification rate were identified as cold spots [ with sigThe sample size of this study was calculated based on the formula of two independent proportions comparison . AccordiEligible index TB cases must have been a resident in the study sites for at least 2 years prior to TB diagnosis. Isolates from individuals who were unable to communicate with investigators and children under the age of five were excluded.At the GXCDC, Mtb DNA extraction was conducted by a genetic sample kit . At Zeta Biosciences (Shanghai), a WGS kit was employed to obtain enough nucleic acid for the sequencing of the downstream analysis. Each sample was quantified by Qubit 2.0 Fluorometer . Next generation sequencing library with 350-base-pair (bp) paired-end preparations were constructed for each purified DNA sample according to the manufacturer’s criterion (Illumina TruSeq DNA Nano Library Prep Kit). Then libraries with different indices were multiplexed and loaded on an Illumina HiSeq instrument with an expected coverage of 100 following the manufacturer’s instructions . After analyzing a short sequence alignment of the Mtb according to the reference genome H37Rv, multiple sequence alignment test strains of SNPs/InDels were used to obtain the corresponding molecular classification . A BurroFst value from Analysis of Molecular Variance (AMOVA) by reducing the matrix dimensions. Clustering of isolates were analyzed based on several levels of SNP distances starting from 12 as generally done but were also done at the SNP distances of 24, 48 and 96, and so on. Isolates with less than 12 SNP distances were considered as recent epidemiologically linked. Clusters of isolates with higher distances were analyzed in regard to geographical proximity. Cluster of isolates having SNP difference within each of these cut points were identified and checked to see whether all clusters members were from the same county, or area (Hot and cold spots). Rank-sum test, a non-parametric analysis, was employed to compare the median of pairwise SNPs distance between two groups.Epi Data (v 3.1) was used for double entering the data at regular intervals while R (v 3.3.2) was used for epidemiological data management and analysis. MEGA-X (v 10.0.5) and Fig Tree (v 1.4.4) were used to build phylogenetic trees with color labels. Multidimensional scaling model (MDS) was employed to test the between and within group of differentiation After excluding 13 participants , a total of 147 isolates from hot spots and 144 from cold spots were included for further analysis. Their phylogenetic trees are shown in Fig. p = 0.022). Compared with the hot spots, the isolates from the cold spots are more genetically diverse. There was no significant difference of Beijing family percentages between the counties in each spot (p = 0.361 and 0.482).Table As shown in Fig. p = 0.05).The Multidimensional Scaling analysis was used to compare the Fst of tuberculosis strains across six counties as shown in Fig. p < 0.001). This is consistent with the higher transmission activities in the hot spot.Among 42,195 pairs of SNPs difference, the shortest distance between these stains is 7 SNPs, and the longest distance pair was 1893 SNPs. The average distance was 703 SNPs. Figure p < 0.05).Table This study identified the molecular biological characteristics of Mtb in different TB epidemic areas of southern China. Only two major lineages (L2 and L4) were found in this study setting. The predominate Mtb strain is lineage 2.2 (Beijing family), and it was significantly higher in TB notification hot spots. Through the population gene structure analysis (AMOVA) and SNPs comparison between cold and hot spots and the multidimensional scaling modeling of each county, we found that the two spot areas had some differences in genetic structure, and the spatial internal consistency was relatively high. Specific SNPs sites between the cold and hot spots with high Fst estimation mapped to special proteins that may contribute to the pathogenicity differences in Mtb. Three genomic (SNPs ≤12) and geographic groups were detected and identified as Mtb recent transmission individuals.Mtb among human originated in Africa and was divided into seven lineages by several thousand years of mutations [Mtb genotype becomes more and more obvious. Therefore, as a southern province of China, Guangxi has more proportion of Ancestral Beijing strains and genetic diversity of Mtb strains than that in northern region [Previous studies have suggested that utations –21. The utations . Althougutations . Moreoven region . The orin region . In thisn region . Thus, in region . Among tn region . Stucki n region . Yet, thIn this study, by comparing all the gene loci of the cold and hot spots strain, it was found that the two populations had mutation differences in some special regulatory proteins. The mutation of Rv1186c (PruC) has a certain significance. Mtb is an obligate aerobic bacterium that needs oxygen to grow. However, paradoxically, it shows a remarkable metabolic flexibility that allows itself to survive and metabolize in oxygen-deprived conditions . It has Mycobacterium tuberculosis many years ago, and the strains might have mutated after a long time of latent infection, proliferation and then endogenous reactivation. Thus, the SNPs distance between the two strains would become larger. Our study also performed contact tracing among included cases [As the dominant genotype, Beijing family strains have been shown to cluster more frequently . This sued cases . The resEither the spreading of the Mtb was local or there were some socioeconomic factors that hinder the transmission between the hot and cold spot areas. Our previous studies on the ecology of tuberculosis suggested that there is a negative correlation between average sunshine time and reported incidence of tuberculosis . TherefoMeanwhile, sub-lineage 2.1 (Protobeijing strain), a special subgroup related to drug resistance, is mainly concentrated in hot spots. Since it has been reported that the virulence and drug resistance of Beijing gene strain is greater than other strains , 40, 41,The limitation of this study is that the sputum isolates were collected mainly from passively detected cases in the public hospital. This may have contributed to the fact that some specimens of the TB cases treated in private practice were not included during the study period, which caused the bias to some extent. However, as TB case management strategies become more widely publicized under the national TB control programme, this impact should diminish , 43. TheMtb genotype distribution is associated with TB incidence. Hot spot area in Guangxi is associated with Beijing family predomination. Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area. These findings demonstrate that promotion of the genetic diagnosis in tuberculosis clinics and early identification of Beijing family strain should be considered in tracking and stopping TB transmission.Additional file 1: Supplementary Table 1. Genetic clustering based on the SNPs (≤12)


Soybean is an important source of protein, oil and carbohydrates, as well as other beneficial nutrients. A major function of proteins in nutrition is to supply adequate amounts of amino acids. Although they are essential for human nutrition, the sulfur-containing amino acids cysteine (Cys) and methionine (Met) are often limited and the genetic control of their content in soybean seeds is poorly characterized. This study aimed to characterize the phenotypic variation and identify quantitative trait loci (QTL) associated with Cys and Met content in a core set of 137 soybean lines, representative of the genetic diversity among Canadian short-season soybean, spanning maturity groups 000-II (MG000-II). Significant phenotypic differences were found among these lines for Cys, Met and Cys + Met content. Using both a mixed linear model and six multi-locus methods with a catalogue of 2.18 M SNPs, we report a total of nine QTLs and seventeen QTNs of which seven comprise promising candidate genes. This work allowed us to reproducibly detect multiple novel loci associated with sulfur-containing amino acid content. The markers and genes identified in this study may be useful for soybean genetic improvement aiming to increase Cys and Met content. Glycine max (L.) Merr) is a legume species native to East Asia and now widely planted for its edible bean, which plays an essential role in global food security1. Although soybeans are classified as an oilseed with 18–23% oil on a moisture-free basis, its increased production worldwide can be attributed also to its high protein content ranging 38–44%2. Soybean seed proteins are categorized as either albumins or globulins based on their solubility patterns3. The main storage protein is comprised of the globulin fraction, accounting for roughly 70% of the total seed protein. The 7S (β-conglycinin) and 11S (glycinin) polypeptides are the major components of the globulin fraction. This fraction provides 18 amino acids, including all 10 essential amino acids, but the sulfur-containing amino acids cysteine (Cys) and methionine (Met) are not present at adequate levels for optimal growth and development of monogastric animals4.Soybean , developing soybean varieties with improved cysteine and/or methionine content is an important breeding objective to address soybean nutritional limitations8. Understanding the precise genetic architecture of these traits and identifying key genes controlling the accumulation of these protein fractions or amino acids would be an important step in this direction. So far, fifteen genes encoding β-conglycinins (CG1–CG15) and five genes (Gy1–Gy5) encoding glycinins have been reported10 (http://www.soybase.org/).Cysteine and methionine contribute highly to human health and animal nutrition by preventing cancer, the development of cardiovascular diseases and promoting proper function of the immune system6. Only a few studies have reported quantitative trait loci (QTL) associated with cysteine and methionine content in soybean seed . Qiu et al.11 predicted 12 candidate genes based on the synteny between 113 genes from a gene mining of sulfur-containing amino acid metabolic enzymes in soybean. These authors also identified many QTLs related to the 7S (β-conglycinin), 11S (glycinin) fractions and Cys/Met content soybean on chromosomes 1, 3, 4, 6, 10, 13, 16, 17, 19 and 20. From linkage mapping, Panthee et al.6 reported a total of seven QTLs associated with Cys, Met and Cys + Met content across five chromosomes  in a population of 101 F6-derived recombinant inbred lines (RILs) (N87-984-16x TN93-99). Using the same population, Panthee et al.12 reported three QTLs associated with glycinin , on chromosomes  respectively, whereas two QTLs were detected for conglycinin (Satt461 and Satt249) distributed on chromosomes 17 and 16. From a bulked segregant analysis in the F2 mapping population derived from the cross of Harovinton and SQ97-0263_3-1a, Boehm et al.13 reported one QTL on chromosome 10 associated with the 7S α′ subunit and five QTLs associated with 11S A-type storage protein subunits respectively on chromosomes . Fallen et al.14 detected two QTLs on chromosomes (Gm13 and 20) associated with both Cys and Met content in progeny of Essex x Williams 82 (282 F5:9 RILs). All these QTLs were reported as a result of QTL mapping in biparental populations and resulted in a poor overlap between the QTLs/QTNs reported in these studies. This is not unexpected since in biparental populations only two sources of allelic variation are evaluated. Moreover, the major limitation of this approach is that they offer poor resolution in detecting QTLs15 and the large confidence intervals surrounding the detected QTLs limits their utility for identifying candidate genes16.Seed content in sulfur amino acids has been shown to be quantitatively inherited and controlled by multiple genes17. In GWAS, we evaluate the association between each genotyped marker and a phenotype of interest that has been scored in a large number of unrelated individuals18. A GWAS can be achieved using a single-locus method where markers are tested individually in a one-dimensional genome scan like the Mixed Linear Model (MLM19) or using a multi-locus method where effects of all potentially associated markers are simultaneously estimated in a multi-locus genetic model such as the multi-locus random-SNP-effect Mixed Linear Model (mrMLM20). Furthermore, the use of next-generation sequencing in the context of GWAS makes it possible to genotype larger populations of plants with a higher density of markers than was previously possible and this contributes directly to increasing GWAS resolution.Population-based mapping approaches such as genome-wide association studies (GWAS) can overcome many of these shortcomings of the biparental mapping approach17 performed a GWAS on two different panels (IL-1996 and MS-1997), exploiting data from the Germplasm Resources Information Network . The IL-1996 panel was composed of 900 cultivars belonging to maturity groups (MGs) III and IV, while the MS-1997 panel was composed of 978 cultivars from MGs V through IX. All the lines were genotyped using the SoySNP50K iSelect Array17 to produce a total of 32 K SNPs with a minor allele frequency (MAF) ≥ 0.05. This allowed these authors to identify a total of fourteen QTLs across 10 chromosomes .With a single-locus approach, Vaughn et al.21 used both MLM and a Multi-Locus Mixed Linear Method (MLMLM) to conduct a GWAS for soybean seed components  on 313 plant introductions (PIs). These accessions belonged to MGs 0 (92%) and 00 (8%) and 91% originated from China. They were genotyped with the SoySNP50K Array and a total of 32 K SNPs with MAF ≥ 0.05 were used for association analyses. Only one QTL on chromosome 15 was associated with both cysteine and methionine. Using the same approach, Song et al.19 conducted a GWAS using phenotypic data collected from five environments for 621 accessions in maturity groups I–IV and 34,014 markers genotyped with the SoySNP50K array to identify one QTL on chromosome 3 and three , respectively, associated with cysteine and methionine.Recently, Lee et al.None of the previous work resulted in the identification of highly promising candidate genes that could be targeted by breeders for developing cultivars with increased content in sulfur-containing amino acids.19) and six multi-locus GWAS methods  were used. Here, we report a total of nine QTLs detected by the MLM method and seventeen major QTNs detected by at least two of the six multi-locus method located on 12 soybean chromosomes. In addition, seven strong candidate genes based on their high degree of association and functional annotation were identified.Thus, to obtain a comprehensive understanding of the genetic architecture of Cys and Met content in soybean seeds, we used a core set of 137 Canadian soybean lines grown on two sites and four replicates in total. The best linear unbiased predictor (BLUP) value of each line and a set of 2.18 M SNP markers [obtained from a combined dataset of genotyping-by-sequencing (GBS) and whole-genome sequencing (WGS)] were used to identify marker-trait associations. Both a single-locus method  for the sulfur amino acid content than the site. A high broad-sense heritability was observed and ranged from 49 to 62%.In view of performing a GWAS, we obtained phenotypic data for the sulfur amino acid content (g/kg TP) on a set of 137 soybean lines by growing single-row plots on two sites (two replicates/site) in 2013. The frequency distributions for Cys, Met and Cys + Met contents are presented in Fig. p < 0.001). The Pearson correlation coefficients between these traits ranged from 0.81 to 0.97  were successfully mapped onto the Wm82.a2.v1 reference genome. A total of 56 K high-quality SNPs were obtained and so called «GBS-derived SNP». To obtain an extensive SNP coverage of the genome, we used a two-step approach to genotype the 137 lines of this association panel Fig. . In a fi2 ≤ 0.5), the optimum number of subpopulation (k) was 7  of SNP markers and a single phenotypic value (BLUP) for each trait were used.To identify genomic regions associated with the seed content in sulfur amino acids, a genome-wide scan was performed using a MLM and six multi-locus models implemented in the mrMLM package v4.0. A pruned set  at the most extreme values . The results of these MLM association analyses are presented as genome-wide Manhattan plots in Fig. p-values ranging from 1.37E−05 to 1.82E−09. There were 41 markers (0.02%) significantly associated with Met content  and 71 SNPs (0.03%) with Cys + Met content  as uncorrected p-values.For the MLM analyses, as can be seen in the Q–Q plots shown in Fig. 27. For SNPs associated with more than one trait, the most significant SNP  was retained to mark a given haplotype block. In total, nine haplotype blocks  varied between 15 and 27%. The magnitude of allelic effects were calculated according as per Kang et al.28 and varied between 0.12 and 0.42 g/kg TP.To identify distinct QTLs, we characterized haplotype blocks formed by these associated SNPs according to Gabriel et al.From the multi-locus analyses, ~ 0.01% of the SNPs  were significantly associated with Cys, Met and Cys + Met content, respectively. The LOD score of these associated SNPs ranged from 3.26 to 17.65 for Cys, 3.05 to 18.98 for Met and 3.04 to 13.15 for Cys + Met content. Across the six multi-locus methods . In total, seventeen QTNs/haplotype blocks were identified in this fashion including three QTNs codetected by both MLM and multi-locus methods  the associated SNP was detected by at least two multi-locus methods and (ii) explained at least 5% of the phenotypic variance (Rds Table . In mostEach dot indicates the degree of association between a single marker and a trait (y-axis) while the x-axis shows the physical position of each marker. A blue horizontal bar indicates the significance threshold (FDR ≤ 0.05) and significantly associated markers are coloured in green. The red numbers (from 1 to 9) identify the different QTLs based on the haplotype blocks formed by the significantly associated markers. The pink vertical stripes highlight QTLs that were common to all three traits and the black arrows indicates the overlapped QTL between MLM and multi-locus methods.p < 0.006) in the mean Cys content between lines carrying contrasting alleles in at least one of the three validation trials. Six out of eight QTLs were validated in at least two trials and five QTLs were validated in all three trials. For Met, of the four QTLs discovered initially, all four were validated (p < 0.01) in all trials. For Cys + Met, all seven QTNs were validated (p < 0.007) in at least one trial, six were confirmed in at least two trials and five were validated in all three trials  did not produce a significant phenotypic contrast between lines carrying alternate alleles at these loci Table . Thus, wTo establish a list of candidate genes, all genes residing within one of the haplotype blocks identified by MLM or the multi-locus methods (ranging in size between 5 and 376 kb) were extracted from SoyBase and their GO annotations examined. The number of genes per haplotype block varied between 1 and 32, and the full list of these genes and their annotations are provided in Table Five other candidate genes were identified within four haplotype blocks identified only by the multi-locus methods and correspond to QTNs #1, #10, #11 and #14 Table . Among tTwo other candidate genes, Glyma.04g237300 and Glyma.16g032200, had an annotation indirectly associated with the methionine biosynthesiss. They were located 43 kb and 23 kb uptream of the peak SNPs  and , respectively. Glyma.04g237300 was annotated to have a spermidine synthase activity and found among 21 other genes in a 243-kb haplotype block while Glyma.16g032200 was located in a 56-kb haplotype block containing 6 genes and is annotated as being involved in ethylene biosynthetiss.We then investigated the expression profile of these seven candidate genes. Based on previous transcriptomic analyses, these genes (except Glyma.08g367600) were known to be mainly expressed in young leaves, flowers and roots but also expressed in pods 7 days after flowering (DAF), pod shells (10–13 DAF) and in seeds (14–17 and 35 DAF) as illustrated in Figs. Top panel constructed from MLM results shows the Manhattan plot for the marker-trait associations showing the region of interest in light orange on Gm20. The blue horizontal line represents the FDR threshold (FDR ≤ 0.05). The central panel shows the position and orientation of all ten gene models present in the haplotype block (bottom panel). The most likely candidate gene  is highlighted with a red asterisk and is 45 kb and 35 kb upstream of the MLM peak SNP  and the multi-locus peak SNP , respectively. The extent of LD is indicated as D′ × 100. The purple squares indicate no LD (D′ = 0) while empty red squares indicate complete LD (D′ = 1).Given the availability of WGS data for 56 lines of our association panel, we looked for structural or nucleotide variation within the eight candidate genes identified previously. No structural variants > 51 bp were identified in any of the candidate genes within these 56 lines. We also examined if SNP variants within coding regions could impact gene function. In total, 49 nucleotide variants were identified within coding regions of seven candidate genes. All of these variants were predicted as having a “low” to “modifier” effect. As such, we do not consider these variants to be likely causal.3 reported 14.8 to 16 g/kg and 13.9 to 14.7 g/kg for Cys and Met content. Song et al.19 reported 12.1 to 14.5 g/kg and 11.5 to 13.7 g kg respectively for Cys and Met contents. However, in terms of range, the results reported here correspond most closely to those reported by3 . Moreover, similarly to previous studies, high and positive correlations (0.81 to 0.97) were seen between cysteine, methionine and the total sulfur amino acid contents. It has been suggested that the high phenotypic and/or genotypic correlations between cysteine and methionine contents are due to a shared biosynthetic pathway or a similar molecular basis of inheritance30.Normal distributions were observed for all the traits  and suggested that these traits are controlled by polygenes. The phenotypic variation ranged from 13.5 to 15.0 g/kg for Cys and from 12.6 to 13.6 g/kg for Met content. The total sulfur amino acid content Cys + Met varied from 26.0 to 28.5 g/kg on the basis of total protein. The observed phenotypic values reported in this study were slightly lower but similar in range to those reported in previous studies when similarly expressed in terms of g of amino acid per kg of total protein. Warrington et al.For marker-trait association analysis, a total of 243 K SNP markers and a single phenotypic value for each line (BLUP) was used in two GWAS approaches (one single-locus (MLM) and six multi-locus  methods). In all cases, we incorporated population structure and family relatedness to control for confounding effects. We reported a total of nine QTLs/haplotype blocks associated with the sulfur amino acid content detected by an MLM approach and seventeen major QTNs detected by at least two of the six multi-locus methods. Interestingly, three chromosomal regions were detected using both approaches. Among MLM-derived QTLs, one third of these SNPs were significantly associated with all three traits.Importantly, approximately two thirds of these QTLs proved extremely robust as they could be successfully confirmed in three additional trials. This suggests that these individual markers would provide a good tool for breeders interested in using marker-assisted selection (MAS) to improve Cys and/or Met content within this germplasm. In contrast, however, the QTNs uncovered in the multi-locus analysis could not be validated in the same fashion. One must keep in mind though that these QTNs were discovered in a model based on the joint consideration of these loci whereas our validation experiment was based on the consideration of loci individually. This may have contributed to our inability to confirm the impact of the QTNs on these traits. Nonetheless, in the context of MAS, it is likely that these QTN would not prove useful; these might be better captured in a genomic-selection scheme relying on a wider set of loci and allowing for multi-locus contributions to the phenotype.31 to 1417 in GWAS studies while 214 and 8 QTLs32 were reported following family-based mapping. As we observed here, a subset of QTLs were common to both cysteine and methionine content31 and, in one case, all the QTLs (eight) were associated with both cysteine and methionine content32. This is unsurprising given the high degree of correlation between these traits and the fact that both amino acids share the same biosynthetic pathway with cysteine being a precursor of methionine production33.In previous mapping work, the total number of QTLs associated with cysteine and methionine content varied from 132 reported one QTL Cys 3–7 located from 3.0 to 35.9 Mb on chromosome 20 associated with seed cysteine content. Moreover, this genomic region fell within QTL qMet_Gm20 and qCys + Met_Gm20 (24.5 to 34.7 Mb) reported by Warrington et al.3 associated with Met and Cys + Met content. Interestingly, this genomic region overlapped with QTL #8 from MLM analysis and QTN #16 from multi-locus analysis located on chromosome 20 at 31.8 Mb. Similarly, Ramamurthy et al.34 reported one QTL on chromosome 20 flanked by BARC-038869–07364 and BARC-039753–07565 (36.5 to 39.8 Mb) simultaneously associated with both seed Cys and Cys + Met content, an interval within resides a second codetected QTL, (QTL/QTN #9/#17 for MLM/ multi-locus) on chromosome 20 .To compare the genomic regions reported by previous studies with the QTLs reported in this study, we used SoyBase to define the physical position of previously reported QTLs. Two of the three QTL/QTN codetected by both approaches in this study fell within genomic intervals identified in previous biparental mapping work. Indeed, Wang et al.35 were located within 500 kb of those reported in this study. Except for the work of Zhang et al.31 in which only one QTL was reported, all other GWAS studies have been conducted within later maturity groups (MG I—IX) and the limited overlap in QTLs could be attributed to differences in the loci controlling these traits within the different maturity groups.None of the seven other QTLs that we reported from MLM analysis in this study coincided with previously reported QTLs intervals identified in family-based mapping. Similarly, none of the QTLs reported by previous GWAS studies12. Interestingly, Ma et al.36 reported two QTLs significantly associated with glycinin and beta-conglycinin content on chromosome 10 (174 kb and 2.7 Mb) and 20 (34.6 to 37.8 Mb) a genomic region spanning QTL #5 and #9 reported in this study (Gm10 at 1.8 Mb) and (Gm20 at 37.0 Mb) significantly associated with all three traits.Considering that sulfur amino acids are components of protein fractions, notably the glycinin (11S) and conglycinin (7S) storage proteins, one might expect that genomic regions reported as significantly associated with sulfur amino acid content also be associated with the abundance of 11S and 7S, which together constitute nearly 70% of total storage proteins in the soybean seed11 to be significantly associated with cysteine content (flanked by BARC-042289-08234 and BARC-045205-08910).For the multi-locus analyses, we reported a total of seventeen QTNs across twelve chromosomes including three shared regions with the MLM method. Across the traits, three QTNs were detected for all three traits. Two QTNs were shared by two trait pairs (one each for Cys/Met and Met/Cys + Met content). Four (Cys), three (Met) and five (Cys + Met) were unique to a single trait. Similar to the QTLs discovered via MLM, very little overlap was observed between previously reported QTLs and the multi-locus QTNs identified in this study. Among the seventeen QTNs, QTN #10 located on chromosome 13  coincided with one QTL reported by Qiu et al.36 that were significantly associated with seed glycinin, beta-conglycinin and seed glycinin to beta-conglycinin ratio content across three chromosomes .Four of the QTNs reported in this study  were significantly associated with all three traits and these coincide with three broad genomic regions reported by Ma et al.The peak SNPs associated with sulfur amino acid content reside in the nine and seventeen haplotype blocks identified through MLM and multi-locus analysis within which one would expect to find the causal genes that control Cys and Met content in this collection of soybean lines. Of the genes located within these haplotype blocks, seven stood out as promising candidate genes based on their GO annotations.38.Of these seven candidate genes, only Glyma.20g129700 was identified using both MLM and multi-locus analysis and encodes a 5-methylthioribose kinase protein. This protein was demonstrated to be a primary enzyme involved in the recycling of the methylthio group of 5-methylthioribose back into methionineA second promising candidate gene identified using MLM, Glyma.08g367600, encodes a protein that is predicted to have an oxido-reductase activity acting on NAD(P)H. Although the annotation for this gene indicates a role in sulfur amino acid metabolism, we have not been able to pinpoint the precise role of the protein encoded by this gene in sulfur amino acid metabolism. Moreover, no information from previous studies or transcriptomic data was available for this gene. Its role in the metabolism of sulfur amino acids needs to be confirmed.11, the spermidine synthase encoding gene was found in association with eleven other genes to contribute 6–38.5% of the genetic variation of sulfur-containing amino acids.Among the five other candidate genes identified from multi-locus analysis, Glyma.04g237300 was annotated as a spermidine synthase and said to be involved in methionine synthesis in plants. From the work of Qiu et al.39.Glyma.13g108800 encode a stress-responsive alpha–beta barrel protein and is thought to be involved in both cysteine and methionine synthesis under stress conditions. Cysteine-containing molecules like glutathione and thioredoxin play a major role in maintaining an intracellular reducing environment and protecting the cell from oxidative damagel-methionine salvage cycle II (in plants). The ortholog of this gene corresponds to the A. thaliana AT3G61510.1 locus, encoding an ACC synthase 1. In plants, the methionine is a precursor of ethylene synthesis. Therefore, this biosynthetic pathway is directly connected to the methionine cycle41.Glyma.16g032200 encodes a protein that is involved in ethylene biosynthetis and in the Although Glyma.14g003200 and Glyma.14g003400 were both annotated as being involved in cysteine biosynthesis, again, no direct link was found between these genes and cystheine biosynthesis through previous studies.As none of the SNPs located inside the coding region of our candidate genes were predicted to cause a functional change, it is likely that the alleles of this gene differ in expression, thus resulting in the observed differences in sulfur-containing amino acids. Taken together, these data strongly suggest that the phenotypic variation observed in this collection of Canadian lines is due to variants located outside the coding region that likely result in differences in gene expression.42. Plant research material was originally provided by four breeding programs, respectively CÉROM at St-Mathieu-de-Beloeil (QC), Agriculture and Agri-Food Canada at Ottawa (ON), University of Guelph (ON) and Semences Prograin Inc at St-Césaire (QC). These lines were grown in field trials conducted on two research farms, namely Woodstock  and St-Mathieu-de-Beloeil  in Canada in 2013. The experimental design was a generalized lattice in which all lines were planted in either 4-m rows with 50-cm spacing or 6-m rows with 30-inch spacing in Woodstock and St-Mathieu-Beloeil, respectively, with two replicates at each site.A set of 137 lines thought to constitute a core set representative of the extent of genetic diversity among soybean varieties belonging to maturity group 000-II ( MG000-II) in Canada was selected from a larger group of 304 accessions based on the analysis of population structure as previously described in43. Descriptive statistical analysis and a mixed linear model were used to determine genotypic variance, environment and genotype × environment effects as well as a Shapiro–Wilk test for normal distribution of the phenotype. The two sites were considered as two environments and all effects were assumed random, the broad-sense heritability for a given trait across the two environments was calculated as follows:nrep is the number of replicates. Restricted maximum likelihood was used to estimate the BLUP to provide a single value for each variety. Pearson’s pairwise and genetic correlations among the traits were estimated using META-R, the genetic correlation was calculated using equations from Cooper and Delacy44j and j′ , For sulfur amino acid content for both mapping and validation population, 25-g samples (from each replicate) of whole seeds were analyzed using near-infrared spectroscopy . The NIR used was calibrated according to manufacturer’s calibration module based on set of 2646 samples. After sample scanning, the concentration of sulfur amino acids was expressed on the basis of the dry matter percentage. Each value was then normalized per kg of total protein (g/kg TP). Three traits were considered in the ensuing analyses: cysteine content (Cys), methionine content (Met) and the sum of both (Cys + Met). Statistical analyses on amino acid content data were performed using META-R42. Briefly, DNA extraction was performed using the Qiagen DNeasy 96 Plant kit, The ApeK1 restriction enzyme was used for library preparation as per45. These archived reads were processed anew to benefit from an improved SNP-calling pipeline (Fast-GBS46) and a more recent annotation of the soybean genome Wm82.a2.v147. Genotypes were called using a minimal read depth of two reads and loci with more than 80% missing data were removed. Imputation was first performed on this catalogue of 56 K GBS-derived SNPs using BEAGLE v548 to fill in any missing genotypes. We then used a set of 4.3 million SNPs derived from the whole-genome sequencing of 102 Canadian elite soybean lines49 as a reference panel to impute all missing loci onto the initial catalogue of GBS-derived SNPs, again using BEAGLE  ≥ 0.05 and heterozygosity ≤ 0.1, thus producing a catalogue of 2.18 M SNPs.A total of ~ 203 million 100-bp Illumina HiSeq2000 single-end reads derived from sequencing 192-plex GBS libraries were available for the 137 lines as described previously byGLE Fig. . Among t2 > 0.5) using PLINK52 to obtain a set of 14 K markers. Population structure was characterized using fastSTRUCTURE53 with the number of subpopulations (K) being set from 1 to 12 with 3 independent runs of each. The most likely K value was determined using a python script (“choosek”) implemented in fastSTRUCTURE based on the rate of change in LnP between successive K values. In order to better support the number of sub-populations, we used two additional tools: (i) a bootstrap consensus phylogenetic tree (2000 replicates) was constructed using the maximum likelihood method based on the Tamura-Nei model implemented in MEGA754; and (ii) a principal component analysis (PCA) was performed using GAPIT55.The resulting marker dataset was pruned by excluding SNPs in moderate linkage disequilibrium (LD) (r28) as covariates. To distinct different QTL/QTN, significantly associated SNPs from the same genomic region were grouped together to form haplotype blocks, as per the LD-based method27, using the complete 2.18 M SNP catalogue. To be chosen as a haplotype block of interest, a block had to contain at least one peak SNP significantly associated with sulfur amino acid content. The extent of each block was used to retrieve all genes and their annotation.Genome-wide association between markers and the phenotypes was assessed in GAPIT and mrMLM R package v4.0 using a catalogue of 243 K SNPs and the best linear unbiased predictors (BLUP) values for each trait. Two GWAS approaches included one single-locus methods (MLM) and six multi-locus  methods were used. For significant SNP markers detection, a significant threshold, FDR ≤ 0.05 and LOD ≥ 3 were used, respectively for MLM and multi-locus methods. To account for population structure and genetic relatedness between the lines, we used the Q matrix obtained from fastSTRUCTURE and a K matrix  for soybeans was used to identify in what tissues and at which developmental stages candidate genes were expressed  alleles among the list of candidate genes by inspecting the catalogue of structural variants reported by Torkamaneh et al.57 and by examining the predicted impact of the full set of nucleotide variants located within genic regions using SnpEff 58. The search for such LOF alleles was limited to the 56 lines for which WGS data were available.Only genes residing within haplotype blocks containing a peak SNP were extracted from SoyBase and were examined for their GO annotations. In order to provide more information about potential candidate genes, the electronic fluorescent pictograph (eFP) Browser (Supplementary information 1.Supplementary information 2.Supplementary information 3.


The human body is exposed to oxidative damage to cells and though it has some endogenous antioxidant systems, we still need to take antioxidants from our diet. The main dietary source of antioxidants is vegetables due to their content of different bioactive molecules. However, there are usually other components of the diet, such as foods of animal origin, that are not often linked to antioxidant capacity. Still, these foods are bound to exert some antioxidant capacity thanks to molecules released during gastrointestinal digestion and gut microbial fermentation. In this work, the antioxidant capacity of 11 foods of animal origin has been studied, submitted to different culinary techniques and to an in vitro digestion and gut microbial fermentation. Results have shown how dairy products potentially provide the highest antioxidant capacity, contributing to 60% of the daily antioxidant capacity intake. On the other hand, most of the antioxidant capacity was released during gut microbial fermentation . Finally, it was found that the antioxidant capacity of the studied foods was much higher than that reported by other authors. A possible explanation is that digestion–fermentation pretreatment allows for a higher extraction of antioxidant compounds and their transformation by the gut microbiota. Therefore, although foods of animal origin cannot be compared to vegetables in the concentration of antioxidant molecules, the processes of digestion and fermentation can provide some, giving animal origin food some qualities that could have been previously unappreciated. Global concern about the increased incidence of chronic diseases such as diabetes, obesity, cancer, and cardiovascular disease has led to paying greater attention to lifestyle habits, especially diet . On the Vegetables’ content in phytochemicals has been pointed out as one of the reasons behind their beneficial effect against such chronic diseases. Many of these compounds have shown great antioxidant activity and thus the potential to play a beneficial role in oxidative stress-related diseases such as cancer, cardiovascular diseases, or type 2 diabetes mellitus ,5. At thOn the other hand, undigested food passes into the large intestine, where it can be used by the gut microbiota as a fermentation substrate; such undigested food can produce compounds with biological and antioxidant activity . TherefoAccordingly, the aim of the present paper was to study the antioxidant capacity of animal origin foods, representing the main dietary categories. Different heat treatments were applied, and then they were in vitro digested and fermented. Next, the contribution of the consumption of animal origin foods to the daily intake of antioxidant capacity in Spain was calculated. Finally, the overall daily antioxidant capacity intake in Spain was calculated, also taking into account the antioxidant capacity of plant foods previously studied . Cysteine, sodium di-hydrogen phosphate, sodium sulphide, resazurin, salivary α-amylase, and pepsin from porcine bile acids (porcine bile extract) were provided by Sigma-Aldrich . Pancreatin from porcine pancreas was provided by Alpha Aesar .DPPH , hydrochloric acid, iron (III) chloride hexahydrate, methanol, sodium acetate, TPTZ -s-triazine) and Trolox ((±)-6-Hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid) were provided by Sigma- Aldrich .Eleven animal foods were investigated belonging to the following groups: dairy, egg, fish, and meat . Animal The foods were submitted to different culinary treatments: boiling, frying, grilling, or roasting . Some ofThe utensils used for sample preparation were the following: a transportable oven (1500 W), fryer, frying pan and saucepan and forks, knives, spoons, and stainless steel. All these utensils were purchased from Centro Hogar Sánchez . Samples were homogenized and stored under nitrogen atmosphere at −80 °C in order to avoid oxidation. All analyses were carried out in duplicate.w/v) composed of salts and α-amylase (75 U/mL). The mix was kept at 37 °C for 2 min in oscillation. Right after, 10 mL of simulated gastric fluid was added, simulating the gastric juices content in salts and pepsin (2000 U/mL). The mix was kept at 37 °C for 2 h, at pH 3 in oscillation. Finally, 20 mL of simulated intestinal fluid was added, simulating the intestinal juices content in salts, bile salts, and enzymes . The mix was kept at 37 °C for 2 h, at pH 7, in oscillation. Once the intestinal phase was finished, tubes were kept in ice to stop enzymatic reactions and thereafter centrifuged at 3500 rpm for 10 min. The supernatant, which represents the fraction available for absorption in the small intestine, was stored in 1 mL tubes at −80 °C until analysis. The solid pellet, which represents the not digested fraction that goes into the large intestine, was used as in vitro fermentation substrate. Samples were subjected to an in vitro gastrointestinal and to an in vitro fermentation according to the protocol previously described , in tripThe in vitro fermentation was carried out using fecal samples from five healthy donors with no previous pathology, who had not taken antibiotics for three months prior to the assay, with a mean (Body Mass Index = 21.3). Individual diets were not assessed since the objective was not to evaluate microbial communities but rather to unravel the potential antioxidant power that average people could extract from animal origin foodstuffs. The fecal samples were pooled together to reduced inter-individual variability. The fermentation was carried out at 37 °C for 20 h. Once the in vitro fermentation was finished, tubes were kept in ice to stop microbial reactions and thereafter centrifuged at 3500 rpm for 10 min. The supernatant, which represents the fraction available for absorption in the large intestine, was stored in 1 mL tubes at −80 °C until analysis. The solid pellet, which represents the fraction not fermented and excreted with feces, was appropriately discarded. Therefore, two fractions were obtained after in vitro gastrointestinal digestion and fermentation: digestion supernatant , and fermentation supernatant (fraction for absorption in the large intestine). Antioxidant capacity was measured in both fractions, considering as total antioxidant capacity the sum of them. Antioxidant capacity of those two fractions was studied. The total antioxidant capacity of the two fractions was taken as the amount of total antioxidant capacity exerted by a given food. . DPPH assay .TEAC The method was based on the protocol of Rapisarda et al. [a et al.  and adjuFRAP assay TEAC. The method followed the protocol of Benzie and Strain [d Strain  to measuThe contribution of each food group to daily dietary antioxidant capacity intake was calculated based on the amount of food per serving, the daily intake , and thep < 0.05). As issue for ANOVA, it had been used form of cooking , sort of food  and sort of sample . Statistical analysis was performed by using boiled or raw foods and mean of all food groups because the reference groups. Pearson parametric statistic was calculated to indicate the lineal relation between antioxidant capacity at a p value < 0.05. To get the significance between the various levels among an equivalent group, the Tukey test was assigned. All the statistical analyses were performed by using Statgraphics Plus software, version 5.1.The statistical significance of the results was checked by one-way analysis of variance (ANOVA) and subsequently by the Duncan test  and after fermentation (antioxidant capacity available for absorption in the large intestine). Two different antioxidant assays were applied. All antioxidant capacity values were corrected, taking into account the antioxidant capacity provided by enzymes, chemicals, and fecal inoculum.p < 0.005), with Spearman’s rank correlation coefficient (rs) around 0.8.In addition, a linear correlation was obtained by the Spearman method between the two methods. The correlation was significant  lower antioxidant capacity than all types of cooking, except for UHT, which was not significant  lower in UHT foodstuffs than that of raw foods, but no significance was found for the other types of cooking  for fried foods, being more antioxidant than raw foods.Regarding TEACnificant A. For TE cooking B. In addDPPH, there were no significant differences (FRAP of UHT showed a significantly (p < 0.05) lower antioxidant capacity than raw foods (Regarding TEACferences A. TEACFRaw foods B. No othp < 0.05): for TEACDPPH, raw foods were more antioxidant than boiled; for TEACFRAP UHT were less antioxidant than the rest of cooked foods except roast ones. For both fractions and for the total antioxidant capacity, the significance in ANOVA paired comparison for TEACFRAP, stated that UHT foods were less antioxidant.In addition, when comparing the means of the different cooking methodologies, the following significant differences were found , eggs, meats  and fish, which included salmon and cod fish .DPPH, meat showed a significantly (p < 0.05) higher antioxidant capacity than the rest of the groups. On the other hand, the antioxidant capacity of dairy products was significantly lower than the average antioxidant capacity of the other food groups  lower to the other food groups, while that of eggs was the highest  higher in meat, whereas they were lower in dairy products, egg, and fish compared with the mean antioxidant capacity of all food groups  was also analyzed. Each group was studied by cooking method and by type of food. Dairy consisted of butter, cheese, milk, and yoghurt; fish consisted of cod fish and salmon and meat consisted of beef, chicken, lamb, and pork .By cooking (DPPH (p < 0.05) higher antioxidant value than grilled products in the fermentation fraction, as well as a higher total antioxidant capacity. Regarding the TEACFRAP method , butter antioxidant capacity was higher than that of cheese in the fermented fraction and total antioxidant capacity; for TEACFRAP . In the case of the fermented fraction and total antioxidant capacity, there were no significant differences, only for TEACDPPH, where boiled fish was less antioxidant than raw. cooking . No signPH assay A; for TEay , salmon (blue fish) was more antioxidant than cod fish (white fish) after digestion; for the TEACFRAP method (p < 0.05).On the other hand, y sample , in the le  than meat in the fermentation fraction and total antioxidant capacity.The antioxidant capacities of meats and fish were also compared. In this sense, fish showed significantly lower antioxidant capacity . This is an important result of our study, since in vitro fermentation potentially release-transform bioactive compounds with high antioxidant capacity. Therefore, the gut microbiota seems to play an important role in the release of these compounds from the indigestible matrix of animal-derived foods ,25, as iThe antioxidant capacity of digested meats  ranged from 13.2 to 20.5 mmol Trolox equivalents/Kg meat , which i3, and phospholipids) are found in milk fat, the main component of butter [In the group of dairy products, butter stood out as the food with the greatest antioxidant capacity. This could be explained, taking into account that some antioxidant compounds in dairy products  gastrointestinal digestion and, more importantly, gut microbiota fermentation, can improve the antioxidant properties of such foods. Most of the antioxidant power of these foodstuffs was released subsequent to in vitro gut microbiota fermentation (around 90%). The food groups with the highest antioxidant capacity were meat and fish, which were increased even more after frying and boiling. The foods that contributed the most antioxidant capacity to the diet in terms of daily consumption were dairy products, while in terms of portion size, the foods with the highest antioxidant capacity were meat and fish. Therefore, the daily antioxidant capacity intake in the Spanish diet has been revisited, finding that foods of animal origin contribute to around 50% of the daily antioxidant capacity intake. So, further studies on antioxidant capacity involving foods of animal origin after in vitro digestion and fermentation should be carried out in the future in order to estimate their contribution to the daily intake of antioxidant capacity.


Genomic selection increases the rate of genetic gain in breeding programs, which results in significant cumulative improvements in commercially important traits such as disease resistance. Genomic selection currently relies on collecting genome-wide genotype data accross a large number of individuals, which requires substantial economic investment. However, global aquaculture production predominantly occurs in small and medium sized enterprises for whom this technology can be prohibitively expensive. For genomic selection to benefit these aquaculture sectors, more cost-efficient genotyping is necessary. In this study the utility of low and medium density SNP panels  to accurately predict breeding values was tested and compared in four aquaculture datasets with different characteristics . The traits show heritabilities between 0.19–0.49, and genomic prediction accuracies using the full density panel of 0.55–0.87. A consistent pattern of genomic prediction accuracy was observed across species with little or no accuracy reduction until SNP density was reduced below 1,000 SNPs (prediction accuracies of 0.44–0.75). Below this SNP density, heritability estimates and genomic prediction accuracies tended to be lower and more variable . A notable drop in accuracy was observed between 200 SNP panels (0.44–0.75) and 100 SNP panels (0.39–0.66). Now that a multitude of studies have highlighted the benefits of genomic over pedigree-based prediction of breeding values in aquaculture species, the results of the current study highlight that these benefits can be achieved at lower SNP densities and at lower cost, raising the possibility of a broader application of genetic improvement in smaller and more fragmented aquaculture settings. Aquaculture is the fastest growing food industry worldwide . While ci.e. the reference population) and the selection candidates. One avenue to democratize genomic selection for smaller-scale, more fragemented aquaculture sectors is to exploit low-density SNP panels for which per-sample genotyping costs can be a fraction of the cost of SNP arrays.One such technology is genomic selection, which utilizes genetic markers to identify the animals with the highest breeding values to select for producing the next generation . Selectia priori that this cost-reduction due to reduced genotype density comes at the expense of reduced prediction accuracy in a breeding program. The improved prediction accuracy of genomic selection compared to pedigree-based approaches is primarily derived from an improved estimation of the genomic similarity between each pair of individuals. In most family-based aquaculture breeding programs, a procedure known as sib-testing (short for sibling testing) is performed whereby trait records are obtained from full siblings of the selection candidates—a process enabled by the high fecundity of aquaculture species. With pedigree-based selection, the genomic similarity between full-sibs is assumed to be 50%, but the reality is that it can vary substantially around this value as a consequence of Mendelian sampling and linkage disequilibrium  challenged with amoebic gill disease (AGD) were phenotyped for mean gill score  and amoebic load , and genotyped using a combined salmon-trout 17K SNP array (Cyprinus carpio) were measured for growth traits (standard length and weight), and genotyped using RAD sequencing for ~12K SNPs (Sparus aurata) challenged with Photobacterium damselae (causative agent of pasteurellosis) were measured for time to death, and genotyped using 2b-RAD sequencing for ~12K SNPs (Crassostrea gigas) challenged with ostreid herpesvirus (OsHV-1-μvar) were measured for time to death and genotyped using a SNP array with ~27K informative Pacific oyster SNPs  Atlantic salmon  Com12K SNPs ; iii) Se12K SNPs ; and iv)ter SNPs .−6) and with minor allele frequencies <0.05. The number of SNPs excluded due to each QC threshold is shown in Genotypes from the four datasets were filtered with PLINK v.1.9 , excludihttps://github.com/SmaragdaT/CVrep/): i) random selection of SNPs within each chromosome (or linkage group for sea bream and oyster) where the number of SNPs selected from each chromosome/linkage group was proportional to its length; and ii) random selection of SNPs across the genome where SNPs were randomly chosen irrespective of their genomic position. For each SNP density, five different SNP panels were selected to account for potential bias arising from SNP subset selection. The results obtained with both selection strategies were similar, therefore only the results of the panels randomly selected across the genome are shown.SNP panels of varying densities were tested by taking subsets of the full QC-filtered SNP panel for each dataset. Panels of the following densities were tested in every species: 100, 200, 300, 400, 500, 600, 700, 800, 900, 1,000, 1,200, 1,400, 1,600, 1,800, 2,000, 2,250, 2,500, 2,750, 3,000, 3,500, 4,000, 4,500 and 5,000. Additionally, 6,000, 7,000, and 9,000 SNP panels were tested depending on the total number of SNPs remaining after quality control . The SNPs for each panel were selected using two different strategies  was calculated using the GenABEL R package . The uni.e. relatedness between unrelated populations will be zero and therefore of no use for prediction) is much more challenging and is likely to require higher SNP densities  to medium density (i.e. 1K–5K) might be a more generally applicable strategy to achieve the optimal balance between economic cost and genetic gain. Previous studies have shown the potential of imputation to achieve near-maximal accuracies in aquaculture populations  and BBSRC Institute Strategic Programme Grants to the Roslin Institute . Christina Kriaridou was supported by Erasmus+ programme of the European Union (ER/SMP-OUT/2018-0033). The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.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.


In order to protect domestic animals’ biodiversity, a deep knowledge of the genomic makeup is required. The authors describe the genomic architecture of the German Short Hair Pointer breed and analyze the inbreeding levels under a genomic and a genealogic perspective. Twenty-four dogs from Italy were genotyped and analyzed jointly with 10 dogs from USA, whose genotypes were available from a published research. The authors investigated the genomic structural variation of the breed using runs of homozygosity—the direct measurement of the proportion of homozygous DNA, i.e., genomic inbreeding. Some traits clearly revealed the selection objectives addressed in the breed. The results describe a low inbred population with quite good levels of genetic variability.The German Shorthaired Pointer (GSHP) is a breed worldwide known for its hunting versatility. Dogs of this breed are appreciated as valuable companions, effective trackers, field trailers and obedience athletes. The aim of the present work is to describe the genomic architecture of the GSHP breed and to analyze inbreeding levels under a genomic and a genealogic perspective. A total of 34 samples were collected , and the genomic and pedigree coefficients of inbreeding have been calculated. A total of 3183 runs of homozygosity (ROH) across all 34 dogs have been identified. The minimum and maximum number of Single Nucleotide Polymorphisms (SNPs) defining all ROH are 40 and 3060. The mean number of ROH for the sample was 93.6. ROH were found on all chromosomes. A total of 854 SNPs (TOP_SNPs) defined 11 ROH island regions (TOP_ROH), in which some gene already associated with behavioral and morphological canine traits was annotated. The proportion of averaged observed homozygotes estimated on total number of SNPs was 0.70. The genomic inbreeding coefficient based on ROH was 0.17. The mean inbreeding based on genealogical information resulted 0.023. The results describe a low inbred population with quite a good level of genetic variability. Dog selection is based on the breed standards that usually define the selection objectives for morphological traits and the behavioral predisposition of each breed . Going bPhysical and physiological characteristics are determined by the genetic composition of the breeds which may have been affected by population bottlenecks due to specific directional selection practices. In this occurrence, a reduced number of ancestors, jointly to the large use of popular sires  may result in an increase in homozygosity at population level ,5,6. th century of kennel clubs that defined breeds’ standards somehow formalized the reproductive isolation within the multiple canine morphologies present at that time [The creation in the mid-19hat time . A “breehat time . The Kenhat time ,8,9,10. Previous studies have shown a decline in the genetic variability of some modern dog populations, characterized by high inbreeding levels like the Lundehund population where the pedigree-based inbreeding was 0.10 calculated on 11 generations ,13,14,15ROH), representing a direct measurement of the fractions of homozygous stretches more likely to be transmitted identically by descent [IS that returns the proportion of observed homozygosity respect the expected one [The traditional approach to inbreeding coefficient (IC) calculation is based on pedigree information: this value is clearly dependent on entries’ data accuracy and known generations in the pedigree (pedigree depth) ,19. The  descent ,19,20,21cted one . The samDuring domestication, hunting ability could have been considered among the most appreciated traits to select for; evidences have been found that 4000 years ago in the Middle East and North Africa, selective breeding for hunting aptitude was applied ,24. The The German Shorthaired Pointer (GSHP) breed represents the optimal evolution of pointing ability in German dog breeds. According to FCI standards, the history of the breed traces back to those dogs from Mediterranean countries that were used to hunt feathered game with nets and with raptors. Those dogs arrived in the German courts where they were selected primarily for their hunting ability and their versatility as gun dogs following the evolution of fire arms. The studbook of the breed, the “Zuchtbook Deutch-Kurzhaar” was firstly published in 1897. The standard of the breed—defining morphology and working characteristics—was written by Prince Albrecht zu Solms-Braunfeld. In Italy, the introduction of the breed began in the 1930s. GSHPs were exported to North America in the 1920s, and they entered the AKC studbook in 1930; recognized worldwide for their hunting versatility. Furthermore, they are appreciated as valuable companions, effective trackers, field trailers and obedience athletes. . The aim of this study is to describe the genomic architecture of GSHP breed and to analyze the inbreeding levels of the breed under a genomic and a genealogic perspective, to supply effective data helpful for the design of breeding plans and conservation projects.The DNA of twenty-four pedigree GSHP samples  was extracted from residual blood samples collected for routine screening of health status and according to the University Ethical Committee opinion n. 2/16 on re-use of collected samples. The samples were taken from unrelated, second-generation dogs from different Italian regions. This approach was aimed to make the sample here considered as much as possible representative of the Italian population and of its genetic variability. According to storage protocols, the dogs’ identities were certified by a veterinarian after the chip control: chip number, ENCI studbook registration number, name, sex and date of birth are the data commonly filled in the automated format used by the ENCI official labs in dog identification and recording procedures.All dogs were genotyped with the Illumina CanineHD BeadChip array containing about 220,853 SNPs and the CanFam3.1 genome assembly (GCF_000002285.3) was considered as reference genome.Ten genotyped German Shorthair Pointer dogs (GSHP_USA) from   and SNP genotypes data were filtered for minor allele frequency (MAF)  and for call rate (0.99), in order to reduce the bias ascribable to missing genotypes in inbreeding coefficients evaluation and in other statistics.ADMIXTURE (v. 1.3.0) software  has beenSVS software has been used to perform ROH detection. The ROH were defined setting a minimum of 1000 kb in size and 40 homozygous SNPs, no heterozygote SNPs are permitted, no missing SNPs were allowed in the ROH, and a maximum gap between SNPs of 1000 Kb was predefined in order to assure that the SNP density did not affect the ROH. ROHs were grouped into 5 classes of length  and all the statistics were calculated across individuals within country (n = 24 for GSHP_ITALY and n = 10 for GSHP_USA) and for overall_GSHP .The genomic regions with the highest frequency of ROH (TOP_ROH), and thus potentially under selection, have been identified by selecting the SNPs most commonly occurring in ROH, i.e., those occurring in at least 50% of samples plus one. The SNPs in the TOP_ROH are here referred to as TOP_SNPs. The TOP_SNPs and the TOP_ROH were annotated on CanFam3.1 genome  using the Variant Effect Predictor (VEP) and the BioMart tools of Ensembl genome browser , respectGraphical representations of ROH were obtained using the R package DetectRUNs .In this study, genomic molecular inbreeding coefficients (FHOM and FROH) have been calculated for the overall_GSHP and the genealogical F for GSHP_ITALY (FPED) from pedigree information available only for Italian GSHP population:HOM) with SVS, following [(i) Inbreeding coefficients based on the excess in the observed number of homozygous genotypes (Following FHOM = (ROH) with DetectRun, according to the following formula: ROH is the total length of all ROHs of an individual, Laut the specified length of the autosomal genome (from 1 to 38) covered by the SNPs used in this study .(ii) Inbreeding coefficient based on ROH (FPED) was calculated using Pedigree Viewer software [(iii) Inbreeding coefficient based on pedigree information . The SVS software identified a total of 3183 runs across all 34 dogs . ResultsThe minimum and maximum number of SNPs defining all ROH are 40 and 3060, respectively.ROH are mainly short in length; in fact, the ROH of 0-2 Mb and 2–4 Mb are the most frequent classes of length identified  A. ROH weThe number of ROH per individual ranged from 71 to 131, with a mean number of ROH for sample of 93.6 . Only thROH were found on all chromosomes: less than 50% of chromosomes (n.17) C have a The We found a total of 854 TOP_SNPs, and FMN1 (n. 26), RYR3 (n. 28), CSMD3 (n.29), OPCML (n. 33), and NTM (n. 50) genes. In addition, four SNPs resulted annotated in missense positions: BICF2P1347925, BICF2S23147347 and TIGRP2P48933_rs8545710 on chr3 and BICF2P847459 on chr30 of HTT, HTT, ADD1, and RYR3 genes, respectively. SNP genotypes of the dogs for each of these positions were verified and, as reported in The highest number of homozygotes SNPs (> 25) was annotated within the CACNG5, CACNG4, CACNG1 are the main involved genes  was 0.04  and individual values ranged from −0.06 to 0.21 for dogs with lower than average homozygosity and vice versa, respectively. The inbreeding coefficient estimated from SNP markers  were slightly higher: a mean value of 0.17, ranging between 0.09 to 0.32. Differences in FROH were found along all chromosomes  have been identified for chrs 9, 13 and 25. Instead, the inbreeding coefficients based on ROH (Fomosomes . The hig2) calculated between FHOM and FROH, were 0.988 and 0.975 . ROH and FPED, resulting in a lower coefficient but similar R2 to FHOM and FPED.The four-generation pedigree analysis resulted in a very low Fas 0.161 . The meaand FPED  showed aNot many studies have explored the ROH pattern and its possible association with inbreeding depression, to morphological and health traits in dog breeds and populations in comparison to researches performed and available in other species . The ROH patterns and their distributions in specific dog breeds remain largely unexplored.To the best of our knowledge, this study is the first attempt to characterize the ROH distribution in the German Shorthair Point dog breed using canine high-density SNP arrays. The genealogical pedigree information was used to sample the 24 individuals that were as un-related as possible. Ten available online genotyped GSHP samples from the GSPH_USA populations were available from a previous published study  and addeThe detection of genomic regions  underlying breed-specific phenotypic characteristics or attitude, can provide indication about a specific genetic structure of a population or breed. ROH, in concordance with their length, inform on a possible artificial or natural selection pressure on specific genomic tracts and on inbreeding levels also providing information on bottlenecks to which the populations have been subjected over the years. Long ROH (~ 10 Mb) occur as a result of recent inbreeding and when recombination events do not interrupt long chromosome segments. Short ROH (~ 1 Mb), instead, are produced by IBD  genomic regions from old ancestors (up to 50 generations ago) .NTM, OPCML, CSMD3, RYR3, FMN1, TMTC2, and HTT. All these genes (except for NTM), together with others (n. 15) have been already associated with dog traits, comprising behavior and morphological traits, as reported in Similar to what has been identified in some hunting dog breeds—the French Pointing dog type the Pyrenee and in Rhodesian Ridgeback dogs, respectively—most of the ROH identified in this study were short in length , suggesting that dogs of these populations are involved in more ancient relatedness ,34. The NTM and OPCML (the most representative) are genes involved in central nervous system functioning. Studies performed in humans proposed that the NTM gene (Neurotrimin) is associated with IQ level and cognitive function performances. In addition, Gurgul et al. [MNT and OPCML (Opioid Binding Protein/Cell Adhesion Molecule Like) genes to the differing horses’ temperaments and to the ability to develop different gaits as a function of motor coordination. It could be supposed that these genes’ expression, considering the presence of many TOP_SNPs, could be related to the peculiar hunting abilities and style of GSHPs. These traits have been strongly selected by the breeders since the 19th century, and they are clearly described in the breed working standards [RYR3 (Ryanodine Receptor 3), together with GRK4 (G protein-coupled receptor kinase 4) located in TOP_ROH_02, resulted genes positively selected in athletic dog breeds (sports and hunting aptitudes). In fact, these two genes could have an important role in field activity: RYR3 because of its function in the activation of muscle skeletal contraction through the coordinate activation of voltage dependent Ca2+ [GRK4 in increasing cardiac output. l et al.  supposedtandards ,35. RYR3ent Ca2+ , and GRKHTT gene. No specific association study results are yet available for this mutation or gene in the dog species. The only exception is for chasing behavior trait, as reported in The only gene for which an SNP missense position (BICF2S23147347) with alternative variant G  has been found , accordiCACNG1  —: a polymorphism of CACNG1 gene has been associated with elite strength athlete status [CACNG1, CACNG4 (subunit gamma 4), and CACNG5 (subunit gamma 5) are genes implicated in five KEGG pathways related to cardiac functions . These three genes are also part of the MAPK signaling pathway, active on the proliferation of mammalian cells, and play an important role at different levels—e.g., the regulation of various diseases (cardiovascular), taking part in anti-inflammatory effects, responses to stress, protection against injury, and the maintenance of gastrointestinal functions [Another gene that we could hypothesize under selection in this breed, according to breed-specific characteristics described in the standard, is that the encoding factors involved in skeletal muscle contraction processes—i.e., e status . CACNG1,unctions .PED in the studied subjects [ROH (equation 2) results, which reveal the genomic relationship among the studied individuals as demonstrated by different researchers [HOM (equation 1) based on SNPs is lower compared to all the results reported in 11 breeds by [The loss of genetic variability and the increase in inbreeding levels coupled with the consequent reduction in the effective population size in a high number of pedigree canine populations could be considered the main risk factor in conservation project definitions ,42,43,44earchers ,16,45. Tearchers  about threeds by , which rreeds by  with a rreeds by . Considereeds by , and in reeds by —in both reeds by , who comThe investigation of the genomic architecture and the molecular dissection of inbreeding play a pivotal role in the conservation and protection plans for animal populations. Furthermore, genomic analysis supplies effective tools with high quality molecular data in the demographic profiling of canine populations. The presented results represent the first description of the molecular dissection of the inbreeding levels in the Italian and USA pointing GSHP breeds. The genomic molecular investigation allowed the authors to finely describe the genetic assets of the breed, even if enlarging the sample size may disclose other regions under recent inbreeding. The obtained results could be considered a powerful and objective tool in breed conservation management. The genomic data here analysed showed important homozygosity for morphological and behavioural traits, whose expression is contributed by known annotated genes. The findings of the research also underline the importance of integrating genealogical and molecular information on dog breeds, in order to obtain meaningful data for breeds’ protection actions.