Whole-genome Single Nucleotide Polymorphism Research Articles

Comparative Analysis of Molecular RFLP and SNP Markers in Assessing and Understanding the Genetic Diversity of Various Chicken Breeds.

Monitoring the genetic diversity of small populations is important with respect to conserving rare and valuable chicken breeds, as well as discovery and innovation in germplasm research and application. Restriction fragment length polymorphisms (RFLPs), the molecular markers that underlie multilocus DNA fingerprinting (MLDF), have historically been employed for this purpose, but over the past two decades, there has been an irreversible shift toward high-throughput single-nucleotide polymorphisms (SNPs). In this study, we conducted a comparative analysis of archived MLDF results and new data from whole-genome SNP genotyping (SNPg) among 18 divergently selected breeds representing a large sample of the world gene pool. As a result, we obtained data that fit the general concept of the phylogenetic distribution of the studied breeds and compared them with RFLP and SNP markers. RFLPs were found to be useful markers for retrospective assessment of changes in the genetic architecture and variability underlying the phenotypic variation in chicken populations, especially when samples from previous generations used for MLDF are unavailable for SNPg. These results can facilitate further research necessary to assess the possibility of extrapolating previous MLDF results to study the long-term dynamics of genetic diversity in various small chicken germplasm populations over time. In general, the whole-genome characterization of populations and breeds by multiple SNP loci will further form the basis for the development and implementation of genomic selection with the aim of effective use of the genetic potential of the domestic gene pool in the poultry industry.

Molecular Breeding of Water-Saving and Drought-Resistant Rice for Blast and Bacterial Blight Resistance.

Rice production is often affected by biotic and abiotic stressors. The breeding of resistant cultivars is a cost-cutting and environmentally friendly strategy to maintain a sustainable high production level. An elite water-saving and drought-resistant rice (WDR), Hanhui3, is susceptible to blast and bacterial blight (BB). This study was conducted to introgress three resistance genes (Pi2, xa5, and Xa23) for blast and BB into Hanhui3, using marker-assisted selection (MAS) for the foreground selection and a whole-genome single-nucleotide polymorphism (SNP) array for the background selection. As revealed by the whole-genome SNP array, the recurrent parent genome (RPG) recovery of the improved NIL was 94.2%. The resistance levels to blast and BB of the improved NIL and its derived hybrids were higher than that of the controls. In addition, the improved NIL and its derived hybrids retained the desired agronomic traits from Hanhui3, such as yield. The improved NIL could be useful to enhance resistance against biotic stressors and produce stable grain yields in Oryza sativa subspecies indica rice breeding programs.

Genetic diversity and population structure of Tongcheng pigs in China using whole-genome SNP chip.

Tongcheng (TC) pigs, distinguished by their superior meat quality, are a Chinese indigenous pig breed. Recently, the genetic resources of TC pigs are under tremendous threat due to the introduction of cosmopolitan pig breeds and African swine fever disease. To promote their management and conservation, the present study assessed genetic diversity and population structure of TC pigs using single nucleotide polymorphism (SNP) markers. A total of 26, 999 SNPs were screened from 51, 315 SNPs in 68 TC pigs. The multi-dimensional scaling (MDS) analysis and neighbor-joining tree revealed that all 68 pigs were from a purebred population. The effective population size decreased over time, and it was 96 prior to generation 20. Both linkage disequilibrium (LD) and neutrality test indicated a low selection of TC pigs with average LD value of 0.15 ± 0.23. Genetic diversity results exhibited a minor allele frequency (MAF) of 0.23, observed heterozygosity (HO) of 0.32, expected heterozygosity (He) of 0.31, and nucleotide diversity (Pi) of 0.31. All these parameters indicated a remarkably high genetic diversity of TC pigs. Additionally, 184 runs of homozygosity (ROH) segments were detected from the whole genome of TC pigs with an average ROH length of 23.71Mb, ranging from 11.26Mb to 69.02 Mb. The highest ROH coverage was found on chromosome 1 (10.12%), while the lowest was on chromosome 18 (1.49%). The average inbreeding coefficients based on ROH (FROH) was 0.04%. Fourteen ROH islands containing 240 genes were detected on 9 different autosomes. Some of these 240 genes were overlapped with the genes related to biological processes such as immune function, reproduction, muscular development, and fat deposition, including FFAR2, FFAR4, MAPK8, NPY5R, KISS1, and these genes might be associated with such traits as meat quality and disease resistance in TC pigs. Taken together, population structure and genetic diversity results suggested that the TC pig represented a valuable genetic resource. However, TC pig breed conservation program remains to be further optimized to ensure adequate genetic diversity and avoid inbreeding depression. Our findings provide theoretical basis for formulating management and conservation strategies for TC pigs.

Core Genome Multilocus Sequence Typing Scheme for Improved Characterization and Epidemiological Surveillance of Pathogenic Brucella.

ABSTRACTBrucellosis poses a significant burden to human and animal health worldwide. Robust and harmonized molecular epidemiological approaches and population studies that include routine disease screening are needed to efficiently track the origin and spread of Brucella strains. Core genome multilocus sequence typing (cgMLST) is a powerful genotyping system commonly used to delineate pathogen transmission routes for disease surveillance and control. Except for Brucella melitensis, cgMLST schemes for Brucella species are currently not established. Here, we describe a novel cgMLST scheme that covers multiple Brucella species. We first determined the phylogenetic breadth of the genus using 612 Brucella genomes. We selected 1,764 genes that were particularly well conserved and typeable in at least 98% of these genomes. We tested the new scheme on 600 genomes and found high agreement with the whole-genome-based single nucleotide polymorphism (SNP) analysis. Next, we applied the scheme to reanalyze the genome of Brucella strains from epidemiologically linked outbreaks. We demonstrated the applicability of the new scheme for high-resolution typing required in outbreak investigations as previously reported with whole-genome SNP methods. We also used the novel scheme to define the global population structure of the genus using 1,322 Brucella genomes. Finally, we demonstrated the possibility of tracing distribution of Brucella strains by performing cluster analysis of cgMLST profiles and found nearly identical cgMLST profiles in different countries. Our results show that sequencing depth of more than 40-fold is optimal for allele calling with this scheme. In summary, this study describes a novel Brucella-wide cgMLST scheme that is applicable in Brucella molecular epidemiology and helps in accurately tracking and thus controlling the sources of infection. The scheme is publicly accessible and should represent a valuable resource for laboratories with limited computational resources and bioinformatics expertise.

Whole-genome single nucleotide polymorphism analysis for typing the pandemic pathogen Fusarium graminearum sensu stricto.

Recent improvements in microbiology and molecular epidemiology were largely stimulated by whole- genome sequencing (WGS), which provides an unprecedented resolution in discriminating highly related genetic backgrounds. WGS is becoming the method of choice in epidemiology of fungal diseases, but its application is still in a pioneer stage, mainly due to the limited number of available genomes. Fungal pathogens often belong to complexes composed of numerous cryptic species. Detecting cryptic diversity is fundamental to understand the dynamics and the evolutionary relationships underlying disease outbreaks. In this study, we explore the value of whole-genome SNP analyses in identification of the pandemic pathogen Fusarium graminearum sensu stricto (F.g.). This species is responsible for cereal diseases and negatively impacts grain production worldwide. The fungus belongs to the monophyletic fungal complex referred to as F. graminearum species complex including at least sixteen cryptic species, a few among them may be involved in cereal diseases in certain agricultural areas. We analyzed WGS data from a collection of 99 F.g. strains and 33 strains representing all known cryptic species belonging to the FGSC complex. As a first step, we performed a phylogenomic analysis to reveal species-specific clustering. A RAxML maximum likelihood tree grouped all analyzed strains of F.g. into a single clade, supporting the clustering-based identification approach. Although, phylogenetic reconstructions are essential in detecting cryptic species, a phylogenomic tree does not fulfill the criteria for rapid and cost-effective approach for identification of fungi, due to the time-consuming nature of the analysis. As an alternative, analysis of WGS information by mapping sequence data from individual strains against reference genomes may provide useful markers for the rapid identification of fungi. We provide a robust framework for typing F.g. through the web-based PhaME workflow available at EDGE bioinformatics. The method was validated through multiple comparisons of assembly genomes to F.g. reference strain PH-1. We showed that the difference between intra- and interspecies variability was at least two times higher than intraspecific variation facilitating successful typing of F.g. This is the first study which employs WGS data for typing plant pathogenic fusaria.

Comparative genomic analysis of Canadian Mycoplasma bovis strains isolated from Bison and Cattle

Mycoplasma bovis (M. bovis) in cattle causes pneumonia, arthritis, otitis media, and mastitis. In addition, multiple outbreaks have been recorded in North American bison. The genomic data on Canadian M. bovis in bison and cattle to date is limited. Whole-genome sequencing (WGS) was used to assess the degree of genome conservation across four Canadian M. bovis strains recovered from bison and cattle. Whole-genome sequences of four M. bovis isolates (Mb1, Mb160, Mb300, Mb304) and the PG45 reference genome were utilized to identify the M. bovis genomic similarity, whole-genome single nucleotide polymorphism (WGS-SNP), virulence determinants, and genomic islands. The pan-genome analysis showed that M. bovis encodes a minimum of 971 genes, while the core genome contained 637 genes. Comparative genomics revealed limited diversity in gene content between bison and cattle isolates. Whole-genome SNP analysis showed that the four M. bovis isolates differed from each other and to PG45. A total of 40 putative virulence genes associated with adhesion, colonization, and destruction of tissues were found in the bison and cattle isolates using the virulence factors database (VFDB). These putative virulence factors were equally distributed among isolates. Genomic Islands (GIs) ranging from 4 to 9 and associated with transposases, restriction-modification, ribosomal hypothetical proteins, variable surface lipoproteins, and unknowns were also identified. Overall, the genomic characterization of these isolates may provide new insights into the mechanisms of pathogenicity in M. bovis.

Genome-Based Analysis of Aspergillus niger Aggregate Species from China and Their Potential for Fumonisin B2 and Ochratoxin A Production

Based on entire genome sequencing, this study focused on the classification of Aspergillus niger aggregation species and investigated their potential for fumonisin B2 (FB2) and ochratoxin A (OTA) production. In the current study, 22 strains were used, namely 17 A. niger strains, four A. welwitschiae strains, and one A. lacticoffeatus (a synonym of A. niger) strain. Traditional multigene phylogenetic analysis, average nucleotide identity analysis (ANI), and the whole-genome single-nucleotide polymorphism (SNP) analyses were used to reconfirm the taxonomic status of A. niger, A. welwitschiae, and A. lacticoffeatus. The ability of A. niger to produce FB2 and OTA on five culture substrates was determined, and the association between FB2 and OTA gene clusters and toxin-producing abilities was explored. The results revealed that the ANI method could distinguish A. niger from A. welwitschiae, with an ANI value of < 98%. The SNP-based phylogenetic analysis suggested that A. niger and A. welwitschiae were two independent phylogenetic species. The ANI, SNP, and multigene phylogenetic analysis supported previous findings that A. lacticoffeatus was a synonymous species of A. niger. Aspergillus niger strains exhibited the varied potential of producing FB2 and OTA on different culture media. The A. niger genome sequence analysis revealed no significant difference in fumonisin gene clusters between FB2-nonproducing isolates and FB2-producing isolates, and the integrity of the ochratoxin biosynthesis genes cluster was clearly associated with OTA production. In conclusion, gene sequencing can be useful in assessing A. niger's ability to produce OTA, but it cannot reliably predict its ability to produce FB2.

Development of Whole Genome SNP-CAPS Markers and Preliminary QTL Mapping of Fruit Pedicel Traits in Watermelon

Fruit pedicel (FP) is an important determinant of premium fruit quality that directly affects commercial market value. However, in-depth molecular and genetic basis of pedicel-related traits has not been identified in watermelon. Herein, a quantitative trait locus (QTL) mapping strategy was used to identify the potential genetic regions controlling FP traits based on newly derived whole-genome single nucleotide polymorphism based cleaved amplified polymorphism sequence (SNP-CAPS) markers. Next-generation sequencing based whole-genome re-sequencing of two watermelon parent lines revealed 98.30 and 98.40% of average coverage, 4,989,869 SNP variants, and 182,949 CAPS loci pairs across the reference genome, respectively. A total of 221 sets of codominant markers exhibited 46.42% polymorphism rate and were effectively genotyped within 100-F2:3 derived mapping population. The developed linkage map covered a total of 2,630.49 cM genetic length with averaged 11.90 cM, and depicted a valid marker-trait association. In total, 6 QTLs (qFPL4.1, qFPW4.1, qFPD2.1, qFPD2.2, qFPD8.1, qFPD10.1) were mapped with five major effects and one minor effect between the whole genome adjacent markers positioned over distinct chromosomes (02, 04, 08, 10), based on the ICIM-ADD mapping approach. These significant QTLs were similarly mapped in delimited flanking regions of 675.10, 751.38, 859.24, 948.39, and 947.51 kb, which collectively explained 8.64–13.60% PVE, respectively. A highly significant and positive correlation was found among the observed variables. To our knowledge, we first time reported the mapped QTLs/genes affecting FP traits of watermelon, and our illustrated outcomes will deliver the potential insights for fine genetic mapping as well as functional gene analysis through MAS-based breeding approaches.

Rapid Multilateral and Integrated Public Health Response to a Cross-City Outbreak of Salmonella Enteritidis Infections Combining Analytical, Molecular, and Genomic Epidemiological Analysis.

On September 21, 2019, the Shenzhen and Dongguan Centers for Disease Control and Prevention received notification of a large cluster of suspected gastroenteritis involving primarily children who sought medical care at hospitals throughout two adjacent cities in China, Shenzhen, and Dongguan. A joint outbreak response was promptly initiated across jurisdictions in a concerted effort between clinical microbiologists, epidemiologists, and public health scientists. Concurrently, multiplex PCRs were used for rapid laboratory diagnosis of suspected cases; epidemiological investigations were conducted to identify the outbreak source, complemented by near real-time multicenter whole-genome analyses completed within 34 h. Epidemiological evidence indicated that all patients had consumed egg sandwiches served on September 20 as snacks to children and staff at a nursery in Dongguan, located near Shenzhen. Salmonella Enteritidis was isolated from case-patients, food handlers, kitchenware, and sandwiches with kitchen-made mayonnaise. Whole-genome single-nucleotide polymorphism (SNP)-based phylogenetic analysis demonstrated a well-supported cluster with pairwise distances of ≤1 SNP between genomes for outbreak-associated isolates, providing the definitive link between all samples. In comparison with historical isolates from the same geographical region, the minimum pairwise distance was >14 SNPs, suggesting a non-local outbreak source. Genomic source tracing revealed the possible transmission dynamics of a S. Enteritidis clone throughout a multi-provincial egg distribution network. The efficiency and scale with which multidisciplinary and integrated approaches were coordinated in this foodborne disease outbreak response was unprecedented in China, leading to the timely intervention of a large cross-jurisdiction Salmonella outbreak.

Development and Characterization of Chromosome Segment Substitution Lines Derived from Oryza rufipogon in the Background of the Oryza sativa indica Restorer Line R974

Dongxiang wild rice (DXWR) (O. rufipogon Griff.), which has the northernmost worldwide distribution of a wild rice species, is a valuable genetic resource with respect to improving stress tolerance in cultivated rice (Oryza sativa L.). In the three-line hybrid rice breeding system, restorer lines play important roles in enhancing the tolerance of hybrid rice. However, restorer lines have yet to be used as a genomic background for development of substitution lines carrying DXWR chromosome segments. We developed a set of 84 chromosome segment substitution lines (CSSLs) from a donor parent DXWR × recurrent parent restorer line R974 (Oryza sativa indica) cross. On average, each CSSL carried 6.27 introgressed homozygous segments, with 93.37% total genome coverage. Using these CSSLs, we identified a single QTL, qDYST-1, associated with salt stress tolerance on chromosome 3. Furthermore, five CSSLs showing strong salt stress tolerance were subjected to whole-genome single-nucleotide polymorphism chip analyses, during which we detected a common substitution segment containing qDYST-1 in all five CSSLs, thereby implying the validity and efficacy of qDYST-1. These novel CSSLs could make a significant contribution to detecting valuable DXWR QTLs, and provide important germplasm resources for breeding novel restorer lines for use in hybrid rice breeding systems.

A Whole Genome Sequencing-Based Genome-Wide Association Study Reveals the Potential Associations of Teat Number in Qingping Pigs.

Simple SummaryTeat number is important for the mothering ability of a sow, but this trait has seldom been investigated by high-depth genomic data-based genome-wide association study (GWAS). Here, we performed GWAS for the teat number-related traits in 100 Chinese native Qingping pigs by recording their left and right teat numbers and analyzing their genetic variations through 10-fold whole-genome sequencing. T-Box Transcription Factor 3 (TBX3) on Sus scrofa chromosome (SSC) 14 and Wnt signaling pathway are revealed to be associated with teat number-related traits, with important roles in mammary gland morphogenesis and development.Teat number plays an important role in the reproductive performance of sows and the growth of piglets. However, the quantitative trait loci (QTLs) and candidate genes for the teat number-related traits in Qingping pigs remain unknown. In this study, we performed GWAS based on whole-genome single-nucleotide polymorphisms (SNPs) and insertions/deletions (Indels) for the total number of teats and five other related traits in 100 Qingping pigs. SNPs and Indels of all 100 pigs were genotyped using 10× whole genome resequencing. GWAS using General Linear Models (GLM) detected a total of 28 SNPs and 45 Indels as peak markers for these six traits. We also performed GWAS for the absolute difference between left and right teat number (ADIFF) using Fixed and random model Circulating Probability Unification (FarmCPU). The most strongly associated SNP and Indel with a distance of 562,788 bp were significantly associated with ADIFF in both GLM and FarmCPU models. In the 1-Mb regions of the most strongly associated SNP and Indel, there were five annotated genes, including TRIML1, TRIML2, ZFP42, FAT1 and MTNR1A. We also highlighted TBX3 as an interesting candidate gene for SSC14. Enrichment analysis of candidate genes suggested the Wnt signaling pathway may contribute to teat number-related traits. This study expanded significant marker-trait associations for teat number and provided useful molecular markers and candidate genes for teat number improvement in the breeding of sows.

Whole-genome sequencing for the characterization of resistance mechanisms and epidemiology of colistin-resistant Acinetobacter baumannii.

BackgroundMultidrug-resistant Acinetobacter baumannii is an important causal pathogen of healthcare-associated infections, and colistin-resistant strains have recently emerged owing to the increased use of colistin. Using next-generation sequencing (NGS), a single whole-genome sequencing (WGS) protocol can identify and type pathogens, analyze genetic relationships among different pathogens, predict pathogenic transmissions, and detect antibiotic resistance genes. However, only a few studies have applied NGS in studying the resistance mechanism and epidemiology of colistin-resistant A. baumannii. This study aimed to elucidate the resistance mechanism of colistin-resistant A. baumannii and analyze its molecular epidemiology through WGS.Materials and methodsThe subjects in this study were patients who visited a university hospital between 2014 and 2018. Thirty colistin-resistant strains with high minimum inhibitory concentrations were selected from various patient samples, and WGS was performed. Comparative genomic analysis was performed for the 27 colistin-resistant A. baumannii strains using a colistin-susceptible strain as the reference genome.ResultsThe WGS analysis found no mutation for lpxA, lpxC, lpx D, pmrA, pmrB, and mcr1, the genes known to be associated with colistin resistance. Fifty-seven coding sequences (CDS) showed differences; they included 13 CDS with known names and functions that contained 21 genes. From the whole-genome multi-locus sequence typing (wgMLST) and single nucleotide polymorphism (SNP) analyses, two major clusters were found for the colistin-resistant A. baumannii strains. However, no differences were observed by the time of detection for each cluster, the samples, the pattern of antibiotic resistance, or the patient characteristics. In the conventional MLST following the Oxford scheme, the typing result showed ST1809, ST451, ST191, ST1837, and ST369 in the global clone 2 (GC2), without any relation with the results of wgMLST and SNP analyses.ConclusionBased on the findings of the resistance gene analysis through WGS and comparative genomic analysis, the potential genes associated with colistin-resistance or CDS were examined. Furthermore, the analysis of molecular epidemiology through WGS regarding colistin-resistant A. baumannii may prove helpful in preventing infection by multidrug-resistant bacteria and controlling healthcare-associated infections.

Diagnosis of Chromosome 15q-Terminal Deletion Syndrome through Elevated Fasting Serum Growth Hormone Levels

Chromosome 15q26-qter deletion syndrome is a rare disease that causes prenatal and postnatal growth retardation, microcephaly, developmental delay, and congenital heart diseases, mainly due to haploinsufficiency of IGF1R. In addition, patients with pathogenic variants of the IGF1R show similar symptoms. We report the case of a 5-month-old girl with prenatal and postnatal growth retardation, microcephaly, and congenital heart disease. At 5 months of age, her length was 54.7 cm (−4.3 SD), her weight was 4.4 kg (−3.1 SD), and her head circumference was 37.4 cm (−2.8 SD), thus presenting severe growth retardation. Repeated pre-feeding serum GH levels were abnormally high (26.1–85.5 ng/mL), and IGF-1 levels (+0.16 to +1.2 SD) were relatively high. The 15q sub-telomere fluorescence in situ hybridization analysis revealed a heterozygous deletion in the 15q terminal region. Whole-genome single nucleotide polymorphism microarray analysis showed a terminal deletion of 6.4 Mb on 15q26.2q26.3. This is the first report showing that fasting GH levels are high in early infancy in patients with IGF1R abnormalities. In addition to relatively high IGF-1 levels, elevated fasting GH levels in early infancy may contribute to the diagnosis of IGF1R abnormalities.

Selection of Genome-Wide SNPs for Pooled Allelotyping Assays Useful for Population Monitoring.

Parasitic worms are serious pests of humans, livestock, and crops worldwide. Multiple management strategies are employed in order to reduce their impact, and some of these may affect their genome and population allelic frequency distribution. The evolution of chemical resistance, ecological changes, and pest dispersal has allowed an increasing number of pests to become difficult to control with current management methods. Their lifestyle limits the use of ecological and individual-based management of populations. There is a need to develop rapid, affordable, and simple diagnostics to assess the efficacy of management strategies and delay the evolution of resistance to these strategies. This study presents a multilocus, equal-representation, whole-genome pooled single nucleotide polymorphisms (SNPs) selection approach as a monitoring tool for the ovine nematode parasite Haemonchus contortus. The SNP selection method used two reference genomes of different quality, then validated these SNPs against a high-quality recent genome assembly. From over 11 million high-quality SNPs identified, 334 SNPs were selected, of which 262 were species-specific, yielded similar allele frequencies when assessed as multiple individuals or as pools of individuals, and suitable to distinguish mixed nematode isolate pools from single isolate pools. As a proof-of-concept, 21 Australian H. contortus populations with various phenotypes and genotypes were screened. This analysis confirmed the overall low level of genetic differentiation between populations collected from the field, but clearly identifying highly inbred populations, and populations showing genetic signatures associated with chemical resistance. The analysis showed that 66% of the SNPs were necessary for stability in assessing population genetic patterns, and SNP pairs did not show linkage according to allelic frequencies across the 21 populations. This method demonstrates that ongoing monitoring of parasite allelic frequencies and genetic changes can be achieved as a management assessment tool to identify drug-treatment failure, population incursions, and inbreeding signatures due to selection. The SNP selection method could also be applied to other parasite species.

Heterotic prediction of hybrid performance based on genome-wide SNP markers and the phenotype of parental inbred lines in heading Chinese cabbage (Brassica rapa L. ssp. pekinensis)

Chinese cabbage (Brassica rapa L. ssp. Pekinensis) is the most widely consumed leafy vegetable in Asia. Most commercial cultivars are F1 hybrids with high yield and good quality. To increase the breeding efficiency, heterotic prediction of hybrid performance was studied. Fourteen parental lines of Chinese cabbage were studied in a half-diallel cross to produce 91 hybrids. The average mid-parent heterosis (MPH) for 14 agronomic traits ranged from −5.07% to 106.76%, while the average high-parent heterosis (HPH) ranged from −109.90% to 80.56%. Significant HPH was observed in the growth period (−109.90%), biomass (80.56%), and plant weight (15.20%), which exhibited comprehensive advantages in breeding. Two methods were used to calculate the genetic distance (GD) between the parents based on 2,444,676 single nucleotide polymorphisms (SNPs): total SNPs (GDtotal) and homozygous differential SNPs (GDhomo). Parental clustering based on total SNPs divided the parents into three major types, namely “flat-topped”, “ovate”, and “cylindrical”. These types were more suitable for their traditional pedigree relationships. The correlation between the GD, mean parental phenotype, and heterosis indicated that the phenotype of the parental inbred lines may be useful for predicting heterosis because it is rapid and simple, whereas GD calculated using SNP markers led to a moderate improvement in heterotic prediction. GDhomo was a better predictor of heterosis and F1 performance than GDtotal. These results confirmed that whole-genome SNP markers are an effective tool for evaluating GD in Chinese cabbage and are useful for parent selection in breeding.

Identification and validation of a regulatory mutation upstream of the BMP2 gene associated with carcass length in pigs

BackgroundCarcass length is very important for body size and meat production for swine, thus understanding the genetic mechanisms that underly this trait is of great significance in genetic improvement programs for pigs. Although many quantitative trait loci (QTL) have been detected in pigs, very few have been fine-mapped to the level of the causal mutations. The aim of this study was to identify potential causal single nucleotide polymorphisms (SNPs) for carcass length by integrating a genome-wide association study (GWAS) and functional assays.ResultsHere, we present a GWAS in a commercial Duroc × (Landrace × Yorkshire) (DLY) population that reveals a prominent association signal (P = 4.49E−07) on pig chromosome 17 for carcass length, which was further validated in two other DLY populations. Within the detected 1 Mb region, the BMP2 gene stood out as the most likely causal candidate because of its functions in bone growth and development. Whole-genome gene expression studies showed that the BMP2 gene was differentially expressed in the cartilage tissues of pigs with extreme carcass length. Then, we genotyped an additional 267 SNPs in 500 selected DLY pigs, followed by further whole-genome SNP imputation, combined with deep genome resequencing data on multiple pig breeds. Reassociation analyses using genotyped and imputed SNP data revealed that the rs320706814 SNP, located approximately 123 kb upstream of the BMP2 gene, was the strongest candidate causal mutation, with a large association with carcass length, with a ~ 4.2 cm difference in length across all three DLY populations (N = 1501; P = 3.66E−29). This SNP segregated in all parental lines of the DLY (Duroc, Large White and Landrace) and was also associated with a significant effect on body length in 299 pure Yorkshire pigs (P = 9.2E−4), which indicates that it has a major value for commercial breeding. Functional assays showed that this SNP is likely located within an enhancer and may affect the binding affinity of transcription factors, thereby regulating BMP2 gene expression.ConclusionsTaken together, these results suggest that the rs320706814 SNP on pig chromosome 17 is a putative causal mutation for carcass length in the widely used DLY pigs and has great value in breeding for body size in pigs.

Heritability and Genomic Architecture of Episodic Exercise-Induced Collapse in Border Collies.

An episodic nervous system disorder triggered by strenuous exercise, termed border collie collapse (BCC), exists in border collies and related breeds. The genetic basis of BCC is unknown but is believed to be a complex genetic disorder. Our goal was to estimate the heritability (h2SNP) of BCC, define its underlying genetic architecture, and identify associated genomic loci using dense whole-genome single-nucleotide polymorphism (SNP) genotyping data. Genotype data were obtained for ~440,000 SNPs from 343 border collies (168 BCC cases and 175 controls). h2SNP was calculated to be 49–61% depending on the estimated BCC prevalence. A total of 2407 SNPs across the genome accounted for nearly all the h2SNP of BCC, with an estimated 2003 SNPs of small effect, 349 SNPs of moderate effect, and 56 SNPs of large effect. Genome-wide association analyses identified significantly associated loci on chromosomes 1, 6, 11, 20, and 28, which accounted for ~5% of the total BCC h2SNP. We conclude that BCC is a moderately- to highly-heritable complex polygenetic disease resulting from contributions from hundreds to thousands of genetic variants with variable effect sizes. Understanding how much the BCC phenotype is determined by genetics and whether major gene mutations are likely to exist inform veterinarians and working/stock dog communities of the true nature of this condition.

Machine learning for identifying resistance features of Klebsiella pneumoniae using whole-genome sequence single nucleotide polymorphisms.

Introduction. Klebsiella pneumoniae, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of K. pneumoniae is increasing year by year, posing a severe threat to public health worldwide. K. pneumoniae has been listed as one of the pathogens causing the global crisis of antimicrobial resistance in nosocomial infections. We need to explore the drug resistance of K. pneumoniae for clinical diagnosis. Single nucleotide polymorphisms (SNPs) are of high density and have rich genetic information in whole-genome sequencing (WGS), which can affect the structure or expression of proteins. SNPs can be used to explore mutation sites associated with bacterial resistance.Hypothesis/Gap Statement. Machine learning methods can detect genetic features associated with the drug resistance of K. pneumoniae from whole-genome SNP data.Aims. This work used Fast Feature Selection (FFS) and Codon Mutation Detection (CMD) machine learning methods to detect genetic features related to drug resistance of K. pneumoniae from whole-genome SNP data.Methods. WGS data on resistance of K. pneumoniae strains to four antibiotics (tetracycline, gentamicin, imipenem, amikacin) were downloaded from the European Nucleotide Archive (ENA). Sequence alignments were performed with MUMmer 3 to complete SNP calling using K. pneumoniae HS11286 chromosome as the reference genome. The FFS algorithm was applied to feature selection of the SNP dataset. The training set was constructed based on mutation sites with mutation frequency >0.995. Based on the original SNP training set, 70% of SNPs were randomly selected from each dataset as the test set to verify the accuracy of the training results. Finally, the resistance genes were obtained by the CMD algorithm and Venny.Results. The number of strains resistant to tetracycline, gentamicin, imipenem and amikacin was 931, 1048, 789 and 203, respectively. Machine learning algorithms were applied to the SNP training set and test set, and 28 and 23 resistance genes were predicted, respectively. The 28 resistance genes in the training set included 22 genes in the test set, which verified the accuracy of gene prediction. Among them, some genes (KPHS_35310, KPHS_18220, KPHS_35880, etc.) corresponded to known resistance genes (Eef2, lpxK, MdtC, etc). Logistic regression classifiers were established based on the identified SNPs in the training set. The area under the curves (AUCs) of the four antibiotics was 0.939, 0.950, 0.912 and 0.935, showing a strong ability to predict bacterial resistance.Conclusion. Machine learning methods can effectively be used to predict resistance genes and associated SNPs. The FFS and CMD algorithms have wide applicability. They can be used for the drug-resistance analysis of any microorganism with genomic variation and phenotypic data. This work lays a foundation for resistance research in clinical applications.

Loss of chromatin remodeler DDM1 causes segregation distortion in Arabidopsis thaliana.

In ddm1 mutants, the DNA methylation is primarily affected in the heterochromatic region of the chromosomes, which is associated with the segregation distortion of SNPs in the F2 progenies. Segregation distortion (SD) is common in most genetic mapping experiments and a valuable resource to determine how gene loci induce deviation. Meiotic DNA crossing over and SD are under the control of several types of epigenetic modifications. DNA methylation is an important regulatory epigenetic modification that is inherited across generations. In the present study, we investigated the relationship between SD and DNA methylation. The ecotypes Col-0/C24 and chromatin remodeler mutants ddm1-10/Col and ddm1-15/C24 were reciprocally crossed to obtain F2 generations. A total of 300 plants for each reciprocally crossed plant in the F2 generations were subjected to next-generation sequencing to detect the single-nucleotide polymorphisms (SNPs) as DNA markers. All SNPs were analyzed using the Chi-square test method to determine their segregation ratio in F2 generations. Through the segregation ratio, whole-genome SNPs were classified into 16 classes. In class 10, the SNPs in the reciprocal crosses of wild type showed the expected Mendelian ratio of 1:2:1, while those in the reciprocal crosses of ddm1 mutants showed distortion. In contrast, all SNPs in class 16 displayed a normal 1:2:1 ratio, and class 1 showed SD, regardless of wild type or mutants, as assessed using CAPS (cleaved amplified polymorphic sequences) marker analysis to confirm the next-generation sequencing. In ddm1 mutants, the DNA methylation is highly reduced throughout the whole genome and more significantly in the heterochromatic regions of chromosomes. Our results showed that the ddm1 mutants exhibit low levels of DNA methylation, which facilitates the SD of SNPs primarily located in the heterochromatic region of chromosomes by reducing the heterozygous ratio. The present study will provide a strong base for future research focusing on the impact of DNA methylation on trait segregation and plant evolution.

Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy.

BackgroundUncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels.ResultsWe describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks.ConclusionsGenome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.