Assessing the conservation impact of Chinese indigenous chicken populations between ex-situ and in-situ using genome-wide SNPs

Conservation programs require rigorous evaluation to ensure the preservation of genetic diversity and viability of conservation populations. In this study, we conducted a comparative analysis of two indigenous Chinese chicken breeds, Gushi and Xichuan black-bone, using whole-genome SNPs to understand their genetic diversity, track changes over time and population structure. The breeds were divided into five conservation populations(GS1, 2010, ex-situ;GS2, 2019, ex-situ;GS3, 2019, in-situ;XB1, 2010, in-situ;and XB2, 2019, in-situ) based on conservation methods and generations. The genetic diversity indices of three conservation populations of Gushi chicken showed consistent trends, with the GS3 population under in-situ strategy having the highest diversity and GS2 under ex-situ strategy having the lowest. The degree of inbreeding of GS2 was higher than that of GS1 and GS3. Conserved populations of Xichuan black-bone chicken showed no obvious changes in genetic diversity between XB1 and XB2. In terms of population structure, the GS3 population were stratified relative to GS1 and GS2. According to the conservation priority, GS3 had the highest contribution to the total gene and allelic diversity in GS breed, whereas the contribution of XB1 and XB2 were similar. We also observed that the genetic diversity of GS2 was lower than GS3, which were from the same generation but under different conservation programs(in-situ and ex-situ). While XB1 and XB2 had similar levels of genetic diversity. Overall, our findings suggested that the conservation programs performed in ex-situ could slow down the occurrence of inbreeding events, but could not entirely prevent the loss of genetic diversity when the conserved population size was small, while in-situ conservation populations with large population size could maintain a relative high level of genetic diversity.

Genome-wide SNP markers provided insights into the reproductive strategy and genetic diversity of the green tide causative species Ulva prolifera in China

Ulva prolifera is the causative species of the annually occurring large-scale green tides in China since 2007.Its specific biological features on reproductivity strategies,as well as intra-species genetic diversity,are still largely unknown,especially at the genome level,despite their importance in understanding the formation and outbreak of massive green tides.In the present study,the restriction site-associated DNA genotyping approach(2b-RAD)was adopted to identify the genome-wide single-nucleotide polymorphisms(SNPs)of 54 individual thalli including samples collected from Subei Shoal in 2019 and Qingdao coast from 2019 to 2021.SNPs genotype results revealed that most of the thalli in 2019 and 2020 were haploid gametophytes,while only half of the thalli were gametophytes in 2021,indicating flexibility in the reproductive strategies for the formation of the green tides among different years and the dominance of asexual and vegetative reproductive mode for the floating period.Besides,population analysis was conducted,and it revealed a very low genetic diversity among samples from Subei Shoal and the Qingdao coast in the same year and a higher divergence among samples in different years.The results showed the efficiency of 2b-RAD in the exploration of SNPs in U.prolifera and provided the first genome-wide scale evidence for the origin of the large-scale green tides on the Qingdao coast.This study improved our understanding of the reproductive strategy and genetic diversity of the green tide causative species and will help further reveal the biological causes of the green tide in China.

SHEsisEpi, a GPU-enhanced genome-wide SNP-SNP interaction scanning algorithm, efficiently reveals the risk genetic epistasis in bipolar disorder

Dear Editor, We developed a GPU-based analytical method, named as SHEsisEpi, which purely focuses on risk epistasis in a genome-wide association study （GWAS） of complex traits, excluding the contamination of marginal effects caused by single-locus association. We analyzed the Wellcome Trust Case Control Consortium＇s （WTCCC） GWAS data of bipolar disorder （BPD） with 500K SNPs.

A simple way to visualize detailed phylogenetic tree of huge genome-wide SNP data constructed by SNPhylo

Phylogenetic trees based on genome-wide single nucleotide polymorphisms （SNPs） among diverse inbreds could provide valuable and intuitive information for breeding and germplasm management in crops. As a result of sequencing technology developments, a huge amount of whole genome SNP data have become available and affordable for breeders. However, it is a challenge to perform quick and reliable plotting based on the huge amount of SNP data. To meet this goal, a visualization pipeline was developed and demonstrated based on publicly available SNP data from the current important maize inbred lines, including temperate, tropical, sweetcorn, and popcorn. The detailed phylogenetic tree plotted by our pipeline revealed the authentic genetic diversity of these inbreds, which was consistent with several previous reports and indicated that this straightforward pipeline is reliable and could potentially speed up advances in crop breeding.

Genome-Wide SNPs Identification and Determination of Proteins Associated with Stress Response in Sorghum (<i>Sorghum bicolor</i>L. Monech) Accessions

Current efforts in sorghum breeding programs are exploiting genotyping-by-sequencing (GBS) data to provide full-genome scans for desired traits. The aim of this study was to utilize GBS approach for the identification of genomic regions associated with stress response in sorghum (Sorghum bicolor L. Monech) accessions. DNA samples of twenty sorghum accessions, having different response to drought, were used to prepare GBS libraries for sequencing. SNPs were called using the TASSELGBS pipeline and the tags that present at least 10 times in the dataset were considered and aligned to the reference genome of Sorghum bicolor. The identified SNPs were all compared with the published sorghum transcript related to stress response gene activity. Overall;94.40% tags were aligned and 69,736 putative SNPs positions were identified. Blast search revealed homology to annotated heat and drought–tolerance associated genes which code for ATPases, Peroxidase, Hydrophobic protein LTI6A, Aquaporin SIP2-1, Aconitate hydratase and phosphatidylinositol-4-phosphate-5-kinase. The phylogeny of the 20 accessions was constructed using the generated SNPs data. Phylogenetic analysis data showed that the phenotypically tolerant line (El9)?makes a separate cluster and the same for the accessions HSD8653 and HSD5612 near to the cluster that includes most accessions with known post-flowering drought tolerance (HSD7410, HDS10033, HSD8552, GESHEISH and HSD8849). Post-flowering drought sensitive accessions (Tabat, Wadahmed, HSD6468 and HSD6478) formed a separate cluster while the sensitive accession HSD9959 and the tolerant accessions HSD8511 and HSD9566 were distributed between the two clusters. Thus, cluster analysis confirmed the variation among accessions in post-flowering drought tolerance. With further validation, these markers may be used for marker assisted selection for breeding new sorghum genotypes with stress adaptation.

Large-scale genome-wide SNP analysis reveals the rugged(and ragged)landscape of global ancestry,phylogeny,and demographic history in chicken breeds

The worldwide chicken gene pool encompasses a remarkable,but shrinking,number of divergently selected breeds of diverse origin.This study was a large-scale genome-wide analysis of the landscape of the complex molecular architecture,genetic variability,and detailed structure among 49 populations.These populations represent a significant sample of the world's chicken breeds from Europe(Russia,Czech Republic,France,Spain,UK,etc.),Asia(China),North America(USA),and Oceania(Australia).Based on the results of breed genotyping using the Illumina 60K single nucleotide polymorphism(SNP)chip,a bioinformatic analysis was carried out.This included the calculation of heterozygosity/homozygosity statistics,inbreeding coefficients,and effective population size.It also included assessment of linkage disequilibrium and construction of phylogenetic trees.Using multidimensional scaling,principal component analysis,and ADMIXTURE-assisted global ancestry analysis,we explored the genetic structure of populations and subpopulations in each breed.An overall 49-population phylogeny analysis was also performed,and a refined evolutionary model of chicken breed formation was proposed,which included egg,meat,dual-purpose types,and ambiguous breeds.Such a large-scale survey of genetic resources in poultry farming using modern genomic methods is of great interest both from the viewpoint of a general understanding of the genetics of the domestic chicken and for the further development of genomic technologies and approaches in poultry breeding.In general,whole genome SNP genotyping of promising chicken breeds from the worldwide gene pool will promote the further development of modern genomic science as applied to poultry.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

Background Copy number variants(CNV)hold significant functional and evolutionary importance.Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock.High-density chips have enabled the detection of CNV with increased resolution,leading to the identification of even small CNV.This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.Results Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV.The majority of CNV in the investigated breeds were of types 0 and 1,and the minimum length of CNV was significantly larger than that reported in previous studies.Interestingly,a high proportion of the length of chromosome 16 was covered by copy number variation regions(CNVR),with the major histocompatibility complex being the likely cause.Among the genes identified within CNVR,only those present in at least five animals across breeds(n=95)were discussed to reduce the focus on redundant CNV.Some of these genes have been associated to functional traits in chickens.Notably,several CNVR on different chromosomes harbor genes related to muscle development,tissue-specific biological processes,heat stress resistance,and immune response.Quantitative trait loci(QTL)were also analyzed to investigate potential overlapping with the identified CNVR:54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size,carcass characteristics,egg production,egg components,fat deposition,and feed intake.Conclusions The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Genome-Wide Association Study and Genomic Selection for Plant Growth Habit in Peanuts Using the USDA Public Data

Peanut (Arachis hypogaea L.) production is valued at $1.28 billion annually in the USA. Plant growth habit can be used to determine plant population density and cultivation practices a given farmer uses. Erect plants are generally more compact and can be more densely planted unlike plants with more prostrate growth. The objectives of this study were to analyze publicly available datasets to identify single-nucleotide polymorphism (SNP) markers associated with plant growth habit in peanuts and to conduct genomic selection. A genome-wide association study (GWAS) was used to identify SNPs for growth habit type among 775 USDA peanut accessions. A total of 13,306 SNPs were used to conduct GWAS using five statistical models. The models used were single-marker regression, generalized linear model (PCA), generalized linear model (Q), mixed linear model (PCA), and mixed linear model (Q) and a total of 181, 1, 108, 1, and 10 SNPs were found associated with growth habit respectively. Based on this dataset, results showed that genomic selection can achieve up to 61% accuracy, depending on the training population size being used for the prediction. SNP AX-176821681 was found in all models. Gene ontology for this location shows an annotated gene, Araip.0F3YM, found 2485 bp upstream of this SNP and encodes for a peptidyl-prolyl cis-trans isomerase. To the best of our knowledge, this is the first report identifying molecular markers linked to plant growth habit type in peanuts. This finding suggests that a molecular marker can be developed to identify specific plant growth habits in peanuts, enabling early generation selection by peanut breeders.

Epistasis-aware genome-wide association studies provide insights into the efficient breeding of high-yield and high-quality rice

Marker-assisted selection(MAS)and genomic selection(GS)breeding have greatly improved the efficiency of rice breeding.Due to the influences of epistasis and gene pleiotropy,ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.In this study,113 indica rice varieties(V)and their 565 testcross hybrids(TC)were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.The original traits and general combining ability of the parents,as well as the original traits and midparent heterosis of TC,were subjected to genome-wide association analysis.In total,381 primary significantly associated loci(SAL)and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.Among these loci,322 candidate genes located within or nearby the SALs were screened,204 of which were cloned genes.A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.All the SALs were used to construct genetic networks,in which 91 pleiotropic loci were investigated.Additionally,we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs,primary SALs,secondary SALs or epistatic effect SALs as covariates.Although the prediction accuracies of the four models were generally not significantly different in the TC dataset,the incorporation of primary SALs,secondary SALs,and epistatic effect SALs significantly improved the prediction accuracies of 5(26%),3(16%),and 11(58%)traits in the V dataset,respectively.These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.

Genome-Wide Association Study of Cooked Rice Textural Attributes and Starch Physicochemical Properties in indica Rice

Rice cooking and eating qualities(CEQ)are mainly determined by cooked rice textural parameters and starch physicochemical properties.However,the genetic bases of grain texture and starch properties in rice have not been fully understood.We conducted a genome-wide association study for apparent amylose content(AAC),starch pasting viscosities,and cooked rice textural parameters using 279 indica rice accessions from the 3000 Rice Genome Project.We identified 26 QTLs in the whole population and detected single nucleotide polymorphisms(SNPs)with the lowest P-value at the Waxy(Wx)locus for all traits except pasting temperature and cohesiveness.Additionally,we detected significant SNPs at the SUBSTANDARD STARCH GRAIN6(SSG6)locus for AAC,setback(SB),hardness,adhesiveness,chewiness(CHEW),gumminess(GUM),and resilience.We subsequently divided the population using a SNP adjacent to the Waxy locus,and identified 23 QTLs and 12 QTLs in two sub-panels,WxT and WxA,respectively.In these sub-panels,SSG6 was also identified to be associated with pasting parameters,including peak viscosity,hot paste viscosity,cold paste viscosity,and consistency viscosity.Furthermore,a candidate gene encoding monosaccharide transporter 5(OsMST5)was identified to be associated with AAC,breakdown,SB,CHEW,and GUM.In total,39 QTLs were co-localized with known genes or previously reported QTLs.These identified genes and QTLs provide valuable information for genetic manipulation to improve rice CEQ.

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

Genome-wide association study of seedling nitrogen-use efficiency-associated traits in common wheat(Triticum aestivum L.)

Nitrogen(N)fertilizer application is essential for crop-plant growth and development.Identifying genetic loci associated with N-use efficiency(NUE)could increase wheat yields and reduce environmental pollution caused by overfertilization.We subjected a panel of 389 wheat accessions to N and chlorate(a nitrate analog)treatments to identify quantitative trait loci(QTL)controlling NUE-associated traits at the wheat seedling stage.Genotyping the panel with a 660K single-nucleotide polymorphism(SNP)array,we identified 397 SNPs associated with N-sensitivity index and chlorate inhibition rate.These SNPs were merged into 49 QTL,of which eight were multi-environment stable QTL and 27 were located near previously reported QTL.A set of 135 candidate genes near the 49 QTL included TaBOX(F-box family protein)and TaERF(ethylene-responsive transcription factor).A Tabox mutant was more sensitive to low-N stress than the wild-type plant.We developed two functional markers for Hap 1,the favorable allele of TaBOX.

Genome-Wide Analysis for Yield-Related Agronomic and Biochemical Traits of Chinese and Bangladeshi Grass Pea Genotypes Using SSR Markers

Grass pea(Lathyrus sativus L.)is an imperative food crop cultured in dryland agricultural ecology.It is a vital source of dietary protein to millions of populaces living in low-income countries in South-East Asia and Africa.This study highlights the improvement of genomic properties and their application in marker-trait relationships for 17 yield-related characters in 400 grass pea genotypes from China and Bangladesh.These characters were assessed via 56 polymorphic markers using general linear model(GLM)(P+G+Q)and mixed linear model(MLM)(P+G+Q+K)in the tassel software based on the linkage disequilibrium and population structure analysis.Population structure analysis showed two major groups and one admixed group in the populace.Statistically significant loci pairs of linkage disequilibrium(LD)mean value(D′)was 0.479.A total of 99 and 61 marker-trait associations in GLM and MLM models allied to the 17 traits were accepted at a 5%level of significance.Among these markers,21 markers were associated with more than one trait;12 marker-trait associations passed the Bonferroni correction threshold.Both models found six markers C41936,C39067,C34100,C47146,C47638,and C43047 significantly associated with days to maturity,flower color,plant height,and seed per pod were detected in the Hebei and Liaoyang location(p≤0.01),and the interpretation rate(R^(2)value)11.2%to 43.6%.Conferring to the consequences,the association analysis methodology may operative system for quantitative,qualitative,and biochemical traits related to gene position mapping and support breeders in improving novel approaches for advancing the grass pea quality.

Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

Combining genome-wide association study and transcriptome analysis to identify molecular markers and genetic basis of population-asynchronous ovarian development in Coilia nasus

Coilia nasus,a migratory fish species found in the middle and lower reaches of the Yangtze River and along offshore areas of China,possesses considerable aquacultural and economic potential.However,the species faces challenges due to significant variation in the gonadal development rate among females,resulting in inconsistent ovarian maturation times at the population level,an extended reproductive period,and limitations on fish growth rate due to ovarian prematurity.In the present study,we combined genome-wide association study(GWAS)and comparative transcriptome analysis to investigate the potential single nucleotide polymorphisms(SNPs)and candidate genes associated with population-asynchronous ovarian development in C.nasus.Genotyping of the female population based on whole-genome resequencing yielded 2120695 high-quality SNPs,39 of which were suggestively associated with ovarian development.Of note,a significant SNP peak on LG21 containing 30 suggestively associated SNPs was identified,with cpne5a determined as the causal gene of the peak.Therefore,single-marker and haplotype association analyses were performed on cpne5a,revealing four genetic markers(P<0.05)and seven haplotypes(r2>0.9)significantly associated with the phenotype.Comparative transcriptome analysis of precociously and normally maturing individuals screened out 29 and 426 overlapping differentially expressed genes in the brain and ovary,respectively,between individuals of different body sizes.Integrating the GWAS and transcriptome analysis results,this study identified genes and pathways related to hypothalamic-pituitary-gonadal axis hormone secretion,extracellular matrix,angiogenesis,and gap junctions involved in population-asynchronous ovarian development.The insights gained from this study provide a basis for a deeper understanding of the molecular mechanisms underlying ovarian development in fish and may facilitate the genetic breeding of C.nasus strains exhibiting population-synchronous ovarian development in the future.

Genome-Wide Discovery and Expression Profiling of the SWEET Sugar Transporter Gene Family in Woodland Strawberry (Fragaria vesca) under Developmental and Stress Conditions: Structural and Evolutionary Analysis

The SWEET(sugar will eventually be exported transporter)family proteins are a recently identified class of sugar transporters that are essential for various physiological processes.Although the functions of the SWEET proteins have been identified in a number of species,to date,there have been no reports of the functions of the SWEET genes in woodland strawberries(Fragaria vesca).In this study,we identified 15 genes that were highly homolo-gous to the A.thaliana AtSWEET genes and designated them as FvSWEET1–FvSWEET15.We then conducted a structural and evolutionary analysis of these 15 FvSWEET genes.The phylogenetic analysis enabled us to categor-ize the predicted 15 SWEET proteins into four distinct groups.We observed slight variations in the exon‒intron structures of these genes,while the motifs and domain structures remained highly conserved.Additionally,the developmental and biological stress expression profiles of the 15 FvSWEET genes were extracted and analyzed.Finally,WGCNA coexpression network analysis was run to search for possible interacting genes of FvSWEET genes.The results showed that the FvSWEET10 genes interacted with 20 other genes,playing roles in response to bacterial and fungal infections.The outcomes of this study provide insights into the further study of FvSWEET genes and may also aid in the functional characterization of the FvSWEET genes in woodland strawberries.

Genome-wide and candidate gene association studies identify BnPAP17 as conferring the utilization of organic phosphorus in oilseed rape

Phosphorus(P)is essential for living plants,and P deficiency is one of the key factors limiting the yield in rapeseed production worldwide.As the most important organ for plants,root morphology traits(RMTs)play a key role in P absorption.To investigate the genetic variability of RMT under low P availability,we dissected the genetic structure of RMTs by genome-wide association studies(GWAS),linkage mapping and candidate gene association studies(CGAS).A total of 52 suggestive loci were associated with RMTs under P stress conditions in 405 oilseed rape accessions.The purple acid phosphatase gene BnPAP17 was found to control the lateral root number(LRN)and root dry weight(RDW)under low P stress.The expression of BnPAP17 was increased in shoot tissue in P-efficient cultivars compared to root tissue and P-inefficient cultivars in response to low P stress.Moreover,the haplotype of BnPAP17^(Hap3)was detected for the selective breeding of P efficiency in oilseed rape.Over-expression of the BnPAP17^(Hap3)could promote the shoot and root growth with enhanced tolerance to low P stress and organic phosphorus(Po)utilization in oilseed rape.Collectively,these findings increase our understanding of the mechanisms underlying BnPAP17-mediated low P stress tolerance in oilseed rape.

Genome-Wide Exploration of the Grape GLR Gene Family and Differential Responses of VvGLR3.1 and VvGLR3.2 to Low Temperature and Salt Stress

Grapes,one of the oldest tree species globally,are rich in vitamins.However,environmental conditions such as low temperature and soil salinization significantly affect grape yield and quality.The glutamate receptor(GLR)family,comprising highly conserved ligand-gated ion channels,regulates plant growth and development in response to stress.In this study,11 members of the VvGLR gene family in grapes were identified using whole-genome sequence analysis.Bioinformatic methods were employed to analyze the basic physical and chemical properties,phylogenetic trees,conserved domains,motifs,expression patterns,and evolutionary relationships.Phylogenetic and collinear analyses revealed that the VvGLRs were divided into three subgroups,showing the high conservation of the grape GLR family.These members exhibited 2 glutamate receptor binding regions(GABAb and GluR)and 3-4 transmembrane regions(M1,M2,M3,and M4).Real-time quantitative PCR analysis demonstrated the sensitivity of all VvGLRs to low temperature and salt stress.Subsequent localization studies in Nicotiana tabacum verified that VvGLR3.1 and VvGLR3.2 proteins were located on the cell membrane and cell nucleus.Additionally,yeast transformation experiments confirmed the functionality of VvGLR3.1 and VvGLR3.2 in response to low temperature and salt stress.Thesefindings highlight the significant role of the GLR family,a highly conserved group of ion channels,in enhancing grape stress resistance.This study offers new insights into the grape GLR gene family,providing fundamental knowledge for further functional analysis and breeding of stress-resistant grapevines.

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data

Coronary artery disease （CAD） is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism （SNP） profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium （WTCCC） SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene-gene interactions involved in these susceptible pathways with their protein protein interaction （PPI） knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer＇s disease, non-alcoholic fatty liver disease, and Huntington＇s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer＇s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer＇s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

基于Super-GBS简化基因组测序技术的柞蚕SNP位点挖掘

基于Super-GBS基因分型(super-genotyping-by-sequencing)技术开展柞蚕单核苷酸多态性标记(single nucleotide polymorphism,SNP)位点挖掘研究,旨在开发性状关联SNP分子标记,为柞蚕种质资源评价鉴定、遗传图谱构建、QTL定位提供数据支撑。以白体色小白蚕为母本、黄体色H04为父本,获得BC1M群体(110个)、F_(1)(3个)、P_(1)(1个)、P_(2)(1个)总计115个柞蚕材料,利用PstⅠ-HF/MspⅠ双酶切基因组构建Super-GBS文库并测序,使用BWA软件将过滤后的序列数据比对到柞蚕参考基因组,采用GATK软件开发SNP标记,使用SnpEff软件注释SNP位点及R语言分析遗传结构。测序共产生序列数据量为106.39 Gb,过滤后的平均读长为0.89 Gb,Q30测序质量值平均为90.11%,比对率平均为98.48%。共得到有效SNP位点141100个,主要位于基因间隔区、内含子区、基因下游、上游,其中C/T、A/G变异类型最多,转换与颠换的比例为1.296187∶1。SNP位点变异主要为同义突变和错义突变,产生修饰(MODIFIER)影响。主成分与聚类分析将115个样品分为4组(P_(1)、P_(2)、F_(1)、BC_(1)M),反映了样品的遗传背景及亲缘关系,群体遗传分化指数F_(ST)在0.0003777~0.8272间,群体遗传距离DR分布在0.0004~1.7556,F_(ST)与DR均表现出明显的遗传背景上的聚类。结果表明,Super-GBS技术能够获得大量柞蚕SNP位点信息,可用于SNP标记开发,且开发的SNP标记能够对115个样品的亲缘关系、体色演变进行解释,为今后柞蚕种质资源评价与鉴定、分子标记辅助育种工作奠定基础。