甜瓜叶绿素含量全基因组关联分析及候选基因预测

【目的】挖掘与叶绿素含量显著关联的单核苷酸多态性(single nucleotide polymorphism, SNP)位点和候选基因,为甜瓜叶绿素含量改良提供分子靶点和基因资源。【方法】以118份具有广泛变异的甜瓜种质为自然群体,采用2 531 449个高质量SNP标记对叶片叶绿素含量进行全基因组关联分析,挖掘优异等位变异,并预测候选基因。【结果】甜瓜自然群体叶绿素含量趋向正态分布,包含5个明显的亚群。利用Q模型对2次试验的叶绿素含量及其最佳线性无偏预测(best linear unbiased prediction, BLUP)值进行关联分析,共检测到15个显著位点,分布在甜瓜第1、2、4、8、11、12号染色体上,表型贡献解释率为5.62%～6.69%。其中,8个位点的不同基因型之间存在显著表型差异。结合关联位点的候选区域和转录组数据,共鉴定到28个差异表达基因,其中MELO3C018513.2和MELO3C003666.2是改良甜瓜叶绿素含量的潜在候选基因。【结论】通过高质量SNP标记Q模型的全基因组关联分析,共检测到15个与叶绿素含量显著关联的位点,筛选出2个可能与叶绿素含...     

部分春大豆主栽品种叶绿素含量全基因组关联分析

叶绿素是植物光合作用主要色素,对大豆产量形成具有重要影响。利用196份已重测序的国内外品种构成自然群体为试验材料,测定该群体苗期叶绿素含量,结合混合线性模型（Mixed linear model）进行全基因组关联分析。结果表明,根据阈值筛选得到37个显著相关SNP位点,分别位于第2、3、4、7、10、13、16号染色体上,在SNP位点上下游各100 kb搜索到194个相关基因。通过GO功能富集分析、KEGG代谢通路富集分析及基因功能注释,筛选得到11个可能与叶绿素含量相关的候选基因,通过相对表达量分析鉴定得到4个Glyma.02G185300、Glyma.03G085000、Glyma.10G259900、Glyma.16G037100与大豆叶绿素含量相关基因。研究结果为探究大豆叶绿素含量遗传机理提供理论参考。     

广益黑猪繁殖性状的全基因组关联分析

选取441头广益黑猪经产母猪为研究对象,利用猪50K SNP芯片对猪耳组织DNA进行基因型分型,PLINK 1.9质控后,采用GMAT中的重复力模型进行猪繁殖性状相关的全基因组关联分析,确定显著位点。结果表明：441头经产广益黑猪母猪的耳组织DNA基因分型共获得50 898个SNPs,经质控剩余46 165个SNPs位点用于关联分析;平均亲缘关系系数为–0.002 2,平均亲缘关系较远,不存在明显的群体分层;总产仔数性状有1个SNP在全基因组范围内达到显著相关,4个SNPs达到潜在显著关联,候选基因包括PIK3C3、ENSSSCG00000003753、MAP3K3、DCAF7;产活仔数性状有6个SNPs潜在显著关联,候选基因包括ZNF585A、ENSSSCG00000022411、ZNF784、ENSSSCG00000029007、PigE–108A11.5、PigE–108A11.3、ENSSSCG00000023343;弱仔性状有1个SNP达潜在显著关联,候选基因包括KRTAP7–1和TIAM1;经基因功能分析推测,PIK3C3、MAP3K3可能是影响猪总产仔数的候选基因。     

甘蓝型油菜角果长度全基因组关联分析

【目的】挖掘与油菜角果长度性状显著相关的SNP位点及候选基因,为揭示油菜角果长度性状的遗传基础和分子机制提供理论依据,为油菜产量分子标记辅助选择育种奠定基础。【方法】在江西农业大学试验地和江西省红壤研究所试验地2个环境下考察300份甘蓝型油菜自交系的角果长度性状,利用简化基因组测序技术(specific locus amplified fragment sequencing,SLAF-seq)对300份甘蓝型油菜自交系基因组DNA进行测序并分析,利用获得的均匀分布于甘蓝型油菜基因组上的201 817个群体SNP(single nucleotide polymorphism,SNP)对角果长度性状进行全基因组关联分析(genome-wide association study,GWAS),探测与油菜角果长度显著相关的SNP位点,并基于群体连锁不平衡分析结果搜寻显著SNP位点两侧100 kb范围内的基因,通过BLAST获得关联区域内基因的注释信息,根据注释信息找出与性状相关的候选基因。【结果】农大试验地角果长度表型变异幅度为46.35—107.07 mm;红壤所试验地角果长度表型变异幅度为39.41—101.35 mm,两性状在2个环境下均表现出广泛表型变异。通过一般线性模型(general linear model,GLM)关联分析,农大环境下共检测到121个角果长度显著关联的SNP位点,分布在A04、A06、A08、A09、C02、C03、C06和C09等8条染色体上,其中,A09染色体上分布最多(83个SNP),红壤所环境下检测到22个角果长度显著关联的SNP位点,其中,1个在C09染色体上,其余21个均分布于A09染色体,在两地探测到20个一致性SNP位点;通过混合线性模型(mixed linear model,MLM)分析,农大环境下共检测到5个角果长度显著关联的SNP位点,其中,3个SNP位点与红壤所环境下检测到3个SNP位点一致,所有位点均位于A09染色体上。对MLM关联分析得到的显著SNP位点两侧100 kb区域内基因进行搜寻并进行功能注释,发现多个候选基因参与调节碳水化合物的运输与合成、花器官和种子的发育、信号转导等,它们可能通过上述功能影响油菜角果的生长,导致角果长度的差异。【结论】通过GLM和MLM两种分析方法探测到多个与油菜角果长度性状显著关联的基因位点,并在显著性位点附近搜寻到相关候选基因。     

春小麦籽粒主要品质性状的全基因组关联分析

[目的]挖掘小麦籽粒品质性状显著相关的SNP位点及候选基因,并揭示其遗传机理,为相关基因克隆和分子标记辅助选择提供理论依据.[方法]通过检测298份国内外春小麦品种(系)5个环境下蛋白质含量、湿面筋含量、沉降值、淀粉含量、籽粒硬度、出粉率和容重等7个籽粒品质性状的表型,并结合小麦55K SNP芯片,采用Q+K关联混合模...     

杜长大猪、二花脸猪和莱芜猪3个群体25种血液性状的全基因组关联分析

【目的】 利用全基因组关联分析定位影响杜长大猪（DLY）、二花脸猪（EHL）和莱芜猪（LW）3个群体25种血液性状的染色体位点,为最后鉴定影响这些性状的因果基因提供前期基础,同时为猪抗病育种和生产提供参考。【方法】将610头杜长大三元杂猪在（180±5）日龄,336头二花脸猪和333头莱芜猪在（300±5）日龄进行统一屠宰。收集2 mL血液于抗凝管中,利用全自动生化分析仪进行25种血液性状的血常规检测。采集猪耳组织提取DNA并测浓度和质量。将质检合格的DNA样品利用Illumina 60K SNP芯片进行基因型判定。运用PLINK软件对判型结果进行质量控制,将合格的SNP标记用于后续的关联分析。使用R语言GenABEL软件包中的广义混合线性模型进行全基因组关联分析,定位影响3个群体25种血常规性状的显著性染色体位点。据全基因组关联分析结果,在Ensembl或NCBI网站上搜寻潜在的位置候选基因。【结果】杜长大猪、二花脸猪和莱芜猪三个群体通过质控的有效表型数据个体数分别为552头、325头和281头。60K SNPs经过质量控制过后,杜长大猪剩余56 216 SNPs,莱芜猪剩余49 343 SNPs,二花脸猪剩余35 974 SNPs,用于Meta分析的SNPs共有32 967。运用全基因组关联分析和Meta分析共定位到610个显著影响3个群体25种血液性状的SNPs,其中135个SNPs达基因组显著水平,475个SNPs达建议水平;分布在所有染色体上。在杜长大猪中共鉴别到32个基因组显著水平SNPs以及85个建议水平SNPs,且8种性状有基因组显著水平的SNPs,分别是淋巴细胞数目（LYM）、淋巴细胞比率（LYMR）、嗜碱性粒细胞数目（BAS）、嗜碱性粒细胞比率（BASR）、平均红细胞体积（MCV）、红细胞分布宽度变异系数（RDW_CV）、平均红细胞血红蛋白含量（MCH）和血小板分布宽度（PDW）。在二花脸猪中共鉴别到33个基因组显著水平SNPs以及139个建议水平SNPs,且9种性状有基因组显著水平的SNPs,分别是LYM、MCH、平均红细胞血红蛋白浓度（MCHC）、单核细胞数目（MON）、单核细胞比率（MONR）、平均血小板体积（MPV）、中性粒细胞比率（NEUR）、大血小板细胞（P_LCC）以及血小板压积（PCT）。在莱芜猪中共鉴别到54个基因组显著水平SNPs以及169个建议水平SNPs,且6种性状有基因组显著水平的SNPs,分别是BASR、红细胞压积（HCT）、MCH、MCHC、MCV和红细胞数目（RBC）。在Meta分析结果中,共鉴别到16个基因组显著水平SNPs以及82个建议水平SNPs,且6种性状有基因组显著水平SNPs,分别是RBC、HCT、MCH、MCHC、MCV以及MON。通过在Ensembl或NCBI网站上搜寻最强相关SNP区域内的候选基因,初步将F13A1、SPTA1、DBNL、SLC25A28、CTSC基因分别确定为影响BASR、HCT、LYM、MCHC、NEUR的重要候选基因。【结论】通过全基因组关联分析和Meta分析共得到610个显著影响杜长大猪、二花脸猪和莱芜猪3个群体25种血液性状的SNP位点,初步确定F13A1、SPTA1、DBNL、SLC25A28和CTSC基因分别是BASR、HCT、LYM、MCHC和NEUR的重要位置候选基因,为解析商业猪和纯种地方猪的血液性状或免疫性疾病提供重要参考。     

小麦苗期根系性状的全基因组关联分析与优异位点挖掘

【目的】植物根系对水分及营养的获取、作物的生长发育和产量的形成至关重要。挖掘小麦苗期根系性状显著关联的SNP位点,预测相关候选基因,为解析小麦根系建成遗传机制及选育具有优良根系构型的小麦品种奠定基础。【方法】以189份小麦品种组成的自然群体为供试材料,调查2种培养条件（霍格兰营养液和去离子水）下培育21 d的苗期根系总长度（TRL）、根系总表面积（TRA）、根系总体积（TRV）、根系平均直径（ARD）及根系干重（RDW）等5个根系性状,试验进行2次重复,同时结合小麦660K SNP芯片的分型结果进行全基因组关联分析（genome-wide association study,GWAS）。此外,通过序列比对、结构域分析和注释信息预测候选基因,并采用竞争性等位基因特异性PCR(kompetitive allele specific PCR,KASP)技术开发根系性状的分子标记。【结果】霍格兰营养液培养条件下的根系性状变异范围较大,根系整体粗短;而去离子水条件下的根系细长、侧根较多。选用贝叶斯信息与连锁不平衡迭代嵌套式模型（BLINK）、压缩式混合线性模型（CMLM）、固定随机循环概率模型（...     

小麦籽粒超氧化物歧化酶（SOD）活性全基因组关联分析

【目的】小麦籽粒超氧化物歧化酶活性对小麦面粉色泽和营养品质具有重要影响,挖掘与小麦籽粒超氧化物歧化酶（superoxide dismutase,SOD）活性显著关联位点及候选基因,为揭示小麦籽粒SOD活性的遗传机理和小麦面粉色泽的遗传改良奠定基础。【方法】采用氮蓝四唑（nitro-blue tetrazolium,NBT）光化还原法对3个环境下种植的212份普通小麦品种（系）进行SOD活性检测,结合90K SNP芯片的16 705个高质量SNP标记对小麦籽粒SOD活性进行全基因组关联分析（genome-wide association study,GWAS）,并对稳定遗传的显著关联位点进行候选基因的挖掘。【结果】不同环境下,各小麦品种（系）间的SOD活性表现出丰富的表型变异,变异系数为4.34%—5.23%,相关系数介于0.60—0.90（P<0.001）。多态性信息含量（polymorphic information content,PIC）为0.24—0.29。全基因组连锁不平衡（linkage disequilibrium,LD）衰减距离为7 Mb。群体结构分析表明,供试材料可分为3个亚群。GWAS分析结果显示,共检测到29个与SOD活性显著关联位点（P≤0.001）,分布在1A、1B、2A、2B、2D、3B、3D、4B、4D、5A、5B、5D、6A、6B、6D和7B染色体上,单个位点可解释5.47%—32.43%的表型变异,其中14个位点在2个及以上环境下均被检测到。9个显著关联位点在3个环境下被同时检测到,分布于1B、2B、4B、5A、5B、6B和6D染色体,贡献率为6.21%—16.62%。对稳定遗传的显著关联位点进行候选基因的挖掘,共挖掘TraesCS2B01G567600、TraesCS3D01G069900、TraesCS3D01G070200、TraesCS5B01G525700、TraesCS5B01G373700、TraesCS6A01G021400和TraesCS6D01G431500等7个SOD基因和TraesCS5A01G263500、TraesCS6B01G707800等2个与SOD活性相关的候选基因,候选基因的功能主要与抑制细胞活性氧积累及参与抗氧化剂再生过程有关。【结论】检测到与小麦籽粒SOD活性显著关联的29个SNP位点,共筛选出7个SOD基因和2个与SOD活性有关的候选基因。     

小麦籽粒镉元素含量全基因组关联分析及候选基因预测

以国内外207份小麦种质为材料,利用660K SNP芯片对其进行基因型检测,并结合不同环境下表型数据和最佳线性无偏预测值 (BLUP,Best linear unbiased prediction) 对小麦籽粒镉元素含量进行全基因组关联分析。结果表明：与小麦籽粒镉元素含量显著关联的SNP 310个,这些SNP分布于除3D和4D外的19条染色体上,单个SNP解释变异率为10.95%～14.66%。不同环境下检测到的关联SNP结果存在差异,其中在原阳地区检测到186个SNP,开封地区检测到71个SNP。基于BLUP值分析获得53个SNP。基于SNP物理位置,将距离较近的SNP进行整合,共获得有效QTL位点52个。同时发现了7个在多环境下表现稳定的SNP,并对其进行单标记效应分析。最后对基于获得的关联SNP进行了候选基因预测,共获得7个与小麦籽粒镉元素含量相关的候选基因,其中 TraesCS1B01G321700和TraesCS1B01G320200可能与镉元素调控相关基因转录有关,而TraesCS7B01G459000和TraesCS7B01G456900可能与镉元素的吸收和转运等代谢过程有关。还筛选出了对镉具有良好避性的部分小麦优异种质,如‘云麦51’‘郑麦379’‘白穗白’‘云麦53’‘双丰收’。     

杜洛克猪生长性状全基因组关联分析

对猪全基因组高密度SNP基因型数据及生长性状表型数据进行全基因组关联分析,以期找到影响这些性状的候选基因,更准确地了解这些生长性状的遗传基础。利用Illumina猪60KSNP芯片对191头杜洛克猪进行基因型检测,使用R语言环境下GenABEL 软件包提供的单标记回归分析模型,对体重达100 kg 日龄(D100)、活体背膘厚(BFT)和活体眼肌面积(LMA)3个生长性状的表型分别进行全基因组关联分析。在D100和LMA2个性状中分别检测到1个基因组水平和6个染色体水平显著关联的SNP,均位于5号染色体;没有检测到与BFT显著相关的SNP。生物信息学分析表明,BTG1和EFCAB6可能是影响生长性状的重要候选基因,但其功能有待进一步研究确认。关键词猪;全基因组关联分析;候选基因;生产性状。     

Genome-wide association study for rib eye muscle area in a Large White×Minzhu F_2 pig resource population

Rib eye muscle area(REMA) is an economically important trait and one of the main selection criteria for breeding in the swine industry. In the genome-wide association study(GWAS), the Illumina Porcine SNP60 Bead Chip containing 62 163 single nucleotide polymorphisms(SNPs) was used to genotype 557 pigs from a porcine Large White×Minzhu intercross population. The REMA(at the 5th–6th, 10th–11th and the last ribs) was measured after slaughtered at the age of(240±7) d for each animal. Association tests between REMA trait and SNPs were performed via the Genome-Wide Rapid Association using the Mixed Model and Regression-Genomic Control(GRAMMAR-GC) approach. From the Ensembl porcine database, SNP annotation was implemented using Sus scrofa Build 10.2. Thirty-three SNPs on SSC12 and 3 SNPs on SSC2 showed significant association with REMA at the last rib at the chromosome-wide significance level. None of the SNPs of REMA at the 5th–6th rib and only a few numbers of the SNPs of REMA at the 10th–11th ribs were found in this study. The Haploview V3.31 program and the Haplo.Stats R package were used to detect and visualize haplotype blocks and to analyze the association of the detected haplotype blocks with REMA at the last rib. A linkage analysis revealed that 4 haplotype blocks contained 4, 4, 2, and 4 SNPs, respectively. Annotations from pig reference genome suggested 2 genes(NOS2, NLK) in block 1(266 kb), one gene(TMIGD1) in block 2(348 kb), and one gene(MAP2K4) in block 3(453 kb). A functional analysis indicated that MYH3 and MYH13 genes are the potential genes controlling REMA at the last rib. We screened several candidate intervals and genes based on the SNPs location and the gene function, and inferred that NOS2 and NLK genes maybe the main genes of REMA at the last ribs.     

Genome-wide association study of the backfat thickness trait in two pig populations

Backfat thickness is a good predictor of carcass lean content, an economically important trait, and a main breeding target in pig improvement. In this study, the candidate genes and genomic regions associated with the tenth rib backfat thickness trait were identified in two independent pig populations, using a genome-wide association study of porcine 60K SNP genotype data applying the compressed mixed linear model (CMLM) statistical method. For each population, 30 most significant single-nucleotide polymorphisms (SNPs) were selected and SNP annotation implemented using Sus scrofa Build 10.2. In the first population, 25 significant SNPs were distributed on seven chromosomes, and SNPs on SSC1 and SSC7 showed great significance for fat deposition. The most significant SNP (ALGA0006623) was located on SSC1, upstream of the MC4R gene. In the second population, 27 significant SNPs were recognized by annotation, and 12 SNPs on SSC12 were related to fat deposition. Two haplotype blocks, M1GA0016251-MARC0075799 and ALGA0065251-MARC0014203-M1GA0016298-ALGA0065308, were detected in significant regions where the PIPNC1 and GH1 genes were identified as contributing to fat metabolism. The results indicated that genetic mechanism regulating backfat thickness is complex, and that genome-wide associations can be affected by populations with different genetic backgrounds.     

Genome-wide detection of selective signatures in a Jinhua pig population

The aim of this study was to detect evidence for signatures of recent selection in the Jinhua pig genome. These results can be useful to better understand the regions under selection in Jinhua pigs and might shed some lights on groups of genes that control production traits. In the present study, we performed extended haplotype homozygosity(EHH) tests to identify significant core regions in 202 Jinhua pigs. A total of 26 161 core regions spanning 636.42 Mb were identified, which occupied approximately 28% of the genome across all autosomes, and 1 158 significant(P0.01) core haplotypes were selected. Genes in these regions were related to several economically important traits, including meat quality, reproduction, immune responses and exterior traits. A panel of genes including ssc-mir-365-2, KDM8, RABEP2, GSG1L, RHEB, RPH3AL and a signal pathway of PI3K-Akt were detected with the most extreme P-values. The findings in our study could draw a comparatively genome-wide map of selection signature in the pig genome, and also help to detect functional candidate genes under positive selection for further genetic and breeding research in Jinhua and other pigs.     

Genome-wide detection of selective signatures in a Duroc pig population

The Duroc pig has high adaptability and feeding efficiency, making it one of the most popular pig breeds worldwide. Over long periods of natural and artificial selection, genetic footprints, i.e., selective signatures, were left in the genome. In this study, a Duroc pig population (n=715) was genotyped with the Porcine SNP60K Bead Chip and the GeneSeek Genomic Profiler (GGP) Porcine Chip. The relative extended haplotype homozygosity (REHH) method was used for selective signature detection in a subset of the population (n=368), selected to represent a balanced family structure. In total, 154 significant core regions were detected as selective signatures (P<0.01), some of which overlap with previously reported quantitative trait loci associated with several economically important traits, including average daily gain and backfat thickness. Genome annotation for these significant core regions revealed a variety of interesting candidate genes including GATA3, TAF3, ATP5C1, and FGF1. These genes were functionally related to anterior/posterior pattern specification, phosphatidylinositol 3-kinase signaling, embryonic skeletal system morphogenesis, and oxidation-reduction processes. This research provides knowledge for the study of selection mechanisms and breeding practices in Duroc and other pigs.     

ADD1基因PCR-SSCPs标记与猪肌内脂肪含量及背膘厚的关系

采用PCR SSCPs方法在苏太猪脂肪细胞定向分化因子 1(ADD1)基因第 347和 374位点发现单核苷酸多态性(SNP) ,分别为ADD1第 90和 99位氨基酸密码子的第 3位碱基 ,但这两个位点碱基的替换均没有引起氨基酸序列的变化。通过对 10 0头苏太猪肥育猪背最长肌中肌内脂肪含量的相关分析 ,发现杂合子AB肌内脂肪含量最高 ,极显著地高于AA纯合子 (P <0 0 1) ,BB纯合子肌内脂肪含量介于AB和AA之间 ,并有高于AA纯合子的趋势 (P =0 11)。各基因型间背膘厚没有显著差异。提示ADD1基因该位点上的PCR SSCPs可能作为选择肌内脂肪含量 ,而不影响背膘厚的一个辅助选择标记     

水稻果皮花青素含量的全基因组关联分析

花青素对人类健康具有重要的保健功能,培育富含花青素的功能性水稻品种是未来绿色健康农业发展的必然需求。然而目前与水稻果皮花青素含量相关的基因资源还十分有限,不利于有色稻米品种的种质创新和遗传改良。为了全面发掘水稻果皮花青素的基因资源,本研究结合花青素无损伤检测和全基因组关联分析方法,以533份水稻种质作为供试材料,检测到了13个果皮花青素含量关联QTL位点,这些QTL位点中包含了除Rc、Rd、Rb及OsMYB3已知与花青素相关的基因外,还包括17个候选基因。通过对候选基因同源性及表达模式分析,初步确定8个MYB基因与1个bHLH基因为新的水稻果皮花青素的候选基因。该研究结果首次全面剖析了水稻果皮花青素的遗传基础,为健康功能性水稻品种的选育提供理论基础与基因资源。     

甜玉米种子营养品质主要性状全基因组关联分析

利用玉米56K SNP芯片评估包含100份甜玉米自交系的甜玉米育种资源群体的群体结构,并对种子营养品质性状进行关联定位。结果表明:100份甜玉米自交系可划分为两个亚群,其中,亚群1包括92份种质,亚群2包括8份种质。利用获得均匀覆盖甜玉米基因组的37 297个高质量SNP发现,PIC值集中在0.19、基因多样性变幅集中在0.36～0.38。甜玉米种子中淀粉含量、蛋白质含量、脂肪含量波动较大,其中,淀粉含量变幅在53.91%～73.70%,蛋白质含量变幅在8.96%～18.01%,脂肪含量变幅在5.53%～18.50%。利用GLM-Q模型关联定位到控制甜玉米种子淀粉含量、蛋白质含量、脂肪含量的SNP位点分别是14、15和20,能够解释表型变异的3.45%～51.69%。其中,在-log₁₀P>3.50水平下,位于3号染色体上Affx-115329496处的qSTA-3-1对淀粉含量贡献率最大,约为20.90%;位于1号染色体Affx-91181539处的qPRO-1-1位点和9号染色体上Affx-115333989处的qPRO-9-2与种子蛋白质含量显著关联;...     

Genome-wide association study for starch content and constitution in sorghum (Sorghum bicolor (L.) Moench)

Starch is the most important component in endosperm of sorghum grain. Usually, two types of starch are present: amylose (AM) and amylopectin (AP). The levels of AM and AP contents play a significant role in the appearance, structure, and quality of sorghum grains and in marketing applications. In the present study, a panel of 634 sorghum (Sorghum bicolor (L.) Moench) accessions were evaluated for starch, AM, and AP contents of grain, which included a mini core collection of 242 accessions from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in India, and 252 landraces and 140 cultivars from China. The average starch content was 67.64% and the average AM and AP contents were 20.19 and 79.81%, respectively. We developed a total of 260 000 high-confidence single nucleotide polymorphism (SNP) markers in the panel of 634 accessions of S. bicolor using specific locus amplified fragment sequencing (SLAF-seq). We performed genome-wide association studies (GWAS) of starch, AM, and AM/AP of grain and SNP markers based on a mixed linear model (MLM). In total, 70 significant association signals were detected for starch, AM, and AM/AP ratio of grain with P<4.452×10^–7, of which 10 SNPs were identified with significant starch, 51 SNPs were associated with AM, and nine SNPs were associated with the AM/AP ratio. The Gene Ontology (GO) analysis identified 12 candidate genes at five QTLs associated with starch metabolism within the 200-kb intervals, located on chromosomes 1, 5, 6, and 9. Of these genes, Sobic.006G036500.1 encodes peptidyl-prolyl cis-trans-isomerase CYP38 responsible for hexose monophosphate shunt (HMS) and Sobic.009G071800 encodes 6-phospho-fructokinase (PFK), which is involved in the embden-meyerhof pathway (EMP). Kompetitive allele specific PCR (KASP) markers were developed to validate the GWAS results. The C allele is correlated with a high starch content, while the T allele is linked with a low level of starch content, and provides reliable haplotypes for MAS in sorghum quality improvement.     

甜玉米籽粒体积和粒重的全基因组关联分析

为挖掘控制甜玉米籽粒体积和粒重的相关基因,2017—2019年,以209份甜玉米自交系构成的关联群体为材料,测定干籽粒的体积和粒重,结合全基因组重测序(De novo sequencing)获得的980万个单核苷酸多态性(Single-nucleotide polymorphism,SNP)标记,采用GLM模型进行全基因组关联分析。结果表明,甜玉米籽粒体积变异范围为0.06~0.15 mL,变异倍数为2.5倍,单粒重变异范围为0.08~0.17 g,变异倍数为2.1倍,均符合正态分布。共检测到15个SNP位点与籽粒体积或粒重显著关联,分别解释籽粒体积55.7%和粒重52.1%的表型变异,其中4个位点和普通玉米报道的QTL重叠,其余11个是新鉴定的位点,通过基因注释发现大部分候选基因为转录因子等调控基因。此外,首次检测到Br2(矮化基因2)与籽粒体积、粒重两性状均显著关联,并且籽粒体积和粒重均随着该基因表达量的升高而增加。