Grain-related Traits in Maize: Genome-wide Association Analysis and Candidate Gene Prediction

CHENXinyi, LIUChenyan, HUAMingzhu, XUXin, FENGWenxiang, WANGBaohua, FANGHui

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Journal of Agriculture ›› 2024, Vol. 14 ›› Issue (4) : 26-36. DOI: 10.11923/j.issn.2095-4050.cjas2023-0092

Grain-related Traits in Maize: Genome-wide Association Analysis and Candidate Gene Prediction

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Abstract

To explore the natural variations in regulating the maize kernel development and to assist in the genetic improvement of maize yield traits, in this study, 150 maize inbred lines with rich genetic variations were selected as materials for investigation. Combining 34,342 SNP markers and three models, a genome-wide association analysis was conducted on five grain-related traits. The results revealed that a total of 18 independent loci were significantly associated with the target traits, with each locus accounting for 12.24% to 15.41% of the phenotypic variations. Additionally, significant epistatic interactions were identified among four pairs of SNPs associated with kernel length, collectively explaining 5.32% of the phenotypic variations. By integrating the dynamic transcriptome data of kernel development in the B73 inbred line and functional annotations of genes, 19 candidate genes were predicted and classified into four categories: 6 enzymes, 3 ribosomal proteins, 1 transcription factor, and 9 other proteins. These candidate genes provide new genetic resources for deciphering the molecular mechanisms of maize kernel development and enhancing maize kernel size and yield. Through this research, we have not only uncovered the natural variations that regulate the development of corn kernels but also provided new genetic resources for the genetic improvement of corn yield traits. These findings are expected to bring new breakthroughs in corn breeding efforts, enhance corn production, and thereby better meet human needs for food.

Key words

maize / kernel size / yield / genome-wide association analysis / candidate genes prediction

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CHEN Xinyi , LIU Chenyan , HUA Mingzhu , XU Xin , FENG Wenxiang , WANG Baohua , FANG Hui. Grain-related Traits in Maize: Genome-wide Association Analysis and Candidate Gene Prediction. Journal of Agriculture. 2024, 14(4): 26-36 https://doi.org/10.11923/j.issn.2095-4050.cjas2023-0092

0 引言

玉米是中国最重要的粮食作物之一,被用作人类主食、动物饲料和工业原料。目前,中国玉米的种植面积和总产量均已超过水稻和小麦,在保障国家粮食安全上具有举足轻重的地位。根据预测,至2050年,全球玉米产量需要加倍才能满足人们日益增长的需求[1],这使粮食安全问题变得日趋紧张。产量是玉米育种的第一目标,在日益严峻的环境胁迫下,如何持续稳定的提高玉米产量是一个亟待解决的问题。
籽粒的大小和重量是产量构成的重要因子,直接影响玉米的产量。阐明玉米籽粒大小和重量的遗传基础,挖掘与玉米产量相关的新基因,对提高玉米产量和指导育种工作具有重大意义。近年来,研究人员通过不同的方法成功克隆出许多与玉米籽粒发育相关的基因。这些基因包括编码线粒体核糖体蛋白的基因,如Dek44[2]Smk4[3]Ppr14[4]等;调控淀粉积累的基因,如,Bt2[5]ZmNAC128ZmNAC130[6]ZmDof3[7];与激素调节相关的基因,如ZmTar1[8]ZmPIN1a[9];以及通过RNA编辑和剪切调控籽粒大小的基因,如Dek2[10]Dek10[11]Dek35[12]UBL1[13]等。这些研究揭示了玉米籽粒发育复杂的调控路径。然而,目前的研究主要依靠反向遗传学方法,往往使用突变体研究基因功能。但是这些基因的功能突变可能导致严重的问题,如籽粒干瘪[14],胚乳异常发育、败育[15],空果皮[16]以及胚胎缺陷[17]等,因此,在玉米育种中的应用受限。与此相反,正向遗传学是由表及里的研究方法,通过观测表型的改变研究其内在的调控基因[18],更易于发现植物的自然变异,有望在育种中应用。
数量性状位点(Quantitative trait loci, QTL)定位和全基因组关联分析(Genome-wide association mapping, GWAS)是解析复杂数量性状遗传结构的常用方法。近几十年来,成百上千个调控玉米产量相关的QTL被鉴定[18-31]。例如,PENG等[24]利用2个F2:3群体在6个环境下鉴定到51~90个与玉米产量相关的QTL,其中包括7个主效QTL。CHEN等[28]利用一个重组自交系群体,结合包含2091个bins的高密度遗传图谱,鉴定到56个与玉米产量相关的位点,并筛选出一个编码含有SBP-box结构域的蛋白作为穗行数QTL (qKRN4-3)的候选基因。LIU等[29]通过10个重组自交系群体的研究,鉴定到729个调控玉米籽粒大小的QTLs,并进一步通过候选基因关联分析证实其中5个基因对玉米籽粒大小/重量有影响。同时,利用转基因技术验证了ZmINCW1的功能,指出其可能参与调控玉米籽粒大小/重量。此外,HU等[32]通过使用多亲本群体和3种统计模型,鉴定了18个调控玉米籽粒淀粉含量的QTL。结合区间关联分析和突变体技术成功克隆了一个调控玉米籽粒淀粉含量的基因ZmTPS9。该基因编码海藻糖-6-磷酸合成酶,突变后导致玉米籽粒淀粉含量增高,进而提高粒重,在玉米产量改良上具有潜在的应用价值。最近,CHEN等[33]利用一个重组自交系群体,鉴定到8个与玉米穗行数相关的位点,并通过图位克隆方法成功分离了qKRN2基因。该基因编码WD40蛋白,突变后能显著提高玉米穗行数,具有很大的增产潜力。此外,GWAS也被广泛应用于鉴定与玉米产量相关的基因。随着测序技术的发展,高质量SNP标记的获取变得容易,显著地促进了GWAS的应用[34-36]。近些年,有多篇关于玉米产量相关性状的关联分析被报道[37-44],鉴定了大量与玉米产量相关的显著SNPs及候选基因,如ATHB-4[40]Br2[44]等。综上所述,尽管突变体研究在揭示玉米产量相关基因方面取得了一定进展,但在分子标记辅助育种的应用中面临一些挑战。相比之下,QTL定位和GWAS等正向遗传学方法在育种中具有巨大的潜力。利用正向遗传学手段,阐明玉米产量的遗传结构,鉴定优良等位基因,将有助于挖掘新的具有应用潜力的玉米产量功能基因,助力高产玉米的分子标记辅助选育和基因组选择育种。
本研究基于一个包含150份玉米自交系的关联群体,利用多种模型揭示了玉米籽粒相关性状的遗传结构,同时挖掘了调控这些性状的候选基因,这些发现为玉米高产的遗传改良奠定了坚实的基础。

1 材料与方法

1.1 植物材料种植

本研究使用的关联群体材料包含150份EX-PVP或重要的公共自交系,于2019和2020年在江苏南通种植。采用随机区组试验,每个自交系单行种植,行长2.5 m,行距0.5 m,选择3~5株进行自交授粉。在成熟期收获后,进行自然晾晒和脱粒处理,妥善保存种子用于后续的表型鉴定。

1.2 表型测量和数据分析

所测表型性状为玉米籽粒大小相关的5个性状,包括粒长(Kernel length, KL)、粒宽(Kernel width, KW)、粒厚(Kernel thickness, KT)、百粒重(Hundred kernel weight, HKW)和籽粒体积(Kernel volume, KV)。具体测量方法为:随机选取20粒成熟的扁平籽粒,测量其总的长、宽、厚,并重复2次取均值,以得到单个籽粒的长宽厚;接着随机选取100粒籽粒,进行百粒重的测量,同样重复2次并取平均值;采用排酒精法对籽粒体积进行测量[44],取20粒籽粒放入加有定量酒精的滴定管中,读取籽粒加入前后2次的读数,差值即为20粒玉米籽粒的体积,同样也重复2次并取平均值。利用SPSS软件对表型数据进行基本统计量分析、相关性分析和图形绘制。为消除环境效应的影响,利用R语言的lme4包对表型数据进行最佳线性无偏估计预测(Best Linear Unbiased Prediction, BLUP)[45]。广义遗传力的评估见公式(1)[46-47]
H2=σg2σg2+σge2n+σδ2nr
(1)
其中σg2为遗传方差,σge2为基因型与环境互作的方差,σδ2为残差,n为环境数,r为重复数。

1.3 基因型鉴定

利用美国Illumina公司开发的MaizeSNP50 BeadChip芯片[48]进行关联群体的基因型鉴定。该芯片包含56110个SNP标记,涵盖19350个玉米基因。利用plink1.5软件[49]对每个标记/个体的缺失率、杂合率和最小等位基因频率(minor allele frequency,MAF)进行筛选,最终有34342个MAF ≤ 0.05的多态性SNP用于后续分析。基因型分析的详细过程已在之前的研究中描述[50]

1.4 群体结构和亲缘关系

利用Admixture1.3软件[51]对关联群体的群体结构进行分析,将其分成3个亚群。不同家系之间的亲缘关系系数是利用Tassel5.0软件的Centered_IBS算法[52]计算得出。

1.5 关联分析

将基因型和表型数据导入Tassel5.2软件,首先采用一般线性模型(General Linear Model, GLM)程序进行全基因组关联分析。随后,群体结构Q被用作协变量来校正群体结构对结果的影响。最后,利用混合线性模型(Mixed Linear Model, MLM)同时控制群体结构和亲缘关系[53],对5个玉米籽粒相关性状进行全基因组关联分析。参考以前的研究,将阈值设置为P<1.0×10-4[29,50]

1.6 上位性互作分析

在进行上位性互作分析时,选取的是每个显著的LD区域中P值最小的SNP。利用双尾方差分析估计单个性状鉴定到的所有位点之间的加性-加性互作效应[54-55],将P<0.05设为显著性阈值。通过比较包含所有显著SNP效应和双位点互作效应的完整模型的残差与不包含双位点互作效应的简化模型的残差,评估上位性互作效应的大小。

1.7 候选基因的表达分析

候选基因的表达量数据来源于CHEN等[56]对玉米籽粒胚、胚乳和种子的动态转录组研究。我们选取了玉米授粉后的3个时期,10、20、30 d的数据进行分析。使用R语言的Pheatmap包绘制了表达热图。

2 结果与分析

2.1 玉米籽粒相关性状的表型数据分析

我们对150份玉米自交系进行了5个玉米籽粒相关性状(包括玉米籽粒大小和重量)的表型测定。结果显示,在该群体中,KL的分布范围为7.37~10.00 mm,平均值为8.75 mm,变异系数为5.83%;KW的平均值为8.17 mm,分布范围为6.82~9.08 mm,变异系数为4.53%;KT的均值为4.79 mm,分布范围为3.97~6.12 mm,变异系数为8.56%;KV为0.17 mL,分布范围为0.10~0.26 mL,变异系数为17.65%;HKW的变异系数最高,达到20.11%,平均百粒重为20.49 g,最大值为31.07 g,最小值为8.28 g(表1)。5个玉米籽粒相关表型的广义遗传力较高,分布范围为0.523~0.995,其中HKW的遗传力最高。这些结果表明玉米籽粒相关性状主要受遗传因素调控,受环境影响较小。大部分表型之间呈显著的正相关,相关系数为0.12~0.82(表2),其中,KV和HKW之间的相关性最高,而KT与KL之间相关性不显著。总的来说,5个性状均呈现出正态分布的趋势,变异较广泛(图1),表明玉米籽粒相关性状是复杂的数量性状,受多基因调控。
表1 5个玉米籽粒相关性状的描述性统计及遗传力
性状 自交系个数 最小值 最大值 平均值±标准差 变异系数 广义遗传力 置信区间
HKW/g 150 8.28 31.07 20.49 ± 4.12 20.11 0.995 0.994~0.997
KL/mm 150 7.37 10.00 8.75 ± 0.51 5.83 0.653 0.530~0.744
KW/mm 150 6.82 9.08 8.17 ± 0.37 4.53 0.916 0.886~0.938
KT/mm 150 3.97 6.12 4.79 ± 0.41 8.56 0.849 0.795~0.888
KV/mL 150 0.10 0.26 0.17 ± 0.03 17.65 0.523 0.354~0.647
表2 5个玉米籽粒性状之间的相关性
HKW KL KW KT KV
HKW 1 4.62E-16 5.70E-16 3.25E-11 3.32E-31
KL 0.65 1 3.34E-05 2.05E-01 4.87E-12
KW 0.65 0.36 1 3.42E-02 1.03E-09
KT 0.55 0.12 0.19 1 2.23E-09
KV 0.82 0.57 0.52 0.51 1
注:左下部分表示性状之间的相关性;右上部分表示P值。
图1 5个玉米籽粒相关性状的表型分布

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2.2 玉米籽粒相关性状的遗传结构

2.2.1 一般线性模型分析

利用一般线性模型对150份玉米自交系的5个籽粒相关性状进行全基因组关联分析(图2a、b)。结果显示,共有18个SNP位点与5个玉米籽粒相关性状显著关联。每个性状可以鉴定到1~12个显著的SNP位点,分布在1、3、5、6、8和9号染色体上。考虑到SNP之间的连锁不平衡(LD),将同一个LD区域的SNP合并后,共有12个独立位点能够调控5个玉米籽粒相关性状。每个位点可以解释的表型变异范围是12.49%~15.41%。其中,KL鉴定到最多的位点(10个),其效应值为12.51%~15.26%;最显著的位点是与KT显著关联的PZE-108040469,位于8号染色体上,P值为1.05×10-5,能解释15.35%的表型变异;HKW只检测到1个位于6号染色体上的显著独立位点,P值为7.25×10-5,能解释的表型变异为12.74%;只有一个位点与KW显著关联,位于3号染色体上,P值为1.1×10-5,能解释15.41%的表型变异;KV也只鉴定到一个显著位点,位于2号染色体,能够解释13.6%的表型变异。
图2 不同模型玉米籽粒相关性状的全基因组关联分析

HKW,百粒重;KL,粒长;KT,粒厚;KW,粒宽;KV,籽粒体积,下图同;

a:一般线性模型的关联分析结果;b:一般线性模型的QQ图;c:Q模型的关联分析结果;d:Q模型的QQ图;e:混合线性模型的关联分析结果;f:混合线性模型的QQ图

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2.2.2 Q模型分析

通过Q模型共检测到10个SNP位点与5个玉米籽粒相关性状显著关联,分布在1、2、3、6、8和10号染色体上,每个性状可以检测到1~4个位点,每个位点解释的表型变异范围为12.24%~15.30%(图2c、d)。同样,考虑到LD的影响,共有8个独立位点能够调控籽粒大小相关性状。其中,2个位点是新鉴定到的,即HKW和KV共同检测到SYN29761,位于1号染色体上,分别解释14.29%和13.51%的表型变异。另一个新鉴定到的位点是位于8号染色体与HKW显著关联的PZE-108019862,能解释12.47%的表型变异,其余6个位点在一般线性模型中已经被鉴定到。

2.2.3 混合线性模型分析

通过混合线性模型共检测到3个独立位点SYN29761、PZE-106060527和PZE-108040469分别与HKW、KT和KL显著关联。KV和KW未鉴定到显著位点。这3个位点分布在1、6和8号染色体上,每个位点解释的表型变异分别是14.29%、15.41%和15.29%(图2e、f)。这3个位点均在一般线性模型或Q模型中被鉴定到。综合3种模型结果共鉴定到16个独立位点与5个玉米籽粒相关性状显著关联,分布在除4、7号之外的8条染色体上(表3)。
表3 5个玉米籽粒相关性状的全基因组关联分析结果及候选基因预测
性状 标记 染色体 物理位置 P R2/% 候选基因_V3 候选基因_V4 功能注释 备注
KL PUT-163a-4730462-2143 1 49131053 7.94E-05 12.51 GRMZM2G038015 Zm00001d028879 bZIP-transcription factor 24
KL PZE-101070408 1 53158367 5.13E-05 13.56 GRMZM2G107463 Zm00001d028989 RING/U-box superfamily protein
HKW SYN29761 1 90219767 2.75E-05 14.29 GRMZM2G154487 Zm00001d029887 Ribosomal L18p/L5e family protein
KV PZE-102077877 2 60656421 5.47E-05 13.80 GRMZM2G016749 Zm00001d000124 Protein-serine/threonine phosphatase
KW PZE-103124207 3 181695567 1.10E-05 15.41 GRMZM2G386991 Zm00001d042938 Serine/threonine-protein kinase AFC1
KL ZM013522-0530 3 222667473 1.22E-05 15.26 GRMZM5G866024 Zm00001d044376 membrane protein
KT SYNGENTA2236 4 5010855 8.07E-05 12.86 GRMZM2G101502 Zm00001d018506 Deoxyhypusine hydroxylase 条件
分析
KL SYN3700 5 216163416 1.93E-05 14.62 GRMZM2G101571 Zm00001d018507 bet1 sft1-related snare
KL PZE-106060527 6 109295972 1.13E-05 15.25 GRMZM2G048194 Zm00001d037151 erwinia induced protein 1
KV PZE-106082684 6 139912054 9.34E-05 12.71 GRMZM2G068496 Zm00001d037972 60S ribosomal protein L29 条件分析
GRMZM2G068323 Zm00001d037975 pentatricopeptide repeat-containing protein
HKW SYN38610 6 165943896 7.25E-05 12.74 GRMZM2G132929 Zm00001d039106 40S ribosomal protein S12-like
HKW PZE-108019862 8 17889483 8.97E-05 12.47 GRMZM2G080722 Zm00001d008736 Monothiol glutaredoxin-S4, mitochondrial
KT PZE-108040469 8 65972918 1.05E-05 15.35 GRMZM2G021331 Zm00001d009488 ATP synthase beta chain
KL PZE-108113799 8 164939218 7.41E-05 14.74 GRMZM2G049269 Zm00001d012211 ankyrin-like protein
KL PZE-109030021 9 33672066 7.05E-05 12.78 GRMZM2G065355 Zm00001d045724 heat shock factor-binding protein 1
KL SYN32340 9 90842290 6.11E-05 13.20 GRMZM2G056166 Zm00001d046531 bri1-kd interacting protein 118
KL PZE-109077339 9 124770857 2.27E-05 14.39 GRMZM2G113866 Zm00001d047335 sigma factor sigB regulation protein rsbQ
KL PZE-110109454 10 148515533 9.38E-05 12.24 GRMZM2G173636 Zm00001d026639 acyl-binding domain-containing protein 6

2.2.4 条件分析

为进一步探究基于3种模型鉴定到的显著SNP位点之外,是否还有其他位点调控玉米籽粒相关性状,将这16个显著位点作为协变量进行了条件分析。结果表明,另有2个新的位点分别调控KT和KV性状(图3)。与KT显著关联的位点为SYNGENTA2236,位于4号染色体上,P值是8.06×10-5,能够解释12.86%的表型变异。而位于6号染色体上的PZE-106082684,与KV显著关联,P值为9.34×10-5,解释的表型变异为12.71%。
图3 5个玉米籽粒相关性状的条件分析

a:Q模型的条件分析;b:Q模型的QQ图;c:混合线性模型的条件分析;d:混合线性模型的QQ图

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综上所述,通过不同的统计模型和条件分析,分别鉴定到3、10、2、1和3个位点与HKW、KL、KT、KW和KV显著关联,利用一般线性模型估算这些位点解释的表型变异,结果发现与HKW显著关联的位点共可解释22.79%的表型变异,与KL关联的位点共可解释53.39%的表型变异,与KT显著关联的位点共可解释22.63%的表型变异,与KW显著关联的位点共可解释15.41%的表型变异,与KV显著关联的位点共可解释20.13%的表型变异。

2.2.5 上位性互作

为进一步分析玉米籽粒相关性状是否存在上位性互作效应,利用一般线性模型评估了同一性状下显著位点之间的加-加互作效应。结果显示,只有KL性状存在上位性互作效应。共鉴定到4对上位性互作,包括PUT-163a-4730462-2143与ZM013522-0530和PZE-109077339之间的互作、PZE-101070408与PZE-110109454之间的互作以及PZE-108113799与PZE-109077339之间的互作(表4)。这些上位性互作共可解释5.32%的表型变异,表明在该关联群体中,KL表型的遗传结构比其他表型更加复杂。因此,综合考虑加性效应和上位性效应,与KL显著关联的位点共解释了58.71%的表型变异。
表4 玉米籽粒相关性状的上位性互作分析结果
性状 SNP1 SNP2 P add_R2/%a epi_R2/%b
KL PUT-163a-4730462-2143 ZM013522-0530 0.02 53.39 5.32
KL PUT-163a-4730462-2143 PZE-109077339 0.03 53.39 5.32
KL PZE-101070408 PZE-110109454 0.02 53.39 5.32
KL PZE-108113799 PZE-109077339 0.01 53.39 5.32
KV - - - 20.13 -
KT - - - 22.63 -
HKW - - - 22.79 -
KV - - - 15.41 -
注:a表示与性状显著关联的加性位点解释的表型变异;b表示与性状显著关联位点的上位性互作解释的表型变异;“-”表示无上位性互作。
综上所述,在该群体中,玉米籽粒相关性状受多基因调控,显著SNP的加性效应对其遗传结构的贡献比SNP之间的上位性效应更大。

2.3 候选基因分析

考虑到LD的影响,从18个显著SNP位点的前后50 kb区间内筛选出82个候选基因。在一个公共的玉米转录组数据库中,获取了其中81个基因在玉米胚、胚乳和籽粒的表达量数据[56],其中,32个基因在玉米胚、胚乳和籽粒的不同发育时期均不表达(FPKM<1,附图1)。结合表达量数据和功能注释信息,筛选出19个候选基因(表3)。随后,对这些基因进行了功能注释分类(图4),发现其中6个基因编码酶或编码具有酶活性的蛋白:Zm00001d000124编码丝氨酸/苏氨酸磷酸酶,Zm00001d042938编码丝氨酸/苏氨酸蛋白激酶,这2个酶能将丝氨酸/苏氨酸磷酸化或去磷酸化,从而激活或抑制目标蛋白质的功能,进而调控基因的功能;Zm00001d018506编码脱氧辅蛋白羟化酶,该酶催化亚精胺到高赖氨酸的生物合成途径中的最后一步,属于翻译后的修饰过程。在该过程中,包含高赖氨酸的蛋白eIF5可能参与调控蛋白质的翻译[57];Zm00001d009488编码ATP合酶β链,与细胞的能量供应相关;Zm00001d012211编码假定的甲基转移酶,可能在表观水平对籽粒发育进行调控;Zm00001d047335编码假定的脂酶。只有一个候选基因具有转录因子活性(Zm00001d028879,bzip24),它编码bzip转录因子24,具有与特定DNA序列结合的能力,可以调控下游基因的表达;另有3个候选基因编码核糖体蛋白:Zm00001d029887编码核糖体L18p/L5e家族蛋白,Zm00001d037972编码60S核糖体蛋白L29,Zm00001d039106编码40S核糖体蛋白S12。鉴于核糖体是蛋白质合成的重要场所,这些基因能够参与核糖体的构成,可能通过影响蛋白质的合成、修饰等过程调控籽粒发育。除此之外,其他候选基因编码不同类型的蛋白质,包括含有五肽重复序列的蛋白质(PPR蛋白,Zm00001d037975)和热休克蛋白(Zm00001d045724)等。
图4 玉米籽粒相关性状候选基因的功能分类

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3 讨论

关联分析在解析复杂数量性状的遗传基础和克隆功能基因上具有明显的优势[58]。近年来,通过关联分析方法已经成功克隆了多个基因,如与产量相关的ZmINCW1[29]、与抗旱相关的ZmVPP1[59]ZmNAC111[60]TaNAC071-A[61]等,与耐盐性相关的ZmHAK4[62]ZmCLCgZmPMP3[63]ZmNSA1[64]等,与耐冷性相关的ZmMPK8[65]、与抗病性相关的ZmFBL41[66]以及与花期相关的ZmCCT[67]等。目前,大多数与玉米产量相关的基因都是通过突变体克隆获得的,但这类基因的突变往往导致籽粒干瘪、败育,难以在育种中应用。相反,利用关联分析鉴定调控玉米产量的自然变异,有利于玉米自交系的定向改良。本研究使用3种统计模型对5个玉米籽粒相关性状进行了全基因组关联分析,鉴定到18个位点与玉米籽粒大小和重量显著关联,其中,约72%(13/18)的位点与其他研究共定位[28-29],5个位点是本研究新鉴定到的,这在一定程度上说明了本研究结果的可靠性。由于单个位点的效应并不高(12.24%~15.41%),综合多个位点及上位性互作,KL性状所解释的表型变异最高(58.71%),其他性状只能解释20%左右的表型变异。这些遗传力的缺失表明在该关联群体中可能仍存在很多调控玉米产量的基因,或者是基因与基因之间的互作尚未被鉴定到。这可能与标记密度低、群体规模较小导致的检测功效较低有关,也说明了玉米籽粒性状的遗传复杂性。
根据基因在籽粒中的表达量及其功能注释分析,本研究筛选出19个候选基因。其中值得关注的是一个尚未报到的影响玉米籽粒相关性状的PPR蛋白基因-Zm00001d037975。PPR(Pentatricopeptide Repeat)是一种三角状五肽重复结构域,是陆生植物中最大的蛋白家族之一,在大多数植物中拥有超过400个成员,在植物生长发育过程中发挥着至关重要的作用[68-69]。先前的研究表明,PPR蛋白的突变或功能缺失会严重影响玉米籽粒的发育,导致胚、胚乳的败育或籽粒大小的改变[4,70-73]。例如,通过影响线粒体特定转录本的碱基编辑来影响线粒体的功能,进而导致籽粒败育的EMP5EMP9[70,72];通过调控nad2内含子的可变剪切来影响线粒体复合物Ⅰ组装,从而影响籽粒发育的EMP10PPR14Dek37[4,72-73];通过影响核糖体蛋白3(rps3)的成熟和翻译来影响籽粒发育的MPPR6[74]。此外,Dek2通过特异性地参与线粒体nad1内含子1的剪接,影响线粒体的氧化磷酸化和籽粒的发育[10]PPR78的功能缺失能够影响nad5的成熟和mRNA的稳定,阻碍呼吸链复合物Ⅰ的组装,进而影响籽粒的发育[75]。由此可知,PPR基因家族在玉米籽粒发育过程中扮演了非常重要的角色。有趣的是,通过在一个最近释放的蛋白互作数据库(http://minteractome.ncpgr.cn/)[76]中搜索,该PPR蛋白可能与Emp32互作。Emp32编码一个靶向线粒体的P型PPR蛋白,其功能的缺失极大降低了nad7第二内含子的剪切效率,阻碍了线粒体复合物Ⅰ的组装及氧化磷酸化过程,进而影响籽粒发育[77]。因此,Zm00001d037975很可能参与Emp32对玉米籽粒发育的调控路径,但其确切的分子机制仍需进一步研究。
此外,本研究还发现了3个未报到的核糖体蛋白编码基因,它们分别编码40S核糖体蛋白S12、60S核糖体蛋白L29以及核糖体蛋白L18p/L5e。核糖体是一种高度复杂的细胞器,被称为细胞内蛋白质合成的机器。多项研究表明,核糖体蛋白参与玉米籽粒的发育过程,其功能的缺失可能导致胚乃至籽粒的败育[2,78-81]Lem1(lethal embryo 1)编码质体核糖体蛋白S9(RPS9),该基因功能缺失导致玉米胚败育,但胚乳发育正常。随后克隆的emb8515lem1突变体具有相似的表型。EMB8515编码质体核糖体蛋白L35,是质体50S核糖体的一部分。该基因突变会导致质体中蛋白合成的缺陷,最终导致胚败育。URB2(Unhealthy Ribosome Biogenesis2)基因与核糖体合成有关,其突变体urb2的籽粒中60S/40S和80S/40S核糖体比值降低,多聚核糖体比值增加,籽粒变薄且发育迟缓。此外,编码线粒体核糖体蛋白的DEK44通过影响线粒体和核基因组中呼吸链相关基因的表达,以及周期蛋白依赖性激酶介导的活性来调控细胞生长和籽粒发育。综上所述,核糖体蛋白确实通过多种途径参与玉米籽粒的发育。
本研究通过全基因组关联分析,鉴定到18个显著的SNP位点与5个玉米籽粒相关性状关联,这些位点可解释12.24%~15.41%的表型变异。在籽粒长度性状中检测到4对SNP之间存在上位性互作,但效应较小。因此,在该群体中,玉米籽粒相关性状的遗传结构主要由加性效应贡献。通过综合考虑加性效应和上位性效应,每个性状可解释15.41%~58.71%的表型变异。在筛选到的19个候选基因中,编码PPR蛋白的Zm00001d037975基因可能与已知调控籽粒发育的Emp32基因互作,参与Emp32对玉米籽粒发育的调控路径,是一个重要的候选基因。其他基因编码不同类型的蛋白,包括酶、转录因子和核糖体蛋白等,暗示这些基因可能从不同方面调控籽粒相关性状。综上所述,本研究鉴定的重要遗传位点和候选基因可为进一步克隆籽粒发育相关基因、揭示其分子机制以及分子标记辅助育种等提供指导。

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The organic acid oxalate occurs in microbes, animals, and plants; however, excessive oxalate accumulation in vivo is toxic to cell growth and decreases the nutritional quality of certain vegetables. However, the enzymes and functions required for oxalate degradation in plants remain largely unknown. Here, we report the cloning of a maize () opaque endosperm mutant that encodes oxalyl-CoA decarboxylase1 (EC4.1.1.8; OCD1). is generally expressed and is specifically induced by oxalate. The mutant seeds contain a significantly higher level of oxalate than the wild type, indicating that the mutants have a defect in oxalate catabolism. The maize classic mutant () was initially cloned for its high lysine trait, although the gene function was not understood until its homolog in was found to encode an oxalyl-CoA synthetase (EC 6.2.1.8), which ligates oxalate and CoA to form oxalyl-CoA. Our enzymatic analysis showed that ZmOCD1 catalyzes oxalyl-CoA, the product of O7, into formyl-CoA and CO for degradation. Mutations in caused dramatic alterations in the metabolome in the endosperm. Our findings demonstrate that ZmOCD1 acts downstream of O7 in oxalate degradation and affects endosperm development, the metabolome, and nutritional quality in maize seeds.© 2018 American Society of Plant Biologists. All rights reserved.
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龚玉林, 贺丹, 卫芸芸, 等. 真菌遗传学方法研究进展[J]. 菌物研究, 2019, 17(3):173-179.
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[20]
TAO Y, JIANG L, LIU Q, et al. Combined linkage and association mapping reveals candidates for Scmv1, a major locus involved in resistance to sugarcane mosaic virus (SCMV) in maize[J]. BMC plant biology, 2013, 13:1-13.
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YANG N, LIU J, GAO Q, et al. Genome assembly of a tropical maize inbred line provides insights into structural variation and crop improvement[J]. Nature genetics, 2019, 51(6):1052-1059.
Maize is one of the most important crops globally, and it shows remarkable genetic diversity. Knowledge of this diversity could help in crop improvement; however, gold-standard genomes have been elucidated only for modern temperate varieties. Here, we present a high-quality reference genome (contig N50 of 15.78 megabases) of the maize small-kernel inbred line, which is derived from a tropical landrace. Using haplotype maps derived from B73, Mo17 and SK, we identified 80,614 polymorphic structural variants across 521 diverse lines. Approximately 22% of these variants could not be detected by traditional single-nucleotide-polymorphism-based approaches, and some of them could affect gene expression and trait performance. To illustrate the utility of the diverse SK line, we used it to perform map-based cloning of a major effect quantitative trait locus controlling kernel weight-a key trait selected during maize improvement. The underlying candidate gene ZmBARELY ANY MERISTEM1d provides a target for increasing crop yields.
[24]
PENG B, LI Y, WANG Y, et al. QTL analysis for yield components and kernel-related traits in maize across multi-environments[J]. Theoretical and applied genetics, 2011, 122:1305-1320.
Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F(2:3) populations derived from crosses Qi319 × Huangzaosi (Q/H, 230 families) and Ye478 × Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2 years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL × environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2 years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.
[25]
JIANG L, GE M, ZHAO H, et al. Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize[J]. PloS one, 2015, 10(4):e0124779.
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MARTINEZ A K, SORIANO J M, TUBEROSA R, et al. Yield QTLome distribution correlates with gene density in maize[J]. Plant science, 2016, 242:300-309.
The genetic control of yield and related traits in maize has been addressed by many quantitative trait locus (QTL) studies, which have produced a wealth of QTL information, also known as QTLome. In this study, we assembled a yield QTLome database and carried out QTL meta-analysis based on 44 published studies, representing 32 independent mapping populations and 49 parental lines. A total of 808 unique QTLs were condensed to 84 meta-QTLs and were projected on the 10 maize chromosomes. Seventy-four percent of QTLs showed a proportion of phenotypic variance explained (PVE) smaller than 10% confirming the high genetic complexity of grain yield. Yield QTLome projection on the genetic map suggested pericentromeric enrichment of QTLs. Conversely, pericentromeric depletion of QTLs was observed when the physical map was considered, suggesting gene density as the main driver of yield QTL distribution on chromosomes. Dominant and overdominant yield QTLs did not distribute differently from additive effect QTLs.Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
[27]
CHEN L, LI C, LI Y, et al. Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize[J]. Molecular breeding, 2016, 36:1-15.
[28]
CHEN L, LI Y, LI C, et al. Fine-mapping of qGW4.05, a major QTL for kernel weight and size in maize[J]. BMC plant biology, 2016, 16:1-13.
[29]
LIU J, HUANG J, GUO H, et al. The conserved and unique genetic architecture of kernel size and weight in maize and rice[J]. Plant physiology, 2017, 175(2):774-785.
Maize () is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice () genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of, a homolog of rice that affects seed size and weight, was characterized in detail. is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis () homozygous mutant line in the gene (Arabidopsis ortholog of ). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.© 2017 American Society of Plant Biologists. All Rights Reserved.
[30]
CHEN L, AN Y, LI Y, et al. Candidate loci for yield-related traits in maize revealed by a combination of metaQTL analysis and regional association mapping[J]. Frontiers in plant science, 2017, 8:2190.
Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci.
[31]
ZHANG X, HUANG C, WU D, et al. High-throughput phenotyping and QTL mapping reveals the genetic architecture of maize plant growth[J]. Plant physiology, 2017, 173(3):1554-1564.
With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize () recombinant inbred line population ( = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.© 2017 American Society of Plant Biologists. All Rights Reserved.
[32]
HU S, WANG M, ZHANG X, et al. Genetic basis of kernel starch content decoded in a maize multi-parent population[J]. Plant biotechnology journal, 2021, 19(11):2192-2205.
Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding of the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping, and a genome-wide association study in a multi-parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large-effect and many small-effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non-starch-pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway-driven analysis identified ZmTPS9, which encodes a trehalose-6-phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4-2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.This article is protected by copyright. All rights reserved.
[33]
CHEN W, CHEN L, ZHANG X, et al. Convergent selection of a WD40 protein that enhances grain yield in maize and rice[J]. Science, 2022, 375(6587):eabg7985.
\n A better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus\n KRN2\n in maize and its rice ortholog,\n OsKRN2\n, experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of\n KRN2\n in maize or\n OsKRN2\n in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways.\n KRN2\n, together with other convergently selected genes, provides an excellent target for future crop improvement.\n
[34]
GORE M A, CHIA J M, ELSHIRE R J, et al. A first-generation haplotype map of maize[J]. Science, 2009, 326(5956):1115-1117.
Maize is an important crop species of high genetic diversity. We identified and genotyped several million sequence polymorphisms among 27 diverse maize inbred lines and discovered that the genome was characterized by highly divergent haplotypes and showed 10- to 30-fold variation in recombination rates. Most chromosomes have pericentromeric regions with highly suppressed recombination that appear to have influenced the effectiveness of selection during maize inbred development and may be a major component of heterosis. We found hundreds of selective sweeps and highly differentiated regions that probably contain loci that are key to geographic adaptation. This survey of genetic diversity provides a foundation for uniting breeding efforts across the world and for dissecting complex traits through genome-wide association studies.
[35]
CHIA J M, SONG C, BRADBURY P J, et al. Maize HapMap2 identifies extant variation from a genome in flux[J]. Nature genetics, 2012, 44(7):803-807.
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BUKOWSKI R, GUO X, LU Y, et al. Construction of the third-generation Zea mays haplotype map[J]. Gigascience, 2018, 7(4):gix134.
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[38]
LI C, HUANG Y, HUANG R, et al. The genetic architecture of amylose biosynthesis in maize kernel[J]. Plant biotechnology journal, 2018, 16(2):688-695.
Starch is the most abundant storage carbohydrate in maize kernel. The content of amylose and amylopectin confers unique properties in food processing and industrial application. Thus, the resurgent interest has been switched to the study of individual amylose or amylopectin rather than total starch, whereas the enzymatic machinery for amylose synthesis remains elusive. We took advantage of the phenotype of amylose content and the genotype of 9,007,194 single nucleotide polymorphisms from 464 inbred maize lines. The genome-wide association study identified 27 associated loci involving 39 candidate genes that were linked to amylose content including transcription factors, glycosyltransferases, glycosidases, as well as hydrolases. Except the waxy gene that encodes the granule-bound starch synthase, the remaining candidate genes were located in the upstream pathway of amylose synthesis, while the downstream members were already known from prior studies. The linked candidate genes could be transferred to manipulate amylose content and thus add value to maize kernel in the breeding programme.© 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
[39]
LIU M, TAN X, YANG Y, et al. Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping[J]. Plant biotechnology journal, 2020, 18(1):207-221.
Kernel size-related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10 ) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10 ) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable-effect SNPs and the co-localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co-localized SNPs, of which zma-miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma-miR164e resulted in the down-regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker-assisted selection (MAS) for high-yield breeding in maize.© 2019 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
[40]
ZHANG X, GUAN Z, WANG L, et al. Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize[J]. Molecular genetics and genomics, 2020, 295:409-420.
Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL mapping and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.
[41]
ZHANG C, ZHOU Z, YONG H, et al. Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping[J]. Theoretical and applied genetics, 2017, 130:1011-1029.
Using combined linkage and association mapping, 26 stable QTL and six stable SNPs were detected across multiple environments for eight ear and grain morphological traits in maize. One QTL, PKS2, might play an important role in maize yield improvement. In the present study, one bi-parental population and an association panel were used to identify quantitative trait loci (QTL) for eight ear and grain morphological traits. A total of 108 QTL related to these traits were detected across four environments using an ultra-high density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319, and 26 QTL were identified in more than two environments. Furthermore, 64 single nucleotide polymorphisms (SNPs) were found to be significantly associated with the eight ear and grain morphological traits (-log(P) > 4) in an association panel of 240 maize inbred lines. Combining the two mapping populations, a total of 17 pleiotropic QTL/SNPs (pQTL/SNPs) were associated with various traits across multiple environments. PKS2, a stable locus influencing kernel shape identified on chromosome 2 in a genome-wide association study (GWAS), was within the QTL confidence interval defined by the RILs. The candidate region harbored a short 13-Kb LD block encompassing four SNPs (SYN11386, PHM14783.16, SYN11392, and SYN11378). In the association panel, 13 lines derived from the hybrid PI78599 possessed the same allele as Qi319 at the PHM14783.16 (GG) locus, with an average value of 0.21 for KS, significantly lower than that of the 34 lines derived from Ye478 that carried a different allele (0.25, P < 0.05). Therefore, further fine mapping of PKS2 will provide valuable information for understanding the genetic components of grain yield and improving molecular marker-assisted selection (MAS) in maize.
[42]
代力强, 吴律, 董青松, 等. 玉米籽粒长度的全基因组关联分析[J]. 西北农林科技大学学报(自然科学版), 2018, 6.
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渠建洲, 冯文豪, 张兴华, 等. 基于全基因组关联分析解析玉米籽粒大小的遗传结构[J]. 作物学报, 2022, 48(2):304-319.
玉米籽粒大小是产量重要构成因子之一, 也是受多基因调控的复杂数量性状, 挖掘玉米籽粒大小相关性状的关键调控基因, 将有助于提高玉米的产量。本研究以212份优良玉米自交系为材料, 于2018年和2019年分别对粒长、粒宽和粒厚进行测定, 并结合均匀分布于玉米基因组的73,006个单核苷酸多态性(single nucleotide polymorphism, SNP)标记进行全基因组关联分析。基于FarmCPU算法, 在玉米的10条染色体上检测到47个与籽粒大小相关性状关联的SNP。结合B73玉米自交系籽粒发育的动态时空转录数据, 在显著SNP标记的连锁不平衡区域内, 共检测到58个与籽粒大小相关的候选基因, 其编码的蛋白与多种蛋白存在互作关系, 参与并调控多个与籽粒发育密切相关的生物学过程。本研究为解析玉米籽粒发育的分子调控机制, 改良籽粒大小和提高作物产量提供了新的参考。
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FANG H, FU X, GE H, et al. Genetic basis of maize kernel oil-related traits revealed by high-density SNP markers in a recombinant inbred line population[J]. BMC plant biology, 2021, 21(1):1-12.
Galls or the neoplastic growth on plants result from a complex type of interaction between the inducers (Acari, Insects, Microbes and Nematodes) and plants. The present study sheds light on the gall inducing habit of a highly host specific eriophyid mite,Aceria pongamiae,on the leaves ofPongamia pinnataleading to the production of abnormal pouch like outgrowths on the adaxial and abaxial surfaces of the foliage. Each leaf gall is a highly complex, irregular massive structure, and the formation of which often leads to complete destruction of leaves, especially during heavy mite infestation, and thereby adversely affecting the physiology and growth of the host plant.
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Heritability (H) on a progeny mean basis is frequently estimated in recurrent selection experiments for the purpose of estimating the expected progress from family selection; however, appropriate measures of precision have been developed for only a few heritability estimators. The objective of this research was to develop a measure of precision for H for certain balanced linear models. Exact confidence intervals for H were derived and are not restricted to a specific experimental design. The confidence intervals were applied to sorghum [Sorghum bicolor (L.) Moench] half‐sib family data.
[47]
FANG H, FU X, WANG Y, et al. Genetic basis of kernel nutritional traits during maize domestication and improvement[J]. The plant journal, 2020, 101(2):278-292.
The nutritional traits of maize kernels are important for human and animal nutrition, and these traits have undergone selection to meet the diverse nutritional needs of humans. However, our knowledge of the genetic basis of selecting for kernel nutritional traits is limited. Here, we identified both single and epistatic quantitative trait loci (QTLs) that contributed to the differences of oil and carotenoid traits between maize and teosinte. Over half of teosinte alleles of single QTLs increased the values of the detected oil and carotenoid traits. Based on the pleiotropism or linkage information of the identified single QTLs, we constructed a trait-locus network to help clarify the genetic basis of correlations among oil and carotenoid traits. Furthermore, the selection features and evolutionary trajectories of the genes or loci underlying variations in oil and carotenoid traits revealed that these nutritional traits produced diverse selection events during maize domestication and improvement. To illustrate more, a mutator distance-relative transposable element (TE) in intron 1 of DXS2, which encoded a rate-limiting enzyme in the methylerythritol phosphate pathway, was identified to increase carotenoid biosynthesis by enhancing DXS2 expression. This TE occurs in the grass teosinte, and has been found to have undergone selection during maize domestication and improvement, and is almost fixed in yellow maize. Our findings not only provide important insights into evolutionary changes in nutritional traits, but also highlight the feasibility of reintroducing back into commercial agricultural germplasm those nutritionally important genes hidden in wild relatives.© 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd.
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Association analyses that exploit the natural diversity of a genome to map at very high resolutions are becoming increasingly important. In most studies, however, researchers must contend with the confounding effects of both population and family structure. TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) implements general linear model and mixed linear model approaches for controlling population and family structure. For result interpretation, the program allows for linkage disequilibrium statistics to be calculated and visualized graphically. Database browsing and data importation is facilitated by integrated middleware. Other features include analyzing insertions/deletions, calculating diversity statistics, integration of phenotypic and genotypic data, imputing missing data and calculating principal components.
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YU J, PRESSOIR G, BRIGGS W H, et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness[J]. Nature genetics, 2006, 38(2):203-208.
As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.
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XIE Y, FENG Y, CHEN Q, et al. Genome-wide association analysis of salt tolerance QTLs with SNP markers in maize (Zea mays L.)[J]. Genes & genomics, 2019, 41:1135-1145.
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CHEN J, ZENG B, ZHANG M, et al. Dynamic transcriptome landscape of maize embryo and endosperm development[J]. Plant physiology, 2014, 166(1):252-264.
Maize (Zea mays) is an excellent cereal model for research on seed development because of its relatively large size for both embryo and endosperm. Despite the importance of seed in agriculture, the genome-wide transcriptome pattern throughout seed development has not been well characterized. Using high-throughput RNA sequencing, we developed a spatiotemporal transcriptome atlas of B73 maize seed development based on 53 samples from fertilization to maturity for embryo, endosperm, and whole seed tissues. A total of 26,105 genes were found to be involved in programming seed development, including 1,614 transcription factors. Global comparisons of gene expression highlighted the fundamental transcriptomic reprogramming and the phases of development. Coexpression analysis provided further insight into the dynamic reprogramming of the transcriptome by revealing functional transitions during maturation. Combined with the published nonseed high-throughput RNA sequencing data, we identified 91 transcription factors and 1,167 other seed-specific genes, which should help elucidate key mechanisms and regulatory networks that underlie seed development. In addition, correlation of gene expression with the pattern of DNA methylation revealed that hypomethylation of the gene body region should be an important factor for the expressional activation of seed-specific genes, especially for extremely highly expressed genes such as zeins. This study provides a valuable resource for understanding the genetic control of seed development of monocotyledon plants. © 2014 American Society of Plant Biologists. All Rights Reserved.
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A naturally occurring unusual amino acid, hypusine [N (epsilon)-(4-amino-2-hydroxybutyl)-lysine] is a component of a single cellular protein, eukaryotic translation initiation factor 5A (eIF5A). It is a modified lysine with structural contribution from the polyamine spermidine. Hypusine is formed in a novel posttranslational modification that involves two enzymes, deoxyhypusine synthase (DHS) and deoxyhypusine hydroxylase (DOHH). eIF5A and deoxyhypusine/hypusine modification are essential for growth of eukaryotic cells. The hypusine synthetic pathway has evolved in eukaryotes and eIF5A, DHS and DOHH are highly conserved, suggesting maintenance of a fundamental cellular function of eIF5A through evolution. The unique feature of the hypusine modification is the strict specificity of the enzymes toward its substrate protein, eIF5A. Moreover, DHS exhibits a narrow specificity toward spermidine. In view of the extraordinary specificity and the requirement for hypusine-containing eIF5A for mammalian cell proliferation, eIF5A and the hypusine biosynthetic enzymes present new potential targets for intervention in aberrant cell proliferation.
[58]
XIAO Y, LIU H, WU L, et al. Genome-wide association studies in maize: praise and stargaze[J]. Molecular plant, 2017, 10(3):359-374.
Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.
[59]
WANG X, WANG H, LIU S, et al. Genetic variation in ZmVPP1 contributes to drought tolerance in maize seedlings[J]. Nature genetics, 2016, 48(10):1233-1241.
[60]
MAO H, WANG H, LIU S, et al. A transposable element in a NAC gene is associated with drought tolerance in maize seedlings[J]. Nature communications, 2015, 6(1):8326.
Drought represents a major constraint on maize production worldwide. Understanding the genetic basis for natural variation in drought tolerance of maize may facilitate efforts to improve this trait in cultivated germplasm. Here, using a genome-wide association study, we show that a miniature inverted-repeat transposable element (MITE) inserted in the promoter of a NAC gene (ZmNAC111) is significantly associated with natural variation in maize drought tolerance. The 82-bp MITE represses ZmNAC111 expression via RNA-directed DNA methylation and H3K9 dimethylation when heterologously expressed in Arabidopsis. Increasing ZmNAC111 expression in transgenic maize enhances drought tolerance at the seedling stage, improves water-use efficiency and induces upregulation of drought-responsive genes under water stress. The MITE insertion in the ZmNAC111 promoter appears to have occurred after maize domestication and spread among temperate germplasm. The identification of this MITE insertion provides insight into the genetic basis for natural variation in maize drought tolerance.
[61]
MAO H, LI S, CHEN B, et al. Variation in cis-regulation of a NAC transcription factor contributes to drought tolerance in wheat[J]. Molecular plant, 2022, 15(2):276-292.
[62]
ZHANG M, LIANG X, WANG L, et al. A HAK family Na+ transporter confers natural variation of salt tolerance in maize[J]. Nature plants, 2019, 5(12):1297-1308.
[63]
LUO M, ZHANG Y, LI J, et al. Molecular dissection of maize seedling salt tolerance using a genome-wide association analysis method[J]. Plant biotechnology journal, 2021, 19(10):1937-1951.
Salt stress is a major devastating abiotic factor that affects the yield and quality of maize. However, knowledge of the molecular mechanisms of the responses to salt stress in maize is limited. To elucidate the genetic basis of salt tolerance traits, a genome-wide association study was performed on 348 maize inbred lines under normal and salt stress conditions using 557 894 single nucleotide polymorphisms (SNPs). The phenotypic data for 27 traits revealed coefficients of variation of >25%. In total, 149 significant SNPs explaining 6.6%-11.2% of the phenotypic variation for each SNP were identified. Of the 104 identified quantitative trait loci (QTLs), 83 were related to salt tolerance and 21 to normal traits. Additionally, 13 QTLs were associated with two to five traits. Eleven and six QTLs controlling salt tolerance traits and normal root growth, respectively, co-localized with QTL intervals reported previously. Based on functional annotations, 13 candidate genes were predicted. Expression levels analysis of 12 candidate genes revealed that they were all responsive to salt stress. The CRISPR/Cas9 technology targeting three sites was applied in maize, and its editing efficiency reached 70%. By comparing the biomass of three CRISPR/Cas9 mutants of ZmCLCg and one zmpmp3 EMS mutant with their wild-type plants under salt stress, the salt tolerance function of candidate genes ZmCLCg and ZmPMP3 were confirmed. Chloride content analysis revealed that ZmCLCg regulated chloride transport under sodium chloride stress. These results help to explain genetic variations in salt tolerance and provide novel loci for generating salt-tolerant maize lines.© 2021 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
[64]
CAO Y, ZHANG M, LIANG X, et al. Natural variation of an EF-hand Ca2+-binding-protein coding gene confers saline-alkaline tolerance in maize[J]. Nature communications, 2020, 11(1):186.
Sodium (Na+) toxicity is one of the major damages imposed on crops by saline-alkaline stress. Here we show that natural maize inbred lines display substantial variations in shoot Na+ contents and saline-alkaline (NaHCO3) tolerance, and reveal that ZmNSA1 (Na+Content under Saline-Alkaline Condition) confers shoot Na+ variations under NaHCO3 condition by a genome-wide association study. Lacking of ZmNSA1 promotes shoot Na+ homeostasis by increasing root Na+ efflux. A naturally occurred 4-bp deletion decreases the translation efficiency of ZmNSA1 mRNA, thus promotes Na+ homeostasis. We further show that, under saline-alkaline condition, Ca2+ binds to the EF-hand domain of ZmNSA1 then triggers its degradation via 26S proteasome, which in turn increases the transcripts levels of PM-H+-ATPases (MHA2 and MHA4), and consequently enhances SOS1 Na+/H+ antiporter-mediated root Na+ efflux. Our studies reveal the mechanism of Ca2+-triggered saline-alkaline tolerance and provide an important gene target for breeding saline-alkaline tolerant maize varieties.
[65]
ZENG R, LI Z, SHI Y, et al. Natural variation in a type-A response regulator confers maize chilling tolerance[J]. Nature communications, 2021, 12(1):4713.
Maize (Zea mays L.) is a cold-sensitive species that often faces chilling stress, which adversely affects growth and reproduction. However, the genetic basis of low-temperature adaptation in maize remains unclear. Here, we demonstrate that natural variation in the type-A Response Regulator 1 (ZmRR1) gene leads to differences in chilling tolerance among maize inbred lines. Association analysis reveals that InDel-35 of ZmRR1, encoding a protein harboring a mitogen-activated protein kinase (MPK) phosphorylation residue, is strongly associated with chilling tolerance. ZmMPK8, a negative regulator of chilling tolerance, interacts with and phosphorylates ZmRR1 at Ser15. The deletion of a 45-bp region of ZmRR1 harboring Ser15 inhibits its degradation via the 26 S proteasome pathway by preventing its phosphorylation by ZmMPK8. Transcriptome analysis indicates that ZmRR1 positively regulates the expression of ZmDREB1 and Cellulose synthase (CesA) genes to enhance chilling tolerance. Our findings thus provide a potential genetic resource for improving chilling tolerance in maize.© 2021. The Author(s).
[66]
LI N, LIN B, WANG H, et al. Natural variation in ZmFBL41 confers banded leaf and sheath blight resistance in maize[J]. Nature genetics, 2019, 51(10):1540-1548.
[67]
YANG Q, LI Z, LI W, et al. CACTA-like transposable element in ZmCCT attenuated photoperiod sensitivity and accelerated the postdomestication spread of maize[J]. Proceedings of the national academy of sciences, 2013, 110(42):16969-16974.
\n Maize was domesticated from teosinte in Southern Mexico roughly 9,000 years ago. Maize originally was sensitive to photoperiod and required short-day conditions to flower. Thus, the reduced sensitivity to photoperiod is prerequisite for maize spread to long-day temperate regions. A gene encoding a CCT domain-containing protein,\n ZmCCT\n, was found by many researchers to modulate photoperiod sensitivity. The current study shows that insertion of a CACTA-like transposon into the\n ZmCCT\n promoter can suppress the\n ZmCCT\n expression remarkably and thus attenuates maize sensitivity under long-day conditions. The transposable element (TE) insertion event occurred in a tropical maize plant and has been selected for and accumulated as maize adapted to vast long-day environments. This selection leaves behind a TE-related linkage disequilibrium block with the very-low-nucleotide variations.\n
[68]
丁安明, 屈旭, 李凌, 等. 植物PPR蛋白家族研究进展[J]. 中国农学通报, 2014, 30(9):218-224.
[69]
BARKAN A, SMALL I. Pentatricopeptide repeat proteins in plants[J]. Annual review of plant biology, 2014, 65:415-442.
Pentatricopeptide repeat (PPR) proteins constitute one of the largest protein families in land plants, with more than 400 members in most species. Over the past decade, much has been learned about the molecular functions of these proteins, where they act in the cell, and what physiological roles they play during plant growth and development. A typical PPR protein is targeted to mitochondria or chloroplasts, binds one or several organellar transcripts, and influences their expression by altering RNA sequence, turnover, processing, or translation. Their combined action has profound effects on organelle biogenesis and function and, consequently, on photosynthesis, respiration, plant development, and environmental responses. Recent breakthroughs in understanding how PPR proteins recognize RNA sequences through modular base-specific contacts will help match proteins to potential binding sites and provide a pathway toward designing synthetic RNA-binding proteins aimed at desired targets.
[70]
LIU Y J, XIU Z H, MEELEY R, et al. Empty pericarp5 encodes a pentatricopeptide repeat protein that is required for mitochondrial RNA editing and seed development in maize[J]. The plant cell, 2013, 25(3):868-883.
In flowering plants, RNA editing is a posttranscriptional mechanism that converts specific cytidines to uridines in both mitochondrial and plastidial transcripts, altering the information encoded by these genes. Here, we report the molecular characterization of the empty pericarp5 (emp5) mutants in maize (Zea mays). Null mutation of Emp5 results in abortion of embryo and endosperm development at early stages. Emp5 encodes a mitochondrion-targeted DYW subgroup pentatricopeptide repeat (PPR) protein. Analysis of the mitochondrial transcripts revealed that loss of the EMP5 function abolishes the C-to-U editing of ribosomal protein L16 at the rpl16-458 site (100% edited in the wild type), decreases the editing at nine sites in NADH dehydrogenase9 (nad9), cytochrome c oxidase3 (cox3), and ribosomal protein S12 (rps12), and surprisingly increases the editing at five sites of ATP synthase F0 subunit a (atp6), apocytochrome b (cob), nad1, and rpl16. Mutant EMP5-4 lacking the E+ and DYW domains still retains the substrate specificity and editing function, only at reduced efficiency. This suggests that the E+ and DYW domains of EMP5 are not essential to the EMP5 editing function but are necessary for efficiency. Analysis of the ortholog in rice (Oryza sativa) indicates that rice EMP5 has a conserved function in C-to-U editing of the rice mitochondrial rpl16-458 site. EMP5 knockdown expression in transgenics resulted in slow growth and defective seeds. These results demonstrate that Emp5 encodes a PPR-DYW protein that is required for the editing of multiple transcripts in mitochondria, and the editing events, particularly the C-to-U editing at the rpl16-458 site, are critical to the mitochondrial functions and, hence, to seed development in maize.
[71]
YANG Y Z, DING S, WANG H C, et al. The pentatricopeptide repeat protein EMP9 is required for mitochondrial ccmB and rps4 transcript editing, mitochondrial complex biogenesis and seed development in maize[J]. New phytologist, 2017, 214(2):782-795.
[72]
CAI M, LI S, SUN F, et al. Emp10 encodes a mitochondrial PPR protein that affects the cis-splicing of nad2 intron 1 and seed development in maize[J]. The plant journal, 2017, 91(1):132-144.
[73]
DAI D, LUAN S, CHEN X, et al. Maize Dek37 encodes a P-type PPR protein that affects cis-splicing of mitochondrial nad2 intron 1 and seed development[J]. Genetics, 2018, 208(3):1069-1082.
Mitochondrial group II introns require the participation of numerous nucleus-encoded general and specific factors to achieve efficient splicing in vivo. Pentatricopeptide repeat (PPR) proteins have been implicated in assisting group II intron splicing. Here, we identified and characterized a new maize seed mutant, defective kernel 37 (dek37), which has significantly delayed endosperm and embryo development. Dek37 encodes a classic P-type PPR protein that targets mitochondria. The dek37 mutation causes no detectable DEK37 protein in mutant seeds. Mitochondrial transcripts analysis indicated that dek37 mutation decreases splicing efficiency of mitochondrial nad2 intron 1, leading to reduced assembly and NADH dehydrogenase activity of complex I. Transmission Electron Microscopy (TEM) revealed severe morphological defects of mitochondria in dek37. Transcriptome analysis of dek37 endosperm indicated enhanced expression in the alternative respiratory pathway and extensive differentially expressed genes related to mitochondrial function. These results indicated that Dek37 is involved in cis-splicing of mitochondrial nad2 intron 1 and is required for complex I assembly, mitochondrial function, and seed development in maize.
[74]
MANAVSKI N, GUYON V, MEURER J, et al. An essential pentatricopeptide repeat protein facilitates 5′ maturation and translation initiation of rps3 mRNA in maize mitochondria[J]. The plant cell, 2012, 24(7):3087-3105.
[75]
ZHANG Y F, SUZUKI M, SUN F, et al. The mitochondrion-targeted PENTATRICOPEPTIDE REPEAT78 protein is required for nad5 mature mRNA stability and seed development in maize[J]. Molecular plant, 2017, 10(10):1321-1333.
[76]
HAN L, ZHONG W, QIAN J, et al. A multi-omics integrative network map of maize[J]. Nature genetics, 2022:1-10.
[77]
YANG Y Z, DING S, LIU X Y, et al. EMP32 is required for the cis-splicing of nad7 intron 2 and seed development in maize[J]. RNA biology, 2021, 18(4):499-509.
[78]
MA Z, DOONER H K. A mutation in the nuclear‐encoded plastid ribosomal protein S9 leads to early embryo lethality in maize[J]. The plant journal, 2004, 37(1):92-103.
Seeds of the lethal embryo 1 (lem1) mutant in maize (Zea mays) display a non‐concordant lethal phenotype: whereas the embryo aborts very early, before the transition stage, the endosperm develops almost normally. The mutant was identified in a collection of maize lines that carried the transposon Activation (Ac) at different locations in the genome. Co‐segregation and reversion analysis showed that lem1 was tagged by Ac. The lem1 gene encodes a protein that is highly similar to the rice plastid 30S ribosomal protein S9 (PRPS9). lem1 maps to chromosome 1L and appears to be the only copy of prps9 in the maize genome. Green fluorescent protein (GFP) fusion constructs containing only the putative transit peptide (TP) of LEM1 localize exclusively to the plastids, confirming that the LEM1 protein is a PRP. In contrast, GFP fusion constructs containing the entire LEM1 protein co‐localize to the plastids and to the nucleus, suggesting a possible dual function for this protein. Two alternative, although not mutually exclusive, explanations are considered for the lem phenotype of the lem1 mutant: (i) functional plastids are required for normal embryo development; and (ii) the PRPS9 has an extra‐ribosomal function required for embryogenesis.
[79]
MAGNARD J L, HECKEL T, MASSONNEAU A, et al. Morphogenesis of maize embryos requires ZmPRPL35-1 encoding a plastid ribosomal protein[J]. Plant physiology, 2004, 134(2):649-663.
In emb (embryo specific) mutants of maize (Zea mays), the two fertilization products have opposite fates: Although the endosperm develops normally, the embryo shows more or less severe aberrations in its development, resulting in nonviable seed. We show here that in mutant emb8516, the development of mutant embryos deviates as soon as the transition stage from that of wild-type siblings. The basic events of pattern formation take place because mutant embryos display an apical-basal polarity and differentiate a protoderm. However, morphogenesis is strongly aberrant. Young mutant embryos are characterized by protuberances at their suspensor-like extremity, leading eventually to structures of irregular shape and variable size. The lack of a scutellum or coleoptile attest to the virtual absence of morphogenesis at the embryo proper-like extremity. Molecular cloning of the mutation was achieved based on cosegregation between the mutant phenotype and the insertion of a MuDR element. The Mu insertion is located in gene ZmPRPL35-1, likely coding for protein L35 of the large subunit of plastid ribosomes. The isolation of a second allele g2422 and the complementation of mutant emb8516 with a genomic clone of ZmPRPL35-1 confirm that a lesion in ZmPRPL35-1 causes the emb phenotype. ZmPRPL35-1 is a low-copy gene present at two loci on chromosome arms 6L and 9L. The gene is constitutively expressed in all major tissues of wild-type maize plants. Lack of expression in emb/emb endosperm shows that endosperm development does not require a functional copy of ZmPRPL35-1 and suggests a link between plastids and embryo-specific signaling events.
[80]
QI W, ZHU J, WU Q, et al. Maize reas1 mutant stimulates ribosome use efficiency and triggers distinct transcriptional and translational responses[J]. Plant physiology, 2016, 170(2):971-988.
Ribosome biogenesis is a fundamental cellular process in all cells. Impaired ribosome biogenesis causes developmental defects; however, its molecular and cellular bases are not fully understood. We cloned a gene responsible for a maize (Zea mays) small seed mutant, dek* (for defective kernel), and found that it encodes Ribosome export associated1 (ZmReas1). Reas1 is an AAA-ATPase that controls 60S ribosome export from the nucleus to the cytoplasm after ribosome maturation. dek* is a weak mutant allele with decreased Reas1 function. In dek* cells, mature 60S ribosome subunits are reduced in the nucleus and cytoplasm, but the proportion of actively translating polyribosomes in cytosol is significantly increased. Reduced phosphorylation of eukaryotic initiation factor 2α and the increased elongation factor 1α level indicate an enhancement of general translational efficiency in dek* cells. The mutation also triggers dramatic changes in differentially transcribed genes and differentially translated RNAs. Discrepancy was observed between differentially transcribed genes and differentially translated RNAs, indicating distinct cellular responses at transcription and translation levels to the stress of defective ribosome processing. DNA replication and nucleosome assembly-related gene expression are selectively suppressed at the translational level, resulting in inhibited cell growth and proliferation in dek* cells. This study provides insight into cellular responses due to impaired ribosome biogenesis. © 2016 American Society of Plant Biologists. All Rights Reserved.
[81]
WANG H, WANG K, DU Q, et al. Maize Urb2 protein is required for kernel development and vegetative growth by affecting pre-ribosomal RNA processing[J]. New phytologist, 2018, 218(3):1233-1246.
Ribosome biogenesis is a fundamental process in eukaryotic cells. Although Urb2 protein has been implicated in ribosome biogenesis in yeast, the Urb2 domain is loosely conserved between plants and yeast, and the function of Urb2 protein in plants remains unknown. Here, we isolated a maize mutant, designated as urb2, with defects in kernel development and vegetative growth. Positional cloning and transgenic analysis revealed that urb2 encodes an Urb2 domain-containing protein. Compared with the wild-type (WT), the urb2 mutant showed decreased ratios of 60S/40S and 80S/40S and increased ratios of polyribosomes. The pre-rRNA intermediates of 35/33S rRNA, P-A3 and 18S-A3 were significantly accumulated in the urb2 mutant. Transcriptome profiling of the urb2 mutant indicated that ZmUrb2 affects the expression of a number of ribosome-related genes. We further demonstrated that natural variations in ZmUrb2 are significantly associated with maize kernel length. The overall results indicate that, by affecting pre-rRNA processing, the Urb2 protein is required for ribosome biogenesis in maize.© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
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