Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

Ning Zhang; Xueqing Huang

doi:10.1371/journal.pone.0245129

. 2021 Jan 6;16(1):e0245129. doi: 10.1371/journal.pone.0245129

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

Ning Zhang ¹, Xueqing Huang ^1,^*

Editor: Maoteng Li²

PMCID: PMC7787474 PMID: 33406127

Abstract

Leaf angle of maize is a fundamental determinant of plant architecture and an important trait influencing photosynthetic efficiency and crop yields. To broaden our understanding of the genetic mechanisms of leaf angle formation, we constructed a F_3:4 recombinant inbred lines (RIL) population to map QTL for leaf angle. The RIL was derived from a cross between a model inbred line (B73) with expanded leaf architecture and an elite inbred line (Zheng58) with compact leaf architecture. A sum of eight QTL were detected on chromosome 1, 2, 3, 4 and 8. Single QTL explained 4.3 to 14.2% of the leaf angle variance. Additionally, some important QTL were confirmed through a heterogeneous inbred family (HIF) approach. Furthermore, twenty-four candidate genes for leaf angle were predicted through whole-genome re-sequencing and expression analysis in qLA02-01and qLA08-01 regions. These results will be helpful to elucidate the genetic mechanism of leaf angle formation in maize and benefit to clone the favorable allele for leaf angle. Besides, this will be helpful to develop the novel maize varieties with ideal plant architecture through marker-assisted selection.

Introduction

Maize (Zea mays L.) is one of the most important cereal crops worldwide, and increasing the grain yield has been the most important goals of maize production [1]. Among the various traits that are normally considered in maize breeding programs, the leaf angle (LA), defined as the angle of leaf bending away from the main stem, is an important trait influencing plant architecture and yield production [2,3]. The less of leaf angle is, the more upright the leaves are. Upright leaves can maximize photosynthesis efficiency through maintaining light capture and reducing shading as canopies went more crowded, which in turn increase yield production in high density cultivation [3–6]. Therefore, an appropriate leaf angle is a prerequisite for attaining the desired grain yield in maize-breeding projects. A more thorough understanding of the molecular and genetic mechanism determining leaf angle will contribute to develop novel maize varieties with ideal plant architecture.

Genetic studies have indicated that leaf angle in maize is a complex trait controlled by both qualitative genes and quantitative genes. According to an incomplete statistic, eleven representative maize genes that control the leaf angle have been cloned, five of which were identified by mutagenesis: knox [7], liguleless1 (lg1) [8], liguleless2 (lg2) [9], liguleless3 (lg3) [10], liguleless narrow (lgn) [11], and six were resolved through QTL-cloning approach: ZmTAC1 [12], ZmCLA4 [13], ZmILI1 [14], and UPA2/UPA1 [15], ZmIBH1-1 [16]. In the past 30 years, a large number of QTL for leaf angle have been obtained by genetic dissection of maize leaf angle using biparental populations [17–24]. Mickelson et al. firstly identified nine leaf angle QTL which were distributed on six chromosomes in two environments using the RFLP marker technique in the B73 × Mo17 population containing 180 RILs [17]. Utilizing 1.49×10⁶ single nucleotide polymorphism (SNP) markers, Lu et al. identified 22 SNP that were significantly associated with leaf angle and located on eight chromosomes, explaining 21.62% of the phenotypic variation [25]. The natural variations in leaf architecture were also discovered in connected RIL populations in maize. Tian et al. used nested association mapping (NAM) population from 25 crosses between diverse inbred lines and B73 to conduct joint linkage mapping for the leaf architecture, and identified thirty small-effect QTL for leaf angle [26]. A total of 14 leaf angle QTL were also identified using a four-way cross mapping population [27]. The large numbers of QTL for leaf angle detected in various mapping populations strengthen the understanding of the genetic mechanism of leaf angle in maize. However, different results were provided by different studies, including QTL number, location, and genetic effect. Inconsistent results of QTL detection in different study shown the importance and necessity of QTL mapping to uncover the tangled genetic mechanism of leaf angle. Therefore, taking the polygenic and complex inheritance nature of maize's leaf angle into consideration, further investigating the QTL that underlie the trait's phenotypic variance is required.

In the present study, a F_3:4 RIL population derived from a cross between inbred line B73 and Zheng58, was constructed to identify QTL for leaf angle. The objective of the study is to further elucidate the genetic architecture that underlie leaf angle, and to further evaluate and confirm the genetic effect of QTL allele through heterogeneous inbred family approach. It is expected that the further study into the genetic mechanism that underlies the leaf angle could provide candidate genes for maize breeding projects.

Materials and methods

Plant materials

The recombination inbred line population was constructed by crossing Zheng58 with B73. The two parents were selected on the basis of maize germplasm groups and their different leaf architecture. Zheng58 is an elite foundation inbred line with compact leaf architecture, as female parent of a famous maize variety Zhengdan958 in China. B73 is a model inbred line with expanded leaf architecture and has been sequenced [28]. A single seed descent from one F₁ progeny and then two generations of self-pollination were applied to produce the recombination inbred line population with 165 lines [29].

Field experiments and statistical analyses

The trials were conducted at the Songjiang experimental station in Shanghai (121°45′E, 31°12′N) from April to September during 2014 and 2015, where experimental field bases have been set up by the school of life sciences, Fudan University. More than two hundred lines were planted and 165 lines were survival. The school of life sciences was approved for field experiments, and the field studies did not involve protected or endangered species. The randomized complete block design with two replications was employed. Every plot had a row of three meters long and 0.67 meters wide with a planting density of 50,000 plants per hectare. Corn field management was in accordance with traditional Chinese agricultural production management methods.

Ten days after pollination (DAP), three plant representatives from the middle of each plot were randomly selected to evaluate the leaf angle. We measured three leaves and used the mean value for data analysis. Traditionally, leaf angle was assessed by measuring the angle of each leaf from a plane defined by the stalk below the node subtending the leaf. Three consecutive leaves were measured for each plant, including the first leaf above the primary ear, the primary ear leaf and the first leaf below the primary ear. The leaf angle data for each of RIL populations was averaged for the three measured plants.

To further verify the authenticity of the QTL mapping results and the allelic effects of the leaf angle QTL, we constructed six heterogeneous inbred family (HIF) lines [30] from F₃ RIL segregating for target leaf angle locus but homozygous for the other major leaf angle loci. Each heterogeneous inbred family consisted of at least 120 plants and each individual from the progeny of these heterogeneous inbred family was genotyped using a molecular marker. And the molecular markers were tightly linked to the target QTL. Meanwhile, the leaf angle phenotype as described above was measured. ANOVA was used to compare and analyze phenotypic differences between different homozygous lines isolated in the target QTL region.

Statistical analysis of the phenotypic mean data measured in the population was performed using SPSS 20.0 software. The broad-sense heritability (h²) was estimated as the proportion of variance explained by between RIL (genotypic) variance and RIL by block (error) variance.

Genetic map construction and QTL mapping

Samples for DNA extraction were collected at the four-leaf stage of the seedlings in the RIL population and parent line, and genomic DNA was isolated using the CTAB method [31]. The F₃ plants were genotyped using SSR markers. Primer sequences are available from the Maize Genetics and Genomic Database (Maize GDB).

The software package MapQTL6.0 was used to identify and locate QTL on the linkage map by using interval mapping and multiple-QTL model (MQM) mapping methods as described by Churchill et al. [32] and Huang et al. [33]. LOD threshold values applied to declare the presence of QTL were estimated by performing permutation tests implemented in Map QTL 6.0 using at least 1000 permutations of the original data set, resulting in a 95% log 10 of the odds ratio threshold values of 2.9. Using MQM mapping, the percentage of variance explained and the estimated additive genetic effect by each QTL and the total variance explained by all the QTL affecting a trait were obtained [33].

DNA library construction and Whole-genome re-sequencing analysis of Zheng 58

Extraction of total genomic DNA from young leaves of inbred line Zheng 58 by modified CTAB method [31]. Separation of genomic DNA used to generate sequencing libraries. The constructed library was first subjected to library quality checks, and the quality qualified library was sequenced by HiSeq system using standard protocols.

The raw readings (double-ended sequences) obtained by sequencing were quality assessed and filtered to obtain Clean Reads for subsequent bioinformatics analysis. The Burrows-Wheeler Alignment (BWA) software aligns the short sequences obtained from the second-generation high-throughput sequencing with the reference genome. The Clean Reads were compared with the reference genome sequence. The SNP and Small InDel were detected and annotated according to the comparison results.

Total RNA extraction and expression analysis of candidate genes

Fresh leaves in V5 stage were sampled from the B73 and Zheng58 [15]. According to the manufacturer’s instructions, total RNA was isolated from sampled fresh leaves using Fast Pure Plant Total RNA Isolation Kit (Vazyme, RC401). 1.0 μg of each sample total RNA was reverse transcribed (Vazyme, R323), and then performed Quantitative PCR (Vazyme, Q711). 18S was selected as housekeeping genes for the internal control, and the primers used in the RT-qPCR are listed in S1 Table. Three independent biological replicates were collected for each sample. The candidate genes expression levels were quantified with the comparative CT(2^-△△CT) method.

Results and discussions

Analysis of leaf angle in F_3:4 population and parental lines

There was significant difference in leaf angle between the two parents B73 and Zheng58. Zheng58 had compact leaf architecture (Fig 1A) with an average leaf angle of 31°, whereas B73 displayed expanded leaf architecture (Fig 1B) with an average leaf angle of 62° (Table 1). Table 1 presented the descriptive statistics of leaf angle for the two parents and the F_3:4 population. The wider range of variation for leaf angle in the F_3:4 population was observed, and normal distribution with transgressive segregation suggested polygenic inheritance of the trait (Fig 1C). The calculated broad-sense heritability (h²) value for leaf angle trait was high as shown in Table 1.

Table 1. Descriptive statistical analysis of phenotypic values of leaf angle in parents and F_3:4 population.

Trait	B73^a	Zheng58^a	F_3:4 population
Trait	B73^a	Zheng58^a	Max	Min	Mean	SD	Kurtosis	Skewness	h² (%)
^bLA	62.78	31.23	76.00	32.00	49.81	6.81	0.87	0.42	80.20

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^aThe data corresponding to leaf angle of the two parents are average values; P < 0.01.

^bLA: leaf angle.

Detection of the leaf angle QTL

189 SSR markers with polymorphic between the two parents were identified by the screen of 393 SSR primer pairs which evenly distributed on the genome of maize genome. These markers were assigned to corresponding chromosome based on their physical position. The total length of the physical map was 2,058.59 Mb. The number of molecular markers distributed on each chromosome varied from 13 to 29, with an average of 18.8. The average physical distance between two adjacent markers was 10.79 Mb, with the shortest marker interval of 1.42 Mb and the longest 38.78 Mb, and the distribution of all markers in chromosome was not crowded and relatively evenly distributed (Fig 2).

QTL analysis of leaf angle was conducted using Map QTL 6.0 software. Eight QTL for leaf angle on chromosome 1, 1, 2, 3, 4, 4, 8 and 8 were detected (Fig 2), respectively, which explained 65.4% of the total phenotypic variance, and each QTL explained phenotypic variance ranging from 4.3 to 14.2% (Table 2). It was noteworthy that all QTL had positive additive effects, suggesting that the B73 parent contributed most alleles for increasing leaf angle (Table 2).

Table 2. Analysis of QTL for controlling leaf angle.

QTL	Chr.	Position (Mb)	Marker interval	The nearest markers to QTL	LOD	Additive effect	Explained variance %
qLA01-01	1	211.78	umc2236-bnlg1025	bnlg1556	4.73	3.253	8.8
qLA01-02	1	285.67	umc2189-umc2243	umc1421	2.96	2.677	4.3
qLA02-01	2	195.48	umc1080-umc2005	bnlg2077	7.55	4.109	14.2
qLA03-01	3	220.49	umc2275-umc1594	bnlg1496	3.16	2.803	5.8
qLA04-01	4	10.68	umc1164-umc2281	nc004	4.95	3.445	9.1
qLA04-02	4	156.88	umc1142-umc1808	umc0371	3.67	3.082	6.7
qLA08-01	8	85.88	umc1904-phi100175	umc1735	5.2	3.687	10.3
qLA08-02	8	132.72	umc1959-umc1777	bnlg162	3.24	2.946	6.2

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Additive effect: A positive value indicates that the B73 allele increases the value of the trait; A negative value indicates that the Zheng58 allele increases the value of the trait.

Compared to previous studies (Fig 3), five of the eight QTL for leaf angle were found to have similar chromosomal locations with different mapping experiments or different genetic background. The result demonstrated that the chromosome regions for these consistent QTL might be hot spots for the important QTL for leaf angle. Also the congruence in QTL detected in this study with previous reports indicated the robustness of our results. However, in our study, no QTL was detected on chromosome 5, 6, 7, 9 and 10, which may be due to the too small genetic effects or no allelic difference between the two parents. Interestingly, three QTL were detected on bottom of chromosome 3 (qLA03-01), which shared an interval of 22.10 Mb from 209.81 to 231.91 Mb, middle of chromosome 4 (qLA04-02), which shared an interval of 45.92 Mb from 135.34 to 181.26 Mb, and middle of chromosome 8 (qLA08-01), which shared an interval of 30.48 Mb from 69.90 to 100.38 Mb, respectively. These three QTL have not been reported in previous researchers (Figs 2 and 3). These novel QTL might be due to the specific genetic background from parent Zheng58 with compact leaf architecture. Furthermore, newly detected major QTL may serve a complementary role in revealing the genetic mechanism of leaf angle trait.

Confirmation of QTL for leaf angle

There were some heterozygous regions in the genome of the F₄ plants. These regions can be applied to validation of QTL through a HIF strategy as described by Tuinstra et al. in 1997 [30]. The HIF strategy has been widely practiced in QTL confirmation and fine mapping [34,35]. In this study, we tried to apply the HIF strategy to validate the allelic effects of six major QTL for leaf angle. HIF segregating for the target QTL to be validated but homozygous for other major QTL regions were chosen. For instance, a RIL (HIF155) with heterozygous region in qLA01-01 was chosen to develop HIF. Theoretically, the leaf angle trait in progenies from selfed HIF155 will be only segregated for qLA01-01. We developed the other five HIFs in the same way. HIF027, HIF025, HIF089, HIF074 and HIF084 were heterozygous at marker umc1421 (qLA01-02), bnlg2077 (qLA02-01), bnlg1496 (qLA03-01), umc0371 (qLA04-02) and umc2147 (qLA08-01), respectively. The overview result for all HIF was presented in Fig 4. In the progenies of all HIFs, the plants carrying B73 alleles at the respective target QTL displayed a significantly bigger leaf angle than those carrying Zheng58 alleles. Therefore, the allelic effects of the major QTL were preliminarily validated.

Fig 4 — The same letter indicates no significant difference between them, and different letters indicate a significant difference (P value < 0.05).

Considering that the phenotype of leaf angle was easily affected by environmental conditions, we planted these 165 lines in the same season and the same field in 2014 and 2015. These 165 lines showed good repeatability in the phenotype of leaf angle and the phenotypic data were used to detected the QTL for leaf angle. The environmental factors affecting leaf angle phenotype were minimized and the QTL X environment effect was not detected. Subsequently, we construct the HIF populations to verify the major QTL, each HIF population with at least 120 plants. These plants were also grown in the same season and the same field in 2016. The results verified the authenticity of the QTL mapping results and showed that these major QTL are stable and inheritable. In this work, the character of the leaf angle trait resulted from the genetic characteristics of selected parents, Zheng58 and B73.

Whole-genome re-sequencing

In order to compare the genomic sequence differences between the two parents and predicted candidate genes for target QTL, Zheng58 was conducted the whole-genome re-sequencing. After filtering, 91.69 G bp Clean-Base was obtained for subsequent data analysis and the Q30 ratio reached 92.93%, with the 91.68% (at least one base coverage) genome coverage (S2 Table). By aligning against the B73 reference genome, the genome coverage on average for the reference up to 98.83%, which can give 37× average genome sequencing coverage depth (S1 and S2 Figs). It can be seen from the figure (S2 Fig) that the genome is covered more uniformly, indicating that the sequencing randomness is better. The uneven depth on the map may be due to repeated sequences and PCR preferences. These data demonstrated that the whole-genome re-sequencing data was robust and can be used to subsequent candidate genes analysis.

Candidate genes prediction in major QTL qLA02-01 region

Comparing the genomic sequence differences in the qLA02-01 region between the two parents, we found that 156 genes were variated in the coding region, of which 18 stop gained SNP and 8 start lost SNP were related to 30 genes and 254 InDel (including 6 stop gained InDel, 2 start lost InDel and 246 frame-shift InDel) were related to 126 genes. Absolutely, stop gained and start lost, as well as frame-shift mutations often have a greater impact on causing changes in gene function. Thence, these mutations stimulated our further research interest. Although the mechanism underlying leaf angle is still unclear, previous studies have shown that genes associated with cell cycle, cell size, gravity and plant hormones may participate in regulation of leaf angle development [36]. By analysis of biological processes in the GO annotation clustering results, combined KEGG metabolic pathway analysis, we screened 33 GO enriched genes in the major qLA02-01 region (Table 3). With the help of GO term and functional annotation of candidate genes, ultimately six candidate genes are targeted: Zm00001d005803, auxin-activated signaling pathway (GO:0009734); Zm00001d005888, response to abscisic acid (GO:0009737); Zm00001d005889, oxidation-reduction process (GO:0055114); Zm00001d006274, auxin-activated signaling pathway (GO:0009734); Zm00001d006494, response to karrikin (GO:0080167); Zm00001d006587, response to blue light (GO:0009637).

Table 3. Selected candidate genes of leaf angle in qLA02-01 with mutations in the CDS region.

Gene ID	GO term	Description	Codon change	Effect
Zm00001d005614	oxidation-reduction process (GO:0055114);	Bifunctional protein FolD 1 mitochondrial	tga/	FRAME_SHIFT
Zm00001d005682	glucuronoxylan metabolic process (GO:0010413);	Protein kinase superfamily protein	atc/	FRAME_SHIFT
Zm00001d005785	isopentenyl diphosphate biosynthetic process, methylerythritol 4-phosphate pathway (GO:0019288);	Pentatricopeptide repeat-containing protein	att/aTtt	FRAME_SHIFT
Zm00001d005779	Biological Process: regulation of transcription, DNA-templated (GO:0006355);	ubiquitin carrier protein 7	Gga/Tga	STOP_GAINED
Zm00001d005792	negative regulation of catalytic activity (GO:0043086);	amidase1	gag/	FRAME_SHIFT
*Zm00001d005803*	auxin-activated signaling pathway (GO:0009734);	SAUR-like auxin-responsive protein family	gcc/gcGGc	FRAME_SHIFT
Zm00001d005808	phosphorylation (GO:0016310);	Probable ethanolamine kinase	cgt/cgTt	FRAME_SHIFT
Zm00001d005812	sister chromatid cohesion (GO:0007062);	sterile alpha motif (SAM) domain-containing protein	tta/ttTa	FRAME_SHIFT
Zm00001d005866	cell redox homeostasis (GO:0045454);	Protein disulfide-isomerase like 2–2	ttg/ttTTg	FRAME_SHIFT
*Zm00001d005888*	response to abscisic acid (GO:0009737);	Heat stress transcription factor B-3	taa/	FRAME_SHIFT
*Zm00001d005889*	oxidation-reduction process (GO:0055114);	abscisic acid 8'-hydroxylase 5	tgccgg/aca/	FRAME_SHIFT
Zm00001d005908	response to wounding (GO:0009611);	Tyrosine-sulfated glycopeptide receptor 1	ttt/ttGt	FRAME_SHIFT
Zm00001d005925	starch biosynthetic process (GO:0019252);	Glucose-6-phosphate isomerase 1 chloroplastic	gtt/	FRAME_SHIFT
Zm00001d005932	oxidation-reduction process (GO:0055114);	Aldose reductase	acg/aAcg	FRAME_SHIFT
Zm00001d006027	regulation of transcription, DNA-templated (GO:0006355);	bZIP transcription factor family protein	gct/tatgac/tcc/tccTCCGTCC	FRAME_SHIFT
Zm00001d006153	defense response by callose deposition (GO:0052542);	1-acylglycerol-3-phosphate O-acyltransferase	cca/	FRAME_SHIFT
Zm00001d006172	Biological Process: protein phosphorylation (GO:0006468);	Serine/threonine-protein kinase Rio1	tGg/tAg	STOP_GAINED
Zm00001d006193	oxidation-reduction process (GO:0055114);	cytochrome P450 family 78 subfamily A polypeptide 8	gcc/	FRAME_SHIFT
*Zm00001d006274*	auxin-activated signaling pathway (GO:0009734);	Auxin-responsive protein SAUR61	ggt/gAgt	FRAME_SHIFT
Zm00001d006295	protein phosphorylation (GO:0006468);	DNA-binding bromodomain-containing protein	ttg/ttgCTTGTTG	FRAME_SHIFT
Zm00001d006344	regulation of transcription, DNA-templated (GO:0006355);	Protein SUPPRESSOR OF FRI 4	ggt/ggGt	FRAME_SHIFT
Zm00001d006389	membrane fusion (GO:0006944);	small G protein family protein / RhoGAP family protein	ttt/att/	FRAME_SHIFT
Zm00001d006437	Biological Process: cell redox homeostasis (GO:0045454);	Monothiol glutaredoxin-S17	atG/atA	START_LOST
Zm00001d006476	glycolytic process (GO:0006096);	aconitase5	cct/ccTt	FRAME_SHIFT
*Zm00001d006494*	response to karrikin (GO:0080167);	Protein DETOXIFICATION 40	gcttttcctctctttttttttccc/aag/aAGGTagatt/aTttctt/ttc/ttCCCCc	FRAME_SHIFT
Zm00001d006536	Biological Process: phosphorylation (GO:0016310);	Cysteine-rich receptor-like protein kinase 10	Gaa/Taa	STOP_GAINED
Zm00001d006548	response to wounding (GO:0009611);	Histone H2A	ctgctt/	FRAME_SHIFT
Zm00001d006586	response to salt stress (GO:0009651);	Peptidyl-prolyl cis-trans isomerase Pin1	tcccgcccgcagctc/	FRAME_SHIFT
*Zm00001d006587*	response to blue light (GO:0009637);	Chlorophyll a-b binding protein CP29.1 chloroplastic	atg/aAtg	FRAME_SHIFT
Zm00001d006622	Biological Process: electron transport chain (GO:0022900);	CYP72A57	Cag/Tag	STOP_GAINED
Zm00001d006644	Biological Process: circadian rhythm (GO:0007623);	MAP kinase kinase kinase27	tgA/tgG	STOP_LOST
Zm00001d006675	DNA repair (GO:0006281);	ATP-dependent DNA helicase	gtt/gTtt	FRAME_SHIFT
Zm00001d006681	negative regulation of transcription, DNA-templated (GO:0045892);	unknown	atg/	START_LOST

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In addition, variations in gene expression levels may also cause changes in gene function. Therefore, we also screened for genes with mutations in the promoter region, and 21 genes showed GO enrichment (Table 4). By analyzing the gene expression level of genes with mutations in the promoter region, we identified seven genes with significantly different expression levels (Fig 5): Zm00001d005803, auxin-activated signaling pathway (GO:0009734); Zm00001d005818, response to desiccation (GO:0009269); Zm00001d005823, oxidation-reduction process (GO:0055114); Zm00001d005889, oxidation-reduction process (GO:0055114); Zm00001d006296, regulation of translational fidelity (GO:0006450); Zm00001d006443, sister chromatid cohesion (GO:0007062); Zm00001d006494, response to karrikin (GO:0080167).

Table 4. Selected candidate genes of leaf angle in qLA02-01 with mutations in the promoter region.

Gene ID	GO term	Description	Effect
Zm00001d005682	glucuronoxylan metabolic process (GO:0010413);	Protein kinase superfamily protein	UPSTREAM
*Zm00001d005803*	auxin-activated signaling pathway (GO:0009734);	SAUR-like auxin-responsive protein family	UPSTREAM
Zm00001d005808	phosphorylation (GO:0016310);	Probable ethanolamine kinase	UPSTREAM
*Zm00001d005818*	response to desiccation (GO:0009269);	Aldehyde dehydrogenase family 7 member B4	UPSTREAM
*Zm00001d005823*	oxidation-reduction process (GO:0055114);	Flavonoid 3-monooxygenase	UPSTREAM
Zm00001d005888	endoplasmic reticulum unfolded protein response (GO:0030968);	Heat stress transcription factor B-3	UPSTREAM
*Zm00001d005889*	oxidation-reduction process (GO:0055114);	abscisic acid 8'-hydroxylase5	UPSTREAM
Zm00001d006027	endoplasmic reticulum unfolded protein response (GO:0030968);	bZIP transcription factor family protein	UPSTREAM
Zm00001d006036	response to salt stress (GO:0009651);	Heat shock 70 kDa protein 9 mitochondrial	UPSTREAM
Zm00001d006153	toxin catabolic process (GO:0009407);	1-acylglycerol-3-phosphate O-acyltransferase	UPSTREAM
Zm00001d006285	auxin-activated signaling pathway (GO:0009734);	SAUR52-auxin-responsive SAUR family member	UPSTREAM
*Zm00001d006296*	regulation of translational fidelity (GO:0006450);	Valine—tRNA ligase mitochondrial 1	UPSTREAM
Zm00001d006389	membrane fusion (GO:0006944);	small G protein family protein / RhoGAP family protein	UPSTREAM
*Zm00001d006443*	sister chromatid cohesion (GO:0007062);	P-loop containing nucleoside triphosphate hydrolases superfamily protein	UPSTREAM
Zm00001d006467	cysteine biosynthetic process (GO:0019344);	adenosine 5'-phosphosulfate reductase-like2	UPSTREAM
*Zm00001d006494*	response to karrikin (GO:0080167);	Protein DETOXIFICATION 40	UPSTREAM
Zm00001d006629	protein phosphorylation (GO:0006468);	Mitochondrial transcription termination factor family protein	UPSTREAM
Zm00001d006631	transmembrane transport (GO:0055085);	Organic cation/carnitine transporter 7	UPSTREAM
Zm00001d006646	phosphorylation (GO:0016310);	unknown	UPSTREAM
Zm00001d006688	transmembrane transport (GO:0055085);	Putative polyol transporter 1	UPSTREAM
Zm00001d006700	root development (GO:0048364);	mTERF family protein	UPSTREAM

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Fig 5 — The expression level of each candidate gene in B73 is set to 1. The data is the mean ± SD (n = 3). P<0.05 (Student’s t-test).

A total of 10 candidate genes were selected based on the structural variation of the gene promoter region and CDS region. There are three genes that have both genetic structure variation and promoter region variation: Zm00001d005803, Zm00001d005889, and Zm00001d006494. Thus, we suggest that Zm00001d005803, Zm00001d005818, Zm00001d005823, Zm00001d005888, Zm00001d005889, Zm00001d006274, Zm00001d006296, Zm00001d006443, Zm00001d006494 and Zm00001d006587 may be important candidate genes for qLA02-01.

Candidate genes prediction in major QTL qLA08-01 region

We found that 29 genes were variated in the coding region, by comparing the genomic sequence differences in the qLA08-01 region between the two parents, of which 18 stop gained SNP, 1 start lost SNP were related to 14 genes. What’s more, 25 InDel were detected, including 1 start lost InDel, 1 stop lost InDel and 23 frame_shift InDel, related to 18 genes. Three of those 18 genes were displayed in SNP mutation as well.

12 GO enriched genes were screened in the major qLA08-01 region (Table 5), by analysis of biological processes in the GO annotation clustering results, combined KEGG metabolic pathway analysis. Besides, based on the promoter region mutation in Table 6 and 2 genes out of 17 shown significantly variations in gene expression levels (Fig 6).

Table 5. Selected candidate genes of leaf angle in qLA08-01 with mutations in the CDS region.

Gene ID	GO term	Description	Codon change	Effect
*Zm00001d009622*	Biological Process: transcription, DNA-templated (GO:0006351);	Putative AP2/EREBP transcription factor superfamily protein	atc/atcGGCGCCCGCATGACGCGGAAGCGCGgct/tcc/tccTatg/	FRAME_SHIFT
				FRAME_SHIFT
				FRAME_SHIFT
				START_LOST
Zm00001d009642	Biological Process: membrane fusion (GO:0006944);	F-box protein	cta/	FRAME_SHIFT
Zm00001d009671	Biological Process: potassium ion transmembrane transport (GO:0071805);	Potassium transporter 10	tGg/tAg	STOP_GAINED
Zm00001d009676	Biological Process: protein phosphorylation (GO:0006468);	serine/threonine protein kinase 3	gac/gaCctcggac/	FRAME_SHIFT
Zm00001d009730	Biological Process: translation (GO:0006412);	unknown	aaa/	FRAME_SHIFT
Zm00001d009737	Biological Process: GTP catabolic process (GO:0006184);	Tubulin beta-2 chain	Cag/Tag	STOP_GAINED
Zm00001d009754	Biological Process: cell wall macromolecule catabolic process (GO:0016998);	unknown	tac/	FRAME_SHIFT
Zm00001d009789	Biological Process: borate transport (GO:0046713);	Boron transporter 4	agg/	FRAME_SHIFT
Zm00001d009802	Biological Process: protein transport (GO:0015031);	Putative homeobox DNA-binding and leucine zipper domain family protein	cta/cCCta	FRAME_SHIFT
Zm00001d009871	Biological Process: transmembrane transport (GO:0055085); Biological Process: GDP-mannose transport (GO:0015784);	GDP-mannose transporter GONST1	gga/	FRAME_SHIFT
Zm00001d009948	Biological Process: response to heat (GO:0009408);	Heat shock 70 kDa protein 14	cgagga/	FRAME_SHIFT
Zm00001d009962	Biological Process: protein import into nucleus (GO:0006606);	Sas10/Utp3/C1D family	gtt/gGtt	FRAME_SHIFT

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Table 6. Selected candidate genes of leaf angle in qLA08-01 with mutations in the promoter region.

Gene ID	GO term	Description	Effect
Zm00001d009580		Urease accessory protein G	UPSTREAM
Zm00001d009593		unknown	UPSTREAM
Zm00001d009594		Aspartic proteinase A1	UPSTREAM
*Zm00001d009610*		Acetamidase/Formamidase family protein	UPSTREAM
Zm00001d009611		unknown	UPSTREAM
Zm00001d009612		DUF1645 family protein	UPSTREAM
Zm00001d009619		Putative WRKY DNA-binding domain superfamily protein	UPSTREAM
Zm00001d009620		Probable protein phosphatase 2C 33	UPSTREAM
Zm00001d009622	Biological Process: transcription, DNA-templated (GO:0006351);	Putative AP2/EREBP transcription factor superfamily protein	UPSTREAM
Zm00001d009631		CTP synthase family protein	UPSTREAM
Zm00001d009679		ATP-dependent DNA helicase	UPSTREAM
Zm00001d009704			UPSTREAM
Zm00001d009813		Nucleotide/sugar transporter family protein	UPSTREAM
*Zm00001d009835*		Triosephosphate isomerase cytosolic	UPSTREAM
Zm00001d010000		Thioredoxin-like 2–2 chloroplastic	UPSTREAM
Zm00001d010009	Biological Process: translation (GO:0006412);	ribosomal protein L17a	UPSTREAM
Zm00001d010152		Histone deacetylase 8	UPSTREAM

Open in a new tab

Fig 6 — The expression level of each candidate gene in B73 is set to 1. The data is the mean ± SD (n = 3). P<0.05 (Student’s t-test).

In all, 14 candidate genes were filtered as candidate gene. And the result indicates that Zm00001d009622 (Biological Process: transcription, DNA-templated (GO:0006351)), Zm00001d009642 (Biological Process: membrane fusion (GO:0006944)), Zm00001d009671 (Biological Process: potassium ion transmembrane transport (GO:0071805)), Zm00001d009676 (Biological Process: protein phosphorylation (GO:0006468)), Zm00001d009730 (Biological Process: translation (GO:0006412)), Zm00001d009737 (Biological Process: GTP catabolic process (GO:0006184)), Zm00001d009754 (Biological Process: cell wall macromolecule catabolic process (GO:0016998)), Zm00001d009789 (Biological Process: borate transport (GO:0046713)), Zm00001d009802(Biological Process: protein transport (GO:0015031)), Zm00001d009871 (Biological Process: transmembrane transport (GO:0055085); Biological Process: GDP-mannose transport (GO:0015784)), Zm00001d009948(Biological Process: response to heat (GO:0009408)), Zm00001d009962 (Biological Process: protein import into nucleus (GO:0006606)), Zm00001d009610 (Acetamidase / Formamidase family protein), Zm00001d009835 (Triosephosphate isomerase cytosolic) may be important candidate genes for qLA08-01.

Conclusion

In conclusion, the study of genetic basis of leaf angle is important for maize breeding. In the study, eight QTL for leaf angle were detected and most QTL were validated through HIF approach. Candidate gene analysis within the qLA02-01 and qLA08-01 regions was conducted by whole-genome re-sequencing and expression analysis and twenty-four candidate genes for leaf angle were predicted. This study provides a better understanding of the genetic basis of leaf angle. To validate the functionality of candidate genes, future studies should be conducted using RNA-seq at the key developmental stage of maize leaf angle formation. This should alleviate inaccuracies due to differences in DNA sequences between the two parents. Furthermore, moderate fine mapping is more operable to eliminate the blindness of the authentic gene identification. Techniques such as gene editing could be utilized to edit the allele of our candidate genes, which could identify the authentic genes for qLA02-01 and qLA08-01. The cloning and function research of genes in qLA02-01 and qLA08-01 would improve our knowledge about plant architecture, and also can supply good candidate genes for molecular breeding of crops.

Supporting information

S1 Fig. The basic situation of the sequencing depth distribution.

(DOCX)

Click here for additional data file.^{(80.2KB, docx)}

S2 Fig. Genome wide distribution of read coverage.

The horizontal axis is the chromosomal position, and the vertical axis is the median of read density of the corresponding position on the chromosome (log (2)). There is no significant difference at the 5% level. Error bars indicate the standard deviation of the phenotypic values for each genotype.

(DOCX)

Click here for additional data file.^{(105.2KB, docx)}

S1 Table. RT-qPCR primer.

(DOCX)

Click here for additional data file.^{(14.9KB, docx)}

S2 Table. Whole genome resequencing results of Zheng58.

(DOCX)

Click here for additional data file.^{(12.6KB, docx)}

Acknowledgments

The authors are grateful to Institute of Crop Science, Chinese Academy of Agricultural Sciences (ICS, CAAS) and Chinese Crop Germplasm Resources Information System (CGRIS) for providing seeds of the maize inbred lines for experiment. We thank the BioMarker Technologies Company for providing sequencing services.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was funded by National Natural Science Foundation of China (grant number 31471151). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0245129.r001

Decision Letter 0

Maoteng Li

19 Oct 2020

PONE-D-20-25942

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

PLOS ONE

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Reviewer #1: Please see more comments in the attached PDF. Those marked handwriting comments and suggestions should be addressed to improve the manuscripts. Some figures should be edited and reupload for publication if accepted.

Reviewer #2: The manuscript mapped 8 major QTLs with F3:4 recombinant inbred lines (RIL) population derived from B73 x Zheng58 for leaf angle and confirmed some of them through a heterogeneous inbred family (HIF) approach. Candidate genes for the qLA02-01 and qLA08-01 regions, with largest contribution effect, were predicted through bioinformatics analysis. The results will benefit to clone the favorable allele for leaf angle or develop the novel maize varieties with ideal plant architecture through marker-assisted selection.

Major issues

Q1 some basic mistakes

L18

Does "biomass" mean “harvest index" here? Because high biomass may not guarantee high grain yield in maize and, in most cases, I believe, it is the grain yield, not biomass, is the major goal for corn production.

L22

Does the leaf angle refer in particular to that of " the upper leaves of the ear"？

L30

11 is the number of all genes that affect leaf angle in maize? or this is only an incomplete statistical number? In my opinion, there are far more known genes involved in leaf angel control in maize. such as CT2 (https://doi. org/10.1371/journal.pgen.1007374)

L173

I guess the auther want to say the B73 allels conribute to the expanded leaf angel with "additive effect". However, it is easiy to lead confusion to change the meaning of a commonly used concept .

L71

Since phenotypes of quantitative traits are easily affected by environment factors, details of the condition during growing seasons, including coordinate, ptotoperiod, temperature and so on should be provided.

L69

Were the 165 lines used in the experiment from one F2 ear or 165 F2 ears?

L75,76

RIL population with 165 lines is small. You may lose some lines during growing in field experiment. Furthermore, phenotypes of quantitative traits are easily affected by QTL X environment effects. However, only two replications were carried out. I need to know how many lines showed good repeatability ? That directly determines the reliability of the data.

L230,L272

When do the candidate genes prediction, you may eliminate more irrelevant genes if you take the synonymous mutation into account when select candidate genes in CDS regions.

Are there any cloned genes that control the leaf angle locate in QTL regions mapped in the manuscript?

L308

“techniques such as gene editing could be utilized to edit the allele of our candidate genes, which could identify the authentic genes for qLA02-01 and qLA083-1.”

Gene editing do can be utilized to edit the allele of candidate genes. However, in this situation, I believe moderate fine mapping is more operable to eliminate the blindness of the authentic gene identification.

L83-85

“Three consecutive leaves were measured for each plant, including the first leaf above the primary ear, the primary ear leaf and the first leaf below the primary ear.”

which one of the three leaves was used for data collection of leaf angle? Why?

“It was noteworthy that all QTL had positive additive effects, suggesting that the B73 parent contributed most alleles for increasing leaf angle (Table 2).”

Why QTL X environment effect was not detected? It is the character of the leaf angle trait, or it resulted from the experiment design because the phenotype was surveyed in the same field, or resulted from the genetic characteristics of selected parents, zheng58 and B73.

Minor issues

Although, in general, the manuscript was written clearly enough, it still requires extensive editing. eg., There are some grammar mistakes or spelling errors in the manuscript (underlined by red lines), eg. L55, 129,145,260.

Many sentences are too wordy and need to be re-organized.

Some figures and tables, such as Fig.5,6, Table 3, are not essentially to contribute to the research results directly could be provided as supplementary data.

L320,

"The cloning and function research of genes in qLA02-01 and qLA08-01" should be more accureate than “The cloning and function research of qLA02-01 and qLA08-01”

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Reviewer #1: Yes: Shuyu Liu

Reviewer #2: Yes: Yong Shi

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PLoS One. 2021 Jan 6;16(1):e0245129. doi: 10.1371/journal.pone.0245129.r002

Author response to Decision Letter 0

18 Nov 2020

Response: Thanks for your comments. According to your comments and suggestions, we have made some modifications to improve the manuscripts. Some figures have been re-edited and re-upload for publication. Please see the marked-up copy of our manuscript that highlights changes made to the original version. As the manuscript is converted to PDF format, some figures may not be displayed clearly in PDF format. However, each figure in TIFF format in submission system is of high resolution. If the manuscript is accepted, we will provide high-resolution TIFF images to meet the publishing requirements.

Q1 Line 37/76/77 should you change all numbers as letters if they are <10?

Response: Thanks for your comments. We have changed all numbers as letters if they are <10. Please see the marked-up copy of our manuscript that highlights changes made to the original version.

Q2 Ten days after pollination (DAP)

Response: Thanks for your comments. We have inserted a space after “pollination”. Please see Line 86 in the marked-up copy of our manuscript that highlights changes made to the original version.

Q3 Line85 you only measured 9 data points per line, right? Is it too few?

Response: Thanks for your comments. In our work three leaves were measured of each plant. Considering maize plant architecture can be typically evaluated by leaf angle of the three leaves: the first leaf above the primary ear, the primary ear leaf and the first leaf below the primary ear. We randomly choose three out of five plant of each line used for collecting leaf angle data, which can represent the phenotypic value of leaf angle for each line.

Q4 line 151 table1 h2/%?

Response: Thanks for your comments. We have deleted “/%” and inserted “(%)”. Please see line 158 table1 in the marked-up copy of our manuscript that highlights changes made to the original version.

Q4 line159-163 Fig 2 this is not a high resolution map. Resolution of Fig 2 is very low, need to redo.

Response: Thanks for your comments. We have re-upload a high resolution map for Fig 2.

Q5 Line 183 also the number of SSRs used for mapping? Line183-185 better mention corresponding mbp.

Response: Thanks for your comments. In our work, all of the 189 SSR markers with polymorphic between the two parents were used for mapping. In Line183-185, the corresponding Mbp were supplemented. Please see Line191-195 in the marked-up copy of our manuscript that highlights changes made to the original version.

Q6 line 190 Fig 3 use chr or chrom instead of chro for abbreviation.

Response: Thanks for your comments. We used chr instead of chro for abbreviation. Please see Fig 3.

Q7 line 200 Theoretically, the leaf angle trait in progenies from selfing HIF155 will be only segregated for qLA01-01.

Response: Thanks for your comments. We have changed “selfing” into “selfed”. Please see Line 209 in the marked-up copy of our manuscript that highlights changes made to the original version.

Q8 line 233 explain more?

Response: Thanks for your comments. Absolutely, stop gained and start lost, as well as frame-shift mutations often have a greater impact on causing changes in gene function. Thence, these mutations stimulated our further research interest. Please see Line 246-248 in the marked-up copy of our manuscript that highlights changes made to the original version.

Q9 ling316-322 this should be in discussion.

Response: Thanks for your comments. These sentences mainly explained the future studies for the qLA02-01 and qLA08-01. There is no particular “Discussion” section in the main text, so we think it's appropriate to put them here.

Major issues

Q1 some basic mistakes

L18

Response: Thanks for your comments. The grain yield, not biomass, is the major goal for corn production. We deleted "biomass". Please see Line 20 in the marked-up copy of our manuscript that highlights changes made to the original version.

L22

Does the leaf angle refer in particular to that of " the upper leaves of the ear"？

Response: Thanks for your comments. In this sentence, the leaf angle refer in particular to the upper leaves of the ear.

L30

Response: Thanks for your comments. Just as you mentioned, such as CT2, some other genes also affect leaf angle. Here we only listed 11 genes because they were representative genes identified by QTL by mutagenesis and QTL-cloning approach. We modified the sentence. Please see Line 32-33 in the marked-up copy of our manuscript that highlights changes made to the original version.

L173

I guess the auther want to say the B73 allels conribute to the expanded leaf angel with "additive effect". However, it is easiy to lead confusion to change the meaning of a commonly used concept .

Response: Thanks for your comments. Here, "additive effect" is easily to lead confusion. We changed "additive effect" to "additive allele effect". Please see Line 180 and Table 2 in the marked-up copy of our manuscript that highlights changes made to the original version.

L71

Response: Thanks for your comments. Environment factors can affect the leaf angle. We supplemented the planting and growing season in the section “Field experiments and statistical analyses”. Please see the Line 78-79 in the marked-up copy of our manuscript that highlights changes made to the original version.

L69

Were the 165 lines used in the experiment from one F2 ear or 165 F2 ears?

Response: Thanks for your comments. The165 lines were selected from one F2 ear.

L75,76

Response: Thanks for your comments. In this work, more than two hundred lines were planted and 165 lines were survival. Considering that the phenotype of leaf angle was easily affected by environmental conditions, we planted these 165 lines in the same season and the same field in 2014 and 2015. So, the environmental factors affecting leaf angle phenotype were minimized. These 165 lines showed good repeatability in the phenotype of leaf angle and the phenotypic data were used to detected the QTL for leaf angle. Subsequently, we construct the HIF populations to verify the major QTL, each HIF population with at least 120 plants. These plants were also grown in the same season and the same field in 2016. The results verified the authenticity of the QTL mapping results and showed the reliability of the data.

L230,L272

When do the candidate genes prediction, you may eliminate more irrelevant genes if you take the synonymous mutation into account when select candidate genes in CDS regions.

Response: Thanks for your comments. Yes, we eliminated many irrelevant genes by taking the synonymous mutation into account when select candidate genes in CDS. Please see the Line 241and Line285 in the marked-up copy of our manuscript that highlights changes made to the original version.

Are there any cloned genes that control the leaf angle locate in QTL regions mapped in the manuscript?

Response: Thanks for your comments. Yes. Just as shown in Fig 3, some genes has been cloned that control the leaf angle located in the QTL we detected, such as UPA1, lg1 and so on.

L308

“techniques such as gene editing could be utilized to edit the allele of our candidate genes, which could identify the authentic genes for qLA02-01 and qLA083-1.”

Response: Thanks for your comments. We supplemented your suggestion in the text. Please see the line 331 in the marked-up copy of our manuscript that highlights changes made to the original version.

L83-85

“Three consecutive leaves were measured for each plant, including the first leaf above the primary ear, the primary ear leaf and the first leaf below the primary ear.”

which one of the three leaves was used for data collection of leaf angle? Why?

Response: Thanks for your comments. In this work, we measured three leaves and used the mean value for data analysis. Considering maize plant architecture can be typically evaluated by leaf angle of the three leaves: the first leaf above the primary ear, the primary ear leaf and the first leaf below the primary ear. We randomly choose three out of five plant of each line used for collecting leaf angle data.

“It was noteworthy that all QTL had positive additive effects, suggesting that the B73 parent contributed most alleles for increasing leaf angle (Table 2).”

Response: Thanks for your comments. Considering that the phenotype of leaf angle was easily affected by environmental conditions, we planted these 165 lines in the same season and the same field in 2014 and 2015. These 165 lines showed good repeatability in the phenotype of leaf angle and the phenotypic data were used to detected the QTL for leaf angle. The environmental factors affecting leaf angle phenotype were minimized and the QTL X environment effect was not detected. Subsequently, we construct the HIF populations to verify the major QTL, each HIF population with at least 120 plants. These plants were also grown in the same season and the same field in 2016. The results verified the authenticity of the QTL mapping results and showed that these major QTL are stable and inheritable. In this work, the character of the leaf angle trait resulted from the genetic characteristics of selected parents, zheng58 and B73.

Minor issues

Response: Thanks for your comments. We have made some modifications for grammar and spelling. Please see the marked-up copy of our manuscript that highlights changes made to the original version.

Many sentences are too wordy and need to be re-organized.

Some figures and tables, such as Fig.5,6, Table 3, are not essentially to contribute to the research results directly could be provided as supplementary data.

Response: Thanks for your comments. We have made some modifications for many sentences. Fig.5,6 and Table 3 were removed to supplementary data. Please see S1 Fig., S2 Fig. and S2 Table. in the marked-up copy of our manuscript that highlights changes made to the original version.

L320,

"The cloning and function research of genes in qLA02-01 and qLA08-01" should be more accureate than “The cloning and function research of qLA02-01 and qLA08-01”

Response: Thanks for your comments. We made the modification according to your suggestion. Please see Line 333 in the marked-up copy of our manuscript that highlights changes made to the original version.

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PLoS One. doi: 10.1371/journal.pone.0245129.r003

Decision Letter 1

Maoteng Li

14 Dec 2020

PONE-D-20-25942R1

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

PLOS ONE

Dear Dr. Huang,

Please submit your revised manuscript by Jan 28 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: L22 “The less of leaf angle is, the more upright the upper leaves of the ear are.” I believe “The less of leaf angle is, the more upright the leaves are.” is more accurate. The author is descripting a general concept here, and could not explain it refer in particular to a situation. In case of a particular situation, you may explain it separately. For example, you may say’ The less of leaf angle is, the more upright the leaves are. Upright upper leaves of the ear can maximize photosynthesis efficiency…’here.

L173

Actually, Additive allele effect and Additive effect are with the same meaning to me. The author is still descripting a general concept refer in particular to a situation. To avoid confusion, you may not need to explain Additive effect here, “A positive additive effect value indicates that the B73 allele increases the value of the trait; A negative value indicates that the Zheng58 allele increases the value of the trait.” is clearly enough.

L69

I do not understand. If the165 lines were selected from one F2 ear (kernels in the ear are F3 generation), then the single seed descents were from the F3, not F2. Usually, F2 population is a good representative of extensive separation for genes of two parents.

L75 76

It is better to put the sentence in the manuscript, especially “more than two hundred lines were planted and 165 lines were survival.” to indicate the reliability of data

L83-85

Put the sentence” we measured three leaves and used the mean value for data analysis.” in the manuscript in order other researchers could repeat the trial.

Although I still believe there should be some QTL X environment effect even the environmental conditions were controlled, if it is not the character of the leaf angle trait, because environmental deviation should exist between years. However, the explication by the author seems acceptable, so put the explication in the manuscript.

**********

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Reviewer #1: Yes: Shuyu Liu

Reviewer #2: Yes: Yong Shi

PLoS One. 2021 Jan 6;16(1):e0245129. doi: 10.1371/journal.pone.0245129.r004

Author response to Decision Letter 1

15 Dec 2020

Reviewer #2:

L22

“The less of leaf angle is, the more upright the upper leaves of the ear are.” I believe “The less of leaf angle is, the more upright the leaves are.” is more accurate. The author is descripting a general concept here, and could not explain it refer in particular to a situation. In case of a particular situation, you may explain it separately. For example, you may say’ The less of leaf angle is, the more upright the leaves are. Upright upper leaves of the ear can maximize photosynthesis efficiency…’here.

Response: Thanks for your comments. We have delete “The less of leaf angle is, the more upright the upper leaves of the ear are.” And we have inserted “The less of leaf angle is, the more upright the leaves are.” Please see Line 21 and line 22 in the marked-up copy of our manuscript that highlights changes made to the original version.

L173

Response: Thanks for your comments. Under the table we have deleted “effect of the situation of the Zheng58 allele by the B73 allele”. And just use “A positive additive effect value indicates that the B73 allele increases the value of the trait; A negative value indicates that the Zheng58 allele increases the value of the trait.” as the explanation. Please see the Line178 in the marked-up copy of our manuscript that highlights changes made to the original version.

L69

Response: Thanks for your comments. Here we did not describe accurately. We have reorganized our description just as “A single seed descent from one F1 progeny and then two generations of self-pollination were applied to produce the recombination inbred line population with 165 lines.” Please see the Line69-70 in the marked-up copy of our manuscript that highlights changes made to the original version.

L75 76

It is better to put the sentence in the manuscript, especially “more than two hundred lines were planted and 165 lines were survival.” to indicate the reliability of data

Response: Thanks for your comments. We have inserted the sentence “more than two hundred lines were planted and 165 lines were survival.” Please see Line76-77 in the marked-up copy of our manuscript that highlights changes made to the original version.

L83-85

Put the sentence” we measured three leaves and used the mean value for data analysis.” in the manuscript in order other researchers could repeat the trial.

Response: Thanks for your comments. We have put the sentence “We measured three leaves and used the mean value for data analysis.” Please see the line 84-85 in the marked-up copy of our manuscript that highlights changes made to the original version.

Response: Thanks for your comments. We have insert the explication into the manuscript. Please see the line218-228 in the marked-up copy of our manuscript that highlights changes made to the original version.

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PLoS One. doi: 10.1371/journal.pone.0245129.r005

Decision Letter 2

Maoteng Li

23 Dec 2020

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

PONE-D-20-25942R2

Dear Dr. Huang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Maoteng Li

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0245129.r006

Acceptance letter

Maoteng Li

28 Dec 2020

PONE-D-20-25942R2

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

Dear Dr. Huang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

Dr. Maoteng Li

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. The basic situation of the sequencing depth distribution.

(DOCX)

Click here for additional data file.^{(80.2KB, docx)}

S2 Fig. Genome wide distribution of read coverage.

(DOCX)

Click here for additional data file.^{(105.2KB, docx)}

S1 Table. RT-qPCR primer.

(DOCX)

Click here for additional data file.^{(14.9KB, docx)}

S2 Table. Whole genome resequencing results of Zheng58.

(DOCX)

Click here for additional data file.^{(12.6KB, docx)}

Attachment

Submitted filename: PlosOneMaizeLA.pdf

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Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Mapping quantitative trait loci and predicting candidate genes for leaf angle in maize

Ning Zhang

Xueqing Huang

Roles

Abstract

Introduction

Materials and methods

Plant materials

Field experiments and statistical analyses

Genetic map construction and QTL mapping

DNA library construction and Whole-genome re-sequencing analysis of Zheng 58

Total RNA extraction and expression analysis of candidate genes

Results and discussions

Analysis of leaf angle in F3:4 population and parental lines

Fig 1. The maize leaf angle trait.

Table 1. Descriptive statistical analysis of phenotypic values of leaf angle in parents and F3:4 population.

Detection of the leaf angle QTL

Fig 2. Construction of genetic linkage maps and mapping of QTL for controlling leaf angle in Maize.

Table 2. Analysis of QTL for controlling leaf angle.

Fig 3. Comparison of QTL mapping results in this study with the results reported by previous researchers.

Confirmation of QTL for leaf angle

Fig 4. Significant analysis of the mean values of different genotypes in the same HIF population.

Whole-genome re-sequencing

Candidate genes prediction in major QTL qLA02-01 region

Table 3. Selected candidate genes of leaf angle in qLA02-01 with mutations in the CDS region.

Table 4. Selected candidate genes of leaf angle in qLA02-01 with mutations in the promoter region.

Fig 5. The expression levels of the candidate genes on qLA02-01 loci in the two parents, B73 and Zheng58.

Candidate genes prediction in major QTL qLA08-01 region

Table 5. Selected candidate genes of leaf angle in qLA08-01 with mutations in the CDS region.

Table 6. Selected candidate genes of leaf angle in qLA08-01 with mutations in the promoter region.

Fig 6. The expression levels of the candidate gene on qLA08-01 loci in the two parents., B73 and Zheng58.

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

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Maoteng Li

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Author response to Decision Letter 0

Decision Letter 1

Maoteng Li

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Author response to Decision Letter 1

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Maoteng Li

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Acceptance letter

Maoteng Li

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Associated Data

Supplementary Materials

Data Availability Statement

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Analysis of leaf angle in F_3:4 population and parental lines

Table 1. Descriptive statistical analysis of phenotypic values of leaf angle in parents and F_3:4 population.