Mining Candidate Genes of Rind Hardness in Watermelon by BSA-seq and RNA-seq

doi:10.7668/hbnxb.20195074

Abstract

Abstract:

In order to identify the key genes controlling rind hardness and breed crack-resistant watermelon varieties.An F₂ segregating population was created using the high-firmness line 901 and the low-firmness line BSH.Both BSA-seq and RNA-seq approaches were utilized to map the genes responsible for rind hardness.The results of BSA-seq revealed an interval region of 2.14 Mb on chromosome 10,spanning from 1 620 000 to 3 760 000,where the intersection of SNPs and InDels identified 150 candidate genes.Among these,two genes showed non-synonymous mutations,and one gene exhibited a frameshift mutation.Correlation analysis between BSA-seq and RNA-seq identified 6 correlated genes,including Cla97C10G187120, Cla97C10G187020,Cla97C10G187430,Cla97C10G187510,Cla97C10G187280,and Cla97C10G186540.Through bioinformatics analysis,the candidate gene Cla97C10G187120 was identified.The result of qRT-PCR indicated that the transcriptome data was reliable.And the relative expression of the candidate gene Cla97C10G187120 was lower in the line 901 than the line BSH.This study lays a crucial foundation for understanding the molecular mechanisms underlying watermelon rind hardness.

Key words: Watermelon, Rind hardness, BSA-seq, RNA-seq, Candidate genes

ZHANG Jingjing, TIAN Peng, YU Hongchun, LI Bing, GAO Xiurui, LIU Wei, WU Nan, ZHAO Xinze, SONG Xue, LIU Huiru, PAN Xiuqing, WU Yanrong. Mining Candidate Genes of Rind Hardness in Watermelon by BSA-seq and RNA-seq[J]. Acta Agriculturae Boreali-Sinica, 2024, 39(5): 63-71. doi: 10.7668/hbnxb.20195074.

/ / Recommend / Download Citations

URL: http://www.hbnxb.net/EN/10.7668/hbnxb.20195074

http://www.hbnxb.net/EN/Y2024/V39/I5/63

Figures/Tables 15

Fig.1 Parent materials of watermelon

Tab.1 The primer sequences of qRT-PCR

基因 Gene	正向引物(5'-3') Forward primer sequence(5'-3')	反向引物(5'-3') Reverse primer sequence(5'-3')	扩增片段长度/bp Product length
Actin	CCTACAACTCAATTATGAAGTGTG	GAAATCCACATCTGCTGGAAGGTG	240
Cla97C10G187120	AGCCGCTTCGTTTTCCACTA	TTTCACCGGAGGATTTGGCA	131
Cla97C10G187020	CTTCTCGGCGAACTCTCTCC	CCGGCGTCGTTAGGTCAATA	244
Cla97C10G187430	AATCATCGTCCCCATCGCTC	ATCTCCATTGCAGTCGTCCC	183
Cla97C10G187510	CTCGGCCACTCCCAATATCC	GGCCATTGCCGTTGTTAGTT	89
Cla97C10G187280	TTGAGAACCGGACCGGAAGA	CCCAACGAAATGCAACACGA	125
Cla97C10G186540	TAGCTGCAGGCATGAGATGG	GTGAGCTGCTGCTTACAACC	114

Tab.2 The sequencing quality of BSA-seq data

样品 Sample	过滤后有效数据 /bp Clean reads	过滤后碱基数/bp Clean base	Q20百分率/% Q20 percentage	Q30百分率/% Q30 percentage	GC 含量/% GC content
901	35 878 991	10 714 703 004	99.21	95.06	35.45
BSH	41 312 412	12 331 557 616	98.38	91.48	35.05
H	56 536 026	16 884 129 450	99.01	94.13	34.34
L	57 055 314	17 040 003 904	99.26	95.42	33.87

Tab.3 Sequence comparison of samples with reference genome and genes and sequence depth

样品 Sample	过滤后所有数据/bp Clean reads	比对率/% Mapped	有效比对效率/% Properly mapped	平均测序深度/× Average depth	至少覆盖1个碱基位点比例/% Coverage at least 1×	至少覆盖10个碱基位点比例/% Coverage at least 10×
901	71 757 982	96.11	89.35	27	99.62	95.72
BSH	82 624 824	97.50	88.77	32	99.72	97.43
H	113 072 052	99.46	90.55	45	99.63	97.39
L	114 110 628	99.54	91.43	45	99.66	97.76

Tab.4 SNP number and quality analysis of BSA-seq of two pools and parents 个

条目Item	901	BSH	H	L
基因间区Intergenic	88 145	73 191	97 888	98 061
内含子区Intronic	9 542	8 468	11 325	11 330
上游Upstream	19 545	16 431	23 215	23 298
下游 Downstream	14 032	11 515	16 303	16 296
可变剪切位点 Splicing	135	130	160	158
起始密码子丢失 Start-lost	5	5	6	8
同义编码突变 Synonymous	1 147	983	1 353	1 353
非同义编码突变 Non-synonymous	1 306	1 220	1 526	1 525
同义终止密码子突变Synonymous stop	2	3	3	2
终止获得 Stop-gain	18	18	22	21
终止丢失 Stop-lost	5	5	5	5
总数 Total number	133 882	111 969	151 806	152 057

Tab.5 InDel number and quality analysis of BSA-seq of two pools and parents 个

条目Item	901	BSH	H	L
基因间区Intergenic	20 638	18 595	23 313	23 589
内含子区Intronic	7 425	6 885	8 101	8 067
上游Upstream	15 173	14 053	17 653	17 621
下游 Downstream	10 944	10 021	12 504	12 499
可变剪切位点 Splicing	82	71	92	87
起始密码子丢失 Start-lost	6	5	5	4
移码突变 Frame-shift	147	126	172	164
移码缺失Frameshift deletion	24	23	31	25
移码插入Frameshift insertion	35	29	39	41
非移码缺失Non-frameshift deletion	14	15	19	17
非移码插入Non-frameshift insertion	16	13	20	22
终止获得 Stop-gain	5	7	6	6
终止丢失 Stop-lost	2	1	1	3
总数 Total number	54 511	49 844	61 956	62 145

Fig.2 Distribution of based linkage value on chromosomes

Tab.6 Three candidate SNP and InDel sites

基因 Gene	染色体 Chromosome	位置 Position	参考 Reference	突变 Alter	突变类型 Type of mutation
Cla97C10G187120	Cla97Chr10	2 681 123	T	TTTCTTCGATC	移码突变
Cla97C10G187040	Cla97Chr10	2 570 629	C	T	非同义突变
Cla97C10G187030	Cla97Chr10	2 564 103	G	A	非同义突变

Fig.3 Volcanic map of up and down regulated genes in 901_18 d vs BSH_18 d

Fig.4 The top 20 enriched GO analysis of biological process for DEGs 1.Pectin catabolic process;2.Cell wall modification;3.Cellulose catabolic process;4.Photosynthetic electron transport in photosystem Ⅰ;5.Pectin biosynthetic process;6.Cell wall organization;7.Photosynthetic electron transport chain;8.Supramolecular fiber organization;9.Establishment of plastid localization;10.Plastid organization;11.Chloroplast organization;12.Chloroplast avoidance movement;13.Response to water deprivation;14.Chloroplast accumulation movement;15.Chloroplast relocation;16.Cellulose biosynthetic process;17.Polyamine biosynthetic process;18.Establishment of organelle localization;19.Organelle organization;20.Glucosylceramide catabolic process.

Fig.5 The top 20 enriched GO analysis of cellular component for DEGs 1.Nucleosome;2.Integral component of membrane;3.Plasma membrane;4.NAD(P)H dehydrogenase complex (plastoquinone);5.Cell wall;6.Plasmodesma;7.Plant-type cell wall;8.External encapsulating structure;9.Photosystem Ⅱ oxygen evolving complex;10.Nitrite reductase complex [NAD(P)H];11.Cell periphery;12.Clathrin-coated pit;13.Chloroplast thylakoid membrane;14.Extrinsic component of membrane;15.Symplast;16.Apoplast;17.Cortical microtubule cytoskeleton;18.Cortical cytoskeleton;19.Clathrin-coated vesicle;20.Cell-cell junction.

Fig.6 The top 20 enriched GO analysis of molecular function for DEGs 1.Transferase activity,transferring glycosyl groups;2.Pectinesterase activity;3.Protein heterodimerization activity;4.Enzyme inhibitor activity;5.Polygalacturonate 4-alpha-galacturonosyltransferase activity;6.Aspartyl esterase activity;7.Cellulase activity;8.Quercetin 7-O-glucosyltransferase activity;9.Quercetin 3-O-glucosyltransferase activity;10.Methyltransferase activity;11.Nickel cation binding;12.Cytoskeletal protein binding;13.Phosphatidylinositol-4,5-bisphosphate binding;14.Glucosylceramidase activity;15.5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase activity;16.Antiporter activity;17.Xenobiotic transmembrane transporter activity;18.Kinase inhibitor activity;19.Cellulose synthase (UDP-forming) activity;20.Pectate lyase activity.

Fig.7 The top 20 enriched KEGG analysis for 1 313 DEGs 1.Amino sugar and nucleotide sugar metabolism;2.Carbon fixation in photosynthetic organisms;3.Fructose and mannose metabolism;4.Cyanoamino acid metabolism;5.Carbon metabolism;6.Glutathione metabolism;7.Glyoxylate and dicarboxylate metabolism;8.Starch and sucrose metabolism;9.Pentose and glucuronate interconversions;10.Biosynthesis of amino acids;11.Glycine,serine and threonine metabolism;12.Arachidonic acid metabolism;13.Zeatin biosynthesis;14.Photosynthesis;15.Pentose phosphate pathway;16.Cysteine and methionine metabolism;17.Other glycan degradation;18.Phenylpropanoid biosynthesis;19.Flavonoid biosynthesis;20.Selenocompound metabolism.

Tab.7 Expression analysis of six genes

基因 Gene	9011_FPKM	9012_FPKM	9013_FPKM	BSH1_FPKM	BSH2_FPKM	BSH3_FPKM
Cla97C10G187120	134.243	128.044	87.503	170.368	183.159	196.403
Cla97C10G187020	0.642	0.529	1.125	1.769	1.874	2.880
Cla97C10G187430	58.839	64.724	42.701	39.130	27.658	38.906
Cla97C10G187510	25.865	25.558	22.007	12.591	12.198	16.062
Cla97C10G187280	9.248	11.721	10.308	21.901	20.634	21.035
Cla97C10G186540	193.472	183.791	162.411	68.575	70.094	89.656

Fig.8 qRT-PCR confirmation of the differentially expressed genes There were significant differences between lowercase letters(P<0.05);There were extremely significant differences between capital letters(P<0.01).

References 29

[1]	Gibert C, Chadœuf J, Vercambre G, Génard M, Lescourret F. Cuticular cracking on nectarine fruit surface:spatial distribution and development in relation to irrigation and thinning[J]. Journal of the American Society for Horticultural Science, 2007, 132(5):583-591.doi:10.21273/jashs.132.5.583.
[2]	张朝阳, 程瑞, 徐兵划, 顾妍, 黄大跃, 孙玉东. BSA联合转录组分析发掘西瓜叶片黄化候选基因[J]. 江苏农业学报, 2024, 40(1):165-173.doi:10.3969/j.issn.1000-4440.2024.01.018.
	Zhang C Y, Cheng R, Xu B H, Gu Y, Huang D Y, Sun Y D. Identification of candidate genes for watermelon leaf yellowing based on BSA and transcriptome analysis[J]. Jiangsu Journal of Agricultural Sciences, 2024, 40(1):165-173.
[3]	任艺慈, 刘喜存, 王文英, 霍建中, 郭春江, 赵卫星. 西瓜抗病毒病研究进展[J]. 中国瓜菜, 2022, 35(2): 1-6. doi:10.16861/j.cnki.zggc.2022.0044.
	Ren Y C, Liu X C, Wang W Y, Huo J Z, Guo C J, Zhao W X. Research progress of virus resistance in watermelon[J]. China Cucurbits and Vegetables, 2022, 35(2):1-6.
[4]	赵尊练, 王鸣. 西瓜种质果实耐贮性机理的研究[J]. 园艺学报, 1994, 21(1):99-100.
	Zhao Z L, Wang M. Study on the mechanism of storage resistance of watermelon germplasm fruit[J]. Acta Horticulturae Sinica, 1994, 21(1):99-100.
[5]	王学征, 杨天天, 刘争, 孙蕾, 朱子成, 高鹏, 刘识, 栾非时. 西瓜果皮硬度相关性状分析[J]. 东北农业大学学报, 2020, 51(2):35-44.doi:10.19720/j.cnki.issn.1005-9369.2020.02.0005.
	Wang X Z, Yang T T, Liu Z, Sun L, Zhu Z C, Gao P, Liu S, Luan F S. Analysis on hardness related characters of watermelon rind[J]. Journal of Northeast Agricultural University, 2020, 51(2):35-44.
[6]	江海坤. 西瓜(Citrulls lanatus)裂果机理及其分子标记研究[D]. 南京: 南京农业大学, 2010.doi:10.7666/d.Y1763371.
	Jiang H K. Mechanism of fruit cracking and molecular marker in watermelon(Citrulls lanatus)[D]. Nanjing: Nanjing Agricultural University, 2010.
[7]	Liao N Q, Hu Z Y, Li Y Y, Hao J F, Chen S N, Xue Q, Ma Y Y, Zhang K J, Mahmoud A, Ali A, Malangisha G K, Lyu X L, Yang J H, Zhang M F. Ethylene-responsive factor 4 is associated with the desirable rind hardness trait conferring cracking resistance in fresh fruits of watermelon[J]. Plant Biotechnology Journal, 2020, 18(4):1066-1077.doi:10.1111/pbi.13276. pmid: 31610078
[8]	Zhan Y F, Hu W, He H, Dang X M, Chen S B, Bie Z L. A major QTL identification and candidate gene analysis of watermelon fruit cracking using QTL-seq and RNA-seq[J]. Frontiers in Plant Science, 2023, 14:1166008.doi:10.3389/fpls.2023.1166008.
[9]	范敏, 许勇, 张海英, 任华中, 康国斌, 王永健, 陈杭. 西瓜果实性状QTL定位及其遗传效应分析[J]. 遗传学报, 2000, 27(10):902-910. pmid: 11192435
	Fan M, Xu Y, Zhang H Y, Ren H Z, Kang G B, Wang Y J, Chen H. Identification of quantitative trait loci associated with fruit traits in watermelon[Citullus lanantus (thanb) mansf]and analysis of their genetic effects[J]. Acta Genetica Sinica, 2000, 27(10):902-910. pmid: 11192435
[10]	Guo S G, Zhang J G, Sun H H, et al. The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions[J]. Nature Genetics, 2013, 45(1):51-58.doi:10.1038/ng.2470. pmid: 23179023
[11]	Yang T T, Amanullah S, Pan J H, Chen G X, Liu S, Ma S W, Wang J M, Gao P, Wang X Z. Identification of putative genetic regions for watermelon rind hardness and related traits by BSA-seq and QTL mapping[J]. Euphytica, 2021, 217(2):19.doi:10.1007/s10681-020-02758-9.
[12]	宋小明. 白菜类作物基因组及重要农艺性状相关基因的生物信息学分析[D]. 南京: 南京农业大学, 2015.doi:10.7666/d.Y3184356.
	Song X M. The genome of brassica Rapa crops and bioinfomatic analyses for the important agronomic traits related genes[D]. Nanjing: Nanjing Agricultural University, 2015.
[13]	张敬敬, 李冰, 史宇凡, 高秀瑞, 潘秀清, 宋雪, 武彦荣. 不同硬度西瓜果皮的转录组测序及相关基因表达分析[J]. 华北农学报, 2022, 37(3):44-52.doi:10.7668/hbnxb.20192957.
	Zhang J J, Li B, Shi Y F, Gao X R, Pan X Q, Song X, Wu Y R. Transcriptome sequencing and gene expression analysis of watermelon peel with different firmness[J]. Acta Agriculturae Boreali-Sinica, 2022, 37(3):44-52. doi: 10.7668/hbnxb.20192957
[14]	Gao Y, Guo Y, Su Z Y, Yu Y, Zhu Z C, Gao P, Wang X Z. Transcriptome analysis of genes related to fruit texture in watermelon[J]. Scientia Horticulturae, 2020, 262:109075.doi:10.1016/j.scienta.2019.109075.
[15]	Guo Z H, Cai L J, Chen Z Q, Wang R Y, Zhang L M, Guan S W, Zhang S H, Ma W D, Liu C X, Pan G J. Identification of candidate genes controlling chilling tolerance of rice in the cold region at the booting stage by BSA-Seq and RNA-Seq[J]. Royal Society Open Science, 2020, 7(11):201081.doi:10.1098/rsos.201081.
[16]	Wang X, Liu C K, Tu B J, Li Y S, Chen H, Zhang Q Y, Liu X B. Characterization on a novel rolled leaves and short petioles soybean mutant based on Seq-BSA and RNA-seq analysis[J]. Journal of Plant Biology, 2022, 65(4):261-277.doi:10.1007/s12374-020-09295-x.
[17]	Ye S H, Yan L, Ma X W, Chen Y P, Wu L M, Ma T T, Zhao L, Yi B, Ma C Z, Tu J X, Shen J X, Fu T D, Wen J. Combined BSA-seq based mapping and RNA-seq profiling reveal candidate genes associated with plant architecture in Brassica napus[J]. International Journal of Molecular Sciences, 2022, 23(5):2472.doi:10.3390/ijms23052472.
[18]	Hill J T, Demarest B L, Bisgrove, Gorsi B, Su Y C, Yost H J. MMAPPR:mutation mapping analysis pipeline for pooled RNA-seq[J]. Genome Research, 2013 23:687-697.
[19]	Fekih R, Takagi H, Tamiru M, Abe A, Natsume S, Yaegashi H, Sharma S, Sharma S, Kanzaki H, Matsumura H, Saitoh H, Mitsuoka C, Utsushi H, Uemura A, Kanzaki E, Kosugi S, Yoshida K, Cano L, Kamoun S, Terauchi R. MutMap+:genetic mapping and mutant identification without crossing in rice[J]. PLoS One, 2013 8(7):e68529.
[20]	吴元明, 林佳怡, 柳雨汐, 李丹婷, 张宗琼, 郑晓明, 逄洪波. 基于BSA-seq和RNA-seq挖掘水稻株高相关QTL[J]. 生物技术通报, 2023, 39(8):173-184.doi:10.13560/j.cnki.biotech.bull.1985.2023-0386.
	Wu Y M, Lin J Y, Liu Y X, Li D T, Zhang Z Q, Zheng X M, Pang H B. Identification of rice plant height-associated QTL using BSA-seq and RNA-seq[J]. Biotechnology Bulletin, 2023, 39(8):173-184.
[21]	曾维英, 赖振光, 孙祖东, 杨守臻, 陈怀珠, 唐向民. 基于BSA-Seq和RNA-Seq方法鉴定大豆抗豆卷叶螟候选基因[J]. 作物学报, 2021, 47(8):1460-1471.doi:10.3724/SP.J.1006.2021.04195.
	Zeng W Y, Lai Z G, Sun Z D, Yang S Z, Chen H Z, Tang X M. Identification of the candidate genes of soybean resistance to bean pyralid (Lamprosema indicata Fabricius) by BSA-Seq and RNA-Seq[J]. Acta Agronomica Sinica, 2021, 47(8):1460-1471.
[22]	孙亚倩, 陈士亮, 褚佳豪, 李喜焕, 张彩英. 基于BSA-seq结合连锁分析发掘大豆荚粒性状QTLs及候选基因[J]. 中国农业科技导报, 2023, 25(7):29-42.doi:10.13304/j.nykjdb.2022.0089.
	Sun Y Q, Chen S L, Chu J H, Li X H, Zhang C Y. Mining of QTLs and candidate genes for pod and seed traits via combining BSA-seq and linkage mapping in soybean[J]. Journal of Agricultural Science and Technology, 2023, 25(7):29-42.
[23]	Zhang J J, Li B, Gao X R, Pan X Q, Wu Y R. Integrating transcriptomic and metabolomic analyses to explore the effect of color under fruit calyx on that of fruit apex in eggplant (Solanum melongena L.)[J]. Frontiers in Genetics, 2022, 13:889461.doi:10.3389/fgene.2022.889461.
[24]	Qin G H, Liu C Y, Li J Y, Qi Y J, Gao Z H, Zhang X L, Yi X K, Pan H F, Ming R, Xu Y L. Diversity of metabolite accumulation patterns in inner and outer seed Coats of pomegranate:exploring their relationship with genetic mechanisms of seed coat development[J]. Horticulture Research, 2020, 7:10.doi:10.1038/s41438-019-0233-4.
[25]	Umer M J, Bin Safdar L, Gebremeskel H, Zhao S J, Yuan P L, Zhu H J, Kaseb M O, Anees M, Lu X Q, He N, Gong C S, Liu W G. Identification of key gene networks controlling organic acid and sugar metabolism during watermelon fruit development by integrating metabolic phenotypes and gene expression profiles[J]. Horticulture Research, 2020, 7:193.doi:10.1038/s41438-020-00416-8. pmid: 33328462
[26]	Anees M, Zhu H J, Umer M J, Gong C S, Yuan P L, Lu X Q, He N, Kaseb M O, Yang D D, Zhao Y, Liu W G. Identification of an Aux/IAA regulator for flesh firmness using combined GWAS and bulked segregant RNA-Seq analysis in watermelon[J]. Horticultural Plant Journal, 2024, 10(5):1198-1213.doi:10.1016/j.hpj.2023.05.018.
[27]	Anees M, Gao L, Gong C S, Umer M J, Yuan P L, Zhu H J, Lu X Q, He N, Kaseb M O, Yang D D, Zhao Y, Liu W G. Aux/IAA gene Cla004102,is involved in synergistic regulation of various endogenous hormones,regulating flesh firmness in watermelon[J]. Scientia Horticulturae, 2023, 310:111719.doi:10.1016/j.scienta.2022.111719.
[28]	易萍, 黄方, 李丽, 孙健, 胡美姣, 毕金峰, 滕建文. 芒果乙烯响应转录因子MiERF113基因的克隆及表达分析[J]. 热带作物学报, 2022, 43(9):1751-1758.doi:10.3969/j.issn.1000-2561.2022.09.001.
	Yi P, Huang F, Li L, Sun J, Hu M J, Bi J F, Teng J W. Cloning and expression analysis of ethylene response factor gene MiERF113 in mango (Mangnifera indica L.)[J]. Chinese Journal of Tropical Crops, 2022, 43(9):1751-1758.
[29]	车永梅, 陈慧婷, 张岁芳, 惠梦玲, 叶青, 侯丽霞, 刘新. 葡萄VvWRKY13介导乙烯生物合成调控果实发育[J]. 华北农学报, 2024, 39(2):99-105.doi:10.7668/hbnxb.20194673.
	Che Y M, Chen H T, Zhang S F, Hui M L, Ye Q, Hou L X, Liu X. VvWRKY13 from Vitis vinifera regulate fruit development by controlling ethylene biosynthesis[J]. Acta Agriculturae Boreali-Sinica, 2024, 39(2):99-105.

Please choose a citation manager

Content to export