Multi-environments and multi-models association mapping identified candidate genes of lint percentage and seed index in Gossypium hirsutum L.

Xing, Huixian; Yuan, Yongsheng; Zhang, Haijun; Wang, Liyuan; Mao, Lili; Tao, Jincai; Wang, Xianlin; Wei, Feng; Wang, Haoran; Wang, Qingkang; Wei, Ze; Liu, Xiangliu; Li, Zhongye; Song, Xiaoling; Sun, Xiulan

doi:10.1007/s11032-019-1063-7

Cited by 8 publications

(14 citation statements)

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“…However, there are also inconsistencies with reports by Huang et al Identi cation of novel stable QTL and elite-allele loci for marker-assisted breeding for lint percentage in cotton Lint percentage is an important factor for determining cotton lint yield (Culp and and Harrell 1975) and also a typically quantitative trait, which is controlled by multi-genes (Si et al 2017;Sun et al 2018). Over the past three decades, several QTLs for LP have been detected based on linkage and association mapping in cotton (Liu et al 2015;Said et al 2013;Shang et al 2016), and some of them were also identi ed by GWAS (Su et al 2016;Huang et al 2017;Sun et al 2018;Song et al 2019;Xing et al 2019;Zhu et al 2020). In our study, a total of 34 SNPs were identi ed to be signi cantly associated with LP (Table 3), corresponding with 22 QTLs (as de ned in this study) (Table S2).…”

Section: Discussionmentioning

confidence: 96%

“…Potential candidate genes and the underlying genetic and molecular mechanisms that control the lint percentage Some candidate genes associated with LP were identi ed via GWAS using different association populations in cotton, such as, Gh_A02G1268 (Su et al 2016), Gh_D08G2376 (Huang et al 2017), Gh_D03G1064, Gh_D03G1065, Gh_D03G1067 and Gh_D03G1069 (Fang et al 2017b), Gh_D03G1064 and Gh_D12G2354 (Sun et al 2018), Gh_D05G0313 and Gh_D05G1124 (Song et al 2019, Gh_A10G0378 (Xing et al 2019). In this study, we detected two candidate/causal genes that maybe participating in the early ber development affecting lint percentage in upland cotton.…”

Section: Discussionmentioning

confidence: 99%

“…With the completion of cotton genome sequencing (Paterson et al 2012;Zhang et al 2015;Hu et al 2019;Huang et al 2020) and the establishment of a high-throughput genotyping platform based on the high-throughput array (Hulse-Kemp et al 2015;Cai et al 2017), a large number of single nucleotide polymorphism (SNP) markers have been developed, which greatly promoted the application genome-wide association analyses in cotton. Recently, GWAS research have mainly focused on ber quality (Gapare et al 2017;Sun et al 2017;Dong et al 2018;Li et al 2018a;Tan et al 2018;Yuan et al 2019b) and cotton yield components (Su et al 2016;Sun et al 2018;Song et al 2019;Xing et al 2019;Zhu et al 2020), disease tolerance (Li et al 2017), reniform nematode resistance (Li et al 2018c), salt tolerance (Yuan et al 2019a), drought stress (Hou et al 2018;Li et al 2020) and other agronomic traits in cotton (Li et al 2018b;Yuan et al 2018;Fu et al 2019). However, there are few reports for revealing loci and candidate genes of the lint percentage (LP, %) by GWAS and WGCNA analysis combining strategy in cotton.…”

Section: Introductionmentioning

confidence: 99%

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Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

Chen¹,

Gao²,

Chen³

et al. 2021

Preprint

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Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop widely cultivated in the world. Lint percentage (LP, %) is one of the important yield factor, thus increasing lint percentage is a core goal of cotton breeding improvement. However, the underlying genetic and molecular mechanisms that control lint percentage in upland cotton remain largely unknown. Here, we performed a Genome-wide association study (GWAS) for LP based on phenotypic tests of 254 upland cotton accessions in four environments and BLUPs using the high-density CottonSNP80K array. A total of 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened and 34 SNPs within 22 QTLs were identified as significantly associated with lint percentage trait in different environments. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2) of upland cotton and 50 hub genes were identified through GO enrichment and WGCNA analysis. Furthermore, two candidate/causal genes, Gh_D01G0162 and Gh_D07G0463, which pleiotropically increased lint percentage were identified and further verified its function through LD blocks, haplotypes and qRT-PCR analysis. Co-expression network analysis showed that the candidate/causal and hub gene, Gh_D07G0463, was significantly related to another candidate gene, Gh_D01G0162, and the simultaneous pyramid of the two genes lays the foundation for a more efficient increase in cotton production. Our study provides crucial insights into the genetic and molecular mechanisms underlying variations of yield traits and serves as an important foundation for lint percentage improvement via marker-assisted breeding.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

Chen¹,

Gao²,

Chen³

et al. 2021

Preprint

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“…Based on the Cotton 63K Illumina Infinium SNP array, Sun Z. et al ( 2017 ) genotyped a natural population of 719 Upland cotton accessions, identified 10,511 polymorphic SNPs, and calculated the mean PIC of the A and D subgenome as 0.287 and 0.283, respectively; Song et al ( 2019 ) genotyped 279 Upland cotton accessions and calculated the mean PIC of the whole genome as 0.250 with 10,660 high-quality polymorphic SNPs. Based on the Cotton80KSNP array, Xing et al ( 2019 ) evaluated the mean PIC of 196 Upland cotton accessions as 0.267 with 41,815 polymorphic SNPs. Using 169 cultivated Upland cotton accessions, Li et al ( 2018 ) identified the mean PIC values of the A and D subgenome as 0.282 and 0.281, respectively, with 49,650 polymorphic SNPs.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races

et al. 2022

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Drought seriously threats the growth and development of Gossypium hirsutum L. To dissect the genetic basis for drought tolerance in the G. hirsutum L. germplasm, a population, consisting of 188 accessions of G. hirsutum races and a cultivar (TM-1), was genotyped using the Cotton80KSNP biochip, and 51,268 high-quality single-nucleotide polymorphisms (SNPs) were obtained. Based on the phenotypic data of eight drought relative traits from four environments, we carried out association mapping with five models using GAPIT software. In total, thirty-six SNPs were detected significantly associated at least in two environments or two models. Among these SNPs, 8 and 28 (including 24 SNPs in 5 peak regions) were distributed in the A and D subgenome, respectively; eight SNPs were found to be distributed within separate genes. An SNP, TM73079, located on chromosome D10, was simultaneously associated with leaf fresh weight, leaf wilted weight, and leaf dry weight. Another nine SNPs, TM47696, TM33865, TM40383, TM10267, TM59672, TM59675, TM59677, TM72359, and TM72361, on chromosomes A13, A10, A12, A5, D6, and D9, were localized within or near previously reported quantitative trait loci for drought tolerance. Moreover, 520 genes located 200 kb up- and down-stream of 36 SNPs were obtained and analyzed based on gene annotation and transcriptome sequencing. The results showed that three candidate genes, Gh_D08G2462, Gh_A03G0043, and Gh_A12G0369, may play important roles in drought tolerance. The current GWAS represents the first investigation into mapping QTL for drought tolerance in G. hirsutum races and provides important information for improving cotton cultivars.

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“…El cultivo de algodón es el más importante para la producción de fibra en todo el mundo, principalmente, la especie Gossypium hirsutum L. Toda la producción de fibra es utilizada en la fabricación de tejidos, de textiles y de confecciones y de las semillas, se puede obtener aceite, la harinolina, como forraje crudo, abono o combustible (Ali et al 2018;Xing et al 2019).…”

Section: Introductionunclassified

Evaluación de fuentes de variación en pruebas multi-ambientes para rendimiento y sus componentes en algodón

Araújo-Vázquez

Camacho²,

Buelvas-Guzmán

et al. 2021

Rev. U.D.C.A Act. & Div. Cient.

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La valoración de las fuentes de variación de los análisis de varianza combinado en las pruebas de evaluación multi-ambientes es de gran importancia en la selección de genotipos para recomendar nuevos cultivares, por su adaptabilidad y estabilidad. El objetivo de esta investigación fue evaluar la significancia estadística y contribución de las fuentes de variación: ambientes, genotipos e interacción genotipo x ambiente para rendimiento de algodón-semilla, porcentaje de fibra y rendimiento de fibra, en las zonas del Caribe seco y húmedo colombiano. Se utilizaron los datos de dos pruebas multi-ambientes por zona, donde se evaluaron 10 genotipos de fibra media diferentes, bajo el diseño de bloques completos al azar, con cuatro repeticiones. Cada prueba estuvo conformada por cuatro ensayos realizados durante las cosechas 2003/2004, 2007/2008 y 2009/2010. Los resultados señalan que, en promedio, el ambiente fue la fuente de variación más importante en significancia (p <0,05 y p <0,01) y variación (>64 %), de los análisis de varianza combinado para rendimiento de algodón-semilla y fibra, con tendencia similar en su comportamiento entre ellas y en las dos zonas del Caribe colombiano. Para el porcentaje de fibra en el Caribe seco, la fuente de variación más importante fue genotipos (74,4 %) y en el Caribe húmedo fue el ambiente (57,2 %). Se sugiere subdividir las dos zonas del Caribe en subzonas más homogéneas ambientalmente o aumentar en más de cuatro el número de ensayos por prueba, para minimizar el efecto del ambiente y la interacción genotipo x ambiente.

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Multi-environments and multi-models association mapping identified candidate genes of lint percentage and seed index in Gossypium hirsutum L.

Cited by 8 publications

References 54 publications

Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races

Evaluación de fuentes de variación en pruebas multi-ambientes para rendimiento y sus componentes en algodón

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