Limits...
Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton.

Liu D, Zhang J, Liu X, Wang W, Liu D, Teng Z, Fang X, Tan Z, Tang S, Yang J, Zhong J, Zhang Z - BMC Genomics (2016)

Bottom Line: The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively.This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis.Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

View Article: PubMed Central - PubMed

Affiliation: Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, 400716, Chongqing, People's Republic of China.

ABSTRACT

Background: Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton.

Results: To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly.

Conclusions: This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

No MeSH data available.


Related in: MedlinePlus

RT-PCR expression of the differentially expressed genes in leaf and during fiber development of RIL118 and Yumian1. All data were normalized to the expression level of actin. Error bars indicate standard deviation of three biological replicates
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4837631&req=5

Fig7: RT-PCR expression of the differentially expressed genes in leaf and during fiber development of RIL118 and Yumian1. All data were normalized to the expression level of actin. Error bars indicate standard deviation of three biological replicates

Mentions: To confirm whether the digital gene expression results were reliable, and to investigate the activation of four differentially expressed genes in the QTL region, we further tested the four genes using qRT-PCR in young leaf and fiber tissues across six time-points, designing primers from the A-subgenome of G.hirsutum [14]. The qRT-PCR analysis demonstrated that three of the four genes were expressed in a manner consistent with the RNA-Seq results (Fig. 7). Among them, GhA06G1256, homologous to Gorai.010G174800, exhibited a dramatic increase in 5 DPA fiber of RIL118. GhA06G1277, homologous to Gorai.010G177300 was up-regulated in Yumian 1. GhA06G1301, homologous to Gorai.010G180100, had higher transcript levels in Yumian 1 than inRIL118. However, the qRT-PCR result for GhA06G1313, homologous to GhA06G1313 homologous to Gorai.010G181500, was not entirely consistent with RNA-Seq. The RNA-Seq data for this gene at different fiber development points was not supported well by qRT-PCR analysis. RNA-Seq data analysis based on the G. raimondii genome may reflect expression of both A and D subgenome-derived loci in G. hirsutum, and qRT-PCR data may only reflect the expression of A subgenome genes of G. hirsutum.Fig. 7


Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton.

Liu D, Zhang J, Liu X, Wang W, Liu D, Teng Z, Fang X, Tan Z, Tang S, Yang J, Zhong J, Zhang Z - BMC Genomics (2016)

RT-PCR expression of the differentially expressed genes in leaf and during fiber development of RIL118 and Yumian1. All data were normalized to the expression level of actin. Error bars indicate standard deviation of three biological replicates
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4837631&req=5

Fig7: RT-PCR expression of the differentially expressed genes in leaf and during fiber development of RIL118 and Yumian1. All data were normalized to the expression level of actin. Error bars indicate standard deviation of three biological replicates
Mentions: To confirm whether the digital gene expression results were reliable, and to investigate the activation of four differentially expressed genes in the QTL region, we further tested the four genes using qRT-PCR in young leaf and fiber tissues across six time-points, designing primers from the A-subgenome of G.hirsutum [14]. The qRT-PCR analysis demonstrated that three of the four genes were expressed in a manner consistent with the RNA-Seq results (Fig. 7). Among them, GhA06G1256, homologous to Gorai.010G174800, exhibited a dramatic increase in 5 DPA fiber of RIL118. GhA06G1277, homologous to Gorai.010G177300 was up-regulated in Yumian 1. GhA06G1301, homologous to Gorai.010G180100, had higher transcript levels in Yumian 1 than inRIL118. However, the qRT-PCR result for GhA06G1313, homologous to GhA06G1313 homologous to Gorai.010G181500, was not entirely consistent with RNA-Seq. The RNA-Seq data for this gene at different fiber development points was not supported well by qRT-PCR analysis. RNA-Seq data analysis based on the G. raimondii genome may reflect expression of both A and D subgenome-derived loci in G. hirsutum, and qRT-PCR data may only reflect the expression of A subgenome genes of G. hirsutum.Fig. 7

Bottom Line: The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively.This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis.Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

View Article: PubMed Central - PubMed

Affiliation: Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, 400716, Chongqing, People's Republic of China.

ABSTRACT

Background: Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton.

Results: To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly.

Conclusions: This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

No MeSH data available.


Related in: MedlinePlus