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

Phenotype valuation during early fiber development. a: Scanning electron microscope mages of the +1 DPA ovule; b, c and d: Anatomy microscope images of the +3, +5, +7 DPA fiber. Scanning electron microscope images were taken at a similar position in the middle of ovules. Scale bars: 200 μm (a); Scale bars: 1 mm (b); Scale bars: 2.5 mm (c, d)
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Fig5: Phenotype valuation during early fiber development. a: Scanning electron microscope mages of the +1 DPA ovule; b, c and d: Anatomy microscope images of the +3, +5, +7 DPA fiber. Scanning electron microscope images were taken at a similar position in the middle of ovules. Scale bars: 200 μm (a); Scale bars: 1 mm (b); Scale bars: 2.5 mm (c, d)

Mentions: To examine fiber cell differentiation in Yumian 1 and RIL118, scanning electron microscopy was used to observe the development of fiber cell initials in the ovular surface at 1 DPA, and anatomy microscopy was used to observe progress in fiber cell elongation at 3 DPA, 5 DPA and 7 DPA. The fiber length of Yumian 1 was much longer than that of RIL118 from 3 to 7 DPA (Fig. 5). This result showed that fiber development at an early stage has a positive effect on final fiber quality.Fig. 5


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)

Phenotype valuation during early fiber development. a: Scanning electron microscope mages of the +1 DPA ovule; b, c and d: Anatomy microscope images of the +3, +5, +7 DPA fiber. Scanning electron microscope images were taken at a similar position in the middle of ovules. Scale bars: 200 μm (a); Scale bars: 1 mm (b); Scale bars: 2.5 mm (c, d)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig5: Phenotype valuation during early fiber development. a: Scanning electron microscope mages of the +1 DPA ovule; b, c and d: Anatomy microscope images of the +3, +5, +7 DPA fiber. Scanning electron microscope images were taken at a similar position in the middle of ovules. Scale bars: 200 μm (a); Scale bars: 1 mm (b); Scale bars: 2.5 mm (c, d)
Mentions: To examine fiber cell differentiation in Yumian 1 and RIL118, scanning electron microscopy was used to observe the development of fiber cell initials in the ovular surface at 1 DPA, and anatomy microscopy was used to observe progress in fiber cell elongation at 3 DPA, 5 DPA and 7 DPA. The fiber length of Yumian 1 was much longer than that of RIL118 from 3 to 7 DPA (Fig. 5). This result showed that fiber development at an early stage has a positive effect on final fiber quality.Fig. 5

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