Mapping By Sequencing and RNA-Seq in Upland Cotton (Gossypium hirsutum) Line MD52ne Identifies Candidate Genes for Fiber Strength and Quality

Wednesday, January 6, 2016: 1:45 PM
Preservation Hall Studios 7 & 8 (New Orleans Marriott)
Md S Islam , USDA ARS
Linghe Zeng , USDA-ARS
Gregory N Thyssen , Cotton Chemistry and Utilization Research Unit, USDA ARS
Christopher D. Delhom , USDA ARS
Hee Jin Kim , USDA ARS
Ping Li , USDA ARS
David D Fang , Cotton Fiber Bioscience Unit, USDA ARS
Fiber strength, length, maturity and fineness determine the market value of cotton and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candidate gene prediction can uncover the genetic and molecular basis of fiber quality traits. Four QTLs (qBFS-c3, qSFI-c14, qUHML-c14 and qUHML-c24) related to bundle fiber strength, short fiber index and fiber length were validated on upland cotton Chrs. 3, 14 and 24, respectively using an advanced generation (F2:3) that originated from the cross MD90ne × MD52ne. A group of 27 novel single nucleotide polymorphic (SNP) markers generated from Mapping-by-Sequencing (MBS) were placed on QTL regions to improve and validate earlier maps. Our refined QTL regions spanned 4.4, 1.8 and 3.7 Mb of physical distance in the Gossypium raimondii reference genome. We performed RNA-seq on 15 and 20 days post-anthesis (DPA) fiber cells from MD52ne and MD90ne and aligned reads to the G. raimondii genome. The QTL regions contained 21 significantly differentially expressed genes between the two near isogenic lines (NILs) which were treated as candidates for the fiber traits. We then identified mapped SNPs that result in non-synonymous substitutions to amino acid sequences of annotated genes. Taken together, transcriptome and amino acid mutation analysis indicate that receptor like kinase pathway genes are candidates for superior fiber strength and length in MD52ne. MBS along with RNA-seq demonstrated a powerful strategy to elucidate candidate genes for the QTLs that control complex traits in a complex genome.