Abstract
BackgroundUnderstanding genetic control of tassel and ear architecture in maize (Zea mays L. ssp. mays) is important due to their relationship with grain yield. High resolution QTL mapping is critical for understanding the underlying molecular basis of phenotypic variation. Advanced populations, such as recombinant inbred lines, have been broadly adopted for QTL mapping; however, construction of large advanced generation crop populations is time-consuming and costly. The rapidly declining cost of genotyping due to recent advances in next-generation sequencing technologies has generated new possibilities for QTL mapping using large early generation populations.ResultsA set of 708 F2 progeny derived from inbreds Chang7-2 and 787 were generated and genotyped by whole genome low-coverage genotyping-by-sequencing method (average 0.04×). A genetic map containing 6,533 bin-markers was constructed based on the parental SNPs and a sliding-window method, spanning a total genetic distance of 1,396 cM. The high quality and accuracy of this map was validated by the identification of two well-studied genes, r1, a qualitative trait locus for color of silk (chromosome 10) and ba1 for tassel branch number (chromosome 3). Three traits of tassel and ear architecture were evaluated in this population, a total of 10 QTL were detected using a permutation-based-significance threshold, seven of which overlapped with reported QTL. Three genes (GRMZM2G316366, GRMZM2G492156 and GRMZM5G805008) encoding MADS-box domain proteins and a BTB/POZ domain protein were located in the small intervals of qTBN5 and qTBN7 (~800 Kb and 1.6 Mb in length, respectively) and may be involved in patterning of tassel architecture. The small physical intervals of most QTL indicate high-resolution mapping is obtainable with this method.ConclusionsWe constructed an ultra-high-dentisy linkage map for the large early generation population in maize. Our study provides an efficient approach for fast detection of quantitative loci responsible for complex trait variation with high accuracy, thus helping to dissect the underlying molecular basis of phenotypic variation and accelerate improvement of crop breeding in a cost-effective fashion.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-433) contains supplementary material, which is available to authorized users.
Highlights
Understanding genetic control of tassel and ear architecture in maize (Zea mays L. ssp. mays) is important due to their relationship with grain yield
quantitative trait loci (QTL) mapping resolution can be improved with larger population sizes and greater marker density to detect the locations of recombination events more precisely [8]
It captures the interest of geneticists and breeders because of the advantages: (1) no prior knowledge of genome information is required, as sequence polymorphisms are detected in the process of genotyping a population, though parental single nucleotide polymorphisms (SNP) information is still needed for assigning genotypes (2) the use of 4 to 8-base barcode adapters allows parallel sequencing of hundreds of DNA samples, dramatically reducing the time and labor required for genotyping; (3) methylation-sensitive restriction enzymes effectively filter repetitive sequences to simplify the complexity of genomes for downstream bioinformatics analysis; (4) the genome-wide approach of SNP detection provides a dense distribution of markers across chromosomes, which is superior to traditional PCR-based markers
Summary
Understanding genetic control of tassel and ear architecture in maize (Zea mays L. ssp. mays) is important due to their relationship with grain yield. High resolution QTL mapping is critical for understanding the underlying molecular basis of phenotypic variation. Advanced populations, such as recombinant inbred lines, have been broadly adopted for QTL mapping; construction of large advanced generation crop populations is time-consuming and costly. The efficiency of QTL mapping largely depends on marker density and population size Advanced populations such as recombinant inbred lines (RILs) and nearly isogenic lines (NILs) are frequently used for QTL mapping to reduce the cost of genotyping due to the high frequency of recombination within a limited population size [10,11,12]. QTL mapping resolution can be improved with larger population sizes and greater marker density to detect the locations of recombination events more precisely [8]. When the marker density was increased in the region of the tb gene, the authors were able to detect additional crossovers in the open reading frame (ORF) and flanking regions, indicating the importance of both population size and marker density for QTL cloning
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
