High Density Linkage Map Construction and Mapping of Yield Trait QTLs in Maize (Zea mays) Using the Genotyping-by-Sequencing (GBS) Technology

Abstract

Increasing grain yield is the ultimate goal for maize breeding. High resolution quantitative trait loci (QTL) mapping can help us understand the molecular basis of phenotypic variation of yield and thus facilitate marker assisted breeding. The aim of this study is to use genotyping-by-sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of all F2 individuals from a cross between two varieties of maize that are in clear contrast in yield and related traits. A set of 199 F2 progeny derived from the cross of varieties SG-5 and SG-7 were generated and genotyped by GBS. A total of 1,046,524,604 reads with an average of 5,258,918 reads per F2 individual were generated. This number of reads represents an approximately 0.36-fold coverage of the maize reference genome Zea_mays.AGPv3.29 for each F2 individual. A total of 68,882 raw SNPs were discovered in the F2 population, which, after stringent filtering, led to a total of 29,927 high quality SNPs. Comparative analysis using these physically mapped marker loci revealed a higher degree of synteny with the reference genome. The SNP genotype data were utilized to construct an intra-specific genetic linkage map of maize consisting of 3,305 bins on 10 linkage groups spanning 2,236.66 cM at an average distance of 0.68 cM between consecutive markers. From this map, we identified 28 QTLs associated with yield traits (100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, corn grains per row, ear weight, and grain weight per plant) using the composite interval mapping (CIM) method and 29 QTLs using the least absolute shrinkage selection operator (LASSO) method. QTLs identified by the CIM method account for 6.4% to 19.7% of the phenotypic variation. Small intervals of three QTLs (qCGR-1, qKW-2, and qGWP-4) contain several genes, including one gene (GRMZM2G139872) encoding the F-box protein, three genes (GRMZM2G180811, GRMZM5G828139, and GRMZM5G873194) encoding the WD40-repeat protein, and one gene (GRMZM2G019183) encoding the UDP-Glycosyltransferase. The work will not only help to understand the mechanisms that control yield traits of maize, but also provide a basis for marker-assisted selection and map-based cloning in further studies.

QTL mapping of three ear traits using a doubled haploid population of maize

“…The cob diameter in the present study was not obtained directly by measuring the cob, but by subtracting the kernel length determined by image‐based software (Shi et al., ) from the ear diameter, which eliminates the possibility of extra errors caused by manual measurement because of threshing leftover on cobs. In reality, the major QTL for CD with PVE of 22.6%, qCD1 , identified in our study overlaps with the QTL mapped based on genotyping by sequencing (Su et al., ) and in a IBM DH population for certain trial conditions (Jansen et al., ). These results indicate that these QTLs are stable across selected lines and conditions, so they may provide robust candidates for the breeding of maize with desired ear traits to improve the overall grain yield.…”

“…A great number of quantitative trait loci (QTLs) for EL, ED and CD have been previously identified (Huo et al, 2016;Liu et al, 2007;Liu, Cai et al, 2008;Sabadin et al, 2010;Su et al, 2017;Tang et al, 2007;Xiang et al, 2001;Xie et al, 2008;Zhang et al, 2010), most of which employed around 300 SSR markers for genetic map construction. However, discrepancies have been observed in the number, location and effect of these QTLs, probably due to differences in mapping populations, such as F 2:3 (Liu et al, 2007;Sabadin et al, 2010;Su et al, 2017;Xiang et al, 2001) and recombinant inbred lines (RILs) (Xie et al, 2008;Zhang et al, 2010), parental lines and experimental conditions. In addition, ear tip barrenness compromises grain yield in maize , so it is considered as an unfavourable trait by breeders.…”

Genome of an iconic Australian bird: High‐quality assembly and linkage map of the superb fairy‐wren (Malurus cyaneus)

“…The utility of a genetic map extends far beyond upgrading a genome assembly. The maps themselves serve as an invaluable resource by enabling us to associate a particular phenotypic trait to specific loci through quantitative trait loci (QTL) mapping (Su et al, 2017), associate different traits through tight linkage of the genes that code for them (Schwander, Libbrecht, & Keller, 2014), and provide an understanding of the variation in genetic diversity within the genome (Burri et al, 2015). It is also of interest to understand how the recombination landscape itself varies between individuals, populations and species, and how it may be influenced by selection, demographic history, genomic features and chromosomal rearrangements (Barton, 1995;Dapper & Payseur, 2017;Ortiz-Barrientos, Engelstädter, & Rieseberg, 2016;Stapley, Feulner, Johnston, Santure, & Smadja, 2017).…”

Combining next‐generation sequencing and progeny testing for rapid identification of induced recessive and dominant mutations in maize M2 individuals

“…These few thousand sequence variants per mutated genome/per M 2 family are distributed among the 10 maize chromosomes covering approximately 2.3 Gbp of DNA sequence, which corresponds to c . 2200 c m of genetic distance (Su et al ., ). The maximal achievable genetic resolution for each mutant population – 16 individuals derived from 32 meiotic events – is c .…”

“…In the segregating dwarf and pale green M 2 populations the mutational load (1357 and 3536 induced mutations) was slightly lower compared with previous EMS mutagenesis in maize (Till et al, 2004), which can be explained by lower concentrated EMS used in our mutagenesis. These few thousand sequence variants per mutated genome/per M 2 family are distributed among the 10 maize chromosomes covering approximately 2.3 Gbp of DNA sequence, which corresponds to c. 2200 cM of genetic distance (Su et al, 2017). The maximal achievable genetic resolution for each mutant population -16 individuals derived from 32 meiotic events is c. (1/32) 3 cM, which corresponds to unresolved regions of c. 6 cM around the causal mutation assuming identical segregation for all sequence variants.…”