SEG-Map: A Novel Software for Genotype Calling and Genetic Map Construction from Next-generation Sequencing

Zhao, Qiang; Huang, Xuehui; Lin, Zhixin; Han, Bin

doi:10.1007/s12284-010-9051-x

Cited by 36 publications

(27 citation statements)

References 18 publications

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“…A slidingwindow approach was used to construct genetic maps built from genotyping-by-sequencing (GBS) based single nucleotide polymorphisms (SNPs) to account for sequencing error and missing individual data at a given SNP site (Huang et al 2009;Zhao et al 2010). The sliding-window imputation method utilizes the available marker data to determine the origin of each individual's marker genotype relative to its parents, thus resulting in a genetic map with no missing data.…”

Section: Mapping Populationsmentioning

confidence: 99%

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

et al. 2014

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QTL were identified for root architectural traits in maize. Root architectural traits, including the number, length, orientation, and branching of the principal root classes, influence plant function by determining the spatial and temporal domains of soil exploration. To characterize phenotypic patterns and their genetic control, three recombinant inbred populations of maize were grown for 28 days in solid media in a greenhouse and evaluated for 21 root architectural traits, including length, number, diameter, and branching of seminal, primary and nodal roots, dry weight of embryonic and nodal systems, and diameter of the nodal root system. Significant phenotypic variation was observed for all traits. Strong correlations were observed among traits in the same root class, particularly for the length of the main root axis and the length of lateral roots. In a principal component analysis, relationships among traits differed slightly for the three families, though vectors grouped together for traits within a given root class, indicating opportunities for more efficient phenotyping. Allometric analysis showed that trajectories of growth for specific traits differ in the three populations. In total, 15 quantitative trait loci (QTL) were identified. QTL are reported for length in multiple root classes, diameter and number of seminal roots, and dry weight of the embryonic and nodal root systems. Phenotypic variation explained by individual QTL ranged from 0.44% (number of seminal roots, NyH population) to 13.5% (shoot dry weight, OhW population). Identification of QTL for root architectural traits may be useful for developing genotypes that are better suited to specific soil environments.

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Section: Mapping Populationsmentioning

confidence: 99%

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

et al. 2014

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“…Second, high‐quality SNPs were obtained from deep sequencing (IBM Syn10 DH, 0.31×; Mo17, 26×) using Illumina Hiseq2000 (Lai et al., ; Xia et al., ). Third, we took the chromosome whose physical distance was approximately 100k as the smallest unit for a recombination event, and the smallest unit was defined as a bin (Zhao, Huang, Lin, & Han, ); we then integrated the same genotyped SNPs as bin markers. For all the above, the overall length of the high‐density map (bin map) was 11198.5 cM (genetic distance), which included 6,618 recombination bin markers, and the average genetic distance between two bin markers was 1.7 cM.…”

Section: Methodsmentioning

confidence: 99%

Identification of quantitative trait loci for leaf‐related traits in an IBM Syn10 DH maize population across three environments

Guan

Zhang

et al. 2018

Plant Breeding

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Leaf‐related traits (leaf length, leaf width, leaf area and leaf angle) are very important for the yield of maize (Zea mays L) due to their influence on plant type. Therefore, it is necessary to identify quantitative trait loci (QTLs) for leaf‐related traits. In this report, 221 doubled haploid lines (DHLs) of an IBM Syn10 DH population were provided for QTL mapping. In total, 54 QTLs were detected for leaf‐related traits in single environments using a high‐density genetic linkage map. Among them, only eight common QTLs were identified across two or three environments, and the common QTLs for the four traits explained 4.38%–19.99% of the phenotypic variation. qLL‐2‐1 (bin 2.09), qLW‐2‐2 (bin 2.09), qLW‐6‐3 (bin 6.07) and qLA‐5‐2 (bin 2.09) were detected in previous studies, and qLL‐1‐1, qLAr‐1‐1, qLAr‐2‐1 and qLA‐7‐1 may be new QTLs. Notably, qLW‐6‐3 and qLA‐5‐2 were found to be major QTLs explaining 19.99% and 10.96% of the phenotypic variation, respectively. Interestingly, we found three pairs of QTLs (qLW‐2‐2 and qLAr‐2‐1, qLW‐8‐1 and qLL‐8‐2, qLL‐3‐3 and qLAr‐3‐3) that control different traits and that were located on the same chromosome or in a nearby location. Moreover, nine pairs of loci with epistatic effects were identified for the four traits. These results may provide the foundation for QTL fine mapping and for an understanding of the genetic basis of variation in leaf‐related traits.

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“…Using GBS technology (Elshire et al, 2011), the 234 RILs genotypes were scored and a recombination bin map was constructed using SEG‐map (Huang et al, 2009; Zhao et al, 2010), which contains 5320 highly informative bin markers. This map was previously published (Burton et al, 2014) and is available in R/qtl format (Broman et al, 2003) as supplemental material within that publication as well as in this registration (Supplements 1 and 2).…”

Section: Characteristicsmentioning

confidence: 99%

Registration of the NyH (Ny821×H99) Maize Recombinant Inbred Mapping Population

Johnson¹,

Muttoni²,

León

et al. 2015

J of Plant Registrations

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The Ny821×H99 (NyH) maize (Zea mays L.) mapping population (MP‐4, NSL 511548 MAP) is composed of 234 recombinant inbred lines (RILs). The population was developed from an initial cross between inbred lines Ny821 and H99 (PI 587129). The parents of this population were selected on the basis of variation for low phosphorus tolerance, with the parent with higher tolerance, Ny821, having a highly branched root system and the parent with lower tolerance, H99, having a simple root system. The population segregates for a number of agronomic traits, including plant height, ear height, leaf number, and flowering time. A genotype‐by‐sequencing approach was utilized to produce a high‐density genetic map. This population, coupled with the dense genetic marker map, is a useful resource for analysis of traits such as root architecture and abiotic stress tolerance.

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SEG-Map: A Novel Software for Genotype Calling and Genetic Map Construction from Next-generation Sequencing

Cited by 36 publications

References 18 publications

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

Identification of quantitative trait loci for leaf‐related traits in an IBM Syn10 DH maize population across three environments

Registration of the NyH (Ny821×H99) Maize Recombinant Inbred Mapping Population

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