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      Reference genome sequences of two cultivated allotetraploid cottons, Gossypium hirsutum and Gossypium barbadense

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          Abstract

          Allotetraploid cotton species (Gossypium hirsutum and Gossypium barbadense) have long been cultivated worldwide for natural renewable textile fibers. The draft genome sequences of both species are available but they are highly fragmented and incomplete1-4. Here we report reference-grade genome assemblies and annotations for G. hirsutum accession Texas Marker-1 (TM-1) and G. barbadense accession 3-79 by integrating single-molecule real-time sequencing, BioNano optical mapping and high-throughput chromosome conformation capture techniques. Compared with previous assembled draft genomes1,3, these genome sequences show considerable improvements in contiguity and completeness for regions with high content of repeats such as centromeres. Comparative genomics analyses identify extensive structural variations that probably occurred after polyploidization, highlighted by large paracentric/pericentric inversions in 14 chromosomes. We constructed an introgression line population to introduce favorable chromosome segments from G. barbadense to G. hirsutum, allowing us to identify 13 quantitative trait loci associated with superior fiber quality. These resources will accelerate evolutionary and functional genomic studies in cotton and inform future breeding programs for fiber improvement.

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          Most cited references 21

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          Fast algorithms for large-scale genome alignment and comparison.

          We describe a suffix-tree algorithm that can align the entire genome sequences of eukaryotic and prokaryotic organisms with minimal use of computer time and memory. The new system, MUMmer 2, runs three times faster while using one-third as much memory as the original MUMmer system. It has been used successfully to align the entire human and mouse genomes to each other, and to align numerous smaller eukaryotic and prokaryotic genomes. A new module permits the alignment of multiple DNA sequence fragments, which has proven valuable in the comparison of incomplete genome sequences. We also describe a method to align more distantly related genomes by detecting protein sequence homology. This extension to MUMmer aligns two genomes after translating the sequence in all six reading frames, extracts all matching protein sequences and then clusters together matches. This method has been applied to both incomplete and complete genome sequences in order to detect regions of conserved synteny, in which multiple proteins from one organism are found in the same order and orientation in another. The system code is being made freely available by the authors.
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            High-throughput genotyping by whole-genome resequencing.

            The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was approximately 20x faster in data collection and 35x more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.
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              A modified algorithm for the improvement of composite interval mapping.

              Composite interval mapping (CIM) is the most commonly used method for mapping quantitative trait loci (QTL) with populations derived from biparental crosses. However, the algorithm implemented in the popular QTL Cartographer software may not completely ensure all its advantageous properties. In addition, different background marker selection methods may give very different mapping results, and the nature of the preferred method is not clear. A modified algorithm called inclusive composite interval mapping (ICIM) is proposed in this article. In ICIM, marker selection is conducted only once through stepwise regression by considering all marker information simultaneously, and the phenotypic values are then adjusted by all markers retained in the regression equation except the two markers flanking the current mapping interval. The adjusted phenotypic values are finally used in interval mapping (IM). The modified algorithm has a simpler form than that used in CIM, but a faster convergence speed. ICIM retains all advantages of CIM over IM and avoids the possible increase of sampling variance and the complicated background marker selection process in CIM. Extensive simulations using two genomes and various genetic models indicated that ICIM has increased detection power, a reduced false detection rate, and less biased estimates of QTL effects.
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                Author and article information

                Journal
                Nature Genetics
                Nat Genet
                Springer Nature
                1061-4036
                1546-1718
                December 3 2018
                Article
                10.1038/s41588-018-0282-x
                30510239
                © 2018

                http://www.springer.com/tdm

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