Purugganan MD, Fuller DQ. The nature of selection during plant domestication. Nature. 2009;457:843–8.
Article
CAS
PubMed
Google Scholar
Mondal S, Rutkoski JE, Velu G, Singh PK, Crespo-Herrera LA, Guzman CG, et al. Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches. Front Plant Sci. 2016;7:991.
Article
PubMed
PubMed Central
Google Scholar
Joukhadar R, Daetwyler HD, Bansal UK, Gendall AR, Hayden MJ. Genetic diversity, population structure and ancestral origin of Australian wheat. Front Plant Sci. 2017;8:1–15.
Article
Google Scholar
Hoisington D, Khairallah M, Reeves T, Ribaut J-M, Skovmand B, Taba S, et al. Plant genetic resources: what can they contribute toward increased crop productivity? Proc Natl Acad Sci. 2002;96:5937–43.
Article
Google Scholar
McCouch S. Feeding the future. Nature. 2013;499:3–4.
Article
CAS
Google Scholar
Gur A, Zamir D. Unused natural variation can lift yield barriers in plant breeding. PLoS Biol. 2004;2:e245.
Article
PubMed
PubMed Central
CAS
Google Scholar
Gamuyao R, Chin JH, Pariasca-Tanaka J, Pesaresi P, Catausan S, Dalid C, et al. The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature. 2012;488:535–9.
Article
CAS
PubMed
Google Scholar
McCouch S. Diversifying selection in plant breeding. PLoS Biol. 2004;2:e347.
Article
PubMed
PubMed Central
CAS
Google Scholar
FAO. The Second Report on the State of the World’s Plant Genetic Resources for Food and Agriculture. Rome: FAO 2010.
Keilwagen J, Kilian B, Özkan H, Babben S, Perovic D, Mayer KFX, et al. Separating the wheat from the chaff - a strategy to utilize plant genetic resources from ex situ genebanks. Sci Rep. 2014;4:14–8.
Google Scholar
Li Y, Zhao S, Ma J, Li D, Yan L, Li J, et al. Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing. BMC Genomics. 2013;14:579.
Article
PubMed
PubMed Central
CAS
Google Scholar
Mehra P, Pandey BK, Giri J. Genome-wide DNA polymorphisms in low phosphate tolerant and sensitive rice genotypes. Sci Rep. 2015;5:13090.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhou Z, Jiang Y, Wang Z, Gou Z, Lyu J, Li W, et al. Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol. 2015;33:408–14.
Article
CAS
PubMed
Google Scholar
Hodges E, Xuan Z, Balija V, Kramer M, Molla MN, Smith SW, et al. Genome-wide in situ exon capture for selective resequencing. Nat Genet. 2007;39:1522–7.
Article
CAS
PubMed
Google Scholar
Hussain M, Iqbal MA, Till BJ, Rahman M. Identification of induced mutations in hexaploid wheat genome using exome capture assay. PLoS One. 2018;13:e0201918.
Article
PubMed
PubMed Central
CAS
Google Scholar
Yao Z, You FM, N’Diaye A, Knox RE, McCartney C, Hiebert CW, et al. Evaluation of variant calling tools for large plant genome re-sequencing. BMC Bioinformatics. 2020;21:1–16.
Article
Google Scholar
Wendel JF, Jackson SA, Meyers BC, Wing RA. Evolution of plant genome architecture. Genome Biol. 2016;17:1–14.
Article
CAS
Google Scholar
Le Nguyen K, Grondin A, Courtois B, Gantet P. Next-generation sequencing accelerates crop gene discovery. Trends Plant Sci. 2019;24:263–74.
Article
CAS
PubMed
Google Scholar
Sims D, Sudbery I, Ilott NE, Heger A, Ponting CP. Sequencing depth and coverage: key considerations in genomic analyses. Nat Rev Genet. 2014;15:121–32.
Article
CAS
PubMed
Google Scholar
Campbell NR, Harmon SA, Narum SR. Genotyping-in-thousands by sequencing (GT-seq): a cost effective SNP genotyping method based on custom amplicon sequencing. Mol Ecol Resour. 2015;15:855–67.
Article
CAS
PubMed
Google Scholar
Dou Y, Gold HD, Luquette LJ, Park PJ. Detecting somatic mutations in normal cells. Trends Genet. 2018;34:545–57.
Article
CAS
PubMed
PubMed Central
Google Scholar
Grubaugh ND, Gangavarapu K, Quick J, Matteson NL, De Jesus JG, Main BJ, et al. An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar. Genome Biol. 2019;20:1–19.
Article
Google Scholar
Tsai H, Howell T, Nitcher R, Missirian V, Watson B, Ngo KJ, et al. Discovery of rare mutations in populations: TILLING by sequencing. Plant Physiol. 2011;156:1257–68.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pan L, Shah AN, Phelps IG, Doherty D, Johnson EA, Moens CB. Rapid identification and recovery of ENU-induced mutations with next-generation sequencing and paired-end low-error analysis. BMC Genomics. 2015;16:83.
Article
PubMed
PubMed Central
Google Scholar
Gupta P, Reddaiah B, Salava H, Upadhyaya P, Tyagi K, Datta S, et al. Next-generation sequencing (NGS)-based identification of induced mutations in a doubly mutagenized tomato (Solanum lycopersicum) population. Plant J. 2017;92:495–508.
Article
CAS
PubMed
Google Scholar
Tramontano A, Jarc L, Jankowicz-Cieslak J, Hofinger BJ, Gajek K, Szurman-Zubrzycka M, et al. Fragmentation of pooled PCR products for highly multiplexed TILLING. G3 (Bethesda). 2019;9:2657–66.
Article
CAS
Google Scholar
Marroni F, Pinosio S, Di Centa E, Jurman I, Boerjan W, Felice N, et al. Large-scale detection of rare variants via pooled multiplexed next-generation sequencing: towards next-generation Ecotilling. Plant J. 2011;67:736–45.
Article
CAS
PubMed
Google Scholar
Duitama J, Kafuri L, Tello D, Leiva AM, Hofinger B, Datta S, et al. Deep assessment of genomic diversity in cassava for herbicide tolerance and starch biosynthesis. Comput Struct Biotechnol J. 2017;15:185–94.
Article
CAS
PubMed
PubMed Central
Google Scholar
Kharabian-Masouleh A, Waters DLE, Reinke RF, Henry RJ. Discovery of polymorphisms in starch-related genes in rice germplasm by amplification of pooled DNA and deeply parallel sequencing. Plant Biotechnol J. 2011;9:1074–85.
Article
CAS
PubMed
Google Scholar
Schlötterer C, Tobler R, Kofler R, Nolte V. Sequencing pools of individuals-mining genome-wide polymorphism data without big funding. Nat Rev Genet. 2014;15:749–63.
Article
PubMed
CAS
Google Scholar
Pereira MB, Wallroth M, Jonsson V, Kristiansson E. Comparison of normalization methods for the analysis of metagenomic gene abundance data. BMC Genomics. 2018;19:1–17.
Article
CAS
Google Scholar
Leonardo A. Crespo-Herrera, Larisa Garkava-Gustavsson, Inger Åhman. A systematic review of rye (Secale cereale L.) as a source of resistance to pathogens and pests in wheat (Triticum aestivum L.). Hereditas. 2017;154(1).
Bartos J, Paux E, Kofler R, Havrankova M, Kopecky D, Suchankova P, et al. A first survey of the rye (Secale cereale) genome composition through BAC end sequencing of the short arm of chromosome 1R. BMC Plant Biol. 2008;8:95.
Article
PubMed
PubMed Central
CAS
Google Scholar
Rabanus-Wallace MT, Hackauf B, Mascher M, Lux T, Wicker T, Gundlach H, et al. Chromosome-scale genome assembly provides insights into rye biology, evolution, and agronomic potential. bioRxiv. 2019. https://doi.org/10.1101/2019.12.11.869693.
Bolibok-Bragoszewska H, Targonska M, Bolibok L, Kilian A, Rakoczy-Trojanowska M. Genome-wide characterization of genetic diversity and population structure in Secale. BMC Plant Biol. 2014;14:184.
Article
PubMed
PubMed Central
Google Scholar
Targońska M, Bolibok-Brągoszewska H, Rakoczy-Trojanowska M. Assessment of genetic diversity in Secale cereale based on SSR markers. Plant Mol Biol Report. 2016;34:37–51.
Article
PubMed
Google Scholar
Maraci O, Ozkan H, Bilgin R. Phylogeny and genetic structure in the genus Secale. PLoS One. 2018;13:1–21.
Article
CAS
Google Scholar
Sidhu JS, Ramakrishnan SM, Ali S, Bernardo A, Bai G, Abdullah S, et al. Assessing the genetic diversity and characterizing genomic regions conferring tan spot resistance in cultivated rye. PLoS One. 2019;14:1–22.
Google Scholar
Monteiro F, Vidigal P, Barros AB, Monteiro A, Oliveira HR, Viegas W. Genetic distinctiveness of Rye in situ accessions from Portugal unveils a new hotspot of unexplored genetic resources. Front Plant Sci. 2016;7:1–17.
Article
Google Scholar
Miedaner T, Laidig F. Hybrid breeding in rye (Secale cereale L.). In: Al-Khayri J, Jain S, Johnson D, editors. Advances in Plant Breeding Strategies: Cereals Cham. Cham: Springer; 2019. p. 343–72.
Chapter
Google Scholar
Geiger HH, Miedaner T. Rye breeding. In: Carena MJ, editor. Cereals (handbook of plant breeding, Vol 3). 1st ed. New York: Springer US; 2009. p. 157–81.
Google Scholar
Gawroński P, Pawełkowicz M, Tofil K, Uszyński G, Sharifova S, Ahluwalia S, et al. DArT markers effectively target gene space in the rye genome. Front Plant Sci. 2016;7:1600.
Article
PubMed
PubMed Central
Google Scholar
Maron LG, Guimarães CT, Kirst M, Albert PS, Birchler JA, Bradbury PJ. Aluminum tolerance in maize is associated with higher MATE1 gene copy number. Proc Natl Acad Sci. 2013;110:5241–6.
Article
CAS
PubMed
PubMed Central
Google Scholar
Santos E, Benito C, Gallego FJ, Figueiras AM. Characterization, genetic diversity, phylogenetic relationships, and expression of the aluminum tolerance MATE1 gene in Secale species. Biol Plant. 2018;62:109–20.
Article
CAS
Google Scholar
Zhang J, Wang F, Liang F, Zhang Y, Ma L, Wang H, et al. Functional analysis of a pathogenesis- related thaumatin-like protein gene TaLr35PR5 from wheat induced by leaf rust fungus. BMC Plant Biol. 2018;18:76.
Article
PubMed
PubMed Central
CAS
Google Scholar
Lv G-Y, Guo X-G, Xie L-P, Xie C-G, Zhang X-H, Yang Y, et al. Molecular characterization, gene evolution, and expression analysis of the fructose-1, 6-bisphosphate aldolase (FBA) gene family in wheat (Triticum aestivum L.). front. Plant Sci. 2017;8:1030.
Google Scholar
Cai B, Li Q, Liu F, Bi H. Decreasing fructose-1 , 6-bisphosphate aldolase activity reduces plant growth and tolerance to chilling stress in tomato seedlings. Physiol Plant. 2018;163:247–58.
Article
CAS
PubMed
Google Scholar
Wilkinson MD, Tosi P, Lovegrove A, Corol DI, Ward JL, Palmer R, et al. The Gsp-1 genes encode the wheat arabinogalactan peptide. J Cereal Sci. 2017;74:155–64.
Article
CAS
Google Scholar
Simeone MC, Lafiandra D. Isolation and characterisation of friabilin genes in rye. J Cereal Sci. 2005;41:115–22.
Article
CAS
Google Scholar
Liu H, Zhou X, Li X, Chen J, Cui D, Chen F. Molecular characterization of secaloindoline genes in introduced CIMMYT primary hexaploid triticale. Crop J. 2017;5:430–7.
Article
Google Scholar
Zhang Z, Zheng X, Yang J, Messing J, Wu Y. Maize endosperm-specific transcription factors O2 and PBF network the regulation of protein and starch synthesis. Proc Natl Acad Sci. 2016;113:10842–7.
Article
CAS
PubMed
PubMed Central
Google Scholar
Haseneyer G, Stracke S, Piepho H, Sauer S, Geiger HH, Graner A. DNA polymorphisms and haplotype patterns of transcription factors involved in barley endosperm development are associated with key agronomic traits. BMC Plant Biol. 2010;10:5.
Article
PubMed
PubMed Central
CAS
Google Scholar
Moehs CP, Austill WJ, Holm A, Large TAG, Loeffler D, Mullenberg J, et al. Development of decreased-gluten wheat enabled by determination of the genetic basis of lys3a barley. Plant Physiol. 2019;179:1692–703.
Article
CAS
PubMed
PubMed Central
Google Scholar
de Souza Jr CL. Cultivar development of allogamous crops. Crop Breed Appl Biotechnol. 2012;11:8–15.
Article
Google Scholar
Poplin R, Ruano-Rubio V, Depristo MA, Fennell TJ, Carneiro MO, Auwera GA Van Der, et al. Scaling accurate genetic variant discovery to tens of thousands of samples. bioRxiv. 2017;1 doi: https://doi.org/10.1101/201178.
Wei Z, Wang W, Hu P, Lyon GJ, Hakonarson H. SNVer : a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data. Nucleic Acids Res. 2011;39:1–13.
Article
CAS
Google Scholar
Bansal V. A statistical method for the detection of variants from next-generation resequencing of DNA pools. Bioinformatics. 2010;1:318–24.
Article
CAS
Google Scholar
Al-Beyroutiova M, Sabo M, Sleziak P, Dusinsky R, Bircak E, Hauptvogel P, et al. Evolutionary relationships in the genus Secale revealed by DArTseq DNA polymorphism. Plant Syst Evol. 2016;302:1083–91.
Article
CAS
Google Scholar
Li F, Shimizu A, Nishio T, Tsutsumi N, Kato H. Comparison and characterization of mutations induced by gamma-ray and carbon-ion irradiation in rice (Oryza sativa L .) using whole-genome resequencing. G3 (Bethesda). 2019;9:3743–51.
Article
CAS
Google Scholar
Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature. 2018;557:43–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Balfourier F, Bouchet S, Robert S, Oliveira R, de Rimbert H, Kitt J, et al. Worldwide phylogeography and history of wheat genetic diversity. Sci Adv. 2019;5:eaav0536.
Article
PubMed
PubMed Central
Google Scholar
Schirmer M, Ijaz UZ, Amore RD, Hall N, Sloan WT, Quince C. Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform. Nucleic Acids Res. 2015;43:e37.
Article
PubMed
PubMed Central
CAS
Google Scholar
Schreiber M, Himmelbach A, Börner A, Mascher M. Genetic diversity and relationship between domesticated rye and its wild relatives as revealed through genotyping-by-sequencing. Evol Appl. 2018:1–12.
Li Y, Haseneyer G, Schön C-C, Ankerst D, Korzun V, Wilde P, et al. High levels of nucleotide diversity and fast decline of linkage disequilibrium in rye (Secale cereale L.) genes involved in frost response. BMC Plant Biol. 2011;11:6.
Article
PubMed
PubMed Central
CAS
Google Scholar
Varshney RK, Beier U, Khlestkina EK, Kota R, Korzun V, Graner A, et al. Single nucleotide polymorphisms in rye (Secale cereale L.): discovery, frequency, and applications for genome mapping and diversity studies. Theor Appl Genet. 2007;114:1105–16.
Article
CAS
PubMed
Google Scholar
Bauer E, Schmutzer T, Barilar I, Mascher M, Gundlach H, Martis MM, et al. Towards a whole-genome sequence for rye (Secale cereale L.). Plant J. 2017;89:853–69.
Article
CAS
PubMed
Google Scholar
Fischer S, Melchinger AE, Korzun V, Wilde P, Schmiedchen B, Möhring J, et al. Molecular marker assisted broadening of the central European heterotic groups in rye with eastern European germplasm. Theor Appl Genet. 2010;120:291–9.
Article
PubMed
Google Scholar
Falke KC, Susić Z, Hackauf B, Korzun V, Schondelmaier J, Wilde P, et al. Establishment of introgression libraries in hybrid rye (Secale cereale L.) from an Iranian primitive accession as a new tool for rye breeding and genomics. Theor Appl Genet. 2008;117:641–52.
Article
CAS
PubMed
Google Scholar
Massa AN, Morris CF, Gill BS. Sequence diversity of Puroindoline-a, Puroindoline-b, and the grain softness protein genes in Aegilops tauschii Coss. Crop Sci. 2004;44:1808–16.
Article
CAS
Google Scholar
Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics. 2012;13:134.
Article
CAS
PubMed
PubMed Central
Google Scholar
Li H, Durbin R. Fast and accurate short read alignment with burrows – wheeler transform. Bioinformatics. 2009;25:1754–60.
Article
CAS
PubMed
PubMed Central
Google Scholar
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment / map format and SAMtools. Bioinformatics. 2009;25:2078–9.
Article
PubMed
PubMed Central
CAS
Google Scholar
García-Alcalde F, Okonechnikov K, Carbonell J, Cruz LM, Götz S, Tarazona S, et al. Qualimap: evaluating next-generation sequencing alignment data. Bioinformatics. 2012;28:2678–9.
Article
PubMed
CAS
Google Scholar
Knaus BJ, Grünwald NJ. Vcfr: a package to manipulate and visualize variant call format data in R. Mol Ecol Resour. 2017;17:44–53.
Article
CAS
PubMed
Google Scholar
Obenchain V, Lawrence M, Carey V, Gogarten S, Shannon P, Morgan M. VariantAnnotation: a bioconductor package for exploration and annotation of genetic variants. Bioinformatics. 2014;30:2076–8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin). 2012;6:80–92.
Article
CAS
Google Scholar
Vaser R, Adusumalli S, Leng SN, Sikic M, Ng PC. SIFT missense predictions for genomes. Nat Protoc. 2016;11:1–9.
Article
CAS
PubMed
Google Scholar
Gleiss A, Dakna M, Mischak H, Heinze G. Two-group comparisons of zero-inflated intensity values: the choice of test statistic matters. Bioinformatics. 2015;31:2310–7.
Article
CAS
PubMed
Google Scholar
Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer New York; 2016.
Book
Google Scholar
Tateno Y, Nei M, Tajima F. Accuracy of estimated phylogenetic trees from molecular data – I. Distantly Related Species. J Mol Evol. 1982;18:387–404.
Article
CAS
PubMed
Google Scholar
Takezaki N, Nei M, Tamura K. POPTREEW: web version of POPTREE for constructing population trees from allele frequency data and computing some other quantities. Mol Biol Evol. 2014;31:1622–4.
Article
CAS
PubMed
Google Scholar
Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Rohlf FJ. NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.2. Exeter Software, Setauket, NY (2005).
ROD PEAKALL, PETER E. SMOUSE, genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes. 2006;6(1):288–95.
R. Peakall, P. E. Smouse, GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics. 2012;28(19):2537–9.
Taylor NE, Greene EA. PARSESNP : a tool for the analysis of nucleotide polymorphisms. Nucleic Acids Res. 2003;31:3808–11.
Article
CAS
PubMed
PubMed Central
Google Scholar