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. 2021 Mar 18;16(3):e0248787. doi: 10.1371/journal.pone.0248787

Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern Colombia using Single Nucleotide Polymorphism (SNP) markers

Jhon A Berdugo-Cely 1,*, Carolina Martínez-Moncayo 2, Tulio César Lagos-Burbano 3
Editor: Tzen-Yuh Chiang4
PMCID: PMC7971539  PMID: 33735184

Abstract

Detailed knowledge on genetic parameters such as diversity, structure, and linkage disequilibrium (LD) and identification of duplicates in a germplasm bank and/or breeding collection are essential to conservation and breeding strategies in any crop. Therefore, the potato genetic breeding collection at the Universidad de Nariño in Colombia, which is made up of diploid and tetraploid genotypes in two of the more diverse genebanks in the world, was analyzed with 8303 single nucleotide polymorphisms (SNP) from SolCAP version 1. In total, 144 genotypes from this collection were analyzed identifying an 57.2% of the polymorphic markers that allowed establishing two and three subpopulations that differentiated the diploid genotypes from the tetraploids. These subpopulations had high levels of heterozygosity and linkage disequilibrium. The diversity levels were higher in the tetraploid genotypes, while the LD levels were higher in the diploid genotypes. For the tetraploids, the genotypes from Peru had greater diversity and lower linkage disequilibrium than those from Colombia, which had slightly lower diversity and higher degrees of LD. The genetic analysis identified, adjusted and/or selected diploid and tetraploid genotypes under the following characteristics: 1) errors in classification associated with the level of ploidy; 2) presence of duplicates; and 3) genotypes with broad genetic distances and potential use in controlled hybridization processes. These analyses suggested that the potato genetic breeding collection at the Universidad de Nariño has a genetic base with a potential use in breeding programs for this crop in the Department of Nariño, in southern Colombia.

Introduction

The potato (Solanum tuberosum L.) is the most important non-cereal crop in the world, with more than 368 million tons produced from approximately 4,000 varieties grown on 17.5 million hectares [1, 2]. This crop is key to food security because of its high nutritional value provided by carbohydrates, proteins, fibers, minerals and vitamins [3, 4]. The increasing world population means the demand for food will increase, requiring the constant development of improved cultivars to meet the needs of consumers, producers and processors, who require potato genetic materials with: 1) better taste and high nutritional value; 2) higher production; 3) resistance to pests and diseases; and 3) low content of reducing sugars and starch, among other compounds [5]. The genetic variability of potato genotypes with potential use in genetic breeding processes for the development of new cultivars must be identified and explored.

In 2018, Colombia ranked 23rd for global potato producers with three million tons cultivated on 133 thousand hectares [2], of which 399 thousand tons of potatoes (tetraploids) and 16 thousand tons of “Criollas” potatoes (diploids) were produced in the Department of Nariño, which is the third largest potato producer nationwide [6]. Although the Pastusa Suprema, Diacol Capiro, Parda Pastusa, Superior and Criolla varieties are the better known and more cultivated ones in the Department of Nariño [7], new genotypes adapted to the agroecological conditions of this region with desirable characteristics for consumers and the industrial use are needed. The project "Technological and productive improvement of the potato system in the Department of Nariño" [8] aims to identify outstanding genetic materials for conditions of abiotic stresses such as a water deficit and low fertilization levels between 2400 and 3000 meters above sea level for southern Colombia. For this, a genetic breeding collection was created consisting of 506 potato genotypes, which include materials with multiple collection origins, mainly the germplasm bank at the International Potato Center (CIP) of Peru (54), the Central Colombian Collection (CCC) (76), and the Universidad de Nariño of Colombia (376). This breeding collection is undergoing a morpho-agronomic evaluation for the selection of promising genotypes for possible use as parents in the potato genetic breeding program at the Universidad de Nariño or as candidate genetic materials for possible registration as new varieties from the Andean region of southern Colombia. This selection could be carried out with genomic tools for the genetic characterization of this collection using molecular markers.

Potato genetic diversity is mainly estimated with morphological and physiological characteristics, such as plant architecture, resistance to diseases, and shape and color of flowers and tubers. However, many of these characteristics are affected by the environment [5, 9]. Therefore, methodologies such as molecular markers, which are not affected by the environment, are currently used for the estimation of genetic variability in plant species because of their neutrality, Mendelian inheritance and ease of detection in any tissue and growth stage in plants [5]. In potatoes, different types of DNA markers have been widely implemented for genetic analysis, including random amplified polymorphic DNA (RAPD), microsatellites (SSR) [10], polymorphic length restriction fragments (RFLP) [11], and amplified fragment length polymorphism (AFLP) [12] but single nucleotide polymorphisms (SNP) are used most often [13].

Molecular markers such as SNPs are point variations in nucleotides throughout genomes and have been used for: 1) analysis of genetic diversity; 2) phylogenetic analysis; 3) identification of genes with agronomic importance with Quantitative Traits Loci (QTLs) and Genome-Wide Association Studies (GWAS) mapping; 4) Marker-Assisted Selection (MAS); and 5) varietal identification, among other applications [14]. High-throughput SNP genotyping platforms based on hybridization and fluorescence have been developed for potatoes, where 8K [15] and 20K [13] SNParrays are available. The 8K array contains a subset of 8303 SNPs selected from a set of more than 69 thousand markers identified between transcriptomics and EST (Expressed Sequence Tag) data for six North American cultivars (Bintje, Kennebec, Premier Russet, Shepody, Snowden, and Atlantic) [16]. This matrix has been used to study the genetic diversity of potato germplasm collections of European origin and from North and South America [17–19]. Additionally, SNPs have been used to infer the phylogenetic relationship of some species of Solanum sect. Petota [20] and to identify gene candidates of economic importance with QTLs [21, 22], and GWAS [23, 24] mapping.

The objective of the present study was to analyze 144 Solanum tuberosum genotypes in the potato genetic breeding collection at the Universidad de Nariño in southern Colombia at the genetic level with single nucleotide polymorphisms to establish the: 1) diversity; 2) genetic structure; and 3) linkage disequilibrium; and 4) identify candidate genotypes for duplicates and/or potential use in controlled hybridization processes.

Materials and methods

Plant material

This study included 144 potato genotypes from the genetic breeding collection at the Universidad de Nariño in southern Colombia (Table 1). The genetic materials in this collection belong from multiple germplasm bank origins: the International Potato Center (CIP) of Peru, the Colombian Central Collection (CCC), and the Universidad de Nariño of Colombia and were selected based on the following criteria: 1) yield, 2) industrial potential, and 3) tolerance to Phytophthora infestans. The working collection is preserved under in-vitro and field conditions. For the former, the collection is kept in the plant tissue culture laboratory of the Grupo de Investigación en Producción de Frutales Andinos located at the Universidad de Nariño at 01°12’13’’LN, 77°15’23’’LW and 2540 masl, with a photoperiod of 12/12 hours light/dark; 20 explants of each genetic material are preserved in Murashige & Skoog (1962) culture medium. For field conditions, this collection was sown on the Granja Experimental La Botana of the Universidad de Nariño in plots with 10 clones per introduction. This farm is located on the high plateau of Pasto at 01°09’12’’LN, 77°18’31’’LW and 2820 masl, with an average temperature of 13°C and 970 hours of sun/year, rainfall at 803 mm/year and 82% relative humidity.

Table 1. List of genotypes from the potato breeding collection of the Universidad de Nariño analyzed in this study.

Code Genotype Code or vulgar name Ploidy by PD1 Country Department Pop_K2 2 Pop_K3 3 Ploidy by GS4
Ext1 UdenarStCr16 C.I.O 31.12 (Ratona morada) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext12 UdenarStCr35 Ñoña D C Nariño S_Nariño_1 P_Nariño_1 D
Ext13 UdenarStCr47 Mambera M1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext148 UdenarStCr178 CIP 703548 D P U S_Nariño_1 P_Nariño_1 D
Ext154 UdenarStCr179 CIP 703572 D P U S_Nariño_1 P_Nariño_1 D
Ext158 UdenarStCr182 CIP 703567 D P U S_Nariño_1 P_Nariño_1 D
Ext16 UdenarStCr55 Ratona La Cocha Reserva Cristales D C Nariño S_Nariño_1 P_Nariño_1 D
Ext162 UdenarStCr176 CIP 703594 D P U S_Nariño_1 P_Nariño_1 D
Ext17 UdenarStCr23 Chaucha pura D C Nariño S_Nariño_1 P_Nariño_1 D
Ext197 UdenarStCr180 CIP 703546 D P U S_Nariño_1 P_Nariño_1 D
Ext2 UdenarStCr44 Dorada D C Nariño S_Nariño_1 P_Nariño_1 D
Ext21 UdenarStGua18 Unica (Cordoba) T C Nariño S_Nariño_1 P_Nariño_1 D
Ext214 UdenarStCr21 C.I.O 40.21 (Pacha negra) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext216 UdenarStCr08 C.I.O 23.4 (Malvaseña) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext229 UdenarStCr17 C.I.O 34.15 (Tornilla Roja) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext241 UdenarStCr54 Ratona blanca criolla la cocha M1 flor morada D C Nariño S_Nariño_1 P_Nariño_1 D
Ext242 UdenarStCr140 Jardinera- 15061382 D C Norte De Santander S_Nariño_1 P_Nariño_1 D
Ext243 UdenarStCr09 C.I.O 24.5 (Calabera) (Chaucha Negra) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext244 UdenarStCr42 America D C Nariño S_Nariño_1 P_Nariño_1 D
Ext245 UdenarStCr01 Andina D U U S_Nariño_1 P_Nariño_1 D
Ext246 UdenarStCr40 Yema de huevo D C Nariño S_Nariño_1 P_Nariño_1 D
Ext248 UdenarStCr10 C.I.O 25.6 (Cachuda) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext250 UdenarStCr129 Argentina Parda- 15061273 D C Boyacá S_Nariño_1 P_Nariño_1 D
Ext3 UdenarStCr57 Ratona morada M4 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext33 UdenarStCr63 Uva negra phureja M4 (nn uva negra) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext4 UdenarStCr45 Kurikinga M1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext40 UdenarStCr67 Ratona Roja M5 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext42 UdenarStCr33 Jardinera D C Nariño S_Nariño_1 P_Nariño_1 D
Ext44 UdenarStCr73 Ratona Gourmet D C Nariño S_Nariño_1 P_Nariño_1 D
Ext45 UdenarStCr52 Nacional 2 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext46 UdenarStCr51 Nacional 1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext47 UdenarStCr75 Criolla Nativa D C Nariño S_Nariño_1 P_Nariño_1 D
Ext48 Unknown Norteña M3 U U U S_Nariño_1 P_Nariño_1 D
Ext52 UdenarStCr50 Morada Sigifredo M1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext54 UdenarStCr66 Nevada pequeña D C Nariño S_Nariño_1 P_Nariño_1 D
Ext55 UdenarStCr62 Tornilla la cocha Cristales Roberto Jojoa D C Nariño S_Nariño_1 P_Nariño_1 D
Ext57 UdenarStCr68 Mambera pintada D C Nariño S_Nariño_1 P_Nariño_1 D
Ext6 UdenarStCr39 Tornilla negra D C Nariño S_Nariño_1 P_Nariño_1 D
Ext60 UdenarStCr74 C.I.O 32.13 (Ratona negra) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext61 UdenarStCr20 C.I.O 39.20 (Curipanga) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext62 UdenarStCr69 Morada NN M5 (nn morada) D C Nariño S_Nariño_1 P_Nariño_1 D
Ext67 Unknown MAMA RATONA MORADA M3 U U U S_Nariño_1 P_Nariño_1 D
Ext68 UdenarStCr43 Botella roja D C Nariño S_Nariño_1 P_Nariño_1 D
Ext71 UdenarStCr60 Tornilla amarilla D C Nariño S_Nariño_1 P_Nariño_1 D
Ext73 UdenarStCr61 Tornilla Blanca M1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext74 UdenarStCr64 Silvania 1 D C Nariño S_Nariño_1 P_Nariño_1 D
Ext8 UdenarStGua19 Guata Roja Antigua La Cocha T C Nariño S_Nariño_1 P_Nariño_1 D
Ext104 UdenarStGua51 15062421—SABANERA T C Cundinamarca S_Nariño_2 P_Nariño_2 T
Ext105 UdenarStCr135 Visinia- 15061323 D C Boyacá S_Nariño_2 P_Nariño_2 T
Ext11 UdenarStGua29 Parda Pastusa Surco 22 M2 T U U S_Nariño_2 P_Nariño_2 T
Ext144 UdenarStGua58 CIP 387164.4 T P U S_Nariño_2 P_Nariño_2 T
Ext146 UdenarStGua96 CIP 398192.592 T P U S_Nariño_2 P_Nariño_2 T
Ext147 UdenarStGua55 CIP 377744.1 T P U S_Nariño_2 P_Nariño_2 T
Ext149 UdenarStGua87 CIP 396012.266 T P U S_Nariño_2 P_Nariño_2 T
Ext150 UdenarStGua79 CIP 393382.44 T P U S_Nariño_2 P_Nariño_2 T
Ext151 UdenarStGua90 CIP 396038.101 T P U S_Nariño_2 P_Nariño_2 T
Ext152 UdenarStGua84 CIP 395193.6 T P U S_Nariño_2 P_Nariño_2 T
Ext153 UdenarStGua57 CIP 384866.5 T P U S_Nariño_2 P_Nariño_2 T
Ext156 UdenarStGua98 CIP 398208.620 T P U S_Nariño_2 P_Nariño_2 T
Ext159 UdenarStGua76 CIP 393371.159 T P U S_Nariño_2 P_Nariño_2 T
Ext160 UdenarStGua69 CIP 392657.8 T P U S_Nariño_2 P_Nariño_2 T
Ext161 UdenarStGua53 CIP 300046.22 T P U S_Nariño_2 P_Nariño_2 T
Ext163 UdenarStGua78 CIP 393371.58 T P U S_Nariño_2 P_Nariño_2 T
Ext164 UdenarStGua89 CIP 396034.268 T P U S_Nariño_2 P_Nariño_2 T
Ext165 UdenarStGua94 CIP 398190.404 T P U S_Nariño_2 P_Nariño_2 T
Ext166 UdenarStGua100 CIP 399075.7 T P Peru S_Nariño_2 P_Nariño_2 T
Ext167 UdenarStGua80 CIP 394611.112 T P U S_Nariño_2 P_Nariño_2 T
Ext168 UdenarStGua54 CIP 300056.33 T P U S_Nariño_2 P_Nariño_2 T
Ext169 UdenarStGua65 CIP 391691.96 T P U S_Nariño_2 P_Nariño_2 T
Ext170 UdenarStGua63 CIP 391058.175 T P U S_Nariño_2 P_Nariño_2 T
Ext171 UdenarStGua68 CIP 392657.171 T P U S_Nariño_2 P_Nariño_2 T
Ext172 UdenarStGua86 CIP 395446.1 T P U S_Nariño_2 P_Nariño_2 T
Ext173 UdenarStGua67 CIP 392633.64 T P U S_Nariño_2 P_Nariño_2 T
Ext174 UdenarStGua83 CIP 395112.32 T P U S_Nariño_2 P_Nariño_2 T
Ext175 UdenarStGua61 CIP 391011.17 T P U S_Nariño_2 P_Nariño_2 T
Ext177 UdenarStGua70 CIP 393073.179 T P U S_Nariño_2 P_Nariño_2 T
Ext179 UdenarStGua77 CIP 393371.164 T P U S_Nariño_2 P_Nariño_2 T
Ext180 UdenarStGua62 CIP 391046.14 T P U S_Nariño_2 P_Nariño_2 T
Ext181 UdenarStGua91 CIP 396285.1 T P U S_Nariño_2 P_Nariño_2 T
Ext182_1 UdenarStGua66 CIP 392285.72 T P U S_Nariño_2 P_Nariño_2 T
Ext182_2 (Control) UdenarStGua66 CIP 392285.72 T P U S_Nariño_2 P_Nariño_2 T
Ext183 UdenarStGua92 CIP 397060.19 T P U S_Nariño_2 P_Nariño_2 T
Ext184 UdenarStGua72 CIP 393079.24 T P U S_Nariño_2 P_Nariño_2 T
Ext186 UdenarStGua82 CIP 394904.20 T P U S_Nariño_2 P_Nariño_2 T
Ext187 UdenarStGua59 CIP 389746.2 T P U S_Nariño_2 P_Nariño_2 T
Ext188 UdenarStGua95 CIP 398192.41 T P U S_Nariño_2 P_Nariño_2 T
Ext189 UdenarStGua64 CIP 391580.30 T P U S_Nariño_2 P_Nariño_2 T
Ext19 UdenarStGua07 Betina T C Nariño S_Nariño_2 P_Nariño_2 T
Ext190 UdenarStGua73 CIP 393079.4 T P U S_Nariño_2 P_Nariño_2 T
Ext191 UdenarStGua93 CIP 397196.3 T P U S_Nariño_2 P_Nariño_2 T
Ext192 UdenarStGua75 CIP 393280.82 T P U S_Nariño_2 P_Nariño_2 T
Ext193 UdenarStGua74 CIP 393220.54 T P U S_Nariño_2 P_Nariño_2 T
Ext194 UdenarStGua97 CIP 398193.553 T P U S_Nariño_2 P_Nariño_2 T
Ext195 UdenarStGua88 CIP 396034.103 T P U S_Nariño_2 P_Nariño_2 T
Ext196 UdenarStGua71 CIP 393077.159 T P U S_Nariño_2 P_Nariño_2 T
Ext198 UdenarStGua85 CIP 395438.1 T P U S_Nariño_2 P_Nariño_2 T
Ext199 UdenarStGua81 CIP 394895.7 T P U S_Nariño_2 P_Nariño_2 T
Ext20 UdenarStGua27 Nevada M6 T C Nariño S_Nariño_2 P_Nariño_2 T
Ext23 UdenarStGua31 Suprema Certificada M2 (Suprema) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext236 UdenarStGua35 Guata Carriza M5 T C Nariño S_Nariño_2 P_Nariño_2 T
Ext237 UdenarStGua37 Morada Sigifredo M1 T C Nariño S_Nariño_2 P_Nariño_2 T
Ext238 UdenarStGua25 Chola Ecuatoriana T C Nariño S_Nariño_2 P_Nariño_2 T
Ext239 UdenarStGua41 San Pedro Invernadero T C Nariño S_Nariño_2 P_Nariño_2 T
Ext240 UdenarStGua26 Guata Negra Cordoba T C Nariño S_Nariño_2 P_Nariño_2 T
Ext247 UdenarStCr49 Monteña M1 D C Nariño S_Nariño_2 P_Nariño_2 T
Ext249 UdenarStGua29 Parda Pastusa Surco 22 M2 T C Nariño S_Nariño_2 P_Nariño_2 T
Ext25 UdenarStGua28 Pamba Lisa T C Nariño S_Nariño_2 P_Nariño_2 T
Ext27 UdenarStGua34 Capiro vieja M1 (Capiro Vieja La Cocha) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext32 UdenarStGua36 Guata M5 Gualcala (Guata Gualcala) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext39 UdenarStGua22 Guata 23 (Surco23) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext43 UdenarStGua10 Guata parda T C Nariño S_Nariño_2 P_Nariño_2 T
Ext59 Unknown MAMA GUATA 22 M2 U U U S_Nariño_2 P_Nariño_2 T
Ext64 UdenarStGua30 Roja Nariño M1 T C Nariño S_Nariño_2 P_Nariño_2 T
Ext78 UdenarStGua22 Guata 23 (Surco23) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext79 UdenarStGua17 Unica (Botana) T C Nariño S_Nariño_2 P_Nariño_2 T
Ext87 UdenarStGua52 15062458—PEDIG-B 69S-76 XB-922-3 T U U S_Nariño_2 P_Nariño_2 T
Ext91 UdenarStCr131 Chaucha- 15061281 D C Quindío S_Nariño_2 P_Nariño_2 T
Ext10 UdenarStGua40 Roja Huila M6 T C Nariño S_Nariño_2 P_Nariño_3 T
Ext14 UdenarStGua21 Guata 21 (Surco21) T C Nariño S_Nariño_2 P_Nariño_3 T
Ext145 UdenarStGua99 CIP 399053.15 T P U S_Nariño_2 P_Nariño_3 T
Ext15 UdenarStCr76 nn vino tinto D C Nariño S_Nariño_2 P_Nariño_3 T
Ext155 UdenarStCr177 CIP 703545 D P U S_Nariño_2 P_Nariño_3 T
Ext157 UdenarStGua60 CIP 391002.6 T P U S_Nariño_2 P_Nariño_3 T
Ext178 UdenarStGua56 CIP 380496.6 T P U S_Nariño_2 P_Nariño_3 T
Ext18 UdenarStGua23 Guata 25 (Chola Surco 25) T C Nariño S_Nariño_2 P_Nariño_3 T
Ext185 UdenarStCr181 CIP 703508 D P U S_Nariño_2 P_Nariño_3 T
Ext217 UdenarStCr80-1 ju 11.2 D C Nariño S_Nariño_2 P_Nariño_3 T
Ext22 UdenarStGua24 Capiro Certificada M2 (Capiro) T C Nariño S_Nariño_2 P_Nariño_3 T
Ext234 UdenarStCr20.1 Curipamba 1.1 D U U S_Nariño_2 P_Nariño_3 T
Ext252 UdenarStCr117 Peruana- 15060543 D P Cajamarca S_Nariño_2 P_Nariño_3 T
Ext26 UdenarStGua16 Capiro Rosada T C Nariño S_Nariño_2 P_Nariño_3 T
Ext28 Unknown Mamá Capiro M6 T U U S_Nariño_2 P_Nariño_3 T
Ext41 UdenarStGua13 Bola de sal o pamba morada T C Nariño S_Nariño_2 P_Nariño_3 T
Ext49 UdenarStCr76 nn vino tinto D C Nariño S_Nariño_2 P_Nariño_3 T
Ext5 UdenarStCr46 Kurikinga M5 D C Nariño S_Nariño_2 P_Nariño_3 T
Ext56 UdenarStGua14 Morasurco grande T C Nariño S_Nariño_2 P_Nariño_3 T
Ext65 UdenarStGua39 Parda Suprema M6 T C Nariño S_Nariño_2 P_Nariño_3 T
Ext7 Unknown San Juan Danita M2 D U U S_Nariño_2 P_Nariño_3 T
Ext72 UdenarStGua32 Guata silvianaM1 (Guata Silvania La Cocha) T C Nariño S_Nariño_2 P_Nariño_3 T
Ext77 UdenarStGua33 Capiro blanca M6 T C Nariño S_Nariño_2 P_Nariño_3 T
Ext80 UdenarStCr18 C.I.O 35.16 D C Nariño S_Nariño_2 P_Nariño_3 T
Ext88 UdenarStCr166 Chaucha Maleña- 15061755 D C Nariño S_Nariño_2 P_Nariño_3 T
Ext9 UdenarStGua09 Leona T C Nariño S_Nariño_2 P_Nariño_3 T
Ext92 UdenarStGua45 15062413-Tocana blanca T C Cundinamarca S_Nariño_2 P_Nariño_3 T
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1 Ploidy assigned according to Passport Data (PD)

2 assignments determined through Bayesian analysis

3 assignments determined through PCA

4 ploidies assigned according to Genetic Structure (GS) analysis. D = Diploid; T = Tetraploid; U = Unknown; C = Colombia; P = Perú.

DNA extraction

For each of the 144 potato materials from the genetic breeding collection at the Universidad de Nariño, young leaves were collected for each genotype grown under in-vitro conditions, from which DNA was isolated using an Extract-N- Amp™ Plant PCR Kit from Sigma-Aldrich, Germany. The quality of the DNA was verified with visualization in 1% agarose gels stained with ethidium bromide (0.5ng/mL), while the DNA concentration was estimated with spectrophotometry using NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, USA). Finally, the DNA was diluted to a final concentration of 100 ng/μL and stored at -20°C until genotyping.

Genotyping and SNP selection

The genotyping of the potato genetic breeding collection at the Universidad de Nariño was carried out with an 8K matrix [15] from Infinium technology; the beadcheaps were read with an Illumina HiScan SQ (Illumina, San Diego, CA) at the Corporación Colombiana de Investigación Agropecuaria—AGROSAVIA in Tibaitatá research center at Mosquera—Colombia. The fluorescence intensities were extracted from the GenomeStudio program (Illumina, San Diego CA) to assign genotypes to each locus (0, 1, 2, 3, 4), which was carried out with the FitTetra library [25] in the R program [26]. The markers that could not be determined or that were monomorphic were discarded; the remaining markers were subjected to a new filter, with more than 20% and 5% of data lost at the population level and for the Minimum Allele Frequencies (MAF), respectively (S1 Table).

Structure and genetic diversity

The analysis of the population structure of the potato genetic breeding collection at the Universidad de Nariño used a tetraploid model (0, 1, 2, 3, 4) with two strategies: A) A Bayesian model implemented in the STRUCTURE program [27] without priori information for the population, evaluating one (K1) to ten (K10) possible subpopulations, with five independent repeats, assuming a mixture model with frequencies of correlated alleles investigated until 150,000 interactions. The optimal number of subpopulations was established with Evanno’s method [28] in the Structure Harvester program [29] and in a model based on a Principal Component Analysis (PCA) carried out with the packages StAMPP [30] and Adegenet [31], where the number of subpopulations was determined with NBClust [32] and Factoextra [33] packages in the R program [26].

The number of subpopulations identified in each analysis was used to determine the genetic differentiation coefficients (FST) and percentages of differentiation between and within the subpopulations with Molecular Analysis of Variance (AMOVA) using the libraries StAMPP [30] and Poppr [34] in the R program [26]. The genetic diversity was estimated with observed heterozygosity (Ho), which was determined for each marker and each subpopulation based on the formula: Ho = Number total of heterozygous genotypes/Total number of genotypes (homozygous + heterozygous).

Linkage disequilibrium

For the analysis of the linkage disequilibrium (LD) of the subpopulations detected in the potato genetic breeding collection at the Universidad de Nariño, the polymorphic SNP markers with a known physical position in the reference genome of Solanum tuberosum group Phureja DM1-3 used PGSC v4.03 Pseudomolecules [35]. Among the five possible genotypes for each marker (0, 1, 2, 3, 4), Pearson correlations (r2) were calculated, and only the values with a level of significance lower than 0.001 were used to determine: 1) Linkage Disequilibrium (LD) averages at the subpopulation level and 2) how LD decays in genome plotting the r2 values against physical distance in megabases (Mb), calculated between each combination of markers included in this analysis. These procedures were performed in the R program [26].

Candidate genotypes for duplicates and/or possible use in controlled crosses

The identification of candidate genotypes for duplicates and/or possible use in controlled hybridization processes in the potato genetic breeding collection at the Universidad de Nariño was carried out through distribution of the Nei genetic distance [36], calculated in the StAMPP library [30] in the R program [26], for all genotypes included in the diploid and tetraploid subpopulations determined with the genetic structure analysis. Genotypes with genetic distances less than 0.010 were considered candidates for duplicates, while combinations of genotypes with genetic distances greater than 0.50 (in diploids) and 0.95 (in tetraploids) were selected as candidates for possible use in controlled crosses. For the identification of duplicates, the Ext_182 genotype (Table 1) was included as a control, which was genotyped in duplicate from two independent biological samples.

Results

Structure and genetic diversity

In the potato genetic breeding collection at the Universidad de Nariño, 4750 polymorphic SNP markers (57.2%) were identified, with an average of 340 markers per chromosome, distributed as follows: Chr 0 (84); Chr 1 (501); Chr 2 (433); Chr 3 (388); Chr 4 (502); Chr 5 (366); Chr 6 (403); Chr 7 (440); Chr 8 (353); Chr 9 (372); Chr 10 (258); Chr 11 (318); Chr 12 (268) and unanchored (64), of which 4602 were mapped on the 12 chromosomes of the potato genome. With all the polymorphic markers in this collection, the Bayesian and PCA analyses detected two (K2) and three (K3) possible subpopulations, respectively (Fig 1A and 1B).

Fig 1. Identification of the number of subpopulations in the potato breeding collection of the Universidad de Nariño.

Fig 1

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A) Bayesian analysis; B) PCA.

The Bayesian analysis implemented in the STRUCTURE program for the potato genetic breeding collection at the Universidad de Nariño revealed that two (K2) clearly differentiated subpopulations were detected in an ACP barplot, which showed 34.76% of the genetic variability (Fig 2A), with an ancestry diagram (Fig 2B) that showed the genetic identity of each genotype in each identified group. The two subpopulations S_Nariño_1 and S_Nariño _2 made up of 47 and 97 genotypes in the high genetic differentiation, with an FST between 0.533 and 63.31% between the populations and with high levels of heterozygosity (Ho> 0.53 and 36.69% of differentiation within the subpopulations), which was higher in the S_Nariño_2 subpopulation (Ho = 0.58) than in S_Nariño_1 (Ho = 0.53) (Table 2 and Fig 2C).

Fig 2. Genetic analysis of the potato breeding collection of the Universidad de Nariño for the two (K2) and three (K3) subpopulations determined through Bayesian and PCA methods.

Fig 2

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A) PCA K2; B) STRUCTURE barplot K2; C) Heterozygosity K2; D) PCA K3; E) STRUCTURE barplot K3; F) Heterozygosity K3.

Table 2. Statistics of diversity, genetic structure, and Linkage Disequilibrium (LD) in the two (K2) and three (K3) subpopulations determined in the potato breeding collection of the Universidad de Nariño.

Analysis Subp PGS1 NS Ho (M/R) LD2 (M/R) AMOVA
FV (%) FTS Total
STRUCTURE K2 S_Narino_1 D 47 0.53 (0.51–0.55) 0.633 (0.47–1) AP 63.31 0.533*
S_Narino_2 T 97 0.58 (0.50–0.64) 0.437 (0.33–0.99) WP 36.69
TOTAL 144 - - - 100 -
     
PCA K3 P_Narino_1 D 47 0.53 (0.51–0.55) 0.633 (0.47–1) AP 44.78 0.536*
P_Narino_2 T 70 0.59 (0.53–0.64) 0.510 (0.39–0.99) WP 55.22
P_Narino_3 T 27 0.56 (0.50–0.59) 0.730 (0.60–0.99) - -
TOTAL 144 - - - 100 -
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PGS1 = Ploidy assigned according to Genetic Structure (GS) analysis; LD 2 (M/R) = Linkage disequilibrium (Mean/Range)

* = Significant at p < 0.001; NS = number of samples; Subp = subpopulations; Ho (M/R) = Heterozygosity (Mean/Range); D = diploids; T = tetraploids; AP = among populations; WP = within populations.

The samples grouped in subpopulation S_Nariño_1 were mainly (80%) from the Department of Nariño in Colombia, and the remaining samples (20%) were from Peru or had unknown origin. According to the passport data, the samples from this group mainly (91.5%) corresponded to diploid genotypes (43). However, four (8.5%) Colombian genotypes (Ext21, Ext48, Ext67 and Ext8) had passport data for tetraploids and/or were unknown (Table 1). On the other hand, subpopulation S_Nariño_2 had samples from Peru (54%), Colombia (40%) or unknown origin (6%), where 82.5% of the genotypes (80) had tetraploid passport data, while 15 (10.4%) genotypes were Colombian, Peruvian or unknown (Ext105, Ext247, Ext59, Ext91, Ext15, Ext155, Ext185, Ext217, Ext234, Ext252, Ext49, Ext5, Ext7, Ext80 and Ext88), with diploid and/or unknown data (Table 1). According to the genetic analyses, this collection had 19 (13.2%) errors identified in the classification of genotypes according to level of ploidy. Thus, S_Nariño_1 and S_Nariño_2 were made up of possible diploid genotypes (2n = 2x = 24) and tetraploid genotypes (2n = 4x = 48), respectively (Table 1).

The analysis of the genetic breeding collection at the Universidad de Nariño based on ACP separated the two subpopulations of diploids (S_Nariño_1) and tetraploids (S_Nariño_2) detected with the Bayesian analysis in three (K3) possible subpopulations with the 47 (P_Nariño_1), 77 (P_Nariño_2) and 27 (P_Nariño_3) genotypes. This analysis also differentiated the diploid samples (S_Nariño_1 = P_Nariño_1) from the tetraploids (S_Nariño_2) and separated the latter into two subgroups, generating the subpopulations P_Nariño_2 and P_Nariño_3. The three subpopulations had a clear genetic differentiation with a FST of 0.536 and 44.78% of differentiation between the populations (Fig 2D and 2E and Table 2) with high levels of heterozygosity, with Ho> 0.53 and 55.22% differentiation within the subpopulations, values that were higher in subpopulation P_Nariño_2 (Ho = 0.59), followed by P_Nariño_3 (Ho = 0.56) and P_Nariño_1 (Ho = 0.53) (Table 2 and Fig 2F). According to the passport data, subpopulation P_Nariño_2 was mainly made up of samples from Peru (66%), and P_Nariño_3 mainly had samples from Colombia (67%).

Linkage disequilibrium of the potato breeding collection

The 4602 polymorphic markers mapped on the 12 chromosomes of the potato genome were used to evaluate the linkage disequilibrium (LD) in the two (K2) and three (K2) subpopulations detected in the potato breeding collection at the Universidad de Nariño, characterized by high levels of LD (r2 > 0.437). For the K2 analysis, the LD levels were higher in subpopulation S_Nariño_1 (r2 diploid = 0.633) than in S_Nariño_2 (r2 tetraploid = 0.437), while in the K3 analysis, the two subpopulations of tetraploid genotypes detected in S_Nariño_2 had differences in the LD levels, which were higher in subpopulation P_Nariño_3 (r2 Colombia = 0.730) than in P_Nariño_2 (r2 Peru = 0.510) (Table 2). Indeed, LD, at a distance of approximately 3Mb, decayed slowly through the genome in all subpopulations detected for K2 and K3. The LD decayed at that distance with r2 values of 0.63 in the diploid genotypes (S_Nariño_1 = P_Nariño_1) and 0.35 in the tetraploids (S_Nariño_1). In the tetraploid subpopulations P_Nariño_2 and P_Nariño_3, the LD decayed at approximately 3Mb with an r2 of 0.52 and 0.73, respectively (Fig 3A and 3B).

Fig 3. Linkage Disequilibrium (LD) analysis for the two (K2) and three (K3) subpopulations determined in the potato breeding collection of the Universidad de Nariño.

Fig 3

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A) LD K2 STRUCTURE; B) LD K3 PCA.

Candidates to duplicates and crossing

The genetic distances between the samples that make up the potato genetic breeding collection at the Universidad de Nariño had a range from 0 to 0.110. These distances were greater in tetraploid genotypes S_Nariño_2 (mean of 0.065 and between 0 and 0.110) than in the diploid S_Nariño_1 (mean of 0.031 and between 0 and 0.056) (Fig 4A and 4B). The analysis of the diploid and tetraploid genotypes identified 25 possible candidates for duplicates with genetic distances less than 0.01, including control duplicate 25, which corresponded to the identical samples Ext_182_1 and Ext_182_2. Additionally, 14 possible genotype combinations were identified in the diploid and tetraploid subpopulations because they had genetic distances greater than 0.50 and 0.95, respectively. The genotype combinations identified here can be used to implement controlled crosses in this collection (Table 3).

Fig 4. Distributions of Nei genetic distances in the subpopulations of the potato breeding collection of the Universidad de Nariño.

Fig 4

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A) Diploids (S_Nariño_1) genotypes; B) Tetraploids (S_Nariño_2) genotypes.

Table 3. Genotypes of the potato breeding collection of Universidad de Nariño selected as candidates for duplicates and possible use in controlled crossing.

Selection Populations Number of duplicates or Crosses Candidates for duplicates and crosses
Duplicates S_Nariño_1 (Diploids) Duplicate_1 Ext1, Ext17, Ext3, Ext44, Ext67
Duplicate_2 Ext12, Ext21, Ext42, Ext48
Duplicate_3 Ext158, Ext229
Duplicate_4 Ext2, Ext45
Duplicate_5 Ext243, Ext250, Ext46
Duplicate_6 Ext245, Ext73
Duplicate_7 Ext246, Ext52
Duplicate_8 Ext33, Ext40
Duplicate_9 Ext4, Ext8, Ext68
Duplicate_10 Ext57, Ext62
S_Nariño_2 (Tetraploids) Duplicate_11 Ext11, Ext59
Duplicate_12 Ext150, Ext173
Duplicate_13 Ext164, Ext240
Duplicate_14 Ext166, Ext199
Duplicate_15 Ext167, Ext170
Duplicate_16 Ext174, Ext181
Duplicate_17 Ext179, Ext190
Duplicate_18 Ext20, Ext79
Duplicate_19 Ext239, Ext78
Duplicate_20 Ext247, Ext91
Duplicate_21 Ext14, Ext22, Ext26, Ext28
Duplicate_22 Ext15, Ext49, Ext72
Duplicate_23 Ext157, Ext65
Duplicate_24 Ext77, Ext92
Duplicate_25 (Control) Ext182_1, Ext182_2
Crosses S_Nariño_1 (Diploids) Crosse_1 Ext2 X Ext162, Ext214, Ext216, Ext229, Ext243, Ext245, Ext248, Ext4, Ext55, Ext8
Crosse_2 Ext214 X Ext2
Crosse_3 Ext216 X Ext2
Crosse_4 Ext229 X Ext2, Ext45
Crosse_5 Ext243 X Ext2
Crosse_6 Ext245 X Ext2, Ext45, Ext46
Crosse_7 Ext248 X Ext2
Crosse_8 Ext4 X Ext2, Ext45, Ext46
Crosse_9 Ext45 X Ext162, Ext229, Ext245, Ext4, Ext8
Crosse_10 Ext46 X Ext162, Ext245, Ext4, Ext8
Crosse_11 Ext55 X Ext2
Crosse_12 Ext8 X Ext2, Ext45, Ext46
S_Nariño_2 (Tetraploids) Crosse_13 Ext155 X Ext152, Ext160, Ext161, Ext166, Ext174, Ext177, Ext181, Ext182, Ext183, Ext187, Ext191, Ext192, Ext199, Ext87
Crosse_14 Ext185 X Ext152, Ext160, Ext161, Ext166, Ext174, Ext177, Ext181, Ext182, Ext183, Ext187, Ext191, Ext192, Ext199, Ext87
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Discussion

Genetic variability is crucial for the development of new cultivars with characteristics that the market requires, such as genotypes with resistance to diseases and/or pests, higher yields, quality and high nutritional values. Therefore, germplasms must be evaluated to identify new genetic sources with potential use in genetic breeding processes. In Colombia, the Department of Nariño has established itself as one of the main potato producers. However, the selection and/or generation of new cultivars adapted to the agroecological conditions of this region could increase the competitiveness of this department in domestic potato production. The potato genetic breeding collection at the Universidad de Nariño was evaluated at the genetic level based on molecular markers to establish parameters related to diversity, genetic structure, and linkage disequilibrium. This information is needed for the identification of candidate genotypes for duplicates and/or with potential use in genetic breeding processes.

The potato genetic breeding collection at the Universidad de Nariño consisted mainly of diploid and tetraploid genotypes originating from the Department of Nariño, known as a center of potato genetic diversity in Colombia [19] and also have genotypes from two of the more diverse genebanks for this specie, i.e. the CIP of Peru [37] and the CCC of Colombia [38]. This breeding collection is undergoing a morpho-agronomic evaluation under field conditions in different locations in the Department of Nariño to identify promising genotypes for the selection and/or development of new varieties that present outstanding attributes, such as high yield, good agro-industrial aptitude, and tolerance to diseases and abiotic stresses.

The collection at the Universidad de Nariño was analyzed with the 8303 SNPs included in the SNParray of SolCAP version 1 [16] to select genotypes, with a polymorphism level of 57.2%. The same panel of SNPs has been used to evaluate different potato populations with multiple origins. Berdugo-Cely et al. [19] identified 72% polymorphism among 809 diploid and tetraploid genotypes from the CCC in Colombia. Endelman et al. [39] identified 61% among 719 tetraploid genotypes from the United States. Esnault et al. [40] identified 61% among 48 tetraploid genotypes from the National Institute for Agronomic Research—INRA in France. Kolech et al. [41] identified 44.5% among 109 tetraploid genotypes from the United States, Europe, Peru and Ethiopia. Hardigan et al. [20] identified 61% among 287 diploid, tetraploid and hexaploid genotypes belonging to various species of Solanum sect. Petota and elite genotypes from the United States. Hirsch et al. [17] identified 77% among 250 monoploid, diploid, and tetraploid genotypes from the United States, and Stich et al. [18] identified 74% among 44 diploid and tetraploid genotypes of varieties grown in Europe. The differences in the percentage of polymorphism between the different studies is related to the number of samples used for comparison in studies that analyzed between 44 [18] and 809 [19] samples, with different levels of ploidy that included genotypes from monoploids [17] to hexaploids [20]. The high number of polymorphic markers identified in this study suggested that the SolCAP 8K matrix is suitable for the genetic analysis of the potato breeding collection at the Universidad de Nariño in Colombia.

The analysis of the population structure of the potato genetic breeding collection at the Universidad de Nariño based on the Bayesian analyses of the STRUCTURE and PCA program identified two and three possible subpopulations associated with the ploidy level, where diploid genotypes separated from tetraploids, and, according to the geographical origin, the tetraploid genotypes of Colombia separated from those of Peru. Multiple studies have described the use of molecular markers to classify and separate potato genetic materials conserved in germplasm banks according to their ploidy level [17–19, 42, 43] and the degree of genetic breeding to discriminate materials according to the varieties, cultivars, elite materials, wild species and/or related species [17, 42, 44–46].

The difference in the number of subpopulations identified between the two methods implemented in this study was related to their statistical bases. The STRUCTURE program identifies groupings with explicit genetic models for multiple population genetic parameters, which are often difficult to verify and require a lot of computing time and computational capacity [47, 48]. On the other hand, cluster analyses based on PCA identify genetic structures in large data sets with low computational capacity and shorter analysis times and do not use genetic models as a basis for identification. However, this alternative does not analyze a range of the number of populations and requires a priori definition of the number of populations to be detected. Additionally, it does not include all the information that STRUCTURE does since it summarizes the genetic variability of analyzed materials in a low number of components [47, 48]. However, it is one of the more commonly used methods for the evaluation of genetic structures in plant populations.

Multiple errors in the classification according to the ploidy level of the genotypes present in the potato genetic breeding collection at the Universidad de Nariño were identified in the tetraploid samples. The errors reported here must be confirmed with strategies such as flow cytometry, which will allow accurate corroboration of the ploidy in these genotypes. Errors in the genetic integrity of germplasm bank materials and genetic breeding collections conserved in field and in vitro conditions resulting from seed mixing, incorrect labeling, and errors in the data for origin and pedigree of the samples can be detrimental to genetic breeding programs [43]. However, these errors can be identified and adjusted with the support of a genetic analysis based on molecular markers, as reported in this study. Errors and adjustments in classifications according to ploidy levels [19, 43] and pedigree [39] of potato genotypes conserved in germplasm banks have been reported.

The diploid and tetraploid populations identified in the potato genetic breeding collection at the Universidad de Nariño had high levels of genetic diversity and linkage disequilibrium (LD) among the markers. The level of genetic diversity was lower in the diploid genotypes than in the tetraploids. At the LD level, differences were identified between the diploid genotypes and the tetraploids from Peru and those from Colombia. The tetraploid genotypes from Peru had greater genetic diversity than those from Colombia, while the genotypes from Colombia had higher levels of LD than those from Peru. Likewise, the LD decayed slowly in the potato genome of the diploid and tetraploid genotypes. In the tetraploids, the LD decayed slower in the genotypes from Colombia than in those from Peru. High values of heterozygosity [17, 19, 40, 42], and LD [17, 19, 40, 49, 50] have been reported in potato germplasm with the use of SNP markers, where diploid genotypes are characterized by a lower genetic diversity [19, 42–44] and higher levels of LD than in tetraploid genotypes [19]. Others diploid Colombian potato collections have been analyzed using SSR [51] and SNP markers [19] identifying high heterozygosity levels. High levels of heterozygosity in potatoes have been mainly associated with its heterozygous nature, allogamy, and broad variability in ploidy levels [52]. The differences between diploid and tetraploid potatoes in the heterozygosity levels has been associated with the ploidy bias, being higher these parameters in polyploid genotypes [53]. However, in this analysis to eliminate this bias all genotypes were analyzed as tetraploids, identifying a minor proportion of heterozygosity levels in diploid genotypes. On the other hand, the differences in the levels of genetic diversity and LD between the tetraploid genotypes from Colombia and Peru could be due to the fact that Peru is the center of origin for this species [52] and the fact that many of the samples analyzed here have not undergone strong selection.

In the potato genetic breeding collection at the Universidad de Nariño, candidates for duplicates and combinations of genotypes with broad genetic distances were identified that can be used to implement controlled crosses to generate populations with a high degree of heterosis. Candidates for duplicates included the Ext_182 control, indicating the reliability of the genetic identity of the proposed duplicates and suggests that the SolCAP 8K chip [16] is a potential tool for the identification of duplicates in potato genotypes preserved and used in germplasm banks and/or breeding collections. Likewise, Kolech et al. [41] evaluated 44 potato genotypes grown in Ethiopia with the 8K chip and identified only 15 unique genetic materials, most of which were duplicate genotypes. The candidates for duplicates reported here must be validated with highly heritable morphological characteristics, such as shape and color of tubers and flowers, variables with high discriminatory power in potato germplasms at the morphological level [19, 54–56]. Errors in classification according to the level of ploidy and taxonomy and the presence of duplicate genotypes in germplasm banks and genetic breeding collections can be detrimental at an economic level in conservation strategies and for the selection of promising genotypes because they can identify materials with full genetic identity. Therefore, these materials must be identified and excluded for the estimation and identification of duplicates with molecular markers rather than conserving and using a duplicate accession as a different accession in a germplasm bank [57].

Genetic analyses with molecular markers can facilitate and support genetic breeding programs since they correct errors that occur in different stages, such as seed mixing and incorrect labeling, and establish genetic breeding strategies through the identification of materials and candidates for use in controlled breeding processes. It has been reported that one of the most important decisions in genetic breeding programs is the selection of the most suitable genotype for carrying out crosses that generate progeny with an increase in genetic gain [58]. The diploid and tetraploid genotypes selected according to levels of diversity and genetic distance for controlled crossing strategies identified in this study can be a baseline for possible genetic breeding strategies to be implemented with the germplasm from this collection. However, these genotypes must be verified with a morpho-agronomic characterization to establish their potential use.

Conclusions

In the potato genetic breeding collection at the Universidad de Nariño in Colombia, high levels of heterozygosity were identified with a clear genetic structure that was mainly associated with the level of ploidy, which separated the diploid and tetraploid genotypes, discriminated the tetraploid genotypes, and differentiated the genotypes from Colombia and Peru. The genetic diversity was greater in the tetraploid genotypes than in the diploid genotypes. The tetraploid genotypes from Peru were more diverse than those from Colombia. The LD level was higher in the diploid genotypes than in the tetraploid genotypes, where the tetraploid genotypes from Colombia had higher LD levels than those from Peru. Multiple errors in the classification and candidates for duplicates in the potato breeding collection according to the level of ploidy were identified and adjusted. In the diploid and tetraploid genotypes, different combinations of candidate genotypes were identified for duplicates and/or for potential use in controlled hybridization processes. The genotype candidates for duplicates with errors in classification and/or potential use in future crosses must be validated with morpho-agronomic characterizations and flow cytometry. All results reported in this study suggested that the potato genetic breeding collection at the Universidad de Nariño has a broad genetic base with potential use for the genetic breeding of this crop in the Department of Nariño in southern Colombia.

Supporting information

S1 Table. Genotypic data of 144 accessions of potato breeding collection of Universidad de Nariño obtained through 8K SNParray technology.

(XLSX)

Click here for additional data file. (2.4MB, xlsx)

Acknowledgments

The authors thank the germplasm banks at the Centro Internacional de la Papa, the Colección Central Colombiana de Papa (AGROSAVIA) of Sistema de Bancos de Germoplasma de la Nación para la Alimentación y la Agricultura (SBGNAA), and the Universidad de Nariño for providing the genetic resources analyzed in this study, the Gobernación de Nariño, Universidad de Nariño and AGROSAVIA for their contribution to the structuring and approval of the project that financed this research.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The resources for the development of this research were provided by the Ministerio de Ciencia y Tecnología de Colombia (Minciencias) and the Gobernación de Nariño through the Fondo de Ciencia, Tecnología e Innovación del Sistema General de Regalias, with the approval of the project "Improvement technological and productive of the potato system in the Department of Nariño”, identified with code BPIN No. 2014000100022. The execution of this project was carried out between the Universidad de Nariño and AGROSAVIA through the macro agreement 480-15. The hours spent by researcher Jhon A. Berdugo-Cely MSc. for the development of this study were provided by AGROSAVIA through Variable Transfer (TV) 2019. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Tzen-Yuh Chiang

24 Feb 2021

PONE-D-21-04514

Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern of Colombia using single nucleotide polymorphism (SNP) markers

PLOS ONE

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Reviewer #1: Partly

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Reviewer #1: Needs to acknowledge and incorporate related work before further review...

Juyó, D., F. Sarmiento, M. Álvarez, H. Brochero, C. Gebhardt, T. Mosquera. 2015. Genetic Diversity and Population Structure in Diploid Potatoes of Solanum tuberosum Group Phureja. Crop Science 55: 760-769.

Technical issue is to acknowledge and incorporate recent publications on ploidy bias, e.g.,...

Bamberg, J. and A. del Rio. 2020. Assessing under-Estimation of Genetic Diversity within Wild Potato (Solanum) Species Populations. American Journal of Potato Research 97:547-553

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PLoS One. 2021 Mar 18;16(3):e0248787. doi: 10.1371/journal.pone.0248787.r002

Author response to Decision Letter 0

2 Mar 2021

Dear Editor,

PLOS ONE

Here describe all answers for the editor and reviewers and the changes made in the manuscript,

Commentary editor

1. All references were cited in the list included the suggested by reviewers.

2. The title of the paper was adjusted being the editor commentary: “Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern Colombia using single nucleotide polymorphism (SNP) markers” in the document and web submission on-line.

3. All manuscript was adjusted being PLOS ONE's style requirements (the format changes as line spacing, tables format and subtitle size was not included in track changes), the author affiliations were corrected because this was inverted to the two last authors.

Commentary reviewers

4. The references suggested was reviewed and included in the manuscript in the lines 340-341 “Others diploid Colombian potato collections have been analyzed using SSR [51] and SNP markers [19] identifying high heterozygosity levels.” and lines 343-346 “The differences between diploid and tetraploid potatoes in the heterozygosity levels has been associated with the ploidy bias, being higher these parameters in polyploid genotypes [53]. However, in this analysis to eliminate this bias all genotypes were analyzed as tetraploids, identifying a minor proportion of heterozygosity levels in diploid genotypes.”. I

5. This, these two new references were included: 51) Juyó D, Sarmiento F, Álvarez M, Brochero H, Gebhardt C, Mosquera T. Genetic Diversity and Population Structure in Diploid Potatoes of Solanum tuberosum Group Phureja. Crop Sci. 2015;55: 760–769. doi:https://doi.org/10.2135/cropsci2014.07.0524 and 53) Bamberg J, del Rio A. Assessing under-Estimation of Genetic Diversity within Wild Potato (Solanum) Species Populations. Am J Potato Res. 2020;97: 547–553. doi:10.1007/s12230-020-09802-3.

Additional changes

6. In the text was included: “The genetic materials in this collection belong from multiple germplasm bank origins: the International Potato Center (CIP) of Peru, the Colombian Central Collection (CCC), and the Universidad de Nariño of Colombia and” in the lines 105-107.

7. The sections of Acknowledgments, Funding were edited, while the Contributions section was deleted.

8. Acknowledgments: The authors thank the germplasm banks at the Centro Internacional de la Papa, the Colección Central Colombiana de Papa (AGROSAVIA) of Sistema de Bancos de Germoplasma de la Nación para la Alimentación y la Agricultura (SBGNAA), and the Universidad de Nariño for providing the genetic resources analyzed in this study, the Gobernación de Nariño, Universidad de Nariño and AGROSAVIA for their contribution to the structuring and approval of the project that financed this research.

9. Funding: The resources for the development of this research were provided by the Ministerio de Ciencia y Tecnología de Colombia (Minciencias) and the Gobernación de Nariño through the Fondo de Ciencia, Tecnología e Innovación del Sistema General de Regalias, with the approval of the project "Improvement technological and productive of the potato system in the Department of Nariño”, identified with code BPIN No. 2014000100022. The execution of this project was carried out between the Universidad de Nariño and AGROSAVIA through the macro agreement 480-15. The hours spent by researcher Jhon A. Berdugo-Cely MSc. for the development of this study were provided by AGROSAVIA through Variable Transfer (TV) 2019.

10. The S1Table was included as supporting information.

Best regards,

Jhon Berdugo

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file. (74.2KB, pdf)

Decision Letter 1

Tzen-Yuh Chiang

5 Mar 2021

Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern Colombia using single nucleotide polymorphism (SNP) markers

PONE-D-21-04514R1

Dear Dr. Berdugo-Cely,

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Tzen-Yuh Chiang

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Tzen-Yuh Chiang

9 Mar 2021

PONE-D-21-04514R1

Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern Colombia using single nucleotide polymorphism (SNP) markers

Dear Dr. Berdugo-Cely:

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on behalf of

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Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Genotypic data of 144 accessions of potato breeding collection of Universidad de Nariño obtained through 8K SNParray technology.

    (XLSX)

    Click here for additional data file. (2.4MB, xlsx)
    Attachment

    Submitted filename: Response to Reviewers.pdf

    Click here for additional data file. (74.2KB, pdf)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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