Gunārs Lācis

Dr. Gunārs Lācis

Institute of Horticulture, Dobele, LV-3701, Latvia
orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 February 2014 in European Journal of Lipid Science and Technology
Verified
Journal Article
Closed access
PDF file
Paweł GórnaśPaweł Górnaś
Paweł Górnaś
ASAleksander Siger
Aleksander Siger
KJKarina Juhņeviča
Karina Juhņeviča
GLGunārs Lācis
Gunārs Lācis
EŠElga Šnē
Elga Šnē
DSDalija Segliņa
Dalija Segliņa

1 November 2014 in LWT
Verified
Journal Article
Open access
Paweł GórnaśPaweł Górnaś
Paweł Górnaś
DSDalija Segliņa
Dalija Segliņa
GLGunārs Lācis
Gunārs Lācis
IPIveta Pugajeva
Iveta Pugajeva

1 November 2015 in Industrial Crops and Products
Verified
Journal Article
Closed access
Paweł GórnaśPaweł Górnaś
Paweł Górnaś
IMInga Mišina
Inga Mišina
AOAnita Olšteine
Anita Olšteine
IKInta Krasnova
Inta Krasnova
IPIveta Pugajeva
Iveta Pugajeva
DSDalija Segliņa
Dalija Segliņa

1 August 2009 in Scientia Horticulturae
Verified
Journal Article
Closed access
GLGunārs Lācis
Gunārs Lācis
IRIsaak Rashal
Isaak Rashal
SRSilvija Ruisa
Silvija Ruisa
VTViktor Trajkovski
Viktor Trajkovski
AIAmy F. Iezzoni
Amy F. Iezzoni

23 February 2021 in Plants
Verified
Journal Article
Open access
PDF file
HNHilde Nybom
Hilde Nybom
GLGunārs Lācis
Gunārs Lācis
Several recent national and international projects have focused on large-scale genotyping of plant genetic resources in vegetatively propagated crops like fruit and berries, potatoes and woody ornamentals. The primary goal is usually to identify true-to-type plant material, detect possible synonyms, and investigate genetic diversity and relatedness among accessions. A secondary goal may be to create sustainable databases that can be utilized in research and breeding for several years ahead. Commonly applied DNA markers (like microsatellite DNA and SNPs) and next-generation sequencing each have their pros and cons for these purposes. Methods for large-scale phenotyping have lagged behind, which is unfortunate since many commercially important traits (yield, growth habit, storability, and disease resistance) are difficult to score. Nevertheless, the analysis of gene action and development of robust DNA markers depends on environmentally controlled screening of very large sets of plant material. Although more time-consuming, co-operative projects with broad-scale data collection are likely to produce more reliable results. In this review, we will describe some of the approaches taken in genotyping and/or phenotyping projects concerning a wide variety of vegetatively propagated crops.

23 September 2021 in Plants
Verified
Journal Article
Open access
PDF file
TBTeresa Barreneche
Teresa Barreneche
MCMaría Cárcamo de la Concepción
María Cárcamo de la Concepción
MDMarine Blouin Delmas
Marine Blouin Delmas
MOMatthew Ordidge
Matthew Ordidge
HNHilde Nybom
Hilde Nybom
JQJosé Quero-Garcia
José Quero-Garcia
Sweet cherry (Prunus avium L.) is a temperate fruit species whose production might be highly impacted by climate change in the near future. Diversity of plant material could be an option to mitigate these climate risks by enabling producers to have new cultivars well adapted to new environmental conditions. In this study, subsets of sweet cherry collections of 19 European countries were genotyped using 14 SSR. The objectives of this study were (i) to assess genetic diversity parameters, (ii) to estimate the levels of population structure, and (iii) to identify germplasm redundancies. A total of 314 accessions, including landraces, early selections, and modern cultivars, were monitored, and 220 unique SSR genotypes were identified. All 14 loci were confirmed to be polymorphic, and a total of 137 alleles were detected with a mean of 9.8 alleles per locus. The average number of alleles (N = 9.8), PIC value (0.658), observed heterozygosity (Ho = 0.71), and expected heterozygosity (He = 0.70) were higher in this study compared to values reported so far. Four ancestral populations were detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA), and two of them (K1 and K4) could be attributed to the geographical origin of the accessions. A N-J tree grouped the 220 sweet cherry accessions within three main clusters and six subgroups. Accessions belonging to the four STRUCTURE populations roughly clustered together. Clustering confirmed known genealogical data for several accessions. The large genetic diversity of the collection was demonstrated, in particular within the landrace pool, justifying the efforts made over decades for their conservation. New sources of diversity will allow producers to face challenges, such as climate change and the need to develop more sustainable production systems.