The Vavilov Institute of Plant Genetic Resources (VIR), in St. Petersburg, Russia, houses a unique genebank, with historical collections of landraces. When they were collected, the geographical distribution and genetic diversity of most crops closely reflected their historical patterns of cultivation established over the preceding millennia. We employed a combination of genomics, computational biology and phenotyping to characterize VIR’s 147 chickpea accessions from Turkey and Ethiopia, representing chickpea’s center of origin and a major location of secondary diversity. Genotyping by sequencing identified 14,059 segregating polymorphisms and genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect traits of agricultural importance. The proportion of polymorphisms shared among accessions is a strong predictor of phenotypic resemblance, and of environmental similarity between historical sampling sites. We found that 20 out of 28 polymorphisms, associated with multiple traits, including days to maturity, plant phenology, and yield-related traits such as pod number, localized to chromosome 4. We hypothesize that selection and introgression via inadvertent hybridization between more and less advanced morphotypes might have resulted in agricultural improvement genes being aggregated to genomic ‘agro islands’, and in genotype-to-phenotype relationships resembling widespread pleiotropy.

The genomes of mammals contain thousands of deleterious mutations. It is important to be able to recognize them with high precision. In conservation biology, the small size of fragmented populations results in accumulation of damaging variants.Preserving animals with less damaged genomes could optimize conservation efforts.In breeding of farm animals, trade-offs between farm performance versus general fitness might be better avoided if deleterious mutations are well classified. In humans, the problem of such a precise classification has been successfully solved, in large part due to large databases of disease-causing mutations. However, this kind of information is very limited for other mammals. Here, we propose to better use information available on human mutations to enable classification of damaging mutations in other mammalian species. Specifically, we apply transfer learning-machine learning methods-improving small dataset for solving a focal problem (recognizing damaging mutations in our companion and farm animals) due to the use of much large datasets available for solving a related problem (recognizing damaging mutations in humans). We validate our tools using mouse and dog annotated datasets and obtain significantly better results in companion to the SIFT classifier. Then, we apply them to predict deleterious mutations in cattle genomewide dataset. K E Y W O R D Sclassification, deleterious mutations, transfer learning | 19PLEKHANOVA Et AL.

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Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

Chickpea (Cicer arietinum L.), a grain legume crop, is considered innovative for the Russian Federation. Over the past fifteen years, its area in our country have increased 20 times and reached 420,300 hectares in 2015. The growing demand of chickpea determines the necessity of breeding new varieties. One of the ways to improve the crop could be the introgression of genes from old landraces, especially those from the regions of species genetic diversity, the centers of its origin (i.e. the primary in Turkey and the secondary in Ethiopia). In this paper the question is raised about the diversity and phenotypic differences of the chickpea gene pool growing in the centers of origin about a century ago and preserved in VIR collection. Here, we first showed the differences in the phenotypic characteristics of the oldest chickpeas from two centers of origin. Fifteen morphological, phenological and agronomic features were studied in 75 local varieties from Turkey and 24 ones from Ethiopia. Both in Turkish and in Ethiopian samples, the most variable signs were the number of seeds per plant (Cv 62.6 and 70.4 %, respectively) and the number of beans per plant (Cv 62.2 and 63.0 %). Principal component analysis showed that the first five factors determined 78.9 % of the total variability of traits. Factor 2 (22.0 % of the variance) can be called a factor of potential seed production. Correlation analysis revealed a much stronger relationships between all the traits studied in the Ethiopian samples. The correlation between seed production and vegetation period were the strongest (r  0.9). We have revealed association of certain traits of chickpea plants with the geographical zones of the sample origins. Landraces from Ethiopia are fairly homogeneous and have small, dark and angular seeds, low attachment of the first bean and low seed productivity, are more early maturated compared with the Turkish ones. Turkish landraces are characterized by a great variety of all the traits studied, revealing all their grades described in the chickpea descriptors. In this region, the landraces typical of the western Mediterranean, as well as for territories bordering Turkey in the east had been grown. The structure of the variability and the strength of the relations of the traits differed in the landraces from the primary and secondary centers. It is obvious that in plants growing in different ecological and geographical environment, there is a specific communications between the traits, reflecting the presence of different blocks of co-adapted genes or another integrated gene complexes that determine adaptation to a particular environment. Useful characters for breeding are found in landraces from both centers of origin and chickpea diversity.