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The assessment of the genetic structuring of biodiversity is crucial for management and conservation. This is particularly critical for widely distributed and highly mobile deep‐water teleosts, such as hoki (Macruronus novaezelandiae). This species is significant to Māori people and supports the largest commercial fishery in New Zealand, but uncertainty about its stock structure presents a challenge for management. Here, we apply a comprehensive genomic analysis to shed light on the demographic structure of this species by (1) assembling the genome, (2) generating a catalogue of genome‐wide SNPs to infer the stock structure and (3) identifying regions of the genome under selection. The final genome assembly used short and long reads and is near complete, representing 93.8% of BUSCO genes, and consisting of 566 contigs totalling 501 Mb. Whole‐genome re‐sequencing of 510 hoki sampled from 14 locations around New Zealand and Australia, at a read depth greater than 10×, produced 227,490 filtered SNPs. Analyses of these SNPs were able to resolve the stock structure of hoki into two genetically and geographically distinct clusters, one including the Australian and the other one all New Zealand locations, indicating genetic exchange between these regions is limited. Location differences within New Zealand samples were much more subtle (global F ST = 0.0006), and while small and significant differences could be detected, they did not conclusively identify additional substructures. Ten putative adaptive SNPs were detected within the New Zealand samples, but these also did not geographically partition the dataset further. Contemporary and historical N e estimation suggest the current New Zealand population of hoki is large yet declining. Overall, our study provides the first genomic resources for hoki and provides detailed insights into the fine‐scale population genetic structure to inform the management of this species.

Cirrhinus mrigala (mrigal) is one of the Indian major carps widely cultured in the whole Indian subcontinent. Population genetic structure of this species from Peninsular Rivers of India is lacking. Among DNA markers, microsatellites are excellent tools to evaluate genetic variation of populations. In this study, genetic variation of six peninsular riverine mrigal populations was evaluated using seventeen microsatellite loci. In analyzing 288 samples, the number of alleles ranged from 4 to 27; observed heterozygosity from 0.595 to 1.00, expected heterozygosity from 0.586 to 0.959 and inbreeding coefficient (FIS) ranged from -0.034 to 0.02. Exact test for Hardy Weinberg disequilibrium revealed that one locus was not in equilibrium across the rivers except one. The AMOVA analysis revealed the main source of genetic variation to be within the population (94.54%) than among the populations (5.46%). The Nei’s genetic distance and structure analysis depict river Narmada and Mahi populations are different from the four east coast rivers. The overall Fst (0.05462) data showed moderate differentiation among the six populations. The results of this study provide essential information to resource recovery and help in delineating populations for fishery management. Besides, the data will provide a valuable baseline for further investigations on the geographic distribution of this commercially important fish species.

Estuaries represent a transition zone for salmon migrating from fresh water to marine waters, yet their contribution to juvenile growth is poorly quantified. Here, we use genetic stock identification and otolith analyses to quantify estuarine habitat use by Chinook salmon (Oncorhynchus tshawytscha) — the Pacific salmon species considered most reliant on this habitat — in Canada’s most productive salmon river, the Fraser River. Two years of sampling revealed subyearling migrant (ocean-type) Chinook from the Harrison River to be the estuary’s dominant salmon population throughout the emigration period. These Chinook salmon were caught predominantly in the estuary’s brackish marshes but shifted to more saline habitats as they grew. Otolith analyses indicated that these Chinook salmon have wide-ranging entry timing (from February to May) and longer estuarine residency (weeks to months, mean 41.8 days) than estimated by prior studies, but similar daily growth rates (mean ± SD: 0.57 ± 0.13 mm) across entry dates and residency periods, implying sufficient foraging opportunities throughout the emigration period and habitats. Together, these results suggest that estuarine habitat is more important for early marine growth of subyearling migrant Chinook salmon than previously recognized.

Research was conducted with the blackcurrant genetic stock collection at the Kokino base station of Federal Horticultural Center for Breeding, Agrotechnology and Nursery (Bryansk Region) during 2014-2020. We studied 110 varieties and 30 selected forms isolated in different years for main marketability criteria. Te study aimed at the selection and creation of cultivars and forms of blackcurrant with economical and breeding advantages to optimise the zoned stock with domestic varieties for industrial and home gardening in the south-west Non-Chernozem Region of Russia and promote further breeding effort. Source material processing and breeding work were carried out using the generally accepted protocols. Cultivars and promising forms with the good winter hardiness, resistance to Sphaerotheca powdery mildew, strength, uniform size and taste of berries have been selected. Of interest are the cultivars producing an average fruit mass >=2.0 g under optimal weather and agrotechnical conditions: Litvinovskaya, Dar Smolyaninovoy, Podarok Astakhova, Yadryonaya, Kudmig, Bryanskiy Agat, Debryansk, Mif, Kudesnik, Istok, Nos. 68-03-1, 36-27-4/05, 5-66-5, 5-03-8. Te best-yield (up to 12.5 t/ha) cultivars identified were: Barmaley, Bryanskiy Agat, Debryansk, Mif, Favorit, Dar Smolyaninovoy, Litvinovskaya, Selechenskaya-2, Kudmig, Tamerlan, Shalunya, Ladushka, Lentiay, Iskushenie, Kipiana, Orlovskiy Valz, selections 68-03-1, 36-27-4/05, 5-66-5 and others.

With advances in molecular genetics, it is becoming increasingly feasible to conduct genetic stock identification (GSI) to inform management actions that occur within a fishing season. While applications of in-season GSI are becoming widespread, such programs seldom integrate data from previous years, underutilizing the full breadth of information available for real-time inference. In this study, we developed a Bayesian hierarchical model that integrates historical and in-season GSI data to estimate temporal changes in the composition of a mixed stock of sockeye salmon (Oncorhynchus nerka) returning to Alaska’s Chignik watershed across the fishing season. Simulations showed that even after accounting for time constraints of transporting and analyzing genetic samples, a hierarchical approach can rapidly achieve accurate in-season stock allocation, outperforming alternative methods that rely solely on historical or in-season data by themselves. As the distribution and phenology of fish populations becomes more variable and difficult to predict under climate change, in-season management tools will likely be increasingly relied upon to protect biocomplexity while maximizing harvest opportunity in mixed stock fisheries.

Direct DNA sequencing is powering a revolution in the application of genetics to resource management, with parentage-based tagging (PBT) increasingly applied to salmon fisheries and hatchery brood stock management and assessment. Genetic stock identification (GSI) and PBT were applied to assessment of 2018 coho salmon (Oncorhynchus kisutch) ocean fisheries and hatchery brood stocks in British Columbia (BC), Canada, with 6391 individuals successfully genotyped in fishery samples and 7805 individuals genotyped in 40 hatchery brood stocks. Population-specific contributions to mixed-stock fisheries and exploitation rates were estimated with coded-wire tags (CWTs) and GSI–PBT technologies for six populations. PBT assignments, verified by CWTs, were 100% accurate for 308 individuals with respect to population of origin and age. There was generally reasonably close agreement of estimated population-specific exploitation rates between CWT and genetic methods. We conclude that a genetic approach can improve upon the results available from the current CWT program for assessment and management of coho salmon fisheries and hatchery brood stocks in BC and provide information critical to aid in implementation of Canada’s Policy for Conservation of Wild Pacific Salmon.

Targeted amplicon sequencing methods, such as genotyping-in-thousands by sequencing (GT-seq), facilitate rapid, accurate, and cost-effective analysis of hundreds of genetic loci in thousands of individuals. Development of GT-seq panels is nontrivial, but studies describing trade-offs associated with different steps of GT-seq panel development are rare. Here, we construct a dual-purpose GT-seq panel for walleye (Sander vitreus), discuss trade-offs associated with different development and genotyping approaches, and provide suggestions for researchers constructing their own GT-seq panels. Our GT-seq panel was developed using an ascertainment set consisting of restriction site-associated DNA data from 954 individuals sampled from 23 populations in Minnesota and Wisconsin, USA. We conducted simulations to test the utility of all loci for parentage analysis and genetic stock identification and designed 600 primer pairs to maximize joint accuracy for these analyses. We then performed three rounds of primer optimization to remove loci that overamplified and our final panel consisted of 436 loci. We also explored different approaches for DNA extraction, multiplexed polymerase chain reaction (PCR) amplification, and cleanup steps during the GT-seq process and discovered the following: (i) inexpensive Chelex extractions performed well for genotyping; (ii) the exonuclease I and shrimp alkaline phosphatase (ExoSAP) procedure included in some current protocols did not improve results substantially and was probably unnecessary; and (iii) it was possible to PCR amplify panels separately and combine them prior to adapter ligation. Well-optimized GT-seq panels are valuable resources for conservation genetics and our findings and suggestions should aid in their construction in myriad taxa.

Sustainable management of wild fisheries requires accurate delineation of reproductively isolated stocks to avoid depletion of a commercially and ecologically important resource. However, there is ...

Groundnut is one of the leading oilseed crops, primarily cultivated for edible oil and protein in arid and semi-arid regions of the world. Drought is the most significant constraint that severely affects the pod yield and growth related traits in groundnut. The present study aims at assessing the genetic variability in groundnut genotypes to terminal drought tolerance The forty groundnut genotypes including advanced breeding lines and existing cultivars were evaluated under irrigated and drought stress conditions during Rabi 2016-17 at the College of Horticulture, Hiriyur using two sets of randomized completely block design with two replications. The results revealed the highly significant differences for all traits studied among the genetic stock indicating the remarkable levels of variability existed among the investigated genetic material that are very essential in groundnut improvement for terminal drought tolerance. The genotypes SB-14, ICGV 15141 and ICGV 15145 were observed better for terminal drought tolerance with high pod yield. It is suggested that these genotypes could be grown under regions of limited rainfall and may be used as parents in breeding programs for developing drought tolerant groundnut cultivars.

The Lake Michigan brown trout (Salmo trutta) fishery is sustained by the stocking of five hatchery strains by four state natural resource agencies. In the absence of exhaustive marking programs, strain-specific measures of stocking success are lacking for brown trout in Lake Michigan. We used microsatellite-based genetic assignment testing and genetic stock identification (GSI) to determine the strain of 122 angler-caught brown trout from four northeastern Lake Michigan ports. We compared strain composition estimates for sportfishing harvest to expected proportions of each brown trout strain in Lake Michigan at the time of harvest using stocking records corrected for age-specific mortality rates. Reassignment rates of individuals from baseline strains averaged 92.1% (range: 84.1–98.0%). Assignment testing and GSI analyses consistently found Wild Rose strain brown trout represented approximately 89% of the northeastern Lake Michigan sportfishing harvest, while only comprising 43.8% of the expected stock. Of the Michigan angler harvest of Wild Rose strain brown trout, approximately half were estimated to have originated from Wisconsin hatcheries, demonstrating a propensity for lake-wide movements. Continued assessments will improve understanding of strain relative contributions to angler harvests that can direct future stocking efforts.

A total of 10 000 M4 individuals in Jao Hom Nil (JHN) mutant population was treated with high temperature (40 °C to 45 °C) during the day time (6 h) from the booting to the harvesting stages, and ambient temperature (33 °C to 35 °C) was used as the control. The results of screening and yield trials found that the mutant line M9962 had a high spikelet fertility of 78% under heat stress. In addition, the other mutant lines, including M3181 and M7988, had a spikelet fertility of approximately 70%. However, the JHN wild type, Sin Lek, RD15 and RD33 had very low spikelet fertility of 34%, 14%, 9% and 4%, respectively. The lower spikelet fertility at an elevated temperature resulted in a dramatic decrease of filled grain and contributed to a loss in 100-grain weight. M9962 is a potential genetic stock for use in a heat tolerance breeding programme. In addition, spikelet fertility at high temperature was representative of heat tolerance and can be used as a screening trait for heat tolerance during the reproductive phase on a large scale. Keywords: High temperature, Rice, Spikelet fertility, Heat tolerance, Mutant

Combining detailed temporal and spatial catch data, including catch per unit effort, with a high-resolution microsatellite genetic baseline facilitated the development of stock-specific coastal migration models for the four largest Atlantic salmon (Salmo salar) populations, Målselv, Alta, Tana and Kola rivers, contributing to the Barents Sea mixed-stock fishery. Målselv salmon displayed a restricted coastal movement with 85% of the fish captured within 20 km of their natal river. Kola salmon also demonstrated limited coastal movements in Norwegian waters, with most (> 90%) caught in eastern Finnmark. Multi-sea-winter (MSW) Alta salmon were caught west of Alta fjord across a broader stretch of coast while one-sea-winter (1SW) fish migrated more extensively along the coast prior to river entry. Tana salmon, however, were detected over a broad expanse (600 km) of the North-Norwegian coast. For all populations MSW salmon dominating catches earlier in the season (May–June) while 1SW fish were more common from July to August. This study provides an example of how traditional catch and effort information may be combined with genetic methods to obtain insights into spatial and temporal changes in Atlantic salmon catch composition and their associated migration patterns in a mixed-stock coastal fishery.

Genetic stock identification (GSI) estimates stock proportions and individual assignments through comparison of genetic markers with reference populations. It is used widely in anadromous fisheries to estimate the impact of oceanic harvest on riverine populations. Here, we provide a formal, explicit description of Bayesian inference in the conditional GSI model, documenting an approach that has been widely used in the last 5 years, but not formally described until now. Subsequently, we describe a novel cross-validation method that permits accurate prediction of GSI accuracy when making Bayesian inference from the conditional GSI model. We use cross-validation and simulation of genetic data to confirm the occurrence of a bias in reporting-unit proportions recently reported in Hasselman et al. (2016) . Then, we introduce a novel parametric bootstrap approach to reduce this bias, and we demonstrate the efficacy of our correction. Our methods have been implemented as a user-friendly R package, rubias, which makes use of Rcpp for computational efficiency. We predict rubias will be widely useful for GSI of fish populations.