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During meiosis, each pair of homologous chromosomes becomes connected by at least one crossover, as required for accurate segregation, and adjacent crossovers are widely separated thereby limiting total numbers. In coarsening models, this crossover patterning results from nascent recombination sites competing to accrue a limiting pro-crossover RING-domain protein (COR) that diffuses between synapsed chromosomes. Here, we delineate the localization dynamics of three mammalian CORs in the mouse and determine their interdependencies. RNF212, HEI10, and the newest member RNF212B show divergent spatiotemporal dynamics along synapsed chromosomes, including profound differences in spermatocytes and oocytes, that are not easily reconciled by elementary coarsening models. Contrasting mutant phenotypes and genetic requirements indicate that RNF212B, RNF212, and HEI10 play distinct but interdependent functions in regulating meiotic recombination and coordinating the events of meiotic prophase-I by integrating signals from DNA breaks, homolog synapsis, the cell-cycle, and incipient crossover sites., Competing Interests: Competing interests statement:The authors declare no competing interest.

International trends of increasing dairy herd sizes coupled with scarcity of labor have necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data were used from 592 milkings across 26 farms (16 herringbones and 10 rotaries). The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator), and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACR), feeders, entry gates, rapid exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine variations in infrastructure, automations, and management practices. Fourth quartile (Q4) herringbones based on cows/h per operator values averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. The Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on first quartile parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size were likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACR significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested that lower CT values (i.e., rotation speed) resulted in increased milking efficiency. Overall, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objective of this study was to document the milking efficiency of a sample of Irish dairy farms and to understand the effects of (1) seasonality, (2) management practices, (3) parlor infrastructure, and (4) parlor automations on milking efficiency metrics. A novel methodology based on empirical data from video cameras, infrastructure surveys, and milk yield data allowed for the accurate computation of milking efficiency metrics and quantification of the effects of seasonality, number of operators, and parlor automations on milking efficiency across 2 parlor types. The data for this study were collected over 2 periods: period 1 (July 28, 2020, to October 23, 2020, peak-late production) and period 2 (April 12, 2021, to May 19, 2021, early-peak production) from a sample of 16 herringbone and 10 rotary commercial Irish dairy farms. Milking efficiency was evaluated on each farm using 3 key performance indicators: (1) cows milked per hour (cows/h), (2) cows milked per operator per hour (cows/h per operator), and (3) liters of milk harvested per hour (L/h). Milking efficiency key performance indicators were calculated using "total process time," defined as the time between the first cow entering the holding yard and the end of the cleaning process. Average herd sizes for herringbone and rotary farms were 180 and 425 cows, respectively. Average system sizes for herringbone and rotary farms were 20 and 50 clusters, respectively. For herringbone farms, the average milking efficiency was 94 cows/h, 73 cows/h per operator, and 1,012 L/h, whereas rotary farms achieved an average milking efficiency of 170 cows/h, 132 cows/h per operator, and 1,534 L/h. Parlor size was strongly correlated with milking efficiency (cows/h) for herringbone parlors (0.91) but was only moderately correlated for rotary parlors (0.50). Hence, we documented the effect of parlor size on milking efficiency is relative to parlor type. Cluster utilization values on herringbone farms were 5 cows/cluster per h, 4 cows/cluster per operator per h, and 51 L/cluster per h, which were 67%, 33%, and 65% greater than rotary farms, respectively. We found for both herringbone and rotary farms hourly cow throughput (cows/h, cows/h per operator) were greatest during period 1 and that the volume of milk harvested per hour (L/h) was greatest for period 2. Thus, we documented an inverse seasonal relationship between hourly rates of cows milked and milk harvested. We observed that for herringbone farms, milking efficiency (cows/h, L/h) had a strong positive correlation (0.75, 0.74) with the levels of automation use. However, the minimal variation in automations used among rotary farms made it difficult to evaluate their effect on milking efficiency. Similarly, we found that the effect of automations on milking efficiency was dependent on parlor type. On average, a second operator at milking for both herringbone (H) and rotary (R) farms increased values for cows/h (+19%, H; +34%, R) and L/h (+21%, H; +12%, R) but lowered values for cows/h per operator (-35%, H; -12%, R). The holistic methodology applied in this study allowed us to add novel data to the literature by quantifying the effects of seasonality, the number of operators present at milking, and parlor automation use on milking efficiency across 2 parlor types., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The genome size of organisms impacts their evolution and biology and is often assumed to be characteristic of a species. Here we present the first published estimates of genome size of the ecologically and economically important ectoparasite, Lepeophtheirus salmonis (Copepoda, Caligidae). Four independent L. salmonis genome assemblies of the North Atlantic subspecies Lepeophtheirus salmonis salmonis, including two chromosome level assemblies, yield assemblies ranging from 665 to 790 Mbps. These genome assemblies are congruent in their findings, and appear very complete with Benchmarking Universal Single-Copy Orthologs analyses finding > 92% of expected genes and transcriptome datasets routinely mapping > 90% of reads. However, two cytometric techniques, flow cytometry and Feulgen image analysis densitometry, yield measurements of 1.3-1.6 Gb in the haploid genome. Interestingly, earlier cytometric measurements reported genome sizes of 939 and 567 Mbps in L. salmonis salmonis samples from Bay of Fundy and Norway, respectively. Available data thus suggest that the genome sizes of salmon lice are variable. Current understanding of eukaryotic genome dynamics suggests that the most likely explanation for such variability involves repetitive DNA, which for L. salmonis makes up ≈ 60% of the genome assemblies., (© 2022. The Author(s).)